No man is an (Urban Heat) Island
Observant readers will have noticed a renewed assault upon the meteorological station data that underpin some conclusions about recent warming trends. Curiously enough, it comes just as the IPCC AR4 report declared that the recent warming trends are “unequivocal”, and when even Richard Lindzen has accepted that globe has in fact warmed over the last century.
The new focus of attention is the placement of the temperature sensors and other potential ‘micro-site’ effects that might influence the readings. There is a possibility that these effects may change over time, putting in artifacts or jumps in the record. This is slightly different from the more often discussed ‘Urban Heat Island’ effect which is a function of the wider area (and so could be present even in a perfectly set up urban station). UHI effects will generally lead to long term trends in an affected station (relative to a rural counterpart), whereas micro-site changes could lead to jumps in the record (of any sign) - some of which can be very difficult to detect in the data after the fact.
There is nothing wrong with increasing the meta-data for observing stations (unless it leads to harassment of volunteers). However, in the new found enthusiasm for digital photography, many of the participants in this effort seem to have leaped to some very dubious conclusions that appear to be rooted in fundamental misunderstandings of the state of the science. Let’s examine some of those apparent assumptions:
Mistaken Assumption No. 1: Mainstream science doesn’t believe there are urban heat islands….
This is simply false. UHI effects have been documented in city environments worldwide and show that as cities become increasingly urbanised, increasing energy use, reductions in surface water (and evaporation) and increased concrete etc. tend to lead to warmer conditions than in nearby more rural areas. This is uncontroversial. However, the actual claim of IPCC is that the effects of urban heat islands effects are likely small in the gridded temperature products (such as produced by GISS and Climate Research Unit (CRU)) because of efforts to correct for those biases. For instance, GISTEMP uses satellite-derived night light observations to classify stations as rural and urban and corrects the urban stations so that they match the trends from the rural stations before gridding the data. Other techniques (such as correcting for population growth) have also been used.
How much UHI contamination remains in the global mean temperatures has been tested in papers such as Parker (2005, 2006) which found there was no effective difference in global trends if one segregates the data between windy and calm days. This makes sense because UHI effects are stronger on calm days (where there is less mixing with the wider environment), and so if an increasing UHI effect was changing the trend, one would expect stronger trends on calm days and that is not seen. Another convincing argument is that the regional trends seen simply do not resemble patterns of urbanisation, with the largest trends in the sparsely populated higher latitudes.
Mistaken Assumption No. 2: … and thinks that all station data are perfect.
This too is wrong. Since scientists started thinking about climate trends, concerns have been raised about the continuity of records - whether they are met. stations, satellites or ocean probes. The danger of mistakenly interpreting jumps due to measurement discontinuities as climate trends is well known. Some of the discontinuities (which can be of either sign) in weather records can be detected using jump point analyses (for instance in the new version of the NOAA product), others can be adjusted using known information (such as biases introduced because changes in the time of observations or moving a station). However, there are undoubtedly undetected jumps remaining in the records but without the meta-data or an overlap with a nearby unaffected station to compare to, these changes are unlikely to be fixable. To assess how much of a difference they make though, NCDC has set up a reference network which is much more closely monitored than the volunteer network, to see whether the large scale changes from this network and from the other stations match. Any mismatch will indicate the likely magnitude of differences due to undetected changes.
It’s worth noting that these kinds of comparisons work because of large distance over which the monthly temperature anomalies correlate. That is to say, that if a station in Tennessee has a particular warm or cool month, it is likely that temperatures in New Jersey say, also had a similar anomaly. You can see this clearly in the monthly anomaly plots or by looking at how well individual stations correlate. It is also worth reading “The Elusive Absolute Surface Temperature” to understand why we care about the anomalies rather than the absolute values.
Mistaken Assumption No. 3: CRU and GISS have something to do with the collection of data by the National Weather Services (NWSs)
Two of the global mean surface temperature products are produced outside of any National Weather Service. These are the products from CRU in the UK and NASA GISS in New York. Both CRU and GISS produce gridded products, using different methodologies, starting from raw data from NWSs around the world. CRU has direct links with many of them, while GISS gets the data from NOAA (who also produce their own gridded product). There are about three people involved in doing the GISTEMP analysis and they spend a couple of days a month on it. The idea that they are in any position to personally monitor the health of the observing network is laughable. That is, quite rightly, the responsibility of the National Weather Services who generally treat this duty very seriously. The purpose of the CRU and GISS efforts is to produce large scale data as best they can from the imperfect source material.
Mistaken Assumption No. 4: Global mean trends are simple averages of all weather stations
As discussed above, each of the groups making gridded products goes to a lot of trouble to eliminate problems (such as UHI) or jumps in the records, so the global means you see are not simple means of all data (this NCDC page explains some of the issues in their analysis). The methodology of the GISS effort is described in a number of papers - particularly Hansen et al 1999 and 2001.
Mistaken Assumption No. 5: Finding problems with individual station data somehow affects climate model projections.
The idea apparently persists that climate models are somehow built on the surface temperature records, and that any adjustment to those records will change the model projections for the future. This probably stems from a misunderstanding of the notion of a physical model as opposed to statistical model. A statistical model of temperature might for instance calculate a match between known forcings and the station data and then attempt to make a forecast based on the change in projected forcings. In such a case, the projection would be affected by any adjustment to the training data. However, the climate models used in the IPCC forecasts are not statistical, but are physical in nature. They are self-consistent descriptions of the whole system whose inputs are only the boundary conditions and the changes in external forces (such as the solar constant, the orbit, or greenhouse gases). They do not assimilate the surface data, nor are they initiallised from it. Instead, the model results for, say, the mean climate, or the change in recent decades or the seasonal cycle or response to El Niño events, are compared to the equivalent analyses in the gridded observations. Mismatches can help identify problems in the models, and are used to track improvements to the model physics. However, it is generally not possible to ‘tune’ the models to fit very specific bits of the surface data and the evidence for that is the remaining (significant) offsets in average surface temperatures in the observations and the models. There is also no attempt to tweak the models in order to get better matches to regional trends in temperature.
Mistaken Assumption No. 6: If only enough problems can be found, global warming will go away
This is really two mistaken assumptions in one. That there is so little redundancy that throwing out a few dodgy met. stations will seriously affect the mean, and that evidence for global warming is exclusively tied to the land station data. Neither of those things are true. It has been estimated that the mean anomaly in the Northern hemisphere at the monthly scale only has around 60 degrees of freedom - that is, 60 well-place stations would be sufficient to give a reasonable estimate of the large scale month to month changes. Currently, although they are not necessarily ideally placed, there are thousands of stations - many times more than would be theoretically necessary. The second error is obvious from the fact that the recent warming is seen in the oceans, the atmosphere, in Arctic sea ice retreat, in glacier recession, earlier springs, reduced snow cover etc., so even if all met stations were contaminated (which they aren’t), global warming would still be “unequivocal”. Since many of the participants in the latest effort appear to really want this assumption to be true, pointing out that it doesn’t really follow might be a disincentive, but hopefully they won’t let that detail damp their enthusiasm…
What then is the benefit then of this effort? As stated above, more information is always useful, but knowing what to do about potentially problematic sitings is tricky. One would really like to know when a problem first arose for instance - something that isn’t clear from a photograph from today. If the station is moved now, there will be another potential artifact in the record. An argument could certainly be made that continuity of a series is more important for long term monitoring. A more convincing comparison though will be of the existing network with the (since 2001) Climate Reference Network from NCDC. However, that probably isn’t as much fun as driving around the country taking snapshots.
2 July 2007 at 9:14
For historical perspective, the very first person to compile weather data that showed global warming, G.S. Callendar back in 1938, already thought of the urban heat island effect and made an effort to compensate for it. All subsequent workers have taken it into account. Debates over just how to compensate for it began seriously as early as 1967. After much debate the issue was pretty much settled, in terms of figuring out how to compensate for the urban effect and detecting a warming trend anyway, by 1990. Refs. here.
Mistaken assumption no. 6-A: We need land station measurements to tell us global warming is underway.
Personally I got convinced that warming was underway in the late 1990s after borehole measurements in rocks around the world, far away from civilization, showed unmistakable evidence of warming over the past century… if you log temperature down the hole, you find that extra heat has been seeping down from the surface. I think any scientists not convinced by that would have been satisfied by the measurements of the oceans in the early 2000s that showed definitively that heat is seeping down there too. After all, most of the excess energy from any radiation imbalance will wind up in the oceans, and the top layers are undoubtedly getting warmer. Temperature measurements in the thin layer of air around cities don’t mean much in comparison. (Except of course for those of us who live in cities!)
2 July 2007 at 9:29
Tamino at Open Mind has some good posts on temperature records and covers the anomaly tracking of disparate stations (as mentioned in assumption 2). Re comment#1 he also covers boreholes pretty well, too.
2 July 2007 at 9:43
Thanks Gavin:
A great summary and one easy to review and use in discussions with those that do not fully understand the breadth of data that indicate global warming and the great pains scientists go to insure the quality of the data they use. Your distinction between a physical model and a statistical model is particularlly clear.
Your comments are reminiscent of the argument Richard Dawkins makes for evolution in “The Ancestor’s Tale”. He states that Darwinian Evolution (DE) is proven beyond any reasonable doubt by the fossil record alone. Like the instrumental meteorological record, the fossil record has problems with temporal and spatial continuity, how representative a particular observation (i.e. fossil occurrence) is and a dearth of observations in many cases.
Using DNA and other biochemical evidence while ignoring the fossil record altogether DE is ALSO a slam dunk.
Here are two independent lines of evidence that both prove DE so it is only a “theory” because the all small details have not been discovered or explained.
Climate science too has more than one conclusive independent line of evidence for GW. So do a thought experiment. Ignore the instrumental record and consider only the other lines of evidence you cited and what conclusion do you come to?
Finally most members of the general public do not appreciate what scientists mean by the term “theory”. There is little in common between a theory like Oliver Stone’s theory of the Kennedy asassination in his film “JFK” and what a scientist calls a theory. Stone’s theory is supported by innuendo and unsubstantiated assertions which are often in many arguments erroneously called “facts”.
To a scientist a “fact” is not a “fact” until is is demonstrated to be true. A fact is not merely an element of an argument for or against a particular issue. Only after an assertion is demonstrated to be true can the “fact” be used to build a logical chain of reasoning that elevates a hypothesis to a theory. Of course a theory in science relies on many “facts”.
2 July 2007 at 9:47
Gavin,
Thanks for this post. It is very timely, as it appears that every denialist has gone into the business of producing their own global temperature trends from “selected” stations. This coupled with the use of 1998 (an anomalous El Nino year) to skew the data and make it look as if global temperatures are now falling, and you have a new onslaught against the contention that the globe is warming. One would think that the decline of the ice sheets might give them some clue. Unfortunately, I’m afraid the denialists will not be reading this missive. They seem bound and determined to trash this site as “biased”. Well, if insisting on good science is a bias, then, thank God for that bias.
2 July 2007 at 10:14
Another great RealClimate post. Thanks Gavin. I especially enjoyed Mistaken Assumption No. 6. Too bad the following also isn’t true:
If enough holes in their arguments can be found, global warming skeptics will go away!
Thanks for working towards the above goal.
2 July 2007 at 10:41
I can see that the UHI is different to the microsite effects you describe. You say that the temperature record is corrected for UHI. Is it corrected for the microsite effects too?
2 July 2007 at 11:01
Thanks Adam (#2) for the endorsement, and thanks to the moderators for the link.
I’ve actually posted often about the themometer record, so to make them easier to find I’ve just posted a list of such posts (with links) on my blog. Enjoy!
2 July 2007 at 11:11
A request for clarification:
Presumably, models are changed, weighted or discarded on the basis of their agreement with observed climate. What’s the practical difference between doing this and “tuning” or “tweaking” the models to agree with the surface data?
[Response: Fair enough question. There is some discussion of this in our last model development paper. In there, you will see (fig 17) a comparison of the average surface temperatures of the model (in different seasons) with the CRU data. Although the pattern correlation is high, there are clear offsets in summer-time mid-continental temperatures (the model temps being up to 5 deg C too warm in places). The pattern of the mis-match is clearly much larger than any individual weather station could have produced and it’s ubiquity (N. Am, S.Am, Asia, Africa) indicates that it is systematic problem. This cannot be fixed by fiddling with a parameter or two, but instead is a symptom of something more fundamental. Thus, model developers are spending a lot of time looking at the processes that are important in summer, continental climates (particularly surface moisture) and trying to see how the simulation of those processes can be made more realistic. What happens then is that the new physics will be tested and we will see whether it has improved the match. Usually it does, but not always, and yet we will generally keep a more realistic treatment in the model rather than go back to something we knew was inadequate. Surprisingly, this does overall reduce the biases in the model with time (see Table 5).
So what are the key points? 1) we only use large scale patterns to match to the models - not individual grid points, and not individual stations, 2) problems are tackled by looking at the physics, not tweaking knobs. Some knob tweaking goes on within the constraints of any physical representation, but there are very strong limits on what can be achieved by that - witness the large biases we still stuck with. 3) we develop the model to improve the match to climatology, not to the trends. - gavin]
2 July 2007 at 11:31
Re #6 Bishop Hill. There are tests done to see if stations “stand out” from their neighbours (amongst others). Such stations can be excluded from the dataset. There’s more detail in some of the links above, or at the GHCN site amongst others. There are probably more technical descriptions to the techniques, but that’s the gist of it.
2 July 2007 at 11:53
Hey, I’m a denialist and I read these missives…
2 July 2007 at 12:16
I am having a little trouble with 5. As a matter of historical fact, would not your first models have “assimilated” the observational data? The way you describe the process, model builing seems awfully Rationalistic (as opposed to Empirical): build the model and then compare. But how do you know how to even begin building your model?
[Response: To answer your first question. No. Physical climate models have never assimilated data in this sense. People started off with basic radiation physics, added in the dynamic equations and then clouds, and then better land surface schemes and oceans and sea ice etc. At each point, the match to observations and the variability improved. This point might become clearer once it’s realised that climate models are not developed just to the climate change problem, but as much more general tools to quantify the net effects of all the different processes we know about. -gavin]
2 July 2007 at 12:45
Can anyone point me to where each of the “Mistaken Assumption” has been stated by someone other than the author of this post?
And, aren’t the “large scale patterns” ultimately set by the individual stations plus unknown procedures/processes and maths? Surely these patterns cannot be independent of the numbers from the individual stations. If this were true, why can’t numbers for the individual stations simply be made up? A pointer to these procedures/processes and equations is also of interest. Absent a pointer to a complete set of records and results, to a level of detail that allows independent verification and replication, will be taken to mean that such information is not available.
Thanks in advance.
[Response: Assuming you are not joking, I suggest you take a look at the comment threads on CA or Pielke Sr’s site. All those and more….. Of course, large scale patterns are made up of individual stations, but they average over a lot of the noise. Micro-site effects and their timing are not coherent over thousands of kilometers - large scale temperature anomalies are. The curious thing is that the GISS effort (exhaustively described in the papers linked to above) was specifically designed to do a different job from what was available from NOAA and CRU - a replication if you will - and the fact that it gives pretty much the same answers is a testament to the robustness of the result. GISS processes the raw data from NOAA and has no access to data other than what you can download for yourself. So if you want to do your own analysis with whatever methodology you choose, please go ahead (in fact I’d encourage it). Try something constructive! - gavin]
2 July 2007 at 12:52
I am sure that there is a need for the NWS to strike a balance between measuring weather in remote places that escape all anthropogenic effects and measuring weather phenomena that effect people the most and can have direct impact on public health and our economy. Many of these stations caricatured as “poorly sited” may be giving excellent data if one’s purpose is not climatological but meteorological. I know that NWS has ongoing scientific studies on these very sorts of problems and has also completed numerous studies in the past of the urban heat island effect.
2 July 2007 at 12:55
It is very clear that changes to certain aspects of the mathematical models, numerical solution methods, and application procedures are in fact based on “the match to observations”. Thus the observations are an implicit part of the modeling effort. If this is not true, then the observations are not needed. Additionally, if the observations are not correct, how can the changes to the models, methods and application procedures be correct?
A straightforward answer to this question might improve the clearity; “Can the models/methods/application procedures be developed in the absence of the obdserved data?” If the answer is “yes” then why are the data needed?
Thanks
[Response: Maybe the fact that ‘data’ is a plural might help you out there…. - gavin]
2 July 2007 at 13:09
Re Gavin’s inline to #11
As near as I can tell, the models always procede from principles of physics, not modeling on the basis of the observed behavior of the system.
When confronted with a contrarian who argues that somehow global warming isn’t taking place, I would point to the Arctic sea ice and glaciers - which have even lasted through the warm periods of the past two thousand years - and probably well before. I would then of course point out that the melting is occuring much more quickly than we anticipated, at least in the case of the Arctic sea ice, Greenland’s glaciers and the Western Antarctic Peninsula.
Of course at this point they are likely to raise the issues of:
“Why should we trust the models if they aren’t doing such a hot job on ice?,” and,
“Why don’t they just incorporate the observed behavior?”
The response to the latter is that the observed behavior has to be modeled on the basis of physical principles - not simply empirical observation. It takes a while to develop such models - but wherever we notice that models appear to be doing a poor job, that is where we focus on developing the appropriate models. Clouds were one of the weakest links in the past, the carbon cycle another and so is the behavior of ice.
But we are working on all three fronts, and have made a great deal of progress on the first, somewhat less on the second and clearly need to do more work on the third. At the same time, this also leaves the first question unanswered, and it would appear that we may be underestimating the rate at which the system as a whole evolves given that all subsystems are coupled, either directly or indirectly, with stronger or weaker coupling between the subsystems. If we underestimate the rate at which one subsystem evolves, it would seem that we are underestimating how all evolve, to one extent or another.
However, once the sea ice is gone, the Arctic should warm up much more rapidly. At present, the thermohaline downwelling is moving poleward.
What happens to ocean currents once the sea ice is gone? And how will this affect the system as a whole?
2 July 2007 at 13:12
Hasn’t the ocean been swelling over the last several decades,leading to a rise in sea level?(That’s rhetorical). In other words, the oceans are acting like a giant thermometer,rising as its temperature rises. The effects are already being felt in low lying atolls and islands in the Pacific and in Bangladesh.
As Claude Raines character said in “Casablanca”- Round up the “usual suspects”. Temperature isn’t the only suspect. As you point out….. “the recent warming is seen in the oceans, the atmosphere, in Arctic sea ice retreat, in glacier recession, earlier springs, reduced snow cover etc…”. Also daily temperature ranges are getting smaller,and plant and animals are migrating northward in this hemisphere. Could they know something the skeptics don’t?
2 July 2007 at 13:37
Adam
Thank-you. Can you be a bit more precise with the reference to the adjustments methodology? I’m going to struggle otherwise.
Does the methodology you describe mean that if a site and its neighbour both suffer from microsite effects then potentially they might both be included in the dataset?
Presumably everyone agrees that where the the site has not been properly maintained, the relevant data should be excluded from the dataset, regardless of any similarity to adjacent sites?
2 July 2007 at 13:38
re: #12 and #14
Gavin, thanks for the extremely high information content in your responses. I would ask again for independent sources for the “Mistaken Assumption(s)”, but I am now sure that there are none. The Mistaken Assumptions are your’s and your’s alone.
By your response in #14, I take the answer to the question, “Can the models/methods/application procedures be developed in the absence of the observed data?” to be “no”. To me that means that the data are in fact a part of the models/methods/application procedures.
I have over the past almost three years tracked down a large number of the papers that are said to contain information to a level of detail that allows independent verification and replication. I have yet to find one for which this has been true. At the same time some in the GCM community have urged me to go out and find funding so that the community can do a better job of documentation; a disingenuous response if there ever was one. Here is another example in your response to #12. The fact that there are Web sites devoted to trying to discover the basic foundations for some aspects of the science conducted in the GCM community is a strong indication to me that I am not alone in my lack of success.
[Response: There are websites devoted to showing the moon landings were faked as well, but that is hardly proof of anything. You have downloaded the GISS model and you are in a position to run it and make any changes you like. You can download the much simpler earlier version of the model through the EdGCM project. Write your own model if you want, but don’t expect already over-committed people to take time out to hold you hand. If you want to contribute constructively go ahead, if not, I’ll assume you are only interested in drive-by criticism. Fun, but hardly useful. - gavin]
2 July 2007 at 14:32
Re: #18 (Dan Hughes)
I have a blog about global warming (which was referenced in the post and recommended in comment #2) through wordpress. Wordpress provides a “tag surfer” feature, which enables bloggers like me to locate other blog posts related to global warming, so I regularly hear what the wordpress blogosphere is saying.
Every one of the mistaken assumptions identified in this post exists in myriad posts in the blogosphere. I have also seen them in published documents and news articles. If you really can’t find any of them, you’re not trying very hard. In fact, you’re probably not trying at all.
I strongly suspect that you’re yet another denialist who is all too eager to deny the truth of something, but unwilling to do any of the work required to learn about the subject.
And to answer your other question, “Can the models/methods/application procedures be developed in the absence of the observed data?” — the answer is yes.
2 July 2007 at 14:42
Just a note on a specific case of Urban Heat Island and microclimate that may illustrate some of the complications.
I am a meteorologist in Cincinnati, OH. The instrumental record, which goes back to 1858 on a daily basis and is mostly complete having a variety on locations that are not directly comparable and were not quality controlled, to Jan. 1, 1814.
If we concentrate on the 1870’s - 1895 the observations were made in Downtown Cincinnati, roughly at an elevation of 400 ft. (~122m) above mean sea level (msl) in the often humid Ohio River Valley. During summer low temperatures around 80F (~27C) were not that uncommon.
In 1895 the official observation was moved to Abbe Observatory, at an elevation of roughly 800 ft.(~244m) msl, just north of the city center. There a morning minimum temperature of 80F (~27C) never happened. Away from the dense network of heat absorbing (daytime) then heat radiating (nighttime) structures which is the Urban Heat Island and above the air with high water vapor content trapped by the valley along the river, not to mention the pall of coal dust over the city, morning low temps were much more like what the natural countryside would experience.
In 1949 the official observation was again moved, this time across the river to what is now the international airport (KCVG)in northern Kentucky, a location about 900 ft.(~274m)msl on a large plateau above the river valley.
There are two very important factors that one must note in using the data from this location.
First micro climate: The airport is a very broad shallow depression. The thermometer is located near the lowest elevation and subject to cold air drainage and what meteorologists call “boundary layer separation”. This means that as the dense cold air flows towards the low spot and pools there the influence of the large scale wind decreases to zero in a shallow layer near the surface. Above the shallow layer the influence of the wind can still be measured. Near the surface the wind goes calm, mixing is near zero and conditions are perfect for re-radiation and minimum temperatures are often much lower than representative temperature for rurals areas.
Second Urban Heat Island Effect: Under meteorological situations that dicate winds out of the northeast through east, warm air from the city is blown towards the airport. The effect is greatest (from my experience, I have not quantified it)with winds from the ENE and a wind velocity of 15 mph (~7 meters per second) or less. Winds that are too rapid increase the mixing and the effect is essentially diluted.
Looking at the meteorological record one would note a rather abrupt cooling trend in the late 1890’s followed by another but smaller in magnitude in the late 1940’s.
Those that would want to use this as an example negating global warming, by ignoring both site and situation changes could do so. By the way the record at the international airport does show warming over the last 30 years.
2 July 2007 at 14:52
Mistaken Assumption No. 1 uses Parker (2006) as evidence of nothing more than local (as opposed to large-scale) impact of the UHI.
A well-accepted feature of the UHI is the ‘modulation’ of the wind speed on the magnitude of the UHI, namely on the difference between urban and rural stations. In calculating no trend between “windy” and “calm” days (with wind data obtained from NCEP/NCAR Reanalysis), Parker (2006), in effect, states that there is no modulation to speak of - in and of itself, that is a remarkable statement, or else there is no UHI to speak of. Since he explicitly states that the UHI is a real phenomenon, it must be the former mechanism that he believes is non-existent.
Why weren’t ‘urban minus rural’ temperature differences used instead? That is the definition of UHI (or else, skin temps, rather than 2-meter temps) and will get right at the UHI signal, not simply the magnitude of the urban value.
Lastly, there is no mention (at least, I could not find it) of how NCEP/NCAR grid point data was interpolated to station locations and station observation time (the gridded data is available only 4 times daily and how the author makes these times match is rather critical).
Because of all these reasons, this paper does not ‘Demonstrate that Large-Scale Warming Is Not Urban’, at least in my view.
2 July 2007 at 14:58
> Presumably everyone agrees … properly maintained …
I’d suggest it’d be safer to ask the people that maintain the stations.
I’d guess ‘properly maintained’ = ‘reported data not found to change abruptly after maintenance’; but ask.
This may help: http://en.wikipedia.org/wiki/Wikipedia_talk:Neutral_point_of_view/Fact_disputedfact_value
2 July 2007 at 15:05
I would like to add to the comment by Spencer and show how warming of the ground surface is manifested in borehole temperature logs. http://www.heatflow.und.edu/Landa2007.htm
The borehole was drilled in 1983 for geothermal research in flat terrain in north central North Dakota. It was cased, plugged at the bottom and the casing was filled with water to facilitate temperature measurements. When we visited the site this summer, we found that the water level had dropped, probably due to leakage at a coupling, and we did not log in air. In any case, one can see how the ground has warmed between each successive measurment. Integrating the temperature change in time over the area (volume) of mass that has been changed gives the excess heat that is stored in the ground.
2 July 2007 at 15:13
re: #19
Gavin and RC. Unfounded and incorrect statements about me have been given in comment #19. Kindly allow me to respond to the ad hominem.
I simply asked for citations to the sources for the Mistaken Assumptions. I think that is a reasonable request and that most people here would agree. I do not see any such citations in the original post.
And now we are to the point that Gavin nor you have answered my simple request. Instead you have now labeled me as a suspected “yet another denialist” based on no information what so ever. That is, yet another ad hominem that dodges the original question. You did not and you cannot provide any supporting evidence for this statement. Nor have I ever labeled anybody to be anything. Additionally you accuse me of not working to try to understand the subject. Yet another false accusation about which you have no information what so ever. You don’t know me and I don’t know you, so how can you know what I do and don’t do.
You devoted about half your post to explaining how the Mistaken Assumptions are just about all over the Web and easily located, yet you failed to point me to a single one.
Straightforward answers given to simple straightforward questions is a very much better way to conduct a conservation.
I will leave it to others to point out the error in your final sentence.
2 July 2007 at 15:13
Re #17 Bishop Hill
Well I’m just an interested reader who’s short on time, so tend to “toe-dip” until my curiosity gets satisfied. I am also very bad at bookmarking references. However a quick retrace of steps has brought up this: http://www.ncdc.noaa.gov/oa/climate/ghcn-monthly/index.php
There’s a couple of papers on here about how they do it. They pay no/little attention to the individual sites but just the data. There’s a umber of statistical methods carried out (see Open Mind for some basic examples) that compare sites to a number of neighbouring stations. The importance is in the multiple numbers thus reducing the chances that they all have the same bias (eg they are all sited next to a barbecue). I think (from memory I haven’t re-read the papers) that they use “high quality” reference sites as well as a comparator.
I’m sure someone who visits here is more up to speed (I’s appreciate any errors on my part to be corrected as well as it’ll highlight any misunderstandings I may have).
The discussion at Open Mind on Shelby County shows how a mere tinkering (as I hope tamino doesn’t mind me calling the post relative to the GHCN QC effort) can raise possible errors and show which stations would be flagged for further investigation.
2 July 2007 at 15:44
I’ve imported the location of all the GISTEMP stations into Google Earth. You can access the KML file here: http://edgcm.columbia.edu/~mankoff/GISTEMP/
This is an initial attempt to recreate the work of Hansen but is a work in progress. The color of the pins is encoded to the temperature trend, the size to the years of data, and the opacity is inverse to proximity to populated centers.
Blue is cooling, red is warming, white is insufficient data (baseline years or recent years). Note all the white pins in Canada! For some reason they seem to have turned off their network in the late ’80s.
2 July 2007 at 15:46
A question: In the article you say that
It seems to me that micro-site changes would overwhelmingly have the effect of raising the station’s reported temperature. What are the scenarios in which the reported temperature would be reduced?
[Response: A tree growing nearby, increased lawn sprinkling, shade from tall buildings, moving away from a road, changes to air flow (any sign), movement to a roof etc. etc. The point is not that any of these things might have a large effect, but that the effects in different stations are going to be uncorrelated. My feeling is that these effects are all much smaller than the site move or time of observation biases that are being corrected for. - gavin]
2 July 2007 at 15:48
Re: #24 (Dan Hughes)
In the response to #12, Gavin pointed you to ClimateAudit (http://www.climateaudit.org/) and Roger Pielke Sr.’s blog (http://climatesci.colorado.edu/), as places you would find the aforementioned misconceptions. Apparently you weren’t willing to do a google search for either, or to do a little rummaging around this site to find what they were.
If you had been the least bit willing to do the slightest amount of work to find information on the web (and it requires very little indeed), you’d have found them even before you posted.
But instead, you chose to make a thinly veiled, and in my opinion rather snide, ad hominem against Gavin himself, when you said, “The Mistaken Assumptions are your’s and your’s alone.”
Now you want to get on a high horse and complain about how you’ve been attacked personally. The greatest damage to your reputation, on this blog, has come from your own comments.
An since your last sentence indicates you’re absolutely convinced that it is not possible to develop the models/methods/application procedures in the absence of the observed data, why did you ask in the first place? Here’s my guess: you had already decided it’s not possible, and you were making another (thinly veiled) derogatory implication against climate models.
2 July 2007 at 15:58
Thanks, Adam; I’m an “interested reader who’s short on time” myself, the cite helps. The page says:
“… quality assurance reviews…. include preprocessing checks on source data, time series checks that identify spurious changes in the mean and variance, spatial comparisons that verify the accuracy of the climatological mean and the seasonal cycle, and neighbor checks that identify outliers from both a serial and a spatial perspective.”
So you write “They pay no/little attention to the individual sites but just the data.”
“They” on the website page for GHCN-Monthly, I’d guess, are the data analysts at headquarters, and the reviews above seem appropriate for them to be doing.
It’d be interesting to know whether the analysts get a “ding” on their review — and inquire of whoever does the maintenance — any time they they detect a change meeting those criteria they use to review.
Do they get a “ding” to look at when someone goes out and scrapes and repaints the box or moves the instruments to a fresh box, is that what you’re wondering?
I’d guess that would be one good measure of whether the stations are getting proper maintenance — if the data analysts don’t notice an oddity occurring when maintenance is done (over time, over the range of the instruments deployed) then it’d suggest that maintenance is being done often enough by definition.
But I’m speculating.
> GHCN-Monthly is used operationally by NCDC to monitor long-term trends in temperature and precipitation….
2 July 2007 at 16:11
#24 Misconceptions about the UHIE (Dan Hughes)
It did not take me long to find this site: http://www.warwickhughes.com/climate/ where there is a lot of nonsense about the UHIE. I realise that this does not constitute definitive proof that “misconceptions are widespread”, but why go looking actively for more rubbish?
2 July 2007 at 16:59
>25, Mankoff
Thanks for your http://edgcm.columbia.edu/~mankoff/GISTEMP/
Very nice! it’s great to be able to see that info so easily for local curiosity purposes.
And thanks for giving “linear fits to the last 10, 25, and 50 years from 2007 (… when sufficient data exist)” as well.
Question– are there error bars for the linear fits? Do the shorter linear fits always have larger errors? I’d guess that’d be true on average, but a station if say improved or moved might have more accurate info recently than overall. Dunno if it’s even available info let alone possible to show.
2 July 2007 at 16:59
re: #28
More completely I said, “I would ask again for independent sources for the “Mistaken Assumption(s)”, but I am now sure that there are none. The Mistaken Assumptions are your’s and your’s alone.” I think that given no pointers to sources for the statements I made a good assumption; not a ” … and in my opinion rather snide, ad hominem against Gavin himself.”
It is very ironic given that you said, ” … and Roger Pielke Sr.’s blog (http://climatesci.colorado.edu/), as places you would find the aforementioned misconceptions. Apparently you weren’t willing to do a google search for either, or to do a little rummaging around this site to find what they were.” That I now point you to this.
2 July 2007 at 17:35
So the new spectator sport is Attack The Model. Foo. What I’ve noticed is a pattern where someone has just enough intellectual stamina to notice that there is a pattern to the overall data and science (which many of us now accept) but not enough to understand where that pattern came from (which most of us at least struggle to understand). The “denialist” personality seems bent on joining the discussion as a peer but without actually accepting the intellectual challenges. Which is NOT to say that there is no room for well-reasoned questioning of data and processes; RC has provided a forum for exactly this, and those who avail themselves of the resources here and elsewhere to further the evaluation of the science are always warmly received in my observation.
The intellectual challenges cannot be down played. This really is rocket science. One doesn’t need to be a genius to join the discussion (look mom! I’m on RC!) but one DOES need to exhibit some basic respect for the combined efforts of countless women and men working very hard on extremely hard problems, an effort that is at best under appreciated and (it seems) usually misunderstood.
2 July 2007 at 17:38
Gavin,
I would appreciate if you add the link to Pielkes own response to your posting:
http://climatesci.colorado.edu/2007/07/02/climate-science-responds-to-real-climates-web-posting-of-july-2-2007/
2 July 2007 at 18:21
Pielke, Sr., specifically cites evidence of Lower Troposphere warming, Middle Troposphere warming, and Lower Stratosphere cooling in time series from the 1980s onwards:
Pielke Sr., R.A. 2007: The Human Impact on Weather and Climate. Bonn, Germany, June 5, 2007
He is clearly not denying that warming is taking place insofar as he specifically endorses temperature records showing that warming is taking place, and he is also concerned about human contributions to these changes. Pielke believes ocean heat content changes are the most reliable metric for assessing global heating and cooling.
But he is also rightly concerned regarding the unreliability of the land surface temperature data, as we all should be. Precisely because there is independent evidence of warming, those climatologists most concerned about AGW should be not be afraid of efforts to understand the nature and extent of the flaws in our surface station temperature records.
A commitment to empirical reality is so fundamental to science that the impulse to ridicule the documentation of microsite problems at surface stations is in danger of back-firing. Anthony Watts has maintained a civil, constructive tone and manner throughout his efforts to document surface station micro-climates. It may well be that his work turns out to be completely irrelevant in the long run. But it is difficult to understand how anyone with a commitment to the most basic scientific ethos could possibly complain about his efforts. Watts’ documentation project is something that every engineer, every high school science teacher, every 9th grade science student can understand - and believe in. His project is as close to Mom and Apple Pie as science gets. Attacking his documentation effort is a very bad p.r. move.
At present some people seem to think that the number of stations with unreliable data is small and could not possibly impact the large data sets on which climate science is based. Maybe so. But the fact is at present no one really knows just how pervasive the problems are. I would not want to bet on the accuracy of our existing system of surface stations. Suppose 60 station sites are selected at random for a trial experiment (ideally, but unrealistically, double-blind) in which an extremely high quality measurement instrument is installed away from all buildings, paved surfaces, etc. and similarly rigorous measurement protocol is followed, and this high quality set of measurements are then compared for a specified period to the data being collected from existing stations. Would Gavin bet that the average deviation between temperatures being recorded at existing stations and those of the hypothetical rigorous network are within .1 degree C? 1 degree C? Or might the problem be worse than 1 degree off on such a random sample of sites?
It seems as if all we really know about surface station data at present is that it is unreliable. We really have no idea exactly how unreliable it is. Why not simply agree to eliminate all dependence on surface station data and focus exclusively on other measures of increased temperature over the last couple decades as Pielke recommends?
[Response: I don’t know who you are addressing here. I have neither complained about nor ridiculed Watts’ efforts. I have merely pointed out that they are unlikely to have as much impact as some would like them to. All data is imperfect, all models are flawed. But, the data do have useful information contained within them, and the models do a reasonable job at simulating what happens. To arbitrarily exclude any source of information simply because it is not perfect is foolish - understanding is only going to come from using as many different independent lines of evidence as possible. There are plenty of additional lines of evidence that suggest the large scale gridded products are consistent with what we can see in other measures, and so there is no need to throw out the baby with the bath-water. -gavin]
2 July 2007 at 18:43
#28 I read ClimateAudit often and would like to comment. For assumption #1, the majority on CA were concerned that despite the increase in energy use and population, Hansen did NOT show some UHI. It was the opinion of commenters that one would expect some. The only comments I remember being close to UHI did not exist were intended IMO to be funny or sarcastic.
#2 I don’t think I have seen anyone claim station data was perfect, anywhere. Instead I see lots of discussion on UHI, stations, Hansen, and other items questioning the extent and reliability of temperature data and other data in general. I tend to give some leeway to comments due to the abbreviated nature of posts. Take as example: “That is to say, that if a station in Tennessee has a particular warm or cool month, it is likely that temperatures in New Jersey say, also had a similar anomaly.” I do not think anyone, has claimed that they can tell the world’s temperature anomolies from just 2 data points by one particularly warm or cool month. But I realize what was meant, a good correlation is still good for something even if someone has not explained it to everyone’s satisfaction. The conversations have been on real or assumed problems with data and sites.
#3 I guess this is a problem with abbreviated comments. NOAA, whom was acknowledged in this argument, does run the US NWS. It is hard to see if we are discussing data that was used for grids for USA, that such a discussion did not occur. It is the use of “produced” versus the discussions on ClimaeAudit of the underlying data, and how the data became the “product”. The comments I have seen do not dwell on GISS or CRU “collecting” the data. Perhaps you or others have spotted this problem because of your expertise in this area. Some of us are looking at the data and relationships of how one gets from point A to point B, not that the attributions are entirely correct.
#4 That Global mean trends are not simply averages of all weather stations has been discussed in many different ways, none of which meet such a simplistic sentence that I remember except comments to the effect how could a person discern if only one trend could be used or how much noise using all the trends entail. There is no question that many on ClimateAudit question much. But this questioning argues directly against assumption #4 applying to CA blog.
I think #5 should state computer climate model projections. After all CA seems to have questions about all models and projections. Even better statement would be “Finding problems with individual station data somehow affects computer climate model projections or it really should because you can’t rely on a model that does not use real data for confirmation”. LOL. I admit I also like to use models that have been verified some way. Otherwise, the model may be as good as a good chess problem…elegant and intelligent, but not particularly useful.
#6 is actually something I have seen the opposite on CA. The comments include not only is global warming occurring today, but several times in the last 10,000 years. They also have the cooling in different times as well, which would imply warming periods at other times.
I do not frequent Roger Pielke Sr.’s blog. You have taken Dan Hughes to task, but included CA through editor’s response to #12. Perhaps you should do some of the work you deride him for not doing. I say this because, though I have seen comments on CA that perhaps could somehow fit these descriptions of assumptions, I find that typically by the most senseless reading of the comment. I note that the editor did not have links to good examples on CA where these assumptions were stated or implicit. I would like to read these and see if it is by one person or many. I would also like to read their reasoning. Such reasoning appears poor to me, but I would rather read and make up my mind, rather than just assume their reasoning is poor. So I would like you to do something constructive for those of us who don’t see what you do but want to look and make up our own minds…post some links.
2 July 2007 at 19:03
Pielke has suggested that you have “ignored” the following two papers in composing this post:
“Pielke Sr., R.A., C. Davey, D. Niyogi, S. Fall, J. Steinweg-Woods, K. Hubbard, X. Lin, M. Cai, Y.-K. Lim, H. Li, J. Nielsen-Gammon, K. Gallo, R. Hale, R. Mahmood, R.T. McNider, and P. Blanken, 2007: Unresolved issues with the assessment of multi-decadal global land surface temperature trends. J. Geophys. Res. in press.”
“Pielke Sr., R.A. J. Nielsen-Gammon, C. Davey, J. Angel, O. Bliss, M. Cai, N. Doesken, S. Fall, D. Niyogi, K. Gallo, R. Hale, K.G. Hubbard, X. Lin, H. Li, and S. Raman, 2007: Documentation of uncertainties and biases associated with surface temperature measurement sites for climate change assessment. Bull. Amer. Meteor. Soc., in press”
When I pointed out that he lists these as “in press”, he claimed that you are “aware” of them. Can you shed some light on this.
[Response: I saw a preprint of the first paper a while back, but I have not seen the final version, nor have I seen the second paper. Roger has my email address, if he wanted me to read them, he could send them along. However, I stress what I said above, I have nowhere said this effort was not worthwhile, indeed I stated that “more information is always useful” - my point was simply that it isn’t going to have the impact some think it will. Roger’s rather aggressive response misses the point entirely. - gavin]
2 July 2007 at 19:41
It seems clear that the UHI effect is a real physical effect and the complaint from AGW skeptics and denialists is that the strong (and real) warming in urban areas is contaminating regional and global temperature averages.
I have thought for a while that the “problem” would go away if the the regional and global averages were area-weighted averages of the data from the various weather stations.
Specifically, use the locations of the weather stations to construct a Voronoi tessellation (see en.wikipedia.org/Voronoi_diagram for a description of the construction) of the land surface of the earth. Assign an area-weight to the temperature data from each station equal to the area of that station’s Voronoi “cell”. Use those area-weights to construct the regional/global averages. This would have the effects of decreasing the weights assigned to urban weather stations — since there are lots of them, they are relatively close together, and the areas of their Voronoi cells will be relatively small — and correspondingly increasing the weights assigned to rural weather locations. This process also captures and appropriately weights the real and strong warming occurring in urban areas.
This Voronoi decomposition could also be used to construct (again by area weighting) gridded temperature time series.
Best regards.
2 July 2007 at 20:12
The things I wonder when I’m measuring something, what is the detail I can get into significant digit wise, and when I was last calibrated to that level of detail. Then how frequent and consistent is my sampling interval. Next is where everything is located, so am I measuring what I think I am.
I would like to see some calculations and figures of what dumping CO2 into the atmosphere over the San Francisco area from 1961-1975 has had on the temperature here from 1991-2005. Or something somewhat similar for someplace or another, esp if compared to a similarly sized rural area etc. There doesn’t usually seem to be that level of detail reported.
2 July 2007 at 22:02
Took a look at Steve McIntyre’s site. Normally something I wouldn’t care to do given that the major scientific bodies and peer reviewed reports came out strongly in favor of Mike Mann - and it is pretty obvious that Steve McIntyre is a man with a vendetta and no love for the hockey stick, but…
Yikes!
I can’t tell whether he is accusing the entire climatology profession of grand conspiracy or simply gross incompetance. But I am not seeing anything resembling systematic analysis in any meaningful sense - at least not yet. Mostly just innuendo and cherry-picking.
Now please pardon me while I go take a shower…
2 July 2007 at 22:28
35:
“Anthony Watts has maintained a civil, constructive tone and manner throughout his efforts to document surface station micro-climates.”
Anthony Watts site, while it may be worthwhile in some way, is meant as a rhetorical “gotcha.” Take the two examples presented on the fornt page of his site. One shows a station in a clearly urban environment, the other in a more rural setting. But the trick is in showing the temp plots inset with the pictures. The bad, mean and undisciplined station shows warming, and the lovely, calm and good station shows cooling. The visual argument is clear: Any wamring must be due to the mean station; therefore, no worries.
If the pictures weren’t meant for a rhetoircal “gotcha” then why cherrypick a cooling, rural station? Why show inset graphs of the temp at all, as this is a red herring vis a vis ideal station setup?
2 July 2007 at 22:35
Thanks for the article Gavin. You prompted me to look at what information the Australian Bureau of Meteorology has on their website about their monitoring program.
Apparently Australia too have thousands of stations. And a sub-set of these have been designated ‘reference’ stations. These were selected using the following criteria:
* High quality and long climate records,
* A location in an area away from large urban centres.
* A reasonable likelihood of continued, long-term operation.
I presume that in order to identify anomalies, data from all the other stations is compared to the data from the reference stations. This would enable the data to be corrected or discarded. Because many of the stations are now automatic with live uplinks to the Bureau, I imagine that it is possible or will soon be possible for problems with stations to be i9dentified as soon as they occur, and for technicians to be dispatched to fix them.
There is a map of the reference stations here. If you click on the orange dots you will see a photograph of each station. Australia is a big empty place, so you’ll see that that they are almost all in quiet lonely places.
If people want to see plots and summary statistics of data derived from the monitoring network, then look here. Plots with particular relevance to tracking climate change are here. A warning to the skeptics - there are very obvious trends for most of the parameters, which accord with climate model predictions for a hotter drier future. A warning for Australians in general, if the trends continue, we’re stuffed. A warning for everyone, if you want to see the Great Barrier Reef or the Northern Tropics rain forests, you had better be quick.
As stated here, the bureau “will soon finish reprocessing much of the data which is used to calculate the climate statistics”.
However, for now there is no detail on the Bureau’s website about how this is being done.
2 July 2007 at 23:08
Another CA (and lately, Pielke) reader here, and I agree with the comments in #36.
In my view no-one who follows the tenets of science should be afraid of criticism and/or an audit of their work - it should be welcomed, because if you’re right, an audit will show it, and if you are wrong, you will have learned something. In either case, knowledge will be gained.
Don’t be afraid of those who examine those pesky details, be grateful that your work has such an impact! Don’t say “it doesn’t matter”, investigate and publish the results of that investigation! Don’t complain about “denialists”, gather data, do experiments, write papers and prove them wrong! And most of all, remember that the truth will win out in the end. It might not be what you think it is now (it probably won’t be, if history is any guide), but providing you contribute to the data and the debate, your input is most welcome - right *or* wrong, pro- *or* anti-, consensus *or* outlier, all contribute, because, if nothing else, they make you *think* and *act*.
2 July 2007 at 23:13
27 gavin> The point is not that any of these things might have a large effect, but that the effects in different stations are going to be uncorrelated.
How can we be sure of that? There are many possible reasons for correlation. One simple one is the introduction of the electronic MMTS to replace manual thermometer reading. I think MMTS uses an RS232 cable with limited length, so sensors may have been relocated closer to buildings, which could systematically increase reported temperature.
3 July 2007 at 0:31
#43: unconvinced
People can poke at data for at least two reasons:
a) Because they do science, and the idea is to get things as right as possible, and that’s good science, and real scientists do it a lot.
OR
b) They want to create uncertainty and controversy, and waste as much time as possible for real researchers who may produce results they don’t like.
Without claiming anyone in particular is doing this here, what you posted is indistinguishable from the classic playbook, famously expressed by Brown & Williamson in 1969 about fighting the cigarette/cancer link:
‘Doubt is our product, since it is the best means of competing with the “body of fact” that exists in the mind of the general public. It is also the best mens of establishing a controversy.’
The whole idea is “that more study is needed” on anything where the outcome isn’t what you like.
The technique was well-learned in the tobacco wars, and used repeatedly (often via the same lobbyists, PR organizations, thinktanks) for:
- smoking
- acid rain
- CFCs
- AGW
Sometimes this strategy is called insisting on “sound science” (that’s the code-phrase), which means in practice: we will accept any random crackpot idea if it supports us, and if there is a strong scientific consensus that we don’t like, “sound science” requires that we study it more until it becomes 100% certain, or if necessary, even better
before any decisions would be made, i.e., preferably never.
If this is idea is new to you, you’ll want to start reading some relevant history, such as Chris Mooney’s first book.
3 July 2007 at 0:40
Your statement on mistaken assumption #5 about climate model projections being theoretically based rather than empirically based is well made. On the other hand, would I be wrong in assuming that a siting issue, like a bank of A/C exhaust vents near a thermometer, would influence the USHCN temperature record at that site?
I understand the attempts to adjust for inhomogeneities. It just seems that of the small number of sites recently photographically surveyed and with the USHCN being [self-described] as a high quality data set, there are a lot of siting issues that might imply a general lack of quality control re: NOAA’s published siting standards and which might speak even more poorly for QC of surface temp. measurement in countries without high budgeting for projects like this. Unlike the modelling projections, the instrumental record is empirical. I just don’t understand how fairly plain heat biases, oil drum trash burners, A/C exhausts, etc., near thermometers are irrelevant to a given site’s recorded Tmax. Since the USHCN states its goal is to assist in detecting regional climate change, US siting issues such as systemic heat biases seem fairly relevant to me.
3 July 2007 at 1:26
It seems that attacks on the validity of the surface temperature record as an attempt to cast doubt on the recent warming trend would have been a bit more convincing back in the day when there were competing satellite temperature records that suggested a cooling trend. These days, with the multiple independent lines of evidence supporting the current anomoly, people seem to be grasping at straws by focusing on poorly sited temperature stations. Yes, there are certainly temperature stations that could be better designed, and yes, the observed surface temperature record might change slightly if all temperature stations were making precisely accurate measurements. Would this change anything substantive about our current understanding of the past warming trend worldwide? Unlikely.
3 July 2007 at 2:18
Here in Australia, we have a large network of weather station, across our (rather big) country. Some are automated (AWS), others are operated in conjunction with proffessional weather observers while others are operated with the help of volunteers (SYNOPs).
Each weather station is attempted to be constructed to WMO standards, in order to reduce interference to a minimum. Also, each station is checked by an engineer every 6 months, (which is again a WMO standard).
Despite this, the station data is imperfect. For instance, a rain event in the south eastern state of Victoria recorded 300mm of rain in 2 hours at one weather station, while the neighbouring stations recorded closer to 60mm. As such, automated and human checks of this data are made before it is put into the climatic data-base.
The data we use is reasonably reliable. There are some problems, and we always welcome input from the public into increasing the fidelity of our network (for example, is a tree has grown to shade our Stevons Screens in the afternoon). As such, projects like surfacestation.org are valuble. But they are unlikley to have a huge effect on the surface temperature record. There are tombs of literature on the subject of the placement of weather stations, and organisations such as BoM take extrodinary care in the placement of stations.
Good on them for trying to help, but in the long run, the averaged temperature record is unlikely to change much.
3 July 2007 at 4:24
Some, but not all, UK weather stations have records of soil temperature dating back over 100 years. An extensive study by A. M. Garca-Suarez and C.J. Butler at Armagh Observatory, N. Ireland found the following:-
‘We have analysed the trends in four long meteorological time series from Armagh Observatory and compared with series from other Irish sites where available. We find that maximum and minimum temperatures have risen in line with global averages but minima have risen faster than maxima thereby reducing the daily temperature range. The total number of hours of bright sunshine has fallen since 1885 at the four sites studied which is consistent with both a rise in cloudiness and the fall in the daily temperature range. Over the past century, soil temperatures at both 30cm and 100cm depths, have risen twice as fast as air temperature.’
see:-
climate.arm.ac.uk/calibrated/soil/soil11.ps
http://climate.arm.ac.uk/calibrated/soil/soilT_Garcia-Suarez_2005.pdf
http://climate.arm.ac.uk/calibrated/soil/soil11.pdf
3 July 2007 at 6:21
I don’t quit see how you can say that individual stations do not matter when a network is a collection of individual stations. I also fail to understand how verification and validation is wrong within the context of making economic and societal changes based on a theory. On the skeptic side I see many wanting to validate and verify all information and on the AGW (CO2) proponent side I see reasoning why validation and verification is not needed.
I say that transparency is the only way to do any thing and something as important as this needs all the assistance that it can get. Release the data, processes, and procedures and take what help you can get. Coming up with arguments for why inputs are to be ignored, such as how many of the stations that are collecting temperature reading are not properly set up or operated, or hiding which stations are used to determine the UHI off-set.
I really don’t expect that this will be posted; most of my posts are not accepted because I am skeptical of taking anyone’s word on just about anything. I just fail to see how putting up a strawman argument instead of actually saying “Ok, check all the stations and help us identify the actual conditions the readings were collect under so we can have the best data.” is doing anything good.
3 July 2007 at 7:09
The following comments can be found on climate audit which imply belief in 4 of the assumptions. I was particularly irritated with the first comment because it is clear from the rest of the article (about Parker 2006) that Steve McIntyre understands the difference, but the diversion completely confused the subsequent discussion. Google them to find the context.
1. Steve McIntyre: If you are not a climate scientist (or a realclimate reader), you would almost certainly believe, from your own experience, that cities are warmer than the surrounding countryside
2. Anthony Watts: If you were conducting an experiment where the results were likely to shape national and world policy, wouldn’t it be prudent to check the origin of the data set?
5. Bob Meyer: Is Schmidt actually suggesting that large changes in the individual station data would have no effect on the grid data because by some occult process they have already “fixed” the deviant station data?
6. David Stockwell: if removing the contaminated stations reduced the 20th century increase to the point there was no increase in temperature, how could that possibly improve model fit, when the models show an increase of 0.5deg?
3 July 2007 at 8:52
re: 50. “I don’t quit (sic) see how you can say that individual stations do not matter when a network is a collection of individual stations.”
I have spent over two decades visiting and approving various meteorological data instrumentation sites for various uses. One critical issue that seems to be conveniently avoided by denialists is that most long-term climate data stations are not urban or airport sites where one gets the daily or current temperature on the radio or TV. Which essentially renders the UHI issue moot. There are well over one thousand long-term climate data stations across the United States. There are a few hundred in my state alone. The overwhelming majority are well-sited and in rural areas; denialists try to make it sound like urban sites are more common. Supposedly (conveniently?) the surfacestations.org study by a non-climate scientist (a “former TV meteorologist”) checked just 40 of them and draws an unpublished conclusion from that small set of select stations. That is about 3 percent of the purported 1200+ stations. It is not clear how the subset of 40 were chosen. There also seems to be a denialist’s myopic tunnelvision focusing on the US observations without realizing that they comprise a small fraction of the *global* database of surface observations. In short, the denialists sudden attempts to try to discredit the database outside of the scientific arena is nothing short of classic data cherry-picking. Of course it is then quickly (desparately?) picked up and regurgitated by typical non-science suspects such as the supposed journalist at the pittsburghlive.com link.
Then there is the fact that surface observations are just one indicator of global warming trends. As noted above, the recent warming “is seen in the oceans, the atmosphere, in Arctic sea ice retreat, in glacier recession, earlier springs, reduced snow cover etc.” Another “inconvenient truth” for denialists to avoid mentioning or acknowledging while overblowing the UHI issue.
3 July 2007 at 8:56
This little bit might help some get an idea of the importance of microsite issues. As referenced in Gavin’s text NOAA are building a Climate Reference Network. Much care has gone into siting. I’ll quote from a tom Karl document avaiable on NOAA’s web site.
Essentialy, it gives you an idea of how to rate sites and the kind of error you get when you put a site around pavement, buildings etc. So, in evaluating the historical netwrk for microsite issues, one should keep this in mind. Microsite issues can be more critical than an urban/rural distinction. So, here is Tom Karl:
NOAA/NESDIS NOAA-CRN/OSD-2002-0002ROUD0
CRN Series December 10, 2002
X030 DCN 06
The USCRN will use the classification scheme below to document the “meteorological measurements representativity” at each site. This scheme, described by Michel Leroy (1998), is being used by Meteo-France to classify their network of approximately 550 stations. The classification ranges from 1 to 5 for each measured
parameter. The errors for the different classes are estimated values.
Class 1 - Flat and horizontal ground surrounded by a clear surface with a slope below 1/3
(<19deg). Grass/low vegetation ground cover <10 centimeters high. Sensors located at
least 100 meters from artificial heating or reflecting surfaces, such as buildings, concrete
surfaces, and parking lots. Far from large bodies of water, except if it is representative of
the area, and then located at least 100 meters away. No shading when the sun elevation >3 degrees.
Class 2 - Same as Class 1 with the following differences. Surrounding Vegetation <25
centimeters. Artificial heating sources within 30m. No shading for a sun elevation >5deg.
Class 3 (error 1C) - Same as Class 2, except no artificial heating sources within 10
meters.
Class 4 (error >= 2C) - Artificial heating sources <10 meters.
Class 5 (error >= 5C) - Temperature sensor located next to/above an artificial heating
source, such a building, roof top, parking lot, or concrete surface.”
That’s not a climate denialist. That’s the criteria NOAA are using to establish the new network. It would seem reasonable to apply the same criteria to the old network. It might seem prudent to not use sites that are class 5.
3 July 2007 at 9:40
What about places where the urban heat island might be important? California is city from north of Los Angeles down to Mexico. I think a thermometer in the middle of all that cement is valid data. If a city is hotter over time, isn’t that a real finding? It seems just as wrong to throw out a reading from downtown LA, and substitute a rural reading for that land area, as it would to make a reading from LA stand in for a rural area.
Is this an issue simply because the trend analysis assumes an equal land area for each temperature measurement used?
3 July 2007 at 9:41
Implications of belief in 4 or not, again, how can a review of stations do any harm? And if there is any “uncertainty or controversy” in the siting or data, it would be better removed. Let’s see what the differences are.
3 July 2007 at 10:01
A couple of points. People need to think not just about whether a particular siting issue, etc. will introduce an error, but what kind of error it will introduce. This post points out that temperature is oversampled by nearly 2 orders of magnitude over what is needed to produce a reasonable picture of temperatures on Earth. If a particular site regularly produces temperature readings higher than those of surrounding sites, this is easily identifiable and probably correctable. If a site produces a short-term spike, again, this will be evident wrt not only the surrounding stations, but also the readings of the same station.
Now let us say that we change instrumentation. If our new instrumentation produces a shift relative to the old instrumentation, that will again be easily identifiable, and the origin of the anomaly would be resolved.
Folks, we are talking about a GLOBAL, trend persisting >30 years. It is consistent with many other trends we are also seeing via completely independent measurements. It is consistent with what would be predicted given well established physical models of the atmosphere. I just don’t see how going around taking photos of a few ill sited stations is going to dent the overwhelming evidence that we are warming.
On the other hand, to represent these few anomalies as the norm rather than the exception can only have the purpose of increasing doubt among the lay population who may not be familiar with the overwhelming evidence. That is not science, but anti-science.
Another point that has been stated again and again but still doesn’t seem to be getting through: The parameters in the models are not unconstrained. There are physical processes and phenomena independent of the temperature than constrain most of these parameters to a pretty narrow range. The models are physics based–not best fits to the data. Changing data for a few stations may increase the anomaly between model and observed data for those few stations. It will not substantively change the models.
3 July 2007 at 10:20
> if there is any “uncertainty or controversy” in the siting or data, it would be better removed.
All that would leave is religion, you know.
3 July 2007 at 10:37
Steven Mosher,
I wasn’t able to find the link to this document by Karl. What is the procedure recommended there for dealing with class 5s? Are they discarded, or is some correction applied to them?
3 July 2007 at 11:07
In #44 Steve Reynolds throws some spaghetti against the wall
“One simple one is the introduction of the electronic MMTS to replace manual thermometer reading. I think MMTS uses an RS232 cable with limited length, so sensors may have been relocated closer to buildings, which could systematically increase reported temperature.”
Except that the NWS system used fiber optic modems for the RS-232 communication. Even using wires, while 19.2 kbaud RS-232 is short range (50 feet) at lower baud rates the range is much longer, 500 feet at 9.6 kb.
I rather suspect that the NWS was aware of the issue. Operators of the automatic weather stations could easily tell us bout this.
3 July 2007 at 11:26
I’m constantly amazed by the general assumption by many laypeople (particularly in the US) that the people devoting their careers to science are generally incompetent. I’m not a climatologists or meteorologist. So I make the assumption that the people who are involved in the these fields are for the most part competent and diligent. So I follow their work with interest while I get on with my own. Sure they will make mistakes, and science is often a two steps forward, one step back process. But on the whole, it seems reasonable both to accept that they are doing their job to the best of their abilities, and to accept that on the whole the science is advancing and that our understanding of the climate system is improving all the time. The climate monitoring networks around the World are very important. Why do people assume that they are run clowns and that the people in charge are for some reason ignoring the inherent messiness of real world data. Their job is all about working with the data. Why do you assume that they don’t know what they are doing?
In his article, Gavin gave a link to a web page page at the National Environmental satellite, Data and Environmental Network website that explains that the United States Historical Climatology Network is a high quality subset of the U.S. Cooperative Observer Network operated by NOAA’s National Weather Surface. It then goes on to explain how quality control is applied to this data. You can read it here. The page explains how the datasets from each station is compared - using various statistical techniques - with (up to 40) other stations that are in places with similar climate. This allows blocks of dodgy data, or trends that are cause by things such as changes to micro-climate, to be spotted and corrected.
The article goes into a fair bit of detail, and provides a list of papers that will take you into much more detail still. Clearly the people who are running the network and working with the data acknowledge the issues with collecting and analyzing real world data. And they have done a huge amount of work to identify which series of data from which stations are problematic, and to correct for it or if necessary exclude it. Furthermore, they continue to monitor the quality of the data from each and every station coming from the network and to improve their techniques.
What is with all you people who are so intent on pretending that meteorologists and climatologists are somehow deluded, incompetent or malevolently pigheaded. Don’t you have anything better to do?
3 July 2007 at 11:37
mankoff (#26) wrote:
Looks like you are putting in the whole world!
Beautiful. I saw one station which the “contrarians” might want to use a little while longer - there are probably others. But I noticed another which had been trending down for quite a while. They might want to skip that one as its reversed course.
This is just the sort of thing that Google Earth is really good for. And of course they already have glacier data in one of the KMLs attached to photos and text on the web.
Once I was looking through and saw the circular thermokarst lakes - methane-emitting thaw lakes pocketing the permafrost. Someone commented on how funny they look, but didn’t know what they were. I knew what they were from the descriptions. However, there is a more recent discussion on KeyHole about them here. I know that they have been doing studies on their evolution. Anyway, I had mentioned them a little while back here. For those who are interested, there is an older post that mentions them here:
12 Dec 2005
Methane hydrates and global warming
http://www.realclimate.org/index.php/archives/2005/12/methane-hydrates-and-global-warming/
In anycase, they visually demonstrate the same point that Spencer made in #1. I am kind of hoping someone will begin a KML specifically on them. It probably already exists. But it would also be nice if all the KMLs relevant to climate change were gathered in the same place - or at least links to the sites where they are available. Somebody may already be doing that. I will have to check.
As for the temperature records, that it something really special. Great work…
Thank you.
3 July 2007 at 11:48
John Mashley (#45) wrote:
Thanks, John.
I couldn’t post the response that I had been writing - my temper was just a little too high to write anything particularly rational at the time and I knew it.
3 July 2007 at 12:02
#52:
“Supposedly (conveniently?) the surfacestations.org study by a non-climate scientist (a “former TV meteorologist”) checked just 40 of them and draws an unpublished conclusion from that small set of select stations. That is about 3 percent of the purported 1200+ stations. It is not clear how the subset of 40 were chosen.”
I believe that right now the goal is to document all of the 1200 or so USHCN and GHCN-GISS sites, not all surface stations in operation across the US. The effort depends on volunteers from across the country to document sites close to them, rather than have two or three individuals visit all 1200+ sites themselves. Because the effort is new, the volunteer pool is small and the few documented sites tend to be physically located near the volunteers. I don’t think there is anything more to read into the selection of the current subset of sites other than that is where the current volunteers happen to live.
It looks like as of yesterday that 84 sites have been documented to one degree or another, so they are up to about 7% now.
Question: how many sites need to be surveyed before the data are sufficient enough for RC scientists to take interest in analyzing them and drawing non-dubious conclusions? Nothing to be read into that question. In the past I worked as an engineer in semiconductor manufacturing and we spent an awful lot of time measuring our tools, gathering data and statistics, and recalibrating the tools, and I often try to draw mental parallels between the science we practiced and the science of climate research.
3 July 2007 at 12:08
As a possible soultion, perhaps we could use different methods to measure the Earth’s tmeprature anomaly. I’ve noticed that claims about the wamring of Mars, Neptune and Pluto are never challenged by sceptics or contrarians. Why not use the methods we use to measure these distant planets to measure the Earth? Since there is little criticism of planetary results, this seems to be be a good middle ground solution.
3 July 2007 at 12:17
Interesting, not one person advocates what is the only sensible thing to do: perform a thorough review of the surface temperature sites.
Instead, abstract, Machiavaellian motives are attached to anyone who dares question the suitability of the sites. Circle the wagons indeed.
3 July 2007 at 12:18
Re #55 [how can a review of stations do any harm?] It can take up the limited time of highly skilled people, that’s how. This in itself doesn’t mean it’s not worth doing, but it does mean the possible benefits need to be weighed against the costs. Given all the independent lines of evidence pointing to average surface warming over the last few decades (satellite measurements, ocean temperatures, sea-level rise, retreating glaciers, phenological changes, shifts in the ranges of temperature-sensitive species), it is highly implausible that it would lead to more than very minor refinements to the current overall picture.
3 July 2007 at 12:31
How to avoid problems with most land-based temperature
weather stations: Use lighthouses as thermometers for accurate and unbiased measurement of surface air temperature.
Here is some data I have obtained. Only a small portion is given due to message box input restrictions.
Weather Station Name: Quatsino, B.C.
Sample Interval : Month
Sample Temperature : Daily Minimum
Sample Range, Years : 1899-1999
El Nino Year 1900
Mean Monthly Min +/- SD Deg K
Jun 284.2 +/- 2.7
Dec 278.2 +/- 2.7
El Nino 1998
Mean Monthly Min +/- SD Deg K
Jun 281.1 +/- 1.0
Dec 274.6 +/- 2.9
La Nina Year 1899
Mean Monthly Min +/- SD Deg K
Jun 280.9 +/- 1.7
Dec 277.3 +/- 3.3
La Nina 1999
Mean Monthly Min +/- SD Deg K
Jun 282.0 +/- 2.0
Dec 275.2 +/- 2.1
These data show that there has been no change in the mean monthly temperature for solstice months at this site for a century. Although there is no stat sig diff among the means, the data suggests a slight cooling over the century.
Note the magnitude of the SD’s. These are so large there would have to an enormous increase in climate warming to be detected by this thermometer.
[Response: Or you could just look at the annual mean data for that station, and calculate an extremely significant trend of 0.91 +/- 0.47 deg C/ century (95% conf). - gavin]
3 July 2007 at 12:41
Boris (#64) wrote:
We have satellite measurements (essentially what you are asking for), ocean temperature measurements, the accelerating decline of the glaciers (Himalayan glaciers should all be gone by 2100), the accelerating decline of the Arctic Sea ice (it should be gone during the summers around 2020), the rising sea levels, the borehole measurements, the thermokarst lakes, the migration of animals, bacteria and viruses (hemorrhagic dengue in Mexico and Taiwann), the fungi at higher latitudes, the tree lines at higher latitudes and altitudes, etc.. This isn’t a matter of a honest difference of rational opinion. The science is on one side - and I am still trying to figure out what is on the other.
3 July 2007 at 12:53
Re: 64
Nice miss direction Boris. Just because someone is skeptical of CO2 based warming does not the same as does not believe in warming. You seem to be saying that if you dont believe the CO2 theory is correct that you do not believe in climate change. That is a false arguement. I believe in climate change, I just have read enough to know that I am not sure about CO2 and being told, that it right because it is an experts opinion does not cut it. I want to see a full and open debate about the facts, not opinion, not personal attacks, etc…
3 July 2007 at 12:56
Boris, Triana got shot down before launch. A satellite in one of the Lagrangian positions is far enough away to image the whole earth for such studies. Too bad that it was associated with Al Gore, maybe when the adults return we can take it out of mothballs and launch.
3 July 2007 at 12:58
re: 65. Because, as already stated several times here, it is a critical issue with respect to AGW despite anti-science denialists attempts to make it so. The warming trends are shown by ocean temperatures, sea-level rise, glacier retreats, satellite measurements, etc. And US measurements are certainly not the critical issue with respect to *global* measurements. Nothing abstract or “Machiavellian” about that in the least. To continue to focus on a small dataset without critical importance to the overall global dataset, other consistent trends and the issue as a whole is to data cherry-pick. A classic denialist move to create doubt, obfuscate, and stall. And frankly waste money. Shades of the acid rain debate of the 1980s.
3 July 2007 at 13:05
re: 69. Precisely. Except it has already been done. And the scientific debate is long over. Read the IPCC peer-reviewed reports which are linked to from this site. No opinions, no personal attacks, just the climate science research results conducted by actual climate scientists among others.
3 July 2007 at 13:11
Re #65 [not one person advocates what is the only sensible thing to do: perform a thorough review of the surface temperature sites. Instead, abstract, Machiavaellian motives are attached to anyone who dares question the suitability of the sites.] If such a course of action were agreed (and how many person-years would be needed?), the denialist response (despite all the independent lines of evidence) would be: “See! Even the AGW believers admit the surface temperature site data is worthless. It would be absurd to take any action while this huge uncertainty remains unresolved.” And of course no review, however thorough, would be deemed satisfactory. The motives I ascribe to the professional denialists (not the members of the public being fooled by them) may be considered Machievellian, but are not abstract: they are money - on the part of Exxon and its paid propagandists, for example; and commitment to “free-market” ideology - the Wall Street Journal editorial staff, for instance.
3 July 2007 at 13:13
Typo in 71: “…it is *not* a critical issue with respect to AGW…”
3 July 2007 at 13:40
Re 60. Craig, My experience has been that the people who are most vociferous in this debate tend to be those who understand the science the least. And since all the evidence is really only on one side, the only recourse of the denialists is to attack the competence and credibility of those who came up with the evidence. We see exactly the same sort of thing with the debates over evolution and over various conspiracy theories. If one has actual evidence, one is usually too busy publishing to get really nasty.
Of course some of what we are seeing is the usual sausage making of science writ large on an international stage. Some researchers do not feel that their pet theories and ideas have been given enough emphasis in the IPCC reports and in other expressions of scientific consensus. Ultimately, however, it is up to them to convince the scientific community that their ideas are important. Taking it directly to the public and press is anti-science. After all, how are they supposed to know the science if they haven’t studied it for 20 years like the experts?
3 July 2007 at 13:42
Dan (#71) wrote:
Yep.
I saw a post by McIntyre of the “unbiased” let’s-audit-your-science gig. An early version of an IPCC report had said something to the effect that global warming was evident in all major oceans, so he ignored all but a fairly small section of the Southern Ocean where he could point out that the temperature was actually decreasing. But temperatures rising as far down as 1500 meters below the sea surface, and I believe eighty meters are what is of greatest concern to hurricane formation.
Then there are a few glaciers in the world which are not as of yet falling into the step decline. Contrarians like to point those out, too. But the global trend is obvious and even more so if you do the math. Accelerating decline of global mass balance - looks something like if you threw your keys straight out. Then there is the growing thunder of glacial melt in Greenland and over a hundred glaciers picking up speed in the Western Peninsula of Antarctica.
3 July 2007 at 13:50
RE #69 Gavin: How can you can conclude that there is a “trend” in the data? These data say there is no trend.
[edit for brevity]
[Response: Possibly your definition of trend is different from mine (and everyone else’s). Take the annual mean data, fit a linear regression, examine whether slope of said regression is significantly greater than zero. Done. There is a trend and it’s pretty much in line with the trends everywhere else. You can make it more complicated, and you can subselect years so that nothing is significant, but you cannot claim there is no trend. Was it colder then and warmer now? Yes. - gavin]
3 July 2007 at 13:52
Bigcitylib,
I always enjoy your comments. Thanks for the civilized question.
The link is here. you should read everything on the site.
http://www1.ncdc.noaa.gov/pub/data/uscrn/documentation/program/X030FullDocumentD0.pdf
It is a wonderful program, so Karl and others need to be commended on creating a quality network.
The document covers site selection. That is, NOAA are trying to prevent the kind of siting issues that you see in the historical network, the network that Hadley and Goddard currently use. Have a look at the specifications for Proper siting.
In the historical network one can find examples of sites that appear to have changed gradually over time. Most humerous examples would be Lake Spaudling, Tahoe City, Marysville, Lodi, Livermore.
Metadata does not capture this, as Gavin notes. Metadata covers things like gross location, elevation, TOBS, and instrument changes.
Think about the MICROSITE issue as an “instrument drift.” Stations are not calibrated, small changes over time go undocumented.
For the CRN there are strict siting guidelines. Photos are required. And an expectation that the site wont change for 50-100 years. ( ask yourself why this is a requirement)
So, to answer your question, The CRN, I would suspect, would REJECT a class 5 site. At Worst, they would a RECORD of its clasification and photos. With the historical network we have neither. The point is the document shows people how to Rate a site for INCLUSION in the CRN. Bottom line: Marysville would be excluded. Lodi would be excluded. Lake spaulding would be excluded. tahoe city would be excluded. In fact, none of these sites or locations nearby are included in CRN.
Also,have a look at a diagrams of how a site should be constructed ( pg 17). This isnt a denialist document.
NOAA is a data source for CRU and GISS. It’s not Peilke saying this. Its Karl.
Now, here is a funny anecdotal thing. If you look at
MARYSVILLE photos for example, you will see a site in a parking lot. ( class 5) If you look at it’s anomaly graph ( ok you have to download the data and calculate this for yourself) you will see it getting hotter by the year. Now, move 20 miles to the northwest. Colusa, CA. (its a class 2 or 3) Construct it’s anomaly graph. Move 30 miles to the west of Marysville. Willows, california. Site is in a field. (class 1 or 2)
construct its anomlay graph. Now move 50 miles to the northwest. ORLAND. Visual inspection and photographic evidence shows a class 1 or class 2 site. construct it’s anolmaly graph.
Question, if the class 5 site show larger warming trends than the class 1-3 sites within 50 miles of that site what does that tell you about the wisdom of including a class 5 site in your grid estimate?
teledisconnection?
Propose a hypothesis. We have a site in Marysville
( used by GISS,, apparently but not by CRU) that is located in a parking lot. It’s a class 5 site, by NOAA CRN standards. It shows a warming trend, a substantial warming trend. Other sites in the area show no significant trends. These sites follow CRN guidelines.
Explain?
I look at that and I say, Well Tom Karl is right. We should pay attention to siting. We probably should not use data from class 5 sites. Ya think? We probably should not try to “adjust” the record; rather, FIX THE SITE or dont use it. CALIBRATE your instrument. Jeeze oh pete.
3 July 2007 at 14:20
An interesting recent Mori poll result of public opinion within the UK about climate change can be found at http://news.bbc.co.uk/1/hi/sci/tech/6263690.stm
Apparently, the survey reveals that dog mess is of more concern to the public than climate change.
I don’t know whether Mori asked any questions about calibration of metereological instrumentation and similar sorts of things.
3 July 2007 at 14:28
If you are studying the mating habits of New Zealand whistling frogs, then I think a case could be made that there aren’t the resources available to re-visit previously covered ground in the research.
However, the impact of CO2 warming could reach trillions. This article (http://www.iht.com/articles/2006/10/30/business/web.1030energy.php) notes spending on climate research has falling from $7.7B in 1979 to $3B today. Assuming a linear decrease over all that time, that is $153B the US has spent on climate research in the last 30 years. Surely there is budget to check and re-check a fundamental assertion that we are warming. And to cross check it several different ways.
It’s better to have a rock solid record indicating warming trends of 0.1 degree/decade than to have a flimsy record indicating 0.15 degree/decade. And you can bet after Anthony Watts has tossed out all the dicey stations that he himself will be a strong believer in the quality of the remaining stations. And they will still show warming.
There are a few on this board that screech “The science is settled” over and over. I’m not sure they are aware just how many times science has become unsettled in a matter of a few years.
It wasn’t too long ago that science had settled that ulcers were due to stress and that satellites indicated we were cooling. And then a ‘crackpot’ doctor found a bacteria called H Pylori and a math error was found and quickly that which had been settled became unsettled and then settled again. That is how science works.
Let folks throw darts. Let folks poke holes. It makes everything stronger. If it takes an army of 500 volunteers 3 hours each to identify high quality stations, then the cost to verify one of the foundations of the thesis was quite low relative to the total spend on climate research.
3 July 2007 at 14:38
I don’t see how any reasonable, intelligent person could disagree with that sentiment.
3 July 2007 at 14:40
RE 56.
As usual Ray makes a world of sense. If the land surface tempature record is OVERSAMPLED by an order of 2x, then it would make sense to remove stations that are clearly in violation of WMO siting standards and CRN siting guides. Thanks Ray!
I propose a test Ray, and Gavin can help.
Anthony Watts has concentrated his study starting from his home in Chico California, radiating outward. This is located in grid 35N-40N, 115W to 120W.
Gavin will publish the list of stations used to provide the grid estimate for this area– both for CRU and for GISS.
Gavin will publish the raw data and programs for adjusting this data.
Gavin will publsih the anomaly history for this grid.
Then, you look at the stations. You will eliminate station data that comes from stations that Violate WMO rules. You will eliminate station data from stations that are class 5. ( by buildings, pavement etc).
Question: does this microsite stuff matter?
Then you recalulate the grid with this reduced number of stations.
After all, the sampling is 2X, so you can cut half the stations right? right ray? just get rid of the stations that are impaired or potentially impaired by microsite issues.
So ray. Lets take the grid 35N to 40N 115W to 120W.
Lets eliminate stations that are class 5 according to NOAA standards. Then recalculate the grid.
Your math is better than mine, So you and gavin work it out. Should take a couple days or so.
[Response: sounds fine, except I have a day job. Someone else might want to volunteer. Note that GISS uses information from up to 1200km away, so that’s a lot of stations. Turn it around. Calculate the trends just with the ones you think are good, and see if it’s different to the GISS or CRU analysis. For GISS, the linear trend from 1900 to 2006, for that grid box is 0.8 deg. - gavin]
3 July 2007 at 15:26
RE: #77 The data say no trend. Look at the SD’s. End of argument. I have more data from lighthouses that support this conclusion.
[Response: I’ll have to admit you are persistent, but you are simply wrong. But since you don’t want to do the calculation, let’s throw it out there into the blogosphere and see what anyone else says. Is there a significant trend here or not? (PS. trend according to Numerical Recipes is 0.91 deg C/century, SD of trend 0.24). - gavin]
3 July 2007 at 15:38
Re 3 80 “Let folks throw darts. Let folks poke holes. It makes everything stronger. If it takes an army of 500 volunteers 3 hours each to identify high quality stations, then the cost to verify one of the foundations of the thesis was quite low relative to the total spend on climate research.”
You can throw all the darts and poke all the holes you want at this site, but I doubt many of them will influence the active researchers in the field of climatology - a couple of the RC moderators who frequently comment here, yes; but the many hundreds (thousands?) of scientists who are busy out in the field collecting data or in their laboratories analyzing data and writing grant proposals and research papers, probably not. I think you need to find a method to promote your skepticism in a way that those researchers will sit up an take notice (once again, publishing in reputable peer-reviewed journals is one way; presenting a paper at a research at a climatology research conference, is another; perhaps there are other ways); arguing with the mostly non-climatologists who actively participate in the RC threads will have virtually no impact, I’m afraid.
3 July 2007 at 15:42
Re #35: “Pielke believes ocean heat content changes are the most reliable metric for assessing global heating and cooling.”
This sounds good since the trend in ocean heat content would be very, very close to the trend for the whole system, but just try finding any sort of calculation of this metric on his site. The problem is that the data isn’t available to be able to produce it in a useful form. It doesn’t seem possible that even Roger is so obtuse as to be unable to grasp this point. (Bite your tongue, Gavin.)
Re #68: Just to note that we seem to have a record low Arctic sea ice anomaly going in the last few days.
3 July 2007 at 16:07
Re: #83 (Harold Pierce Jr.)
Gavin is right, the data linked to do indeed show a significant trend. Your protest “Look at the SD’s. End of argument.” indicates that you really don’t understand the statistics of trend analysis.
3 July 2007 at 16:17
59 Eli Rabett> Except that the NWS system used fiber optic modems for the RS-232 communication.
From your (informitive) link: “In the mid- and late-1980s, the widely used air temperature radiation shield called the Cotton Region Shelter (CRS) was gradually replaced by the Maximum and Minimum Temperature System
(MMTS) in the cooperative weather station network. In the 1990s the Automated Surface Observing System (ASOS) replaced conventional observations at National Weather Service (NWS) and Federal Aviation Administration stations that report hourly observations.”
The question is then how many MMTS in the cooperative weather station network were converted to ASOS?
I rather suspect that the number is small. Does anyone have that info?
3 July 2007 at 16:25
re 64
“I’ve noticed that claims about the wamring of Mars, Neptune and Pluto are never challenged by sceptics or contrarians. Why not use the methods we use to measure these distant planets to measure the Earth? Since there is little criticism of planetary results, this seems to be be a good middle ground solution”
Let’s see what planetologists have to say
The trend for a global warming on Mars since the last 20 years seems confirmed, but has actually apparently little to do with the earth warming. According to the NASA scientist who highlighted this warming, it is due to the deposits of bright dust on Mars surface.
http://humbabe.arc.nasa.gov/~fenton/
Note that this global warming as been studied by only one research team and presented in one article (to be compared to the thousands of articles studying climate trends on earth), based on partial satellite data, and there is a serious debate now amongst the planetologists community to determine if this is a persistent trend or if it will stop in a few years.
As for Pluto, I actually know of a few articles (a little small to make a consensus) that assesses plutonian atmosphere is thickening, presumably showing a warming of its surface. Knowing that Pluto is the most distant planet from the sun, that the amount of energy it receives from the sun is hundreds of times inferior to the one that reaches the earth, and that we almost don’t know anything about this little rock and its atmosphere(no probe has ever approached it), I wouldn’t bet much on a relevant and well established trend for now.
http://www.newscientist.com/article/mg17623653.100
http://www.space.com/scienceastronomy/pluto_warming_021009.html
Finally for Neptune, again I find only one relevant scientific study, from Hammel and Lockwood (Hammel, H. B., and G. W. Lockwood, 2007. Suggestive correlations between the brightness of Neptune, solar variability, and Earth’s temperature, Geophysical Research Letters).
?
They seem to establish an upward trend in infrared radiation of the planet since 1980, but no particular trend between 1950 and 1980.
This study, as far as I know, didn’t make much noise in the planetologists world. I’m not the most qualified to make a judgment on their scientific work, but the two authors seem eager to attribute those measurments to an increase of solar irradiance since 1980, though no serious discussion about the other possible mechanisms (like atmospheric changes) is made in the paper. More important, it is to be noticed this increase of solar irradiance as not been measured by anyone yet (despite the 24/7 observations of the solar activity since long before 1980). They also are eager to link this “warming” to the Earth global warming, recognizing themselves that they have found no serious correlation between the two phenomenon but yet stating:
“Nevertheless, the striking similarity of the temporal patterns of variation should not be ignored simply because of low formal statistical significance. If changing brightnesses and temperatures of two different planets are correlated, then some planetary climate changes may be due to variations in the solar system environment.”
Which is a quite unusual scientific statement (we have nothing to link those two phenomenon, but we still think they are linked anyway). By the way, could someone explain me what “suggestive correlation” exactly means
So basically, those uncontested planet warmings are based each one on a very few studies(as far as I know, if anyone finds new data, I’m interested). Each one is poorly measured. In the case of Neptune and Pluto, the mechanism for this supposed warming still has to be found.
Most important when going further, none can apparently be linked with Earth Global Warming.
Finally and for fun, one should try to google a little bit with “Pluto warming” and “Neptune warming”. I did it and found an impressive quantity of links to contrarian blogs, but not much to peer reviewed scientific literature
3 July 2007 at 16:39
Steve Mosher,
It really only makes sense to eliminate stations if they give consistently bad data. If the data are oversampled, any anomalies will be identifiable by rather simple analysis.
No system is ever perfect. The question you have to ask yourself is whether any improvement to the system will make a significant difference. I suspect that it would not for several reasons. First, as I said, in an oversampled system, anomalies are easy to identify. Second, we are looking at global trends, so unless there is a systematic error in siting/readings etc. bad stations will at worst produce noise on the overall trend. Even if a particular bad station had a paucity of good stations around it, it is unlikely that it would affect the global trend.
Should we look hard at station site quality for future stations. You bet! Should we have any doubt about the trends seen to date. No.
3 July 2007 at 18:26
>Assumption #6 “…If the station is moved now, there will be another potential artifact in the record.”
This appears to contradict #4 which suggests that individual stations have little effect on gridded data.
>An argument could certainly be made that continuity of a series is more important for long term monitoring.
It would be a poor argument indeed that preferred the continuity of problematic sitings over good data. Surely if there is a significant problem with sitings, the solution is to discard problematic data. Not that surfacestations.org is even close to showing that a significant problem exists yet!
Stepping aside from the whole GW debate, aren’t people hear surpised/shocked that there are multiple sites near A/C vents, ashpalt, and buildings?
3 July 2007 at 18:34
Steve Milesworthy #51
For Assumption 1. Steve McIntyre: “If you are not a climate scientist (or a realclimate reader), you would almost certainly believe, from your own experience, that cities are warmer than the surrounding countryside From that, itâ��s easy to conclude that as cities become bigger and as towns become cities and villages become towns, that there is a widespread impact on urban records from changes in landscape, which have to be considered before you can back out what portion is due to increased GHG. One of the main IPCC creeds is that the urban heat island effect has a negligible impact on large-scale averages such as CRU or GISS.”
It is quite plain that the difference is that Steve McIntyre is claiming that IPCC and climate scientists are ignoring (has negigible impact) what is an accepted fact. That assumption stated “Mainstream science” which is not what Steve Mcintyre stated. However one may feel, think, or know about AGW, taking a stated group(s) to task is not to take everyone such would be included by any reasonable definition of “mainstream science”, unless this is code for IPCC and climate scientists who make up only a small part of what is considered “mainstream science”.
#2 thinks that all station data are perfect.
“By not checking the point of data collection and â��assumingâ�� that the weather station meets the published NOAA and WMO standards appears to have been standard practice for many researchers. If you were conducting an experiment where the results were likely to shape national and world policy, wouldnâ��t it be prudent to check the origin of the data set? Government (NCDC, Karl, et al) was charged with providing a relatively homogenous data set.” Isn’t it prudent to check data? Perfection is not claimed, care is. The claim is that lack of care and incorrect assumptions (I would think verification) appear to have been standard practice. There is no claim of perfection here.
No. 5: “Finding problems with individual station data somehow affects climate model projections. This probably stems from a misunderstanding of the notion of a physical model as opposed to statistical model. However, the climate models used in the IPCC forecasts are not statistical, but are physical in nature.” I think the discussion of this item is most appropriate. It does highlight one of the major contentions or faults in current discussions. It is a computer model based on physics. It is not the physics itself. IPCC forecasts are not physical in nature, they are computer models of known physics. A problem with this is that it is unlikely all physical relations are known, or even could be modelled with current technology. But that does not make the models useless by any means. The question becomes how can the models be verified? It appears the assumption was made that the models used actual data for verification. Many have expressed concern that actual data was not used for verification. I am in that crowd. I expect that if IPCC presses for carbon reductions based on such, it will be strongly opposed until verification has been obtained and the verification itself verified. As it stands, if my state or the US proposed carbon reductions and could not provide the information in suitable format and every “i dotted and every t crossed”, I would vigorously oppose it. Not from any sense of denial, but from not having the information in hand that I could use to show management that the monies were a justifiable expense. I do not wish to be fired for incompetence.
#6. If only enough problems can be found, global warming will go away
“David Stockwell: if removing the contaminated stations reduced the 20th century increase to the point there was no increase in temperature, how could that possibly improve model fit, when the models show an increase of 0.5deg?” Steve these are two different concepts. Asking that question is valid for determining if the data fits the requirements of showing global warming. It has been stated by most if not all warming has occurred, the extent and how accurately we have measured this have been discussed. Nor is it trivial if you happen to have concluded that GW is equal to AGW. In order to determine the best course and plan, the extent and sensitivity of the relationship are needed. Otherwise you will be asking engineers such as myself to waste time and money. According to most AGW people, time should not be wasted. As an engineer in regulations and energy, money should not be wasted either. Lest you think there is some ulterior motive, remember an axiom of engineers, time and money are often interchangeable; Wasting money on a failed solution is also a waste of time.
3 July 2007 at 19:03
Re 65: - “Interesting, not one person advocates what is the only sensible thing to do: perform a thorough review of the surface temperature sites.
Instead, abstract, Machiavaellian motives are attached to anyone who dares question the suitability of the sites. Circle the wagons indeed. ”
As far as I am concerned go for it!!! The problem with people asking for such a review is normally they also ask for somebody, anybody, else to do it rather than themselves.
If you are capable of conducting such a review and are prepared to write the research proposal and get funding and do the man years of work necessary to do such a review then go for it. I am sure you would have the support of everyone in the field as long as you share the data and publish peer reviewed work.
The people that work in the field on climate science freely acknowledge the problems with the sensors however as they have problems getting funding and time for what they are struggling to do now they would rather work with the system they have and compensate for the problems. They are satisfied that the system even with it flaws, as long as you understand them, gives accurate enough answers.
The people who scream the loudest that the surface temperature record is flawed are strangely silent when it is suggested that they actually do something about it.
3 July 2007 at 19:24
A lot of posts on this thread have appealed to the logic of checking the data for correctness. Isn’t it prudent to check the data? Of course it is.
I suspect most of those posting such comments don’t realize just how much effort has been expended doing exactly that. Those who want to know more (and haven’t already made up their minds that AGW is a crock) should carefully read Hansen et al. 1999 and Hansen et al. 2001. The data are not perfect, neither are the procedures, but these papers belie the assertion that care has not been taken.
I would also add another mistaken assumption to the list:
Mistaken Assumption No. 7: Bad data will artificially inflate the estimated global warming. In fact bad data are as likely to artificially deflate the estimated warming as to inflate it. Those who wish to discredit AGW by insisting on more thorough data checking should consider that they may be unhappy to get what they ask for; when the data are checked even more carefully, we may find that the global surface temperature increase is even higher than presently believed.
3 July 2007 at 19:41
#91 John Pittman,
Hmm, making statements in support of the scientific consensus position:
Intergovernmental Panel on Climate Change (IPCC) 2007
Joint science academies� statement 2007
Joint science academies� statement 2005
Joint science academies� statement 2001
U.S. National Research Council, 2001
American Meteorological Society
American Geophysical Union
American Institute of Physics
American Astronomical Society
Federal Climate Change Science Program, 2006
American Association for the Advancement of Science
Stratigraphy Commission of the Geological Society of London
Geological Society of America
American Chemical Society
Engineers Australia (The Institution of Engineers Australia)
Making a completely mealy-mouthed, noncommital statement:
American Association of State Climatologists–they accept that humans are changing climate–just don’t know what it will mean.
Dissenting from the scientific consensus:
American Association of Petroleum Geologists (hmm, wonder why)–oh but wait, they’re considering changing their statement and moving into the mealy-mouthed camp.
Yeah, I’d say that mainstream science is pretty much in the consensus camp, wouldn’t you? Or did I miss a significant field relevant to climate change?
3 July 2007 at 19:47
Allow me to make a simple declarative statement and ask a simple direct question, neither having any motive other than clarification.
I see no error bounds on the data in this graph.
Can a true and correct trend be determined under this condition?
Thanks
3 July 2007 at 20:00
Ref #26
“Blue is cooling, red is warming, white is insufficient data (baseline years or recent years). Note all the white pins in Canada! For some reason they seem to have turned off their network in the late ’80s.”
As one who was involved in Environment Canada at the time that’s pretty well what happened. I won’t go into the details, but it still burns!
Great post and I appreciate the level of discussion that RC maintains!
3 July 2007 at 20:11
Re 89. Ian, it may surprise you, but the goal of science is not to take data with the smallest possible error, but rather to take data where the errors are understood. Errors that are understood can be corrected for or used to make bounding estimates, etc. Errors that are not understood cannot be guaranteed to stay insignificant in all applications.
So, continuity of a data set is a perfectly legitimate reason for not moving a station.
Also, note that Gavin said that the artifact would be in the record–that is the data, not in the model. Don’t confuse the two. And no, throwing out the data is not the answer. Data with errors/noise are not necessarily bad data. If it is intermittently bad, and you can identify the bad points, you use what’s still good. If it is skewed, you may be able to correct it. Even the information you get about the errors in the data is useful in correcting data.
It has been my experience that a graduate student who is desperate to get out of school is an excellent source for ideas on how to use marginal data. Of course, he or she would prefer to have pristine data, but if the choice is doing the experiment over again or correcting the data he or she has, most are more than willing to write an additional chapter on data correction in their thesis.
3 July 2007 at 20:28
==Post # 65 by Dan: ==
==”The warming trends are shown by ocean temperatures, sea-level rise, glacier retreats, satellite measurements, etc. And US measurements are certainly not the critical issue with respect to *global* measurements.”==
Dan, you are avoiding the issue. If surface temperature site data is being used by climate scientists, and it is, these sites must be properly audited, or the data sets must be discarded. The rest of your post is peripheral to the issue.
==Comment #65 by Nick Gotts:==
==”If such a course of action were agreed (and how many person-years would be needed?)”==
Not long to photograph the sites, that’s for sure. That this has not been carried out already on a regular basis by climate professionals using the data is astounding.
==”. . . . the denialist response (despite all the independent lines of evidence) would be: “See! Even the AGW believers admit the surface temperature site data is worthless. It would be absurd to take any action while this huge uncertainty remains unresolved.”==
We’re not doing anything serious about AGW at present anyways, so we might as well improve the data until we do, if we do, decide to act.
3 July 2007 at 21:52
People should be concerned about UHI for health reasons. Data trends at climate station with 100 years of record show increasing UHI in areas having experienced large economic growth like at Fort Collins, Billings, Minneapolis.
http://picasaweb.google.com/npatphotos
http://new.photos.yahoo.com/patneuman2000/albums
3 July 2007 at 23:53
Harold Pierce Jr,
I just did a quick regression analysis (using Excel) of the Quatsino, B.C. weather data. I looked at the annual average temperatures and obtained the exact same trend as Gavin — annual Tave has increased at the rate of 0.91deg per century. This trend is very highly significant (P=0.00026).
There’s 90+ years worth of data available. Seems kind of silly to toss out all of that and only look at a couple of data points in the manner that you did.
(BTW, why did they stop data collection in 1990??)
4 July 2007 at 1:18
> these sites must be properly audited, or the data sets must be discarded.
And you’re the decider?
4 July 2007 at 2:55
Just as an aside..
Urban areas (apparently from a google search, anyway) take up around 1% of the area of the planet as a rounded value. So a UHI of 3K would average out globally as 0.03K, or around 5% of the total AGW effect..
I suspect that the number above is an over estimate, but the conclusion would be that by removing UHI from the records we will be making a slight underestimate of global anthopogenic temperature increases.
4 July 2007 at 4:13
Re #98 [”See! Even the AGW believers admit the surface temperature site data is worthless. It would be absurd to take any action while this huge uncertainty remains unresolved.”==
We’re not doing anything serious about AGW at present anyways, so we might as well improve the data until we do, if we do, decide to act.]
You (deliberately?) miss the point. The rising temperature trend is abundantly clear from multiple lines of evidence. The main cause is known with a high degree of confidence. There are those who, for their own selfish reasons or from ideological conviction, continue to deny these facts. They will use any means they can to delay and obstruct the necessary action.
4 July 2007 at 5:09
Dan Hughes in #95 asks why there are not error bars on the points in a graph of yearly average temperatures from a single station in the GISSTEMP data set. Perhaps if he looked at the way the data is gathered into the GISSTEMP gridded temperature record (in detail of course) he would understand why.
4 July 2007 at 6:05
I seem to remember a hearing conducted in the House shortly after the Republican takeover of Congress in 1994 where the scientific basis of climate change was attacked. The hearing was co-chaired by Congressmen Tom Delay and James Doolittle. Doolittle and Delay–it would appear that the agenda has not changed much.
Most of science is not really about radical new discoveries, but rather about how to use imperfect data to make those new discoveries. Anyone who is alarmed by imperfectins in a dataset, probably hasn’t done much science. Why should we think that they are competent to carry out an analysis of the systematic errors contributed by station siting? Even a relatively simple jackknifing analysis to look for potential problem stations (probably much more profitable than a photo campaign) would represent a considerable level of effort given that it would have to be conducted over time and globally.
Then there is the question of what it would accomplish. There are well developed procedures for removing artifacts, glitches, etc. The trends shown by the land stations are consistent with every other line of evidence.
I am not saying that the effort to document station placement should not be done, but I wouldn’t assign it a high priority. Moreover, I certainly would not hold out any hope that it will change the conclusions of the IPCC analysis. Since there is zero indication that there is any problem with the conclusions drawn to date, policy should be made on the basis of those conclusions and not delayed for a detour down a rabbit hole.
4 July 2007 at 6:23
[[Why not use the methods we use to measure these distant planets to measure the Earth?]]
Because we’re standing on it.
Seriously, there is a lot of satellite data on the Earth’s climate. What makes you think there isn’t?
4 July 2007 at 6:38
[[[Response: I’ll have to admit you are persistent, but you are simply wrong. But since you don’t want to do the calculation, let’s throw it out there into the blogosphere and see what anyone else says. Is there a significant trend here or not? (PS. trend according to Numerical Recipes is 0.91 deg C/century, SD of trend 0.24). - gavin]]]
Gavin — I took the annual figures, eliminated the years with no figures (1895, 1907, 1908, and 1970), and regressed the annual figures on the year for the rest of them. With N = 92, I got 14% of variance accounted for by trend alone, and it was statistically significant at better than the 99.9% level, with t = 3.8 for the year variable. The slope was 0.009105 with 95% confidence level boundaries of 0.004354 to 0.013856. In short, there has been warming at this station and it has been significant. The guy you’re replying to doesn’t understand elementary statistics.
4 July 2007 at 6:51
Paul G - “Dan, you are avoiding the issue. If surface temperature site data is being used by climate scientists, and it is, these sites must be properly audited, or the data sets must be discarded”
So go ahead and do it!!! I am sure that everyone would welcome better data if that is the result of your ‘audit’. If you are not prepared to do it then you, like the rest of the community, will have to make do with what they have.
“Not long to photograph the sites, that’s for sure. That this has not been carried out already on a regular basis by climate professionals using the data is astounding.”
Is that your idea of an audit??????? What would a photograph give you?? I thought that you were asking for better quality data. I guess the climate professionals where doing something far more constructive instead.
4 July 2007 at 6:59
#102
I thought this was about microsite issues (which can affect any station)rather than UHI (affecting only urban ones).
4 July 2007 at 7:15
#94 Your contention is that all these have supported that “the actual claim of IPCC is that the effects of urban heat islands effects are likely small”? Whereas the listed groups may agree with the conclusions of certain papers or even the IPCC, could you help me find where they claim this. Of interest is WG1 chapter 2 for IPCC. But even the IPCC with confidence in studies 1990 and prior for small effect admit “However, greater urbanisation influences in future cannot be discounted” which brings us to the comments of 2007. My quotes and comments are about the present and do the effects extend or even are they real. Please note that I am asking that they specifically weighed in the conclusion that UHI has had a negible effect, not that they have signed on that IPCC or any other group has done a credible job.
4 July 2007 at 7:42
Auditing Stations
Looking through the above it is pretty obvious that “contrarians” wish to make auditing the stations the central issue so that “bad data can be thrown out.” The problem is that these sites are audited - repeatedly, and the conditions and readings they give determine how their readings are adjusted, weighted or filtered. However, data isn’t thrown out simply on the basis of location - or because one individual or another doesn’t like the reading it gives. There is a methodology which is designed to make use of as many data points as possible to achieve a higher level of accuracy than if the only measurements which were used were those that were considered prestine enough by the “standards of contrarians” assuming such a beast existed. (Inline to #35, #57,#56, #97, #93)
But why exactly are they focusing on the auditing of that which is already subject to a fairly rigorous methodology for maintaining accuracy? Among those who are aware of this methodology, the only reason that comes mind for me at least is that they wish to make a non-issue the central issue so that the real issue becomes peripheral: regional and global temperatures are rising - and the rate at which they are rising is accelerating.
On at least a couple of occasions it was pointed out that there are many other independent lines of evidence justifying the conclusion that the global average temperature is rising, and that it is rising dramatically. (#68, #71) However, this has been deemed irrelevant by those who demand that the stations be audited. And what auditing have they engaged in so far? Cherry-picking those stations which, from the perspective of someone - who is entirely unfamiliar with how rigorous scientific methodology has become and who might assume that scientists would simply average all readings independently of even the most basic commonsense - would think the worst possible stations to include in the process. From what I can see, they have no more desire to improve a process which is in fact working quite well than they have to take into account the many other independent lines of evidence which cooberate the averages which are being obtained by means of a scientific methodology.
As I see it, their purpose is to shift the focus from the rising temperatures to cherry-picked stations as if this were the only evidence for rising temperatures, then to discredit the process by which regional and global trends in temperatures are identified so as to discredit the claim that temperatures are rising. Once this is done, they believe that they will no longer have to deny the trends in temperatures - because the question will rarely arise - at least for the time being.
It has been claimed before that applying price controls to an economy where the government is inflating the money-supply to pay for programs is roughly equivilent to nailing the needle immobile on a pressure gage. If so, this would be roughly equivilent to throwing away the thermometer just as the temperatures start becooming dangerously high. Such actions do not postpone the negative consequences - those consequences simply become maske - temporarily, so that the trends leading to those consequences are not questioned or even recognized until it is too late.
4 July 2007 at 7:50
All of the organizations listed support the consensus position that humans are largely responsible for the undeniable changes in climate we are seeing and that these changes represent a significant concern. If the UHI cast any doubt on that conclusion, it would not have such wide support.
This is not to say that the effect is unimportant. I suspect it will be very important when it comes to improving regional climate models and improving the extrapolation of global effects to the local level.
In order to understand the potential importance of the effect, let’s look at what it could do to our understanding of climate:
1)It will have zero effect on the global climate models, because
a)the constraints on these models are derived from other sources
b)the effect is known and there are methods for dealing the errors they introduce
c)the effect they introduce is local, not global, so they cannot be responsible for the signal/trend we see, but would at most introduce noise into that signal
2)It will not alter the conclusion that the climate is changing or even the degree to which it is changing because of c) above and because that conclusion is supported by multiple additional lines of evidence, all of which are consistent with the trends shown in the land stations.
The attempts to chip away at the evidence for climate change are akin to the efforts of creationists to chip away a mountain to see if they can find human and dinosaur footprints side by side. It is the aggregate of the evidence that supports climate change. Indeed it is the only hypothesis that can explain that evidence in a self-consistent fashion.
Science is a methodology for drawing reliable conclusions from imperfect data. It works. If you want to ponder perfection, may I recommend the study of theology. If you want to draw reliable conclusions that can make a difference in the human condition now and in the future, science is your best bet.
4 July 2007 at 8:16
RE #100 So what? What counts is the natural variation of temperature. The trend is just a possible reflection of the climate recovering from the Little Ice Age. Complete recovery from which occurred at or about 1980.
I doing most of these calculations manually. I claim that you don’t have to crunch enormous gobs of data when a minimal set will do. Go to the USHCN and crunch data from Telluride CO. It is not that easy to find temp records from remote sites that go back before 1900
[Response: Well, we’re making progress. “there is no trend” goes to “there is a trend, but it’s natural variability” - only two more stages to go! - gavin]
[Response: PS. Telluride data also shows a significant trend: 1.0 deg C/century (+/- 0.6 95% conf). Your point? - gavin]
4 July 2007 at 8:25
Re #67, #77, #83, #86, #100, #107 Is there a trend?
Just of the hell of it I redid the calculation on the Quatsino data. Earlier results confirmed: trend = 0.0091 deg/year, significance p=0.00026, correlation r=0.37.
Seems like we are moving to a consensus on this one.
4 July 2007 at 8:28
RE #100 The records go upto present. However, there something is quirky about access. If you are logged on and try to access a temperature record, the computer seem to choke. Log off and try again. Like magic the records suddenly appear.
4 July 2007 at 8:38
thanks gavin! I’ll See if anyone over at CA with better math skills than mine cares to have a go at it. Hard as it is for some to believe, but there is a class of folks who just like to double check, understand things for themselves. Not deniers. Not believers. In the Middle. One more thing, the 1200km figure. Is there a document that shows which stations are associated with which stations
4 July 2007 at 8:51
Gavin, one more request. I made a error in specifing the grid of interest. 35N-40N, 120W-125W. in my prev. post I said 115W, sorry. Can I get the linear trend for the right grid. 35N-40N, 120W-125W. my mistake
[Response: same thing. Large scale anomalies etc…. - gavin]
4 July 2007 at 8:54
In response to #103, and if Gavin will allow this message, let me try again, and I promise I will try not to make a fool of myself this time. But the question of the trend in average global temperatures (AGTs) is a subject which fascinates me. I hope no-one denies that over the last X years (where X is greater than 30), AGTs have ben rising. There are two rival ideas as to why this is happening; a dramatic increase in the amount of CO2 in the atmosphere as proposed by the proponents of AGW; and extraterrestrial factors, notably the sun, as proposed by the deniers.
A few words on the future of these two ideas. If the UNFCC meeting in Bali this December does not agree on some form of hard cap on global CO2 emissions, then the concentration of CO2 in the atmosphere is going to go on rising at unprecedented rates, and hence AGTs will go on rising at an equally unprecedented rate. If solar cycle 24 does not start until September 2008, and if cycle 25 is as low as predicted (a level unseen since just after the Maunder minimum), then average global temperatures are going to plummet.
The question is, what is going to happen in the 21st century? There seem to be two answers; either temperatures are going to rise at an average annual rate as predicted by the IPCC and the GCMs, or temperatures are going to reach a maximum and then decline. If the latter scenario comes, then looking back with 20/20 hindsight, the start of the cooling period will be seen to be the maximum of the warming period.
So to me the question that needs to be answered is not have temperatures been rising; they certainly have. Rather, here in 2007, are temperatures rising as fast as the GCMs predict? This is a much more difficult question the answer. The data is extremely noisy. We have at least 4 ways of analyzing the same temperature data, which come up with different numbers for AGTs, and whose methodology is not necessarily completely transparent. For other indicators - glacial retreat, sea level, arctic ice extent, etc. - the data is equally noisy, and it is difficult having a sensible discussion without the inevitable cherry-picking on both sides of the argument. All I can say is that my funny internal feelings tell me that there is no hard data to show that average global temperatures, in 2007, are rising as fast as the GCMs predict. But if I am asked to defend this position scientifically, I cannot. Can anyone provide hard data which demonstrates that, here in 2007, average global temperatures are rising as fast as the GCMs predict?
4 July 2007 at 9:15
I worked with climate data in hydrologic model development and calibration at a NOAA National Weather Service (NWS) River Forecast Center (RFC) from 1976-2005.
The NWS has uses software for analysis of inconsistencies in data due to changes in station locations, vegetation and other characteristics that influence temperature and precipitation readings. The software is used in selection of climate stations for use in river flow calibration. Quality control and editing of temperature is performed by RFC staff and contracted workers in deriving representative mean areal precipitation (MAPs) time-series for sub-basins which are used in calibration the river basin model parameters that are then input to the operational hydrologic models used by RFC staff in flood forecasting and extended hydrologic guidance.
NWS management did not allow work in evaluating Urban Heat Island (UHI), mainly because of the stigma of being related to what NWS viewed as the political and controversial nature of the climate change / global warming subject.
I was removed by NOAA NWS for doing research on climate and hydrologic change on July 15, 2005. I still continued to evaluate climate station data and historical and operational river flow data in my tracking of climate warming in the US, including Alaska, for personal interest.
Although I no longer have access to the double-mass and consistency plotting software being used at NWS RFCs I have an approach, which I believe to adequate, for finding what I believe are the best temperature station records to use and I do quality control on the data I use in plots, viewable by the public. My approach is partially documented in my paper at the link below.
http://www.mnforsustain.org/climate_snowmelt_dewpoints_minnesota_neuman.htm
Links to temperature data plots, showing temperature and snowmelt runoff data plots at stations in the US, including Alaska, are in #99, above.
4 July 2007 at 9:30
Re: #95 (Dan Hughes)
Yes.
The data themselves constrain the size of the errors present. For example, we know that the errors are less than, say, 100 degrees C, because if they were that large, there would be dramatically more scatter in the data. The total variance in the data gives an upper limit to the errors, and using that upper limit we can compute a statistically reliable estimate of the significance of the trend.
Re: #105 (Ray Ladbury)
Exactly that is part of the procedures documented in Hansen et al. (1999 and 2001).
Re: #107 (BPL)
Quite right.
I did the same with the monthly figures (N = 1,111). I included the effect of autocorrelation, and got a slope of 0.00902 with 95% confidence limits 0.00516 to 0.01288, significant at better than the 99.9% level. There has indeed been a significant warming at this location.
But more detailed examination shows that the trend is not actually linear. The location warmed to a peak in 1942, declined to a low around 1972, and since that time has warmed consistently and rapidly. The trend from 1972 to the present is at a rate of 0.0779 deg.C/yr (that’s about 4 times faster than the global rate) with 95% confidence limits 0.0414 to 0.1143, again significant at greater than 99.9% confidence.
4 July 2007 at 9:39
#106:
Don’t feel bad, a lot of people missed my sarcasm.
The point I was making is that the contrarian/sceptic crowd seem to accept that Mars, Neptune and Pluto are warming without much question. Yet, the warming of the Earth is somehow questionable. Anthony Watts posted about Neptune and Mars warming as some sort of solar proxy (even thoguh he knows that solar trends are flat since the 1950s–he published a graph on his blog.) In fact, Watts says:
“So we have three planets now with a warming trend; Earth, Mars, and Neptune. That’s not an insignificant coincidence.”
It seems odd to accept such a paucity of data on Neptune and Mars, while quesitoning the vast amount of data on global tmeperature and using his site to suggest that poor siting issues derail global warming completely (see my #41). The “audit” of surfacestations is motivated by political bent more than scientific inquiry.
4 July 2007 at 9:41
Re: Predictions by GCMs
Apologies, this is somewhat OT. In a recent discussion about GCMs I was challenged to provide some GCM output, in particular a comparison of model and actual rainfall in the Sudan over the 20th century.
Of course GCMs are not capable of making local predictions, but Sudan (2.5 million sqkm) comprises 16 cells or so (in my ClimatePrediction model), so I suppose numbers found for the country as a whole must have some meaning.
If so, does anybody know a place where I could find detailed comparisons of local time series? What I tend to find on the net are global comparisons.
4 July 2007 at 10:17
#112 “If the UHI cast any doubt on that conclusion, it would not have such wide support.” I do not have an opinion on this. I asked if they specifically responded to the question of UHI influence. Your lead “All of the organizations listed support the consensus position that humans are largely responsible for the undeniable changes in climate we are seeing and that these changes represent a significant concern” does not have necessarily a relationship to my specific question. It appears you have offered me an assumption. Of note, the use of “any” is not reccommended. I understand what you mean, but truthfully if UHI cast only 10% doubt, would you expect it would not have such wide support? I beleive it would have still about 99% of the present support because most would realize 90% is still a great fraction explained. I have to admit that your 1,a,b,c,2, is typical of arguments I see. But I have some issues with them, whether it is real may be a matter of wording, or even a matter of findings. I have not seen the information. Of information I have seen, is that recent archeological finds indicate that without doubt recent temperatures are approaching or equal to periods of higher if not highest temperatures for up to about 12000 years. Suppose you do not want this to occur and decide to do something about it. Whether you have a range of .6C and need to do .1C may change if the range is .5C and whether you still need a .1C change or not. It also applies if you think that man is causing the problem or the sun plus man. Of interest is your claim of “a)the constraints on these models are derived from other sources”. With that being the case one can see that correctly measuring this temperature difference either it will make the goal easier to reach or indicate that we have a much harder goal than thought. But in that they (models) have been “derived” from other sources and not be effected indicates they are not useful, of which I do not have an opinion. #2 is as far as I can tell incorrect. Assume it is somehow shown that the UHI is .2C of .6C and it all occurred in the decade of 1996 to 2006 indicating that only the most modest of the models was close to coming correct and that all those models so rigorously derived from other sources had errors of 33% for a decade and a cumalitve error of 2c over a century and humans needed to be concerned with .4C TOTAL change. To say that this would not alter the way we look at either temperature changes or model predictions would be incorrect. It would also be convincing evidence that we need to do better at fundamental measurements. After all, I would hope that these other derived sources also have quality data and relationships, otherwise GIGO from a computer.
4 July 2007 at 10:47
Re #120: {The trend from 1972 to the present…]
Perhaps a graph of trends would be useful. That is, starting from the first year the data was collected, compute the trend to the present, then do the same starting at the second year, third year, and so on. Or perhaps some other measure that would show any rate of change of the trend.
I’ll leave it to you to figure out error limits and such. I don’t understand statistics all that well, but unlike some people, I at least know that I don’t
4 July 2007 at 11:25
Re 123. John said “Assume it is somehow shown that the UHI is .2C of .6C and it all occurred in the decade of 1996 to 2006 indicating that only the most modest of the models was close to coming correct and that all those models so rigorously derived from other sources had errors of 33% for a decade and a cumalitve error of 2c over a century and humans needed to be concerned with .4C TOTAL change.”
Well, first there would have to be a model that differed from the others by 33%. I don’t think there is–but I’m willing to be wrong. Second, how do a bunch of KNOWN local effects, which are known and effectively dealt with by techniques currently employed, produce a GLOBAL signal? People have looked at the signal even without urban stations–guess what, still there. Moreover, the trend agrees with every other indicator!
John, this is not a fragile signal. It won’t go away or even diminish significantly as a result of subtracting out a couple of stations. I know it sounds reasonable to derive the data from only the most pristine of locations, but that is not necessarily the best solution. Actually, I suspect that many calling most loudly for a “cleanup” know this, and that their real motivation is to aggravate doubts among the uninformed with a few nonrepresentative pictures. Indeed, this is what is already being done with the photos gathered so far.
4 July 2007 at 11:59
#103 Nick: You (deliberately?) miss the point. The rising temperature trend is abundantly clear from multiple lines of evidence. The main cause is known with a high degree of confidence. There are those who, for their own selfish reasons or from ideological conviction, continue to deny these facts. They will use any means they can to delay and obstruct the necessary action.
I think the US has the most complete monitoring network in the world. Take a look at the raw data from the network showing all 1200 US USHCN: Much of the US has cooled over the last 100 years.
Then after all the corrections and adjustments are applied.
To my eye, the raw data from all the networks shows considerable cooling in the US over the last 100 years. The adjusted data shows considerable warming. Deciding how to adjust was largely made by humans sitting in an office, not out in the field. If Anthony Watts study is the first validation of the adjustment procedure, isn’t that a good thing? How many have validated the adjustment procedure? Did the peer review effort include field trips to visit sites and confirm that in a spot check of 10 sites that at least 90% were adjusted correctly?
[Response: Most of the adjustments you mention are for Time of Observation and station move biases and presumably you are not suggesting that known problems not be corrected? However, you are missing the fundamental point, the gridded data (which attempt to correct for UHI etc.) show a) much smaller trends than the individual station hot spots that jump out of your first figure, and b) clearly reflect the fact that the south east US has in fact cooled. Thus to what extent do you claim that the gridded products do not reflect reality? - gavin]
4 July 2007 at 12:09
Re. #106,
the whole “warming on other planets” thing is such a bunch of baloney. But the best way to kill that argument quick is to point out that if the phenomenon is truly solar related, it should apply to ALL of the planets. However, you can tell people that, as a matter of scientific fact
(http://www.boulder.swri.edu/~layoung/eprint/ur149/Young2001Uranus.pdf)
…its getting colder on Ur Anus.
4 July 2007 at 12:13
Re: #124 (James)
I’ve graphed the 5-year averages, as well as a wavelet smooth on a 5-year timescale (both of which give a pretty good picture of the overall trend), at this post in my blog. The post is on another topic entirely, but if you scroll down to look for the “UPDATE UPDATE UPDATE” then you’ll find the graphs.
On an earlier discussion topic: for those who want to see an example of the mistaken assumptions at work in the blogosphere, here is an example of complete and utter denial of the validity of the thermometer record.
4 July 2007 at 12:25
re 89. As always Ray is always on target with his comments and analysis.
This is what ray wrote:
“It really only makes sense to eliminate stations if they give consistently bad data.”
Question: how does one tell what is “bad data” without a standard. especially, if many of the sites are impaired.? I will keep this simple, because I am slow and there is alot you can teach me Ray. WMO has standards for siting. CRN has standards for siting.
FOR EXAMPLE, don’t put the sensor on a roof top. WHY? because they studied this and the data from this kind of site is bad. Here is another example. Don’t put the site on a slope. WHY? cause we studied this and the data is bad. ( sun exposure ray) Here is another example, don’t put the site over PAVEMENT. Why? hmmm ..
What do you think ray. Do you think that Karl and NOAA and WMO know what matters in siting or not? I don’t know a thing about microsite issues like multipath, waste heat, evapotranspiration, and wind shelter. But I trust Karl, NOAA, the WMO. Bad siting leads to bad data.
If bad siting ( sensors in the shade, under tree, by a transformer, next to air conditioner exhaust) did,’t matter, if bad data could be magically rooted out or adjusted for by statistical techniques, then why expend all the time and effort to specifying siting criteria?
The consensus in siting science says: Don’t place a land surface temp sensor NEXT TO AN INCINERATOR.
Some people seem to adopt the following logic. We will accept a temp. sensor next to an incinerator until somebody else proves it is a problem. I recall a funny cartoon with three monkeys.. one has his hands on his eyes..
Now, the ray continued to shine:
“If the data are oversampled, any anomalies will be identifiable by rather simple analysis.”
Actually some started this analysis. I suggested that deviations ( at a station level) from global or grid level Tmin trends could be an indicator of site impairement.
Very simply, one could hypothesize that site impairment would hit the Tmin record more severely than the Tmax record, narrowing the diurnal range, and raising the mean, consequently. A quick look at the data suggested this might be an interesting signal to look at. But, for now, we will just stick to something every vistor to RC can see for themselves ( google gisstemp)
So, we think anomalies are easily spotted? Ok. Go to GISSTEMP. select the site at ORLAND, CA. It follows WMO and CRN guidelines. ( Photoverified) Plot its temp.
Now, search for MARYSVILLE, ca. Plot its temp. Hmm.
One site follows the guidelines. one site does not.
One site shows warming. one site does not. I’m a curious fellow. Which data is “bad”? Now, There are other sites in the grid that also break the CRN rules and WMO rules. These sites look like Marysville in regards to temp records. Funny how the sites located by pavement and building and wind breaks have “simliar” trends. on the other hand there PRECIOUS FEW sites in the grid that follow the rules. Orland is one. Willows is another. Lake Spauling used to be a good site up to a couple years ago.
So, consensus would say… toss the sites that dont follow the rules. Now, say that 24 of the 25 sites in the grid break the rules. Now say those 24 show a positive linear trend of .8C since 1900 and the 1 site that follows the siting guidelines doesnt show this trend. Which site is anomalous? Put another way, if 1 site out of 25 follows the siting guidelines, and 24 don’t, which site do you think will identified as an anomaly by merely looking at the data file?
Bottom line. Document the sites. Delete those that break siting guidelines. Let the data fall where it may. It’s an oversampled grid after all.
Further illumination:
“No system is ever perfect. The question you have to ask yourself is whether any improvement to the system will make a significant difference. ”
Agreed. No system is perfect. Delete the class 5 sites.
make it better. Second, I don’t have to ask myself if an improvement will make it “significantly” different.
First, The cost of “improving” the data is ZERO. don’t include bad sites. Second, The burden of proof is backwards in your analysis. The stations don’t meet standards. The instrument has not been calibrated. Show that INCLUDING them has no impact on trend or error.
Imagine a drug maker who said, Prove my drug is ineffective! Finally, NOAA have already said that an improved network is required.
Further illumination:
“I suspect that it would not for several reasons. First, as I said, in an oversampled system, anomalies are easy to identify.”
anomalies are easy to identify. If you look at the site photographs and temp records you will find that the sites that comply with siting guidelines are anomalies. ( psst, you think bad sites are anomalies, it might be the other way round ray…DOH)
Continuing:
“Second, we are looking at global trends, so unless there is a systematic error in siting/readings etc. bad stations will at worst produce noise on the overall trend. ”
Really? Well, that would depend on the number of bad stations ( we have no clue), the magantude of the error( we have no clue) any directionality in the error ( we have no clue).
So, best case, bad stations create a noise farm. This is bad for climate science. Fix it. Worst case, The land record might have a small positive bias, a minor annoyance but utterly correctable if proper QA is employed. Put QUALITY DATA IN, rather then testing for JUNK DATA after you put it in. Nobody thinks that attending to Quality is a bad thing. We have a QA consensus. And only a few folks in this project think that the warming will go away. Too many independent sources confirm the global increase. The issue is quality, reliability, and accuracy. Don’t farm the noise, if you don’t have to.
And…
“Even if a particular bad station had a paucity of good stations around it, it is unlikely that it would affect the global trend.”
you have a supposition about global trends. You think this siting issue won’t matter. That’s because you think bad stations are the exception and not the rule. This is a testable hypothesis. This is what we are investigating. How about you take some pictures for the project? we have 130 volunteers, 131 would be GREAT!
You conclude:
“Should we look hard at station site quality for future stations. You bet! Should we have any doubt about the trends seen to date. No. ”
Well, we agree. The “trend” upwards is supported by many independent threads. ( SST trends, Troposphere trends) the EXISTENCE of a trend is not our issue ( ok My issue ) The issue is quality, magnatude of the trend, error of the trend and the proceedure for incorporating the CRN into Goddard products in the future. So, you misconstrue the target of the doubt.
We should have doubt. Doubt is good. Denial is another thing altogether.
4 July 2007 at 12:50
re #104 and #120
Thanks Eli, I have been working my way through the papers that Gavin linked in his post. Do you have a pointer to reports and papers that might contain the actual equations and area data used in those calculations? Pointers to any software used in the calculations are of special interest.
Due to an oversight on my part I did not state my question precisely enough. I wanted to ask about the precision of the instruments, the accuracy with which the device can be read, recording the data, and calculations associated with reducing the data to its reported form. So far the papers seem kind of light on these, but maybe I will run across those discussions later in the papers.
Thanks too, tamino. I am not familiar with that concept. Can you point me to a textbook that contains the details? An online discussion would be more helpful actually. I am especially interested in the mathematical details outlined in this sentence; “The total variance in the data gives an upper limit to the errors, and using that upper limit we can compute a statistically reliable estimate of the significance of the trend.” BTW, does the total concept include discussions of the number of significant digits available from recorded data?
Thanks again
4 July 2007 at 13:25
Re: 89, 119
Regional changes in temperatures are more informative to me than globally averaged temperatures,
I show regional trends in temperature data based on US climate station data (1890s-2007). Temperature changes indicate greenhouse gas driven global warming with strong warming trends in the mid-high latitudes and elevations and the greatest diurnal increases in daily minimums in winter months.
Streamflow data supports warming by showing earlier in the year snowmelt runoff trends on rivers in the Upper Midwest and northern Great Plains, beginning in the 1970s and continuing to recent.
4 July 2007 at 13:32
#125 You now somewhat seem to be evolving towards my position. Note that I asked you if the sources of mainstream science organizations had agreed to specifically that UHI was known to be neglible versus having only agreed to IPCC is basically correct. You are avoiding, it seems. I will assume unless shown otherwise that my assumption about these organizations is true.
You ask “Second, how do a bunch of KNOWN local effects, which are known and effectively dealt with by techniques currently employed, produce a GLOBAL signal?” There are two fundamental problems with this statement. You claim that KNOWN local effects are effectively deealt with by techniques currently employed. I find in peer reveiwed/cited literature that this statement is not considered correct. You also claim about GLOBAL while it is far as I can tell from IPCC that Global is made of many local measurements. I have not made assumptions to their problems if any because I have not reveiwed them. However, why assume they are correct especially if one sees in peer reveiwed literature, and from obvious data that a general local, the USA, that they have not been effectively explained and other data indicates problems. Why not look instead of assuming.
That the trend agrees with every other indicator (don’t know what an indicator is necessarily…it was not defined by IPCC…lol) does not address my comment about accuracy at all. As far as I know they are either based on temperature or based on measurements that do not directly relate to temperature that is Global in your comment. Take an indicator like glacier retreat that some say is an indicator. While it might indicate warming, or lack of precipitation, it does not measure incorrect temperature measurements in the USA.
You said “Actually, I suspect that many calling most loudly for a “cleanup” know this, and that their real motivation is to aggravate doubts among the uninformed with a few nonrepresentative pictures. Indeed, this is what is already being done with the photos gathered so far.” Though this comment may be true, I have no opinion on this since I can’t read minds. I pointed out, using the assumptions I made, that an UHI effect could be important. You have done little to indicate that my assumptions or conclusions about a UHI effect were necessarily wrong which is what my #123 was about.
4 July 2007 at 13:41
Re 113 Harold Pierce Jr: “The trend is just a possible reflection of the climate recovering from the Little Ice Age. Complete recovery from which occurred at or about 1980.”
You do know that the “Little Ice Age” was not actually an ice age, don’t you?
And shouldn’t that be 1880?
4 July 2007 at 13:52
Steven Mosher, A network that corrects error-free data is not necessarily better than a network that collects data with errors that are well understood. The are several fundamental problems with your approach:
1)You are looking at stations individually, rather than as part of a network. Information theory suggests that if our oversampling is at least 3:1, we can have up to 1/3 of our stations be totally wrong with no real loss of information–and those are random errors. The siting criteria are excellent guidelines for single stations, and I would not site any single new station that did not comply (unless there were an overriding reason). Most of the station that violate the siting criteria, however, are old, with a long history. This is important, because:
2)On the other hand, systematic errors can be characterized and bounded (thus determining what weight to apply) or the result corrected. Such studies provide important information in and of themselves (how do you think the siting criteria were developed?).
3)You give no consideration to what kind of error a particular violation would produce–either prior to or after corrections are applied.
4)In essence jackknifing studies already do what you are asking for–look at the effect of excluding single stations from the analysis.
5)Your methods have a very high risk of being misappropriated by denialists to cast unwarranted doubt on a result that is incontrovertible–indeed, that is how they have been used to date.
6)There is no evidence of a systematic problem with the data or procedures, and plenty of evidence to the contrary.
So, Steven, if it were not for 5), I would consider your efforts to be at best a welcome volunteer effort and at worst an innocuous waste of time. However, there are plenty of actors out there with very deep pockets and far less than simon pure motives. They have already demonstrated that they will misuse any fact (warming on Mars, increasing snowfall inland in the Antarctic…) to sew doubt in the minds of the nonexpert. It would be naive to expect them to give your effort a pass.
4 July 2007 at 14:53
Re #78: “So, to answer your question, The CRN, I would suspect, would REJECT a class 5 site. At Worst, they would a RECORD of its clasification and photos. With the historical network we have neither. The point is the document shows people how to Rate a site for INCLUSION in the CRN. Bottom line: Marysville would be excluded. Lodi would be excluded. Lake spaulding would be excluded. tahoe city would be excluded. In fact, none of these sites or locations nearby are included in CRN.”
Well, here and in the rest of your comment you seem to have a lot of faith in Tom Karl and the CRN standards. If what you say is correct, then presumably they have a plan for abandoning the sites you have defined as “bad.” I’m probably just poor at searching, but I can’t seem to locate that plan. Pointer? Alternatively, as others have suggested, perhaps even these “bad” sites provide some useful data and one result of the CRN will be to improve that data. BTW, Lodi isn’t all that far from the Merced CRN site.
Re #129: “Now, There are other sites in the grid that also break the CRN rules and WMO rules.” Very likely *all* of the sites break the CRN rules in some degree.
Re #130: Dan, your stated expertise in quality assurance so greatly exceeds that of everyone here that I don’t see how you could rely on pointers from anyone else. Independent research is the answer. Let us know how that turns out.
4 July 2007 at 15:09
#130 I wanted to ask about the precision of the instruments, the accuracy with which the device can be read, recording the data, and calculations associated with reducing the data to its reported form.
http://www.srh.noaa.gov/ohx/dad/coop/EQUIPMENT.pdf notes that if an MMTS agrees with a thermometer within a degree, then the MMTS unit is good. Also, observers record temps only to the nearest degree.
So, there is actually a 3 degree window in which a measurement is valid. For example, the actual temp could be 71.5 and the recorded temp could be 70.0 on one units, and 73 degrees on the unit right next to it. This would be in specification.
Errors on a specific device will remain very close to constant over time, but it’s possible for a replacement device to measure almost 1.5 degrees higher or lower than the previous device and still be acceptable according to my reading.
Given the size of the network, most all of these errors will cancel each other out.
4 July 2007 at 16:07
#136 Thanks Matt. I’ll check in over there.
#130 And Steve B as you always do, you made up words that I have not said, addressed an issue that I did not mention, and failed yet again to discuss any technical aspects.
4 July 2007 at 16:12
Gavin: Most of the adjustments you mention are for Time of Observation and station move biases and presumably you are not suggesting that known problems not be corrected? However, you are missing the fundamental point, the gridded data (which attempt to correct for UHI etc.) show a) much smaller trends than the individual station hot spots that jump out of your first figure, and b) clearly reflect the fact that the south east US has in fact cooled. Thus to what extent do you claim that the gridded products do not reflect reality? - gavin
Gavin, of course biases should be corrected. All significant biases should be corrected. And potential biases should be investigated. However, I’ll admit to being a bit suspicious that the raw record shows little warming, and the adjusted record shows considerable warming. Bias correction can sometimes equal agenda injection. I think there are folks with an agenda on both sides of this argument and history shows repeatedly that those in positions of trust (presidents, governments, doctors, transmission repair shops) frequently withhold information to make their case more convincing. It’s not lying, but it’s not being 100% transparent either. Scientists working on pharamcuticals do it, working for cigaretee companies do it, and posters on this board do it. Why wouldn’t a climate scientist with an agenda do it? I worked at the USGS for a few years as an intern, and yes, there were folks there with an agenda. No budget, but they still had an agenda
My attitude might sound cynical, but the population as a whole is just as skeptical when it comes to what scientists tell us. Frankly, the louder folks hear “the science is settled” the more people go “yeah, right”
I suspect the gridded maps largely reflect reality, though I also think that the extremes might be somewhat muted if 10% of stations are faulty because they are sitting next to an AC, parked car or BBQ grill.
I don’t quite understand why folks are upset that a private citizen, on his own dime and own time are looking at this. If he finds something the first set of eyes missed, then great. If not, then Anthony Watts ends up that much smarter on the subject.
4 July 2007 at 16:33
John, and Steve Mosher, OK, so you say you are going to carry out a scientific analysis of siting. So what is your hypothesis going in? At how many sites do you expect to find problems? What kind of problems do you expect to find? What sorts of errors do you anticipate that these problems will introduce to the database? What sorts of analyses and noise/error rejection procedures might be effective against these errors? Are there any types of errors you might expect to find against which no commonly used mitigation algorithm would be effective?
If you can answer all of these questions going into your investigation, you are doing science. Otherwise, you’re goin’ fishin’. In particular, I think you need to think about the implications of these stations being in a heavily oversampled network with a long temporal database.
4 July 2007 at 16:59
[[“So we have three planets now with a warming trend; Earth, Mars, and Neptune. That’s not an insignificant coincidence.”]]
So how does he explain that Uranus is cooling?
http://www.boulder.swri.edu/~layoung/eprint/ur149/Young2001Uranus.pdf
4 July 2007 at 17:07
= Comment # 134 by ray ladbury” =
=”6)There is no evidence of a systematic problem with the data or procedures, and plenty of evidence to the contrary.”=
And how do you know this ray? The small amount of photographic evidence available so far does indicate there is a problem of some degree, which requires further analysis to ascertain how serious the issue is. Sweeping the issue under the rug is not an option.
4 July 2007 at 17:47
Contrarian Doubt: causes and consequences
Matt (#136) responded to an earlier comment:
… for essentially the same reason that the larger the number of coin tosses one performs with an unbiased coin, the more likely the number of heads divided by the number of tosses will be one half.
Of course contrarians will point out that instruments at poorer sites will have a bias, but as tamino (#91) points out, this bias is corrected for, and it is quite possible that given the methodology employed, removing the urban sites would actually result in a higher average temperature, and as Hansen points out (see tamino’s first reference in #93), the bias introduced by urban sites is quite negligible.
But why include them?
For the sake of consistency - as ray ladbury (#97) points out. Removing them would mean that we are no longer measuring temperature the same way, and as such would introduce new artifacts into the statistics so that the measurement from one year wouldn’t be directly comparable to the next. Similarly, replacing one station with another station would be replacing known errors which were already being taken into account previously with unknown errors and would suffer from the same sort of incommensurability.
Adding new sites with the appropriate precautions taken with respect to their location increases the number of data points, in essence paying for the additional noise which they introduce into the trends - in the same way that increasing the number of coin tosses leads to a heads to tosses ratio closer to one half. Simple replacement of older stations does not.
Additionally, what actually matters most in terms of the trends is not so much the temperature in any given year, but the change in temperature from one year to the next. But by focusing on the location of one particular station or another and how its location may result in slightly lower or higher measurements, contrarian rhetoric obscures this essential issue in popular perceptions.
Likewise, Dan (#52) points out that the good majority of sites are in rural settings. But by focusing on urban settings, contrarian rhetoric further distort popular perceptions.
Boris (#121) points out that contrarians are more than happy to accept the trends calculated for a few distant planets if it obscures the cause of the trends seen on Earth - even though the data which we have on those trends have a great deal more uncertainty associated with them (see Nicholar L’s #88), and as an explanation in terms of solar variability is not credible (ibid.), and solar irradiance has been flat since the 1950s (see Boris’ #121).
Dan (#52) also points out that the very same trends which we are seeing on land are showing up in temperature records at sea and the atmosphere, and as Spencer (#1) points out, in boreholes, and as I have pointed out, in the ocean depths down to 1500 meters. Moreover, Ray Ladbury (#125) points out that we are seeing the same trends even when the urban areas are thrown out and we simply use rural ones.
The trends we are seeing are not the result of urban heat islands. If they were, then the trends would be higher in the tropics than in the higher altitudes, as gavin points out in the essay itself:
Scientists include older urban sites not because they are ignorant of urban heat island effects, but because continuing to include them improves the accuracy of our identification of temperature trends. The contrarian’s purpose for focusing on urban heat islands is not to improve accuracy but to cast unreasonable doubt upon a process which is working quite well. Likewise, they prefer to debate urban heat island effects rather than to discuss the rising temperature trends, other clear signs of rising temperatures, the positive feedbacks which are beginning to kick in so that climate change will take on a life of its own independently of what we do in the future if changes are not made now (#111, “Storm World” post, comment #141) and what such climate change will imply for humanity as a whole (Curve manipulation, comment #74, A Saturated Gassy Argument, comment #116). They prefer debate which in which they can more easily manipulate public perception to their own ends rather than recognizing what is actually happening to our world as the latter would demand actions which given their nearsightedness they would prefer to avoid.
4 July 2007 at 18:13
re #44;
John, nowhere in my post did I suggest that anyone is wrong or deceptive or ignorant or anything else. All I suggested was that having someone else go over your work to look for mistakes and/or clarify your implicit assumptions (ie make them explicit) was a good thing and that anyone who cares about the truth and the scientific ethos should not be upset that someone “dares to question” their work. Nor did I suggest that money should be diverted from important work to audit other work. If someone wants to spend time and money doing this audit work, then they may have an agenda or they may not - just as those who did the original research may have had an agenda or they may not (and once again, there is no implication that this is the case for any particular field, researcher or paper)
Now, don’t get me wrong here - I certainly understand that, like most people, you will be confident in your own work; you are, after all, the one closest to it, and therefore have the best understanding of exactly what was done, how it was done and why it was done. But that doesn’t mean it’s right, it also doesn’t mean that you didn’t make a mistake, and it certainly doesn’t mean that you took everything relevent into account - you’re only human, after all.
In my experience, taking the time to explain your work to someone else who is *not* closely involved in it is a highly valuable exercise and one that, it seems to me, is not particularly popular in scientific circles. For better or worse (IMO worse), many scientists seem to become frustrated when asked to explain their work. That’s unfortunate IMO, and I would encourage you to try this out for yourself - in the effort to organise your thoughts in order to explain your work you will, in many cases - although not all - have an “Ah-ha!” moment, where it all “clicks together”. Of course, the person you are attempting to explain it to will probably end up rather frustrated with you as you run off to investigate your new insight, but that’s a small price to pay. How is this relevent? Auditors ask pesky questions! They demand documentation! Yes, it’s annoying, but it’s also valuable on many fronts: it ensures you properly document all steps in your work, making it more “bulletproof”; and as above, it makes you organise your thoughts in a different way, leading to new insights.
So, as per my original post, please don’t see just the negatives in an “audit”. Instead, look for positives, and use the whole process to your advantage. After all, if you believe your work is sound (why wouldn’t you?), you have nothing to lose and everything to gain.
4 July 2007 at 18:35
Re #65 [not one person advocates what is the only sensible thing to do: perform a thorough review of the surface temperature sites. Instead, abstract, Machiavaellian motives are attached to anyone who dares question the suitability of the sites.]
There are hundreds of papers that do this. Its a pretty standard scientific process. I can also point you to two very large PhD theses in Australia which are nice cook book examples.
The development of a high quality historical temperature data base for Australia. University of Melbourne, Simon James Torok. 1996. and Extreme temperature events in Australia. University of Melbourne, Blair C. Trewin.
2001
With a team of 100 students and a few million dollars for airfares you could do this work on a global scale. You couldn’t do it remotely, though, because most station meta data is tucked away on paper records in national archives (sure this should all be digitised, but who has the billions of $ that are required to do this).
4 July 2007 at 18:58
ray ladbury you said in 134: “Steven Mosher, A network that corrects error-free data is not necessarily better than a network that collects data with errors that are well understood.” Temperature, means and anomolies are so misunderstood? Why would any one want to correct error free data for temperature? This is what several on CA are implying is occurring by AGW proponets and procedures: The data do not support AGW so it must be “not necessarily better” and must be corrected (ie error free data or data that does not agree with an AGW hypothesis is wrong).
I have assumed you were talking of the same network data like temperature of the US. So let’s examine data that is “error free” but “not necessarily better”. I can’t think of one if it is about the same phenomena. I can think of several that mean little…number of prosecutions for drugs versus impact of drugs on human health. Yes, you can count and get an extremely accurate number, highly accurate for prosecutions, but the impact is more important. So what is the impact? Therefore what is so misunderstood about temperature?
You ask #1 “John, and Steve Mosher, OK, so you say you are going to carry out a scientific analysis of siting. So what is your hypothesis going in?” I think this should read “a scientific analysis of siting implementation according to accepted standards”.
Hypothesis: Cement, flaming grills. etc. next to temperature sensors do not meet accpeted standards nor make for accurate measures of temperature that should be used in a global computations or grids, assuming accuracy is important. Ray, please note, I think and have commented that accuracy is important.
#2 “At how many sites do you expect to find problems?” The better question is how many sites would it take to have a demonstrable effect on grid analysis? The answer is one or two in certain grids. The extent of this paper is to show that it can effect a grid. the actual extent needs further investigation. The hypothesis could be “Micro-site temperature influences impact specific site temperature data”. One is enough. Or choose a ramdom selection…there are several methods available, or do what paleos are claimed to do and cherry pick, and then show that what they choose are most important. Choose what Anthony Watts wants to do and do all. Each has its limits. But for me and Stevem we only have to show #1 with 1 site , and then proceed. If you want a hypothesis after step 1., perhaps you should wait as I would and do one hypothesis at a time.
#3 “What kind of problems do you expect to find?” SEE ABOVE. Several have been shown and I have commented on hand waving by Eli Rabbet (sp?) on CA in particular. Not that I know the answers already, you know the “deal”; you are quoting the first part, but that it should be investigated because the handwaving fell far short of obvious data in the photographs. This goes back to number 1 that I expect to find cement in close proximaty and walls to show increased temperature as has been repeatedly shown in literature. This may not be true if the station is not taking data correctly, but I guess all have to live with that if you use the data. There could be unknown and unresolved problems with the data, but I assume this is outside either your ability or mine? If you have information otherwise I would appreciate you providing it.
“What sorts of errors do you anticipate that these problems will introduce to the database? What sorts of analyses and noise/error rejection procedures might be effective against these errors? Are there any types of errors you might expect to find against which no commonly used mitigation algorithm would be effective?” I anticipate that microsite errors could introduce as documented in the literature up to a 3C false positive per site, and for GLOBAL (your emphasis) grids that have an underlying basis of one or two accepted sites, a 1.5 to 3C false positive on a claimed .6C phenomena. At present, noise/error rejection procedures have an underlying assumption that they are correct, verification has not been provided and analyses that claim the ability to reject have been demonstrated false in peer reveiwed literature. However, these also should be investigated after step 1. I find, by lack of consensus, commonly used mitigation algorithms do not address hypothesis 1 in any verifiable manner, which is why #1 was chosen to take primacy.
“If you can answer all of these questions going into your investigation, you are doing science. Otherwise, you’re goin’ fishin’. In particular, I think you need to think about the implications of these stations being in a heavily oversampled network with a long temporal database. ” Science does not have to answer all questions at once; it answers questions. Your “ALL” (emphasis mine) is the totality of anti-scientific thought. Darwin did not explain “all”, but still is considered one of the major modern scientists (please note I did not specify one Darwin over the other in case you are familar with modern evolutionary theory or say which one deservers the accolades). I am sure all the engineeers and physicists who have studied Newton’s law, and Einstein are grateful that Newton did not have to explain or answer “all”. Am sure Einstein would like to compare notes with Hawking.
Actually more than one scientist has gone fishing…”Otherwise, you’re goin’ fishin’.” Pastuer went fishing and founded modern biology, ie some of his hypotheses were shown to be utterly untrue. But he is still credited for what he accomplished, not “all” that he tried. However as the traffic cop asked the motorist he caught speeding who complained that others were speeding ” When you go fishing, do you catch every fish?” The motorist admitted he did not. The traffic cop said “Well neither do I, but you are a keeper!” The analogy is that is does not matter if I or Anthony Watts are fishing or not, if we show a real problem, it is real whether you complain, or not how we arrived at it.
There is no requirement that any scientist do “all” of a phenomena’s hypothesis at once. In fact ray ladbury, it is expected you do one at a time and use your time effectively (your word). MY hypothesis was and is “Cement, flaming grills. etc. next to temperature sensors do not make for accurate measures of temperature that should be used in a global grid, and do not meet accepted siting standards.”
I have little firm opinion yet on much of this. However, I think #1 should be done first, then conclusions or other hypotheses will be more appropriate for consideration.
4 July 2007 at 19:03
#137 Ray, what are you talking about? People all the time do blind audits of their work and the work of other engineers hoping NOT to find a problem. And if you sample 5% of the population and don’t find a problem, you can start to feel pretty good that things are OK.
But if you sample 5% of the population and find problems in a third of the samples, then you need to worry. And I think that is where Anthony Watts is: he found a site that he knew was wrong, did a quick check of another few sites and found problems there too, and formed a hypothesis that a huge portion of the network was poorly sited.
“Huh, that’s weird. I wonder if…” drives most science and engineering.
4 July 2007 at 19:38
It seems pretty clear that some HCN sites do not meet standards set by NWS. Some effort (and funding) should be made to do this and reanalyze existing data (instead of just whining about data). I know of a half dozen folks capable of making competent inspections, but only one listens to Limbaugh.
Instrument Requirements and Standards for the NWS Surface Observing Programs (Land) NWS inst. 10-1302, September 20, 2005. Appendix E Siting and Exposure Standards for the Climate Observing Program.
Other guidelines:
Guide to Meteorological Instruments and Methods of Observation, WMO-No. 8, World Meteorological Organization, draft 7th ed. (2006).
On-Site Meteorological Program Guidance for Regulatory Modeling Applications, EPA-450/4-87-013 or EPA-454/R-99-005, 1987 et seq. Office of Air Quality Planning and Standards, Research Triangle Parks, North Carolina 27711.
Heights and Exposure Standards for Sensor on Automated Weather Stations, The State Climatologist, 1985, v. 9, No. 4, October, 1985, American Association of State Climatologists.
Question:any other refs?
It should be noted that several insurance firms have become very interested (financially invested) in meteorologic data. It is quite likely that some data will be facing legal scrutiny, and may well be used in denying claims. Certainly aviation meteorological data has already reached legal status. I would strongly suggest that meteorological and climatological professional associations work with ANSI and NOAA (and possibly with Congress) about getting some legal standards set, and getting support to meet those standards.
Question: Which HCN sites were used for calibration of or reconciliation with satellite data?
4 July 2007 at 20:29
Groan,
I’m repeating myself, but this page (the link to which Gavin included in his article) you will find details of how the data is cleansed/rectified. Much of what is being posted ignores what is actually being done with the data (possibly because a lot of people don’t understand the statistics terminology - or because they would rather stick to their straw man reasoning).
Also, the Australian climate monitoring reference network consists of about 100 stations in remote places with long recording histories. You can read about them here. See photos of them all by clicking the orange dots on the map here. Data from the Australian climate monitoring network is plotted here. You can get the here. Contact the Australian Bureau or Meterology for raw data - they are helpful folks.
If the US network were to miraculously somehow be shown to be giving false trends, then you would have to explain how there can be no warming in the US when the Australian network shows it clearly across a variety of parameters. And note in addition that in addition to the warming, there are strong trends toward decreasing rainfall across the Antipodean continent, which are backed up by tragically decreased river and stream flows, severe water restrictions in most states (starting to ease in some places due to recent floods), and a significantly increased farmer suicide rate.
Also, we know that the climate models are able to match the meteorological records remarkably well (including the observed mid century cooling episode due to aerosols, and the post Pinubo eruption cooling). If would be truly remarkable if the output of the US climate monitoring network is bogus, but somehow inexplicable matches the output from models that are based on atmospheric physics.
I look forward to Mr Pielke and his cadres visiting and photographing some of our more noted metropolises, such as Oodnadatta, Tibooburra and Meekatharra in order to document microsite effects, not to mention Maquarie Island and other Antarctic spots such as Casey and Davis Stations.
4 July 2007 at 21:43
OT: I just happened across an excellent newish ocean acidification blog. It’s run by a French scientist who appears to be an expert in the field. It’s not really a comment blog (although that may just be due to lack of traffic), but the author seems to be doing a thorough job of keeping abreast of the field via regular posts on significant new papers, media coverage, conferences, etc. It’s well worth a look IMHO.
4 July 2007 at 22:17
re 137. Fishing .
Ray wrote:
“John, and Steve Mosher, OK, so you say you are going to carry out a scientific analysis of siting. So what is your hypothesis going in?
1. well, actually, If I got paid for this instead of charged for this
I would suggest the following.
A. complete a photo survey of the network. 1221 stations.
B. Complete a CRN siting ranking of the sites.
C. Re analyze the land record with class 4 and class 5 sites
removed.
D. Hypothesis. The difference between these trends will be non zero ( with and without class4-5)
( bad stations warm the record)
E. Issue, will the test have the power to see the difference
at a significant level? This would be my biggest concern.
One might find a .05C difference at say 50% confidence.
So, Power of the test. which is your point in a round
about way. Always my biggest concern.
Next Question:
At how many sites do you expect to find problems?
well there are, supposedly, 1221 sites.
I’ve bounced around between thinking it should be normal.. that is,
with sites ranked 1-5, I’d probably started thinking it was normalish, with 5% class 5 sites.. 15% class4..
On the other hand, I had some days when I thought, it will be uniform
and we would see 40% in the class 4 to class 5 category.
So, put a gun to my head…. I guess 25% in the class 4- class 5. hows that?
Since we have a fixed sample, and since Anthony and team are intent on collecting EVERYTHING, then I don’t know if this estimate is necessary.
Since I showed Anthony the rating criteria his plan is to start classifying sites when we have sampled 10% of the population. Anyway, I have also been struck by the comment, made by someone ( i thought it was gavin) that you only need 60 good sites. If true, that would be heartening no?
Next Question:
“What kind of problems do you expect to find?
What sorts of errors do you anticipate that these problems will introduce to the database? ”
Well, we never expected to kind stations on rooftops and we never expected to find burn barrels by Stations.
and we never expected to find a Mig jet parked by one.
and we never expected to find batteries and light bulbs in stations
and we never expected to …
Seriously, it very simple. I would expect to find a distribution
of sites ranging from class 1 ( ORLAND) to Class 5 ( Marysville)
I would expect to find that the class 1 sites will exhibit different
warming trends ( perhaps only in TMin) than class 5.
As for errors in the database, I will show you a small example
tommorrow. Let’s call it a pilot study. If I had all the data,
the time, the money, the photos, I’d do exactly what gavin suggested.
Pick the good stations ( lets say 1-3s) calculate the trend.
HINT, the warming wont GO AWAY. Like I said there are too many
other sources that indicate warming. If a study of station
data made the warming GO AWAY, the study would be wrong.
Next Question:
“What sorts of analyses and noise/error rejection procedures might be effective against these errors? ”
Well, one method is to select different sites. The current approach
seems to favor sites with the longest records ( that’s good) but if the site becomes impaired over time, you have an issue. Their are other sites, sites that are well situated ( agricultural monitoring systems for example) BUT, one would have to “patch” together a record from several sites. So, Not a simple answer.
Its EASY to throw stones, but not unscientific.
last Question:
“Are there any types of errors you might expect to find against which no commonly used mitigation algorithm would be effective?”
I don’t think this issue is like a “SST bucket adjustment” or a
TOBS adjustment or an adjustment for lapse rate due to altitude change.
If the site were ALWAYS located in a parking lot, then ANOMALY approach
will “correct” for that, since trend is what matters.
The issue is gradual change over time that goes undocument. Trees get cut down, pavement added, building built, parking lot added, air conditioner put in. It gives one pause. BUT,
one can and should still believe in a global warming trend. That “observation” is supported by too many other tenacles to be taking down by some small errors in the weather stations.
Oh wait, One thing. I’ve wondered if this type of site impairment only impacts TMIN. That is, the mircosite issues may work to Bias Tmin up. But Tmax may be more robust ( variance analysis shows this I’ve been told)
So, one could still construct a trend of sorts from TMAX
Understand Tmean is simply (Tmax+Tmin)/2. So, I was pondering whether Tmax might not contain all the information ( trend wise) that one needs and that Tmin might not add that much “information” Tmin being more variable, and more prone to contamination from things like UHI and microsite issues
So, that was a line of thought I had… Plus the idea of using a narrwing diurnal range ( TMIN rising faster than TMAX) as being a proxy of sorts for impairment.
So, just some thoughts, ponderings.
You closed:
“If you can answer all of these questions going into your investigation, you are doing science. Otherwise, you’re goin’ fishin’. In particular, I think you need to think about the implications of these stations being in a heavily oversampled network with a long temporal database.”
I hear you Ray. So, you’ve been kind and patient. As Always. I’ll toss a little task at you tommorrow. Just tell me what you think.. and if it would make you curious… Not doubtful, just curious.
4 July 2007 at 22:52
re 134.
Hi Ray, sorry I’m working backward through the comments, crablike.
You wrote:
“Steven Mosher, A network that corrects error-free data is not necessarily better than a network that collects data with errors that are well understood. The are several fundamental problems with your approach:”
Well, first you have to establish What kind of errors you have, before
you can characterize them as “well understood” You do that by looking.
Continuing:
“1)You are looking at stations individually, rather than as part of a network. Information theory suggests that if our oversampling is at least 3:1, we can have up to 1/3 of our stations be totally wrong with no real loss of information–and those are random errors. ”
Well, to establish the oversampling rate I suppose one must have a
understanding of the signal structure and probabilities. So yes,
Mr Shannon and Mr Nyquist play a role here. I have not seen any evidence
that the climate signal at the grid level is over sampled. Ground truth
is kinda missing. PLus, one can look at the STATION and the network.
After all, Hansen et al, look at stations to account for things lke urbanization, and record length, etc… So FALSE DILEMMA.
“The siting criteria are excellent guidelines for single stations, and I would not site any single new station that did not comply (unless there were an overriding reason). Most of the station that violate the siting criteria, however, are old, with a long history. This is important, because:”
Well ray. you are funny. Orland CA, for example, is a fine site.
In the same place since 1883. Do not assume. LOOK. OBSERVE.
INVESTIGATE. You assumed the older sites violate. You didnt even
Look. every site survey has a siting history. read the file.
You say Most of the stations that violate are old? How many
of the 80 sites surveyed violate siting? We havent even started
evaluating all of them. If you have reviewed all of them and classified
them according to CRN standards.. COOL. pass the data son!
You go on:
“2)On the other hand, systematic errors can be characterized and bounded (thus determining what weight to apply) or the result corrected. Such studies provide important information in and of themselves (how do you think the siting criteria were developed?).”
True. Think about noise reduction and error correction.
“3)You give no consideration to what kind of error a particular violation would produce–either prior to or after corrections are applied.”
Well, actually I have. See later comments. Still GIGO.
“4)In essence jackknifing studies already do what you are asking for–look at the effect of excluding single stations from the analysis.”
It is absolutely clear to me that 1 station will not make a difference. Worst case, I’d guess that 20-25% of the sites are impaired
I’ll go through all the 35-40, 120-125 sites and do a count, but I’d rather someone else rate the sites, double blind like. I already “know” what sites have squirrely records… from looking at the data so I’m not
confortable making any rating determination.
“5)Your methods have a very high risk of being misappropriated by denialists to cast unwarranted doubt on a result that is incontrovertible–indeed, that is how they have been used to date.”
Yes, but sunshine is a good thing.
“6)There is no evidence of a systematic problem with the data or procedures, and plenty of evidence to the contrary. ”
Well, SYSTEMATIC evidence would come from a system wide study.
You find one roach. Look for more. You find one bad batch
of dog food, screen for more… When the owner of the dog food
factory says ” go away” you get curious.
So, do you have a camera and GPS Ray, its a fun way to spend the day
5 July 2007 at 2:39
Timothy Chase writes in 142: Of course contrarians will point out that instruments at poorer sites will have a bias, but as tamino (#91) points out, this bias is corrected for, and it is quite possible that given the methodology employed, removing the urban sites would actually result in a higher average temperature, and as Hansen points out (see tamino’s first reference in #93), the bias introduced by urban sites is quite negligible.
Some biases are corrected for (time of observation, re-siting to place), but it is fair to say not all biases are accounted for. For example, if over 20 years a big tree grows up and puts the station in the shade much of the day, that isn’t accounted for. If a parking lot gets added adjacent the sensor, that isn’t accounted for.
The logical thing to do here is take a reasonable sample, say 10% of the sites, throw out the ones that aren’t sited correctly, and look again at the trends. If the trend stays about the same, then great. False alarm. If it shows a fraction of the current warming, well, then that is interesting too. If the trend show even more warming, then that is interesting too.
It is a bit interesting to me that many are willing to let site issues slide, but the time of observation bias not slide. To me, with enough stations, time of observation is a non-issue. Some measure early AM, some measure late PM. As long as everyone measures their own station at the same time everyday it should work itself out. But I read Karl’s paper and seems that isn’t the case. Thus, there could very well be a significant bias from station location.
There’s a convincing arguement on Climate Science that all non-ideal site issues (pavement, trees + plants, paint deterioration) will result in a positive bias and that if you initially had a correctly installed site that you won’t see a negative bias.
5 July 2007 at 4:18
Dan Hughes re #19. If we’re just doing a head count, I agree entirely with tamino, and not at all with you. so that’s 2 who agree with tamino, and 1 (you) that agrees with you. Just empirically testing your “most people” believe your request for cites is reasonable.
I second the “unwilling to look” probability, and the likelihood of being “just another denialist,” and I add that this is obviously a ploy to get people to waste time. The topic of debate is, roughly, “Is global warming just an artifact of bad meterological station data?” Gavin points out 6 mistaken assumptions he sees leading to the topic question being answered in the affirmative. You claim they’re, in essence, strawmen created by him out of intellectual dishonesty. Fine.
You, not us, need to find a source that maintains the affirmative that does not use one of those assumptions. The burden of proof, again, is not on the person who bothered to make the Real Climate post, it’s on the person who challenged him, to actually cite data, not simply rail against him with spurious claims of logical fallacies and rhetorical tricks you cannot, seemingly, justify.
Again: the burden is on you to find a source that affirms that global warming is being registered, or the accepted magnitude of global warming is being registered, due to faulty meteorological station data, that does not use one of those assumptions. Or perhaps to explain why there is a campaign to harass stations and describe their activity as a “cover up.”
5 July 2007 at 4:24
== Post # 134 by David: ==
“Re #65 [not one person advocates what is the only sensible thing to do: perform a thorough review of the surface temperature sites. Instead, abstract, Machiavaellian motives are attached to anyone who dares question the suitability of the sites.”
= David says: = =” There are hundreds of papers that do this. Its a pretty standard scientific process. I can also point you to two very large PhD theses in Australia which are nice cook book examples.”=
How does the scientific process correct for an undocumented parking lot? Or a rooftop sensor? It still seems to me that applying corrections to a site whose characteristics are unknown to the scientists doing the correction is not the best science. Kind of like a doctor who only diagnoses over the telephone without ever seeing the patient.
5 July 2007 at 4:31
Re 145. Now wait a minute–how do you KNOW that such artifacts will not be corrected. Keep in mind that you have a time series as well as a spatial grid of stations. A station with readings that drift will be noticed. A systematic trend in one station over time that is not evident at neighboring stations will be seen. A momentary glitch at one station not seen at its neighbors. There are statistical techniques for dealing with these different types of errors.
Time of day is just another error they need to correct for. The problem is that you are assuming that other errors are not similarly corrected–and that simply is not the case. And that is precisely the problem with a bunch of people going out traipsing around stations–they may find siting errors, but they will have absolutely no idea what they mean for the conclusions drawn with the dataset. Data by themselves–especially vast amounts of data–really mean nothing. You have to analyze the data to draw conclusions that are meaningful.
Removing a “bad” station from the database does not necessarily improve the quality of the dataset–and it may even deteriorate it. On the other hand, if the station gives consistently unreliable readings, it would be removed via the statistical techniques used on the data.
My experience is that people love data–numbers–they glaze over when you start talking about what you do to the data to make them meaningful. How many times have we seen someone select two stations “randomly” and see that they don’t show significant warming over a limited range of time and conclude there’s no climate change?
If you do not understand the station in the context of the network and the methodology for analyzing the data, you are at best wasting your time (a hobby akin to train spotting), and at worst creating a tempest in a teapot of those who are similarly ignorant (which would include pretty much everyone who isn’t familiar with the entire network and its dataset going back to inception).
5 July 2007 at 5:24
#149 - read the page linked in #147, they account for those trends. Anyway, having read all 150 comments I agree that microsite issues are probably not a concern, and while a survey of HCN sites is worthwhile, it’s also very easily used as a distraction for the deniers. However, the AGW side is not much better, with articles like this that basically say we’re all doomed unless “emissions of greenhouse gases are reduced by 60% over the next 10 years” (for 2 deg C rise, and the chance of avoiding each further 1 deg C rise is given as “poor” due to cascading effects) which isn’t going to happen, becuase, well, China. At which point I stop caring since we’re either screwed from AGW or we’re not becuase GW isn’t AGW, most governments are trying to reduce CO2 emissions (see AP6 which includes China and India unlike Kyoto) and I have better things to do with my time.
5 July 2007 at 5:42
[[The logical thing to do here is take a reasonable sample, say 10% of the sites, throw out the ones that aren’t sited correctly, and look again at the trends.]]
No. You don’t throw out the ones that aren’t sited correctly. You estimate what their biases are and correct for them. That’s what’s actually done in practice, and for good reason — you don’t throw out data, even distorted data, if you can correct for the distortion.
[[ If the trend stays about the same, then great.]]
What part of “the rural stations show approximately the same trend as the urban stations” did you not understand? For the 17th time, the land surface temperature record is not the only thing that shows global warming. Sea temperature series reflect it too — are there urban heat islands on the sea? Boreholes reflect it too — are the boreholes poorly sited? Glaciers and tree lines and migration of plants and animals and sea ice and sediments and seashells show it too — are they all poorly sited?
You can’t get rid of global warming by throwing doubt on the land temperature records.
5 July 2007 at 6:29
Re 131.
Temperature records at US climate stations in Minnesota, Wisconsin, North Dakota and Montana show 3-5 deg F upward trends in annual mean data, 1890s through 2006.
In determining which stations to use for estimating the trends it was easy to pick out the stations with low quality data records by comparing the trends and data at the particular station being evaluated with records at its nearby stations.
For example, the record at St. Cloud didn’t fit with its nearby stations so St. Cloud records were not used in determination average regional trends. The station at St. Cloud was moved a few decades ago due to expanding economic growth at the old site to a new site which has frequent fog. A cooler annual mean temperature record than its nearby stations can be seen for the recent decades since the station was moved to the new site due to the more frequent days with fog. Although St Cloud is an exception to otherwise numerous high quality climate stations and data records, the records have been used frequently by climate change skeptics of global warming, e.g. John Daley, deceased, and others.
Temperature plots for US climate stations (from regional climate center data bases).
http://picasaweb.google.com/npatphotos
http://new.photos.yahoo.com/patneuman2000/albums
5 July 2007 at 7:06
I’m not surprised Pluto is warming. Its orbit is eccentric and it is a lot nearer the sun than it used to be — moving away again, but probably still showing the results of its time as the eighth planet.
JF
5 July 2007 at 8:52
I, for one, believe the preponderance of data indicate the climate is changing and trending warmer. I remain skeptical that CO2 is the primary culprit or even that a warmer earth is a bad thing (by the way, can anyone tell me what the temperature or climate should be?)
But let’s put all that aside. If the belief that rising CO2 emissions are going to cause catastrophic changes to the climate force policy changes that result in real, measurable reductions in emissions and pollution, is that a bad thing? Is it wrong to “go with the flow” if I feel the right thing will ultimately happen?
I tend to think it is not wrong - it is OK to go with the flow. So long as our efforts are directed at lessening our impact, then I’m all for it.
My concerns only pop up when there is talk of attempting artificial changes to the climate (force cooling) or simply moving the problem from point A to point B (carbon trading).
5 July 2007 at 9:00
#134: “A network that corrects error-free data is not necessarily better than a network that collects data with errors that are well understood.”
I have read and re-read this statement a few times and wondered if you could explain why this should be so. Is the first “correct” correct? I still struggle with it reading “collect”..
thx
5 July 2007 at 9:24
Re 161. Alan–yup, it’s a typo. It should be “collect”. Sorry for the confusion.
5 July 2007 at 9:42
#157 BPL: No. You don’t throw out the ones that aren’t sited correctly. You estimate what their biases are and correct for them. That’s what’s actually done in practice, and for good reason — you don’t throw out data, even distorted data, if you can correct for the distortion.
After you understand the impact of local influences and can dial those out, of course you can leave the sites in. But please explain to me how you account for the fire chief pulling his SUV next to the temp sensor? Does he arrive at the fire station everyday in a guassian or rayleigh distribution?
Because you can’t know that, you can’t eliminate the bias at this point. So the reasonable thing to do is to delete the 10% of that sited poorly and recalc. The system is oversampled, so you can easily see if the trend changes significantly. If it does, then it means the biases at the tossed out sites, while unknown, are significant. If you decide you want to recover the info in the tossed out but biased sites, then you set about determining the bias.
What part of “the rural stations show approximately the same trend as the urban stations” did you not understand? For the 17th time, the land surface temperature record is not the only thing that shows global warming. Sea temperature series reflect it too — are there urban heat islands on the sea? Boreholes reflect it too — are the boreholes poorly sited? Glaciers and tree lines and migration of plants and animals and sea ice and sediments and seashells show it too — are they all poorly sited?
The land temp has the most data points of any historical record, so it’s interesting. Note that I believe rural stations were classified based upon nighttime sat photos. Lots of lights around a station means it’s not rural, and no lights means it’s rural. But a site surrounded by a parking lot and next to a large brick building in the middle of nowhere coudl certainly exhibit temp distortions in spite of being in the sticks and being classified as rural, right? Have you read any recent “peer reviewed” research on UHI?
You can’t get rid of global warming by throwing doubt on the land temperature records.
You mean the way some wanted to get rid of MWP?
Seriously, though, we both know that. Again, getting this validated isn’t costing me or you a dime. Why worry?
5 July 2007 at 9:57
I have to smile at the commentors who seem to believe that an audit of all 1221 data collection stations wouldn’t be a large task. As an engineer who’s worked on a large number of cost proposals I’d like to offer a rough order of magnitude (ROM) estimate of the time and money it would take to do a complete audit.
To adequately audit a site would require more than just a drive-by photograph. You’d need take the photographic survey of the site but you’d also need to inspect the sensor mounting, power supplies and data acquisition system. You’d need to review maintenance and operation logs for completeness and anomalies. And, of course, you’d need to check the accuracy of each sensor against a calibrated standard. All of this could probably be accomplished in one 8-hour workday. Add a second day for the auditor to write up the findings and travel to the next site.
So each auditor could inspect roughly 2.5 sites per work week, or about 125 sites per 50 week man-year. Thus it would take about 10 man-years to audit all 1221 sites. Give or take a few man-years.
The defense firm I work for prices out technical manpower at between $150K to $200K per man-year (for salary, benefits, and overhead). For this estimate I’ll use the lower end of the cost range but given the high amount of travel involved a more definite figure could well be higher.
So 10 man-years at $150K per man-year would be 1.5 million dollars. That’s a lot of money if you’re a private citizen, or even a university. But it’s not a lot of money for a major fossil fuel company. It’s less than the cost of a commercial during the Superbowl, and much less than companies such as Exxon are spending on their FUD campaigns. Does anyone seriously believe that Exxon, or another of its ilk, would hesitate to spend that money if they believed it would support their position?
5 July 2007 at 9:59
Steven Mosher,
Hopefully you understand that my concern is not that any systematic audit of stations will overturn the conclusion that climate is changing. Were that possible, it is undoubtedly something we would all wish for. My concern is that there are plenty of unscrupulous (and often highly paid) elements in the denialist camp who will stop at nothing to delay action on climate. (I also hope you understand that I do not impute ulterior motives to you.)
There are many ways of dealing with imperfect data–trying to perfect it is only one solution, and often not the best or most efficient. In many cases, excluding less than perfect data can actually diminish the overall quality of the dataset. And if a particular station were really problematic, a good statistical analysis procedure would effectively eliminate it from the analysis anyway.
I would very strongly urge you before taking part in this effort to familiarize yourself with the network and analyses as a whole. Understand the statistical quality controls used and how they work, and if you discover a problem site, look at the types of errors it might produce, how they would be identified/treated and what the ultimate post-analysis effect on the conclusions of the analysis might be.
Just so you know, I’ve been on both sides of this issue in the past. My thesis experiment (experimental particle physics) featured very noisy data that I had to clean up without manufacturing a signal. On numerous occasions, I had folks running up to me very alarmed saying, “Did you know…” Based on the fact that I did get my doctorate, you can assume that I did know and did come up with procedures for dealing with the faults in the data. In my current incarnation as a radiation engineer, I often find issues with electronics and rush to the satellite design engineer and say, “Did you know…” More often than not, they say, “Yeah, and this is what we did to mitigate that…” Orbiting observatories like Hubble are a devils playground for radiation effects, which can corrupt data and cause systematic drifts over time as radiation dose mounts. The data are imperfect, but there is always some desperate grad student who finds a way to use it.
Also, note that I said that the stations that have problems are more likely to be those that are old–not that invariably old stations will have problems. And keep in mind that imperfect data is not unusable data.
5 July 2007 at 9:59
Re #12, and others, Dan Hughes’s questions:
I was checking out the always-amusing conservapedia (”The Trustworthy Encyclopedia”)regarding global warming, and here’s the very first sentence of their explanation of what they call “The Modern Warm Period”.
(The two citations are to Pielke Sr’s blog.) Given this wording, and the prominence conservapedia gave this issue, it’s clear they hold Mistaken Assumptions 1 and 6 in Gavin’s post. Given the nature of Conservapedia, I think that it’s safe to say that this is a fairly common belief, held by more than one or two people.
5 July 2007 at 10:11
And as people begin to understand the issue, and realize this isn’t going to be a killer complaint we start to hear all the other beliefs relied on as rationalizations for doing nothing come out again — it can’t be real, it’d cost too much to avoid the cliff maybe the car will grow wings before we crash, my life is too short to care what happens after I die, I can’t believe it’s a problem, anything people do is natural change …. each time a new supposed magic bullet is pulled out to kill the monster and fails, the same litany of reasons gets expressed. People, when you find yourself chanting the litany of beliefs that reassure you that you don’t have a problem, you have a problem.
5 July 2007 at 10:23
#162 - thx Ray, I’m still interested in why it’s better to have well-understood errors rather than no errors?
[Response: False dichotomy. There are always errors and one should strive to understand them as best as possible. The idea that there are any error-free sources of information about the real world is an illusion. - gavin]
5 July 2007 at 10:25
Re #38
I suppose my problem in #38 was using a phrase — Voronoi tessellation — that no one was familiar with. I’ll try again.
To construct the Voronoi tessellation of the land surface of the earth using met station locations, you do the following: 1) take a station, 2) connect it with line segments to all the nearest adjoining stations, 3) construct the perpendicular bisectors of each of the line segments, and finally 4) construct the convex cell (with polygonal boundary) formed by joining of all of these perpendicular bisectors.
The “cell” so constructed will consist of all of the points on the earth that are closer to the station you started with than to any other station. In an urban area with several met stations, that cell will be relatively small. In a rural area with the nearest stations tens or hundreds of miles away, the cell will be relatively large. Assign to that station’s data times series a weight equal to the area of its cell.
Now the global/regional/local “average” temperatures/precipitation/etc. will be calculated using area-weighted averages of the individual station time series.
This process has the following virtue:
Anyone who has lived in an urban area for a few decades and listened to or watched weather reports for that time is aware that the urban heat island is a real phenomenon — telling us that a real part of the real earth has experienced accelerated warming. That warming may be a product of land use changes, thousands of exhaust air streams of air conditioners, construction of thousands of heat storage structures (Trombe walls?), or less-than-ideal locations of met station instruments (or, for that matter, less-than-ideal location of urban residents). The weighted average described here will assign to that real warming of small part of the earth’s surface the appropriate (small) weight.
What RC’s visiting denialists are calling “bad” local met station data is, in most cases, perfectly good data recording what is really happening in one small part of the earth’s surface.
If you wanted the global/regional/local averages to somehow provide a measure of average human misery due to increasing temperatures, then population-weighted or un-weighted averages will probably capture that, since the density of met stations is a reasonable proxy for population density.
Best regards.
5 July 2007 at 10:31
re reply to 67
The Quatsino data is surpringly like the SST temperatures with the so-called ‘bucket correction removed. That correction distorts the Hadcrut3 temperature plot - I believe the correction was originally required to make one of the major GCMs produce accurate land temperatures - and should now be re-examined.
I came to suspect something wrong with Hadcrut3 because of my own toy theory of global warming (briefly, oil and surfactant spill reduce marine strato-cumulus cloud, lower the eath’s albedo and warm the ocean), which predicts a temperature blip during WWII caused by the Kreigesmarine effect. Removing the bucket correction from SST records shows this blip loud and clear, as does the Quatsino record. This means that we can bypass the UHI troubles by accepting uncorrected SSTs as valid — a huge data pool of uncorrupted temperatures. Eyeballing, the Quatsino data shows a warming of .14 deg/decade for the last 100 (ish) years. So does the SST data.
Even toy theories have value it seems.
BTW, if this duplicates, my apologies: the first attempts didn’t show up.
Julian Flood.
5 July 2007 at 10:55
Re 167. ” People, when you find yourself chanting the litany of beliefs that reassure you that you don’t have a problem, you have a problem.”
Maybe we could come up with a 12-step program for denialists. Except these usually put everything in “God’s hands”, and then people could go right back to ignoring the issue saying, “Oh, God will sort it out.” The inability to accurately assess risk may be the fatal flaw in the human intelligence. The irony is that the condition while not curable is treatable by large doses of pragmatism and a strict avoidance of ideology (left or right) and complacency.
5 July 2007 at 11:03
#165 Ray Ladbury My concern is that there are plenty of unscrupulous (and often highly paid) elements in the denialist camp who will stop at nothing to delay action on climate. (I also hope you understand that I do not impute ulterior motives to you.)
Delaying action will already happen, because “doing a little” (Kyoto) doesn’t change the outcome appreciably, and “doing the amount needed” will cause rioting in the streets once the western world understands what they will need to give up.
And you don’t think there are those that stand to make millions if global warming is indeed a serious problem? Do you honestly believe there are no agendas on the “believer” side of things? For real?
Make no mistake, while there are indeed a few humble scientists toiling away on the subject, there are forces lining up on both sides that will make (or continue to make) lots of money (cash, fame, adulation, free dinners) on this. Be very suspicious of both arguments when this much money is at stake. First in line at the cash register is Al Gore with his clean energy fund. If folks don’t believe in warming, his fund tanks. If they are scared to death of warming, his fund soars.
5 July 2007 at 11:08
Re: 158.
Taking out stations with low quality data records does not mean the data at those stations is never used. The station where a bias or shift is know to exist in the data record may still be used in estimation of missing reports at nearby high quality stations for non-critical points (i.e not a recent, warm or cold value. The data from that site can be used with as little as three known good quality values by deriving a year-to-year change at that station and applying the difference to determine an estimate of for a point at a station of high quality where a single data value is missing or questionable.
5 July 2007 at 11:11
Alan K., Gavin is of course right–error-free data does not occur in nature–or at least it does not occur in a context where you can do anything meaningful with it. In order for a dataset to be error free, you would have to constrain the problem to such a degree that it would no longer apply to the real world. Moreover, a dataset that was advertised as error free, would lead to overconfidence both in the data and to what it could be used for.
The old aphorism applies here: “A man with one watch always knows what time it is; a man with two is never sure.” Maybe so, but two watches gives you much more of an idea of how unsure you should be (though to really know, you need at least 3, since that’s the minimum number you can use to calculate a meaningful variance.).
5 July 2007 at 11:13
My problem/concern with global temperature measurements, briefly summarized as (and still…) “margin of error”, is amplified by the borehole and ocean depth “validation”. If, for the sake of discussion, measuring the year-by-year temperatures and coming up with anamolies that add up to 0.7 degrees over 100 years or so is dicey, measuring reliably the even finer temperature gradient one meter, five meters, 100 meters, whatever, has to be damn near physically impossible, is it not? Scientifically at least.
I do recognize a practical dilemma if my contention has merit. And that is if you wait for global temp measurements that satisfy my accuracy requirements, the global average would have to be 5-10 degrees or so hotter, so we finally validate the warming a couple of days before we die. You have no choice but to use what you have, but I see no need (other than politically) to ballyhoo it.
For the record (and speaking for myself, not the skeptic community), with a couple of nuances and one generality, I agree the six “skeptic arguments” of this thread have little scientific credibility. The nuances: #1) I remember when the issue of urban heat islands there was a hue and cry from AGW proponents that UHIs did not exist. Though I don’t recall if those proponents were politicos or scientists. At any rate when it was pretty much determined that UHIs do exist but are easily accounted for in the mathematics it became a non-issue except for the small contingent of loud bottom-feeding skeptics (I feed only at the shoreline [;-} ). #5) Your refutation of this (individual station errors) is valid but only up to a point. Clearly there could be cases where individual station errors would lead to erroneous results. Though I don’t believe we’re currently there. Admittedly my nuances, while I think accurate, are not very important in the scheme of things. Overall, while I don’t necessarily fully agree with Pielke (see, I can disagree with far more intelligent people than me on both sides of the table with no shame what-so-ever!), I do think he has a general point that AGW scientists are too quick and too willing to solidify in gold data and information that, while significant, is less than perfect.
I also think that proof coming from Arctic sea ice, glacier retreats, etc. might be indications, but are just one step away from the cherry blossoms blooming early, the 26+ storms we had in 2005, Ted Turner’s statement, “it’s hotter than hell outside”, etc. “proofs” that are thrown out by some. There is no “proof” that these are more than natural occurrences (or, admittedly, neither that they are not) and require, for now, really contorted tortuous explanations ( snow/ice getting covered with soot, Arctic really getting lots warmer than the few tenths of a degree of the global average just the past 2-3 decades, etc.) why AGW is causing them — though they are professed with religious conviction.
5 July 2007 at 11:49
Matt,
I do not care about Al Gore. The impetus to deal with this issue is not coming from him, but from what the science is telling us. Listen to the scientists–they are very nearly all on the same side on this one. I have nothing against someone making money if they do so honestly. I deplore those who lie to make a buck or to preserve their privileged status–and that is what the denialist disinformation machine is doing in this case.
5 July 2007 at 12:01
Rod, please read some science.
You write:
> There is no “proof” that these are more than
> natural occurrences
You’re right, of course.
You’re a longtime reader and commenter here.
You’ve either missed one of the basic things about science that people have been trying to help you learn, or you know better and you’re posting the talking point from the PR people consciously.
Read the cartoon in the link below at least, please.
For any new readers who don’t understand why the insistence on “proof” or even proof in science is a bogus claim, this may help:
http://zenoferox.blogspot.com/2007/05/truth-with-capital-t.html
5 July 2007 at 13:42
Ray,
Do you include Pielke Sr. in your “denialist disinformation machine”? What are his motives for raising contrarian questions? You suggest we “listen to the scientists” but some scientists do disagree, as you indicate. [edit]
Who else do you include in the denialist cabal? Please name names so we know who to avoid.
5 July 2007 at 14:26
I am sorry, I do not understand this thread. It appears to me that Mr. Watts project involves checking (by photo) the existing weather sites in the U.S. Why would a scientist NOT want to periodically check his instraments, from which he recieves data, to assure their accuracy?
5 July 2007 at 14:33
Gary, when you take a picture of a thermometer, what does that tell you about its accuracy?
When you take a record every day of hundreds of thermometers all around your home and compare them, will you know any more about the temperature where you live? That’s what the instruments are used for — the accuracy is an outcome of the large number of measurements taken, and of quality control checks on the data.
The picture tells you only that there really is a box at the location described. Looking at the temperature record in the database tells you if there’s anything odd about the record over time. Looking at the other records tells you if there’s anything odd about that location over time.
Nobody’s argued it’s not good to consider whether the picture shows a problem. If there’s a tree on top of the box or a car parked on it or a big hole in it or a barbeque restaurant’s open pit fire next to it, that’s good to know.
5 July 2007 at 14:51
Re 178. Some scientists will always disagree. All will have their own motives. That is why scientific consensus is critical to the progress of science. Pielke is problematic, because he has never said whether he really believes climate change will just go away if all his concerns are addressed.
Re 179. The stations are checked. The data are checked. And checked again. And measured against other indicators. The real question is why this extraordinary level of checking is insufficient for some.
5 July 2007 at 14:51
Gary (#179) wrote:
Scientists check their instruments by visual, instrumental and statistical means. But contrarians either wish to have stations eliminated (even though we can get useful information from them by correcting the data using well established statistical methods and closing stations would reduce the accuracy of our temperature estimates) or what is more likely, simply wish to change the focus from the well-established rise in temperatures (by means of many independent lines of investigation including the shrinking of the Arctic Ice Cap) to the fact that some stations are not ideal in order to discredit the science which has established that climate change is taking place and that it threatens countless lives.
In some cases, the motivation for opposing the science are financial (e.g., due to someone being in the pay of Exxon), in other cases it is a concern for the economy, but it may also be more ideological in nature. I personally suspect that the latter two categories taken together are more common than the first. I have some sympathy for the second, although I believe it is misplaced given the likely consequences for the global economy of climate change simply in terms of this century considered by itself.
5 July 2007 at 15:19
The use of ‘denialist’ and ‘alarmist’ and their variations has reached entirely new depths of disgust in this thread. Unfortunately, the RealClimate Web site has already started to lose its creditability because of the presumptive and unilateral applications of these labels by quite a few people who post here. What was started to be a source of correct and reliable science information has degenerated to its present state of mess.
If a poster decides to presumptively and unilaterally apply any label to other posters, they should be required to state exactly which subject matter the label applies too. After all there are an almost uncountable number of things that can be the subject of denial and alarm. More importantly they should be required to cite references in which the target of the label has explicitly stated ‘denial’ or ‘alarm’ about the subject.
The subjects of this thread are basically related to the quality of empirical data. So, ‘denial’ and ‘denialist’ must mean that some people are denying that the data shall be of highest quality. Others, apparently, are ‘alarmed’ that the data are of highest quality.
“Science should not tolerate any lapse of precision, or neglect any anomaly, but give Nature’s answers to the world humbly and with courage.” Sir Henry Dale, past President of the Royal Society of London.
5 July 2007 at 15:52
#177
re: your statement to “please read some science”
I like that article. Science is traditionally a difficult thing to define. Math is formal science. Climatology is a natural science. Climatology is a soft science (much like economics, archaeology or geology are) so it’s difficult to prove theories and is open to interpretation. Not only that, but AGW has a social science aspect to it since the claim is that it is caused by humans.
5 July 2007 at 16:00
Re #178: For those interested in RP Sr., see this Stoat thread and in particular this comment by me. The ultimate arrangement of these particular tea leaves seems to me to point to an explanation that’s more psychological-social-political than scientific.
5 July 2007 at 16:13
Re #179: [Why would a scientist NOT want to periodically check his instraments, from which he recieves data, to assure their accuracy?]
The real issue here is not checking the instruments (which, as people have been pointing out, has been and is being done), it’s the motivations of the people who are now calling for the checking. Their argument is essentially “We don’t like what your instruments tell us, therefore they must be wrong, or at least we can make enough noise shouting about it to drown out the real issues.”
Let’s do a little thought experiment. Since these people claim instrument error, let’s pretend that no one ever invented an accurate thermometer until today. Throw out all temperature records, and make a judgement based on all the other lines of evidence: arctic & glacial melting, earlier spring thaws, runoff patterns, plant & animal cycles & migrations, and all the rest. Doesn’t all that tell exactly the same story as those allegedly inaccurate temperature records? And doesn’t that mean that either the temperatures must be pretty much right, or that the whole darned world is wrong?
Which, come to think of it, is the problem in a nutshell: the world as it is doesn’t suit these people, so they pretend it’s otherwise
5 July 2007 at 16:31
Dan Hughes (#183) wrote:
Dan,
By suggesting that climatologists need to have their stations audited, contrarians are implying that climatologists incapable of monitoring themselves, either because they are extremely incompetent, grossly negligent, dishonest, ideologically motivated or involved in some sort of conspiracy, or perhaps a little of all of the above. That is of course their privilege - for the most part.
However, given the fact that in the vast majority of the cases they refuse to acknowledge the overwhelming evidence from many different lines of investigation which cooberates the trends that are being discovered by means of temperature measurements, this leads me to the conclusion that they are not sincere or particularly concerned with the truth. At that point I believe it is appropriate to discuss their motivations - and it would be dishonest to treat them as genuine seekers of the truth.
Nice blog, by the way:
http://danhughes.auditblogs.com/
5 July 2007 at 16:34
ok, I promised myself I would not respond to some things but Let’s have a look at the local epistemologist.
Timothy Chase:
“Scientists check their instruments by visual, instrumental and statistical means. ”
There is no evidence that Hansen Jones or Parker ever did a visual inspection of weather sites.
Parker even claimed that Urban sites were located in PARKS. More on this later. I have yet to see a SINGLE calibration record for any HISTORICAL site. link one, please.
Now, I want you to Check JONES’ treatment of the instrument error at stations. You go hunt down his paper. Then see if you can spot the error he made in estimating instrument error over a month long period.
Timothy Chase:
“But contrarians either wish to have stations eliminated (even though we can get useful information from them by correcting the data using well established statistical methods and closing stations would reduce the accuracy of our temperature estimates) ”
Well, on one hand I have Ray telling me that the “grid” is over sampled ( like he knew the frequency) and on the other hand I have you telling me that We can get good information from these junk stations, begging the question. You all should get your story straight.
either, believing ray, the grid is over sampled by a factor of 3 and we can live with Noise, or delete stations; or believeing you, excising stations that don’t meet QA standards will corrupt the “SIGNAL”.
You believe in the signal.
Timothy Chase:
“or what is more likely, simply wish to change the focus from the well-established rise in temperatures (by means of many independent lines of investigation including the shrinking of the Arctic Ice Cap) to the fact that some stations are not ideal in order to discredit the science which has established that climate change is taking place and that it threatens countless lives.”
Motive hunting. Hansen and Karl, initiated this criticism of the historical network. NOT US.
Let me quote HANSEN Karl. Then you decide.
“Are we making the measurements, collecting the data, and making it available in a way that both todayâ??s scientist, as well as tomorrowâ??s, will be able to effectively increase our understanding of natural and human-induced climate change? We would answer the latter question with an emphatic NO. There is an urgent need for improving the record of performance.”
more from Hansen/karl
“It is necessary to fully document each weather station and its operating procedures. Relevant information includes: instruments, instrument sampling time, station location, exposure, local environmental conditions, and other platform specifics that could influence the data history. The recording should be a mandatory part of the observing routine and should be archived with the original data. ”
[edited to remove pejoratives - please stay polite]
5 July 2007 at 16:37
Eli thinks that a lot of people don’t have a clue about how stations are run and calibrated and checked. There is literature out there folks, go read it before running off telling everyone that you are going to save the world by taking pictures.
Hint: One picture says nothing about the HISTORY of the station
5 July 2007 at 17:09
Dave Blair (#184) wrote:
From what I can see, you would regard chemistry and physics to be soft sciences. This isn’t how term “soft science” is generally used. The term “soft science” is generally contrasted against “hard science” which would include physics and chemistry.
“Soft science” typically refers to those sciences which study humans, particularly where human psychology becomes involved. Climatology does not study humans - although it may be used to identify where human causation has resulted in certain effects within the climate. But this would be no different from an analysis in terms of physics of how a driver stepping on a gas pedal resulted in the car plowing into a bus.
In truth climatology is best regarded as an advanced branch of physics - although there are certainly elements of chemistry to it.
5 July 2007 at 17:40
James: The real issue here is not checking the instruments (which, as people have been pointing out, has been and is being done), it’s the motivations of the people who are now calling for the checking. Their argument is essentially “We don’t like what your instruments tell us, therefore they must be wrong, or at least we can make enough noise shouting about it to drown out the real issues.”
Maybe it is just me, but the way to combat this is to not take the Timothy Chase route and devine what’s in their souls to decide if a response is necessary, but rather to make sure that everything is documented so that these questions won’t come up in the future. If their questions are foolish then it should be easy to refute.
To a casual observer like myself it looks like things might have been a bit sloppy (weather station that is on a new parking lot, cities marked as rural when they are now urban) and that instead of trying to fix the issue people on here are trying to say that they are being persecuted.
5 July 2007 at 17:52
Well
Today’s question for the curious.
Gavin gave me a nice little project. THANKS!. basically, GISS
estimates that the land record for the period since 1900 has increased at about .8C +-.2C ( 95%CI) or .008C per decade +-.002C
Since Anthony Watts started his search in Chico california, I thought it would make sense to try to understand what the science said about that grid.
So, Gavin provided me with the linear trend for increase in temps in Anthony’s grid: 35N-40N, 120W, 125W.
The linear Trend, per gavin, is .8C/century. I didnt get a CI from him… so, I’ll assume the global CI
Ok.. back to the investigation.. just begining
Let’s talk about 35N-40N, 120W -125W. It is in california.
includes San Fransisco, San Jose, Sacramento, Sac valley,
And inches towards Tahoe. It’s geographicaly diverse.
Coastal, Urban, Rural, agricultral..
GISS, best as I can tell, uses 20 stations in this GRID.
Data from those stations is “used”.
Now, 3% of the world’s land surface is URBAN. California is about 5% urban.
I Have no reason to believe that 35-40N, 120W-125W varies from this
percentage in a substantial way.
But, Lets imagine that 10% of the land mass in this grid were URBAN.
twice the mean for the state 3 times the mean for the world.
Ok.. imagine that 10% of 35N-40N, 120W to 125W is Urban.
Now. I have a list of weather stations in this grid.
Weather stations that are “used” ( according to gisstemp files)
Now, if 10% of your land mass were URBAN and 90% rural, and you randomly picked 20 locations to sample the climate, how many would
come from Urban areas ?
questions:
1. if 10% of the land is Urban, how many stations out of 20 are CATEGORIZED as urban?
a. 2 (10%)
b. 5 (25%)
c. 10 (50%)
d. 15 (75%)
2. What percentage of weather stations are located at Airports and or Military bases?
a. 10%
b. 20%
c. 40%
d. 60%
3. If the Urban landscape is oversampled and the rural lanscape is undersampled, can you perform powerful discriminating tests comparing the two? More specifically, if 5% of your population ( urban land)
is represented by 50% of your sampling, and if 95% of your population ( rural land) is represented by the other 50% of your sample, What kind of claims can you make about difference between the two?
5 July 2007 at 18:34
steven mosher (#188) wrote:
Not personally.
However, if you have ever taken time out for economics you might have learned about the division of labor. Population growth tends to result in that sort of thing and the efficiencies of scale which follow from it.
Oversampling is part of what makes it possible to get good information out of the grid. Cross-verification, and when one station or another is on the fritz you have other stations to fall back on.
Context please. References…
If you look at what he is actually saying, he seems to be concerned with improving the quality of the science. I presume this means that you will be throwing your full support behind his efforts? Advocating the kind of funding which it will require?
*
In any case, there are always motives.
In science the primary motive is curiosity and the reward a sense of wonder. One might also believe that one is under a moral obligation to understand to the best of one’s ability. Patterns in human action will suggest different motives. But in any case, one begins with identification which precedes evaluation, and in communication, one begins with the assumption that others are engaged in a similar process - until one has sufficient evidence for thinking otherwise.
5 July 2007 at 19:05
Dan Hughes - “The subjects of this thread are basically related to the quality of empirical data. So, ‘denial’ and ‘denialist’ must mean that some people are denying that the data shall be of highest quality. Others, apparently, are ‘alarmed’ that the data are of highest quality.
“Science should not tolerate any lapse of precision, or neglect any anomaly, but give Nature’s answers to the world humbly and with courage.” Sir Henry Dale, past President of the Royal Society of London. ”
I am not sure that this has been said in the 192 posts on the subject however if it has please delete this comment.
The most completely obvious comment that sort of takes all the wind out of McIntyre’s sails is that the network of weather stations is not the property of climate scientists. It is not climate scientist’s responsibility to calibrate, check or collect data from these weather stations. They are provided with sufficient accuracy for the purpose for which they were designed - that of helping to predict the weather. For their primary task they are sufficiently accurate. If climate scientists had the money and opportunity to set up a system I am sure that they would demand sensors of the highest precision sited in ideal locations. However they have to work with what they have. Lacking the funds to build a parallel network with higher precision, they make use of this imperfect data because the network is extensive, already in place, has a long history and is paid for by someone else and not draining scarce research funds.
Rabbeting on about climate scientists should do this and they should not put up with data of dubious quality is completely missing the point that they are not in charge of the data. Start harassing the relevant meteorology departments to improve the network. However they will probably tell you that the network serves admirably for its primary purpose and why should they spend money upgrading it?
If you are so concerned with the data then pay to setup a higher precision network with carefully chosen sites. It should only cost a few million dollars which would be fossil fuel companies’ money better spent. I honestly think that this is not really not an ideal wedge issue and that a better one needs to be found.
5 July 2007 at 20:13
RE 183,
I find it interesting that you quote a past president of the Royal Society, Dan, maybe you should check out what they say about AGW.
http://www.royalsoc.ac.uk/landing.asp?id=1278
5 July 2007 at 20:19
Re #191: […but the way to combat this is to not take the Timothy Chase route and devine what’s in their souls…]
I have to disagree, simply because that’s where the problem lies. The questions related to weather station siting & accuracy have been addressed, here and in the links people have provided. I’ve seen nothing that persuades me that the people claiming problems have even looked at any of this, let alone understood it, or would allow their opinions to be affected if they had.
[To a casual observer like myself it looks like things might have been a bit sloppy (weather station that is on a new parking lot, cities marked as rural when they are now urban) and that instead of trying to fix the issue…]
Because you don’t, or won’t, give the matter enough study to understand that it has been fixed. The problem is that even after being fixed, what the data is showing isn’t what the people asking the question want to hear, so they ignore the answer and go on repeating the question in order to convince their audience that it’s a valid question. This is a basic underhanded debating tactic, used by everyone from major religions & political movements down to UFO cultists & 9/11 conspiracy theorists.
5 July 2007 at 20:32
Re: 188
——–
In the US the answer is yes, yes and no.
5 July 2007 at 20:37
> quote HANSEN karl …
He’s quoting second hand from Climate Adit:
climateaudit.org/?m=20070605
5 July 2007 at 20:55
Yes, yes, in theory anyways, but still a no for public availability unless they have lots of money to spend on 100 year historical records and recent observations.
… The National Weather Service (NWS) makes observations and measurements of atmospheric phenomena as required for climatological, hydrologic, meteorological, and oceanographic services. …
http://www.nws.noaa.gov/hdqreorg.php#od
5 July 2007 at 21:16
Some of this criticism seems to be confusing different scales of “error” that have different functional meanings. My training is in soil science so this may be outside my area of expertise and maybe I’m way off-base. However I have assisted with the set-up and analysis of meteorological stations in my own research (on small watersheds in the New York City Watershed).
Much of this debate seems to be confusing “measurement error” with a spatial covariance of land-use and temperature trends (someone with a Phd: is “heteroscadasticity” a correct term for this?). Measurement error can be either be due to instrument error or artifacts due to poor siting (”the asphalt effect”).
But it strikes me that this type of error is something different than the UHI effect (though on the face of it they would appear to be related). But this “instrument” and “siting” error geostatistically speaking is expressed as a microscale variability which is what I believe is “corrected for”. And as far as the “asphalt effect” we should also consider that there is an intrinsic natural, microscale variability in the micro-climate system. I’m thinking for example of how we modeled a basic estimate of evapotranspiration using the temperature gradient derived from a surface and 1.5 meter temperature reading.
But isn’t the UHI effect something other than this “microscale variability” that would be evident at a regional, spatial scale as a “hot spot” for instance (thus the urban heat island). Yes? No? Shut-up?
5 July 2007 at 21:17
Steven Mosher, I mean no disrespect by this, but your responses give an impression that you have never worked with very large datasets or with a very large geosciences information network. Among others, the assertion that useful data cannot be gleaned from the extra stations in an oversampled network–even if tossed off flippantly–is so far off the mark that it indicates that you don’t have a lot of experience in data analysis. You seem to completely discount the validity of algorithmic and statistical filtering, leading me to wonder whether you have seen what it can do. If I am not too far off the mark, then why should we have confidence that you will be able to competently assess the implications of any siting irregularities that you find? Would your time not be better spent first learning something about the analyses that use the data you seek to improve? After all, how can you improve the product when you do not understand the needs of your customer? I have no objection in principle to what you are doing. It may be particularly valuable as we move from global to regional climate modeling (where the oversampling is a lot less). What I object to is effort wasted in an attempt to “help” when you don’t understand what help is truly helpful.
5 July 2007 at 23:33
Re 188 Responses by steven mosher
You seem to be making one very fundamental mistake here: No offense to Ray or Timothy, but neither is a climatologist (as they frequently point out in their posts), so what they write on this blog carries no weight in field of climatology. So, it really doesn’t matter whether they agree or contradict one another - you can choose to believe one, or the other, or both, or neither, and it makes no difference; the reality of anthropogenic global warming does not hinge on their ability to explain or defend the measurement of temperature.
What you should be reading and trying to understand is the peer-reviewed literature that underlies the conclusions in the ICPP reports. If there are serious problems with the raw data, report this in a venue that will be read or heard by the scientists making the temperature measurements and using those data in their analyses - your criticsms are falling on deaf ears here, as far as I can tell (I’ve seen no evidence that anyone is taking your concerns seriously, as you seem to be saying that which scientists who study climate already know, and have known for a long time).
5 July 2007 at 23:46
#176: Ray Ladbury: I do not care about Al Gore. The impetus to deal with this issue is not coming from him, but from what the science is telling us. Listen to the scientists–they are very nearly all on the same side on this one. I have nothing against someone making money if they do so honestly. I deplore those who lie to make a buck or to preserve their privileged status–and that is what the denialist disinformation machine is doing in this case.
Hi Ray. I didn’t ask if you cared about Al Gore, I asserted that there are those on both sides driven by an agenda. Do you disagree?
When something isn’t completely understood, it doesn’t matter if 100% of scientists believe it is true. H Pylori. Nobel Prize. It’s a very good example of how modern peer review stumbled for 40+ years. Even the IPCC agrees there are major components of our climate that are poorly understood. And like particles in the mid 90’s, these misunderstanding could indeed have a substantial impact on long-term estimates. Please state if you disagree and I’d be keen to adjust my mindset.
Again, I don’t think either side is lying here. I think both sides aren’t being completely transparent with data. And when I hear of lost data, secret source codes and hidden techniques, I get suspicious. And you should too!
We have a very interesting article for our discussion here: http://www.climateaudit.org/?p=1798#comments
Are you interested in making this a case study for the discussion as a whole? From my perspective, folks here are arguing this stuff has been vetted multiple times. I look at another set of folks that can’t find original data or techniques, and their conclusions are that somebody just decided to add 3 degrees of warming to NYC during the last 20 years.
If you are correct, then there’s an answer here and a few minutes with Dr. Karl et al will clear things up. If the other team is correct, then yes, things look fishy and unvetted and we should be suspicious.
[edit]
6 July 2007 at 0:23
dan hughes realclimate is losing credibility only with dead-enders out in the far standard deviations of the Bell curve. You need to own your statements. there IS no balance. the people calling mainstream science alarmists are mostly liars. Some of them are fools. The rest are simply of a contrary opinion by happenstance.
On the other hand, the mainstream scientists and average people calling the denialists denialists are correct. There is an observable running from science - attacks on the very concept of peer review, of a consensus developing on what evidence means, on wanting more funds for gathering more data, on the stations that gather data, and so on.
Since the less than 1% is mostly paid Exxonists, what has gained or lost credibility (and frankly, that’s a falsehood, you’ll ALWAYS claim RealClimate is “losing credibility”, implying that it had any with dead-enders) among them is irrelevant. Don’t waste people’s time with such boilerplate. If you ever have a point to make, now would be a good time to make one.
6 July 2007 at 1:22
Dave Blair (190). Geology with economics and psychology? That’s non-sense. Geology maybe more of an integrative discipline that uses physics, chemistry, biology, mathematics, but it is far from the approximation of the others you mention.
6 July 2007 at 1:48
Chuck Booth (#188) wrote:
None taken.
I am here principally to learn. I also enjoy participating in the discussion - much like those who never let their qualifications stand in the way of criticizing that which they do not understand, but with the objective of understanding that which I do not understand. Oh, and I would like to be helpful, if possible.
I am quite satisfied with that.
*
“I could be bounded in a nut shell and count myself a king of infinite space, were it not that I had bad dreams.”
Hamlet, Act II, scene ii
6 July 2007 at 2:34
== Re: Post #189 by Eli Rabett: ==
=”Eli thinks that a lot of people don’t have a clue about how stations are run and calibrated and checked. There is literature out there folks, go read it before running off telling everyone that you are going to save the world by taking pictures.”=
That old saying keeps coming to mind: “A picture is worth a thousand words.” From some of the embarassing photos seen, I would say those photos trump every single word posted on this thread in defense of the current surface site situation.
== Eli goes on to say: ==
Hint: One picture says nothing about the HISTORY of the station.==
I don’t understand your point. A picture of a bad site speaks of professional neglect. That there have not been regular photos taken of core sites speaks of neglect too as the history of the site becomes suspect also.
That people do not “understand” how sites have been run/calibrated/checked is understandable. One needs proper documentation to understand something.
6 July 2007 at 5:34
re 203
“We have a very interesting article for our discussion here: http://www.climateaudit.org/?p=1798#comments”
Fascinating indeed…
- About what people can lose their time at (determine the position of the station to the centimetre was a great achievement). So one presumably bad measurement station in NY and the whole data is to throw in the garbage? Just one thing about this analysis, it would have been smarter I think to compare the adjustments made with the energy consumption of the city, for exemple, rather than to the population (unless one thinks body heat has a great role in UHI…)
I’m also astonished by the local dimension of the debate. Some people apparently don’t want to rely on the American meteorological data. I still don’t get why, but whatever… The fact is, America is only a small part of the world, and many other countries have pretty darn good meteorological networks.
If I take my own country, France, we have at our disposal one of the best and most complete (specially for our relatively small territory) meteorological data network. This network is run by a public office named Meteo France, whose only agenda is to predict as accurately as possible national weather. Their data collections are then reused for climate studies.
For those you are keen on French , here is the link to their site, and the link to the maps that show the French meteorological data collection network:
http://www.meteofrance.com/
http://climatheque.meteo.fr/aide/climatheque/reseauPostes/
So, what does Meteo France has to say about temperature variations in France during the 20th century?
http://secours-meteo-fr.axime.com/FR/climat/img/tempminimaxi.gif
If you know France a bit, you’ll notice that the regions that experienced the highest warming trends are rural areas… Could there be a Rural Heat Island?
Of course this is all local data, but I guess one could find the same kinds of results when looking at other meteorological networks around the world. But wait a minuteâ?¦ isn’t it precisely what climate scientists are doing when collecting global data?
6 July 2007 at 6:55
Matt,
First, what do you mean “lost data, secret source codes and hidden techniques”–the techniques are published. The code has been peer reviewed and the data are available to any fool with a high-speed internet connection–as illustrated by your climateaudit post, which makes a reconstruction for a single station and uses it to draw ridiculous conclusions about the network as a whole.
And do you really equate the state of medical science–which really still isn’t all that scientific–and physical science? In any case, you will note that as soon as there was any evidence of the link between H. Pylori and ulcers, it was accepted almost immediately. This shows that peer review works, not that it fails. And in the case of climate change, ALL the evidence is on the side of the consensus–which is precisely why it is so strong. The denialists have no evidence and no coherent theory to back up their position.
You emphasize the “uncertainties” in the model, but completely ignore the likely effect of these uncertainties–which is that they are extremely unlikely to significantly change the conclusions of the analysis. Likewise you emphasize the siting errors without a thorough understanding of their likely effect in light of analysis procedurss–namely, the effect of removing “bad” stations on the conclusions will be butkis.
6 July 2007 at 6:58
[[I remain skeptical that CO2 is the primary culprit or even that a warmer earth is a bad thing (by the way, can anyone tell me what the temperature or climate should be?)]]
No doubt better climates are possible. But our agriculture and our economy are adapted to THIS climate. That’s why changing it is a bad idea. Where the hypothetical optimum lies is completely irrelevant to the actual threat.
6 July 2007 at 7:03
[[First in line at the cash register is Al Gore with his clean energy fund. If folks don’t believe in warming, his fund tanks. If they are scared to death of warming, his fund soars. ]]
Global warming theory existed long before Al Gore was born and if he disappeared tomorrow it would still be happening. Ad hominem attacks on Gore do nothing to disprove the very clear scientific evidence that the world is warming, that we’re doing it, and that it’s a serious problem.
6 July 2007 at 7:08
[[Climatology is a soft science (much like economics, archaeology or geology are) so it’s difficult to prove theories and is open to interpretation. ]]
Climatology is a “soft science?” Geology is a “soft science?” What in the world are you talking about? Have you ever studied either?
6 July 2007 at 7:12
[[Maybe it is just me, but the way to combat this is to not take the Timothy Chase route and devine what’s in their souls to decide if a response is necessary, but rather to make sure that everything is documented so that these questions won’t come up in the future. ]]
You just don’t get it. It HAS BEEN documented, over and over again. Temperature stations are checked a number of ways. The urban heat island effect has been studied a number of times. The things the denialists keep screaming that we should do have already been done. The point is, no evidence would be good enough for them. They don’t have the intelligence to look at what has already been published on the subject, so they keep saying the climatologists don’t check their data, which is wrong. Not an interesting new point of view, just flat-out dumbass wrong.
6 July 2007 at 7:19
[[When something isn’t completely understood, it doesn’t matter if 100% of scientists believe it is true. H Pylori. Nobel Prize. It’s a very good example of how modern peer review stumbled for 40+ years. Even the IPCC agrees there are major components of our climate that are poorly understood.]]
There are. But the reality of global warming and its cause is not one of those components. We know enough to understand what’s going on and why it’s going on, and not anything you say about the consensus is going to change that. Sure, the consensus has been wrong in the past. But it’s been right a lot more often, and that’s the way smart people will continue to bet. See if you can look up Isaac Asimov’s 1961 article, “My Built-In Doubter,” to understand why.
6 July 2007 at 7:34
Al Gore is the political face of climate change, after all climate change is about burning fossil fuels, stop that and you can stop some climate change, the worst bits hopefully but we have already signed up to 1 to 1.5 degrees I believe with 2 degrees getting more and more likely each year.
Economic and politics will dictate how far AGW goes, at the moment 3 degrees is getting more likely by the year and 2 degrees seemingly a certainty.
There is plenty that politicians can do to mitigate climate change but the laws of physics seem to be against us otherwise we would not be burning all of the available coal, gas and oil. Thanks nature for the free prosperity and progress but we might just cause a bit of a issue whilst using it all.
ironic isn’t a big enough word for it.
6 July 2007 at 7:53
Paul G.–your contention that a bad site speaks of professional neglect is absolutely unsupportable. In many cases, the site was fine, but a city grew up around it. So, do you throw out a long data history and make do with only pristine, brand new stations? Hell no. You learn about the errors introduced by the changed circumstances and find a way to use the data.
Your post illustrates the reason why this technique raises concerns: It is because the photos give no context to how the data are used. And most who see the photos will lack any knowledge of this context (as you do) and draw conclusions based on that ignorance. Context is everything when dealing with a complicated network and if you don’t understand context, your efforts are likely to generate more heat than light.
6 July 2007 at 8:01
H. pylori isn’t a good example for the denialists since it isn’t the cause of all stomach ulcers that the popular press has made it out to be.
Misrepresentation of the science. Where have we heard that before?
6 July 2007 at 10:28
That political face of climate change (Al Gore) was used in year 2000 to stop my research and communication efforts on climate and hydrologic change in the Upper Midwest and global warming at the NOAA National Weather Service (NWS) North Central River Forecast Center (NCRFC) in Chanhassen, MN. I continued my efforts from 2002-2005 until I was removed by NWS. It was important to me that I act as I believe concerning climate change and public service. I would be surprised to learn that anyone here at realclimate has spent more time and effort evaluating climate and hydrologic data in the US than I did in my career in runoff modeling and river forecasting from 1976-2005. Less weight should be given to number crunching statistics and more weight to manual evaluation of data would help. More effort should go into tracking regional changes in temperatures which has been shown to be following the course of rapid greenhouse global warming.
6 July 2007 at 10:31
I’m sorry but I am still not clear on this. First, I suspect that if weather sations are examined that most willl be found to be accepable. BUT, NOAA tells us that NON URBANIZING land use changes can cause changes in station temperature measurements. And when theses changes occur 95% result in warmer temperatures http://www.agu.org/pubs/crossref/2006/2006GL026358.shtml And Dr Hansen tells us that staions may have a 5 standard deviation from the average monthly mean and still be considered accurate. http://pubs.giss.nasa.gov/abstracts/1999/Hansen_etal.html So it does seem that there could be a potential warm bias in the raw data. Since National and international policies are being formed based on the rate of global warming isn’t it very important to assure that you instraments are not giving us biased data? Since some one appears to be willing to get at least visual information on these sites for free I don’t see how this is not a good idea. Alternatively the government could instruct people who maintain the sites to take a couple of pictures for annalysis by whom ever is interested. Isn’t it better for people to be concerned about global warming than Paris Hilton?
[Response: You misinterpret both papers you cite. In any situation where there is a real increasing trend in temperatures, trends before any particular point will be smaller than trends after. Thus you cannot use the Hale et al result to claim causality - and in fact the authors specifically state that. Similarly, the Hansen et al exclusions are to get rid of obviously flawed data, not to certify that everything remaining is perfect. -gavin]
6 July 2007 at 11:13
I am most likely wrong but over sampling to reduce errors in the data would only work if the errors were random. I don’t have a back ground in climatology or statistics but I do in telecommunications and electronics. My back ground says that you can over sample to pull a signal out of RANDOM back ground noise, but if there is a bias, then the bias comes though with the wanted signal.
I from what I have read so far, the problem with surface stations is not that they be in the shade, but that man-made structures and activities are too close… this would indicate a temperature increase bias and I don’t understand how over sampling with remove a bias.
6 July 2007 at 11:16
Ref 211. As I tried to ask in #118, where is the evidence, here in 2007, that the world is still warming up? There is quite clearly lots of evidence that in the last 30 years or so, global temperatures have been rising. (Why is in dispute). But where is the evidence that this warming trend is continuing as we sit here and now in July 2007? The latest NSIDC data for June 2007 shows that there is more ice in the arctic than there was at the same time last year. This is almost certainly not significant as the data is extremely noisy, but it is still a fact. The Hadley/CRU data shows that the average annual temperature for 2007 is unlikely to set a record, as forecast by the UK Met. Office. The average temperature anomaly for the first 5 months of the year is 0.476 C, third highest on an annual basis. Not all glaciers are retreating. There is contradicatory evidence as the whether sea levels are rising, and no clear data that they are, in fact, rising. We have not seen the first hurricane of 2007 in the North Atlantic. I am not talking about the predictions of GCMs. I am talking hard measured data. To repeat, where is the hard measured data, here in July 2007, that the warming trend is continuing?
[Response: Well in my location, temperatures have gone up by about 10 deg C in the last few hours. But possibly that’s too short a period to be matched to long term climate model trends? Indeed…. - gavin]
6 July 2007 at 11:24
#190
Soft science is usually controversial, subjective and have hypothesis that can’t be tested. Global Warming is very controversial and political.
Even Physics has some soft aspects to it to - for example String Theory. However, most physics hypothesis can be test and are not controversial.
#205
There are aspect of all those science areas that are certainly “hard science” but relatively speaking they fall on “soft” side of the spectrum as does climatology.
#212
Geology has many hypothesis that cannot be directly tested.
6 July 2007 at 11:53
Gavin in the news! It seems a new study http://www.boston.com/news/local/articles/2007/07/06/greenland_ice_yields_hope_on_climate/?page=2
indicates that the Greenland ice did not melt in the previous interglacial about 125,000 years ago. The temperature then was higher than predicted by current models and higher than temperatures current models associate with the total loss of the Greenland ice. In the Boston Globe article, Gavin weighs in, saying well at least the ice melted 450,000 years ago, and hey maybe the ice 125,000 years ago was really thin.
[Response: I was simply pointing out that evidence for an unglaciated Greenland sometime in the last half a million years indicates that the ice sheet is in fact unstable. Other than the fact that some ice must have remained during the last interglacial, this data point provides no information on the size of the Greenland ice sheet at that time - and you still need to explain 4 to 6 m of sea level rise. It is almost inconceivable that this could have happened without a substantial Greenland component. - gavin]
6 July 2007 at 11:55
#221 Jim, Ice is still melting and the mass balance is still negative–that’s a pretty good indication we are still warming. Winters are still starting later and ending earlier. Again a pretty good indication. And temperatures, while not as high as 2005 or 1998 are still historically high. Just because every year is not warmer then the one before doesn’t meant he trend has reversed.
And if you were so inclined, you could look at the physics, but you do not seem to be so inclined.
6 July 2007 at 11:57
Any comments on the recent Science paper about evidence for a stable Greenland ice sheet?
6 July 2007 at 12:11
Re #218, the rapid pace of climate change is not rapid enough for many humans to take notice. For rapid can mean many things, geologically rapid is still millenia whilst humanly rapid is in decades at the most or a life time.
I personally believe what the scientists are saying just like a believe Astronomers, cosmologists, biologists, chemists and physicists in general. I feel sorry for climate scientists as they are being accused of many things that other scientists simply are not being accused of, cooking their data, misinterpreting their findings, getting it wrong.
I believe in the scientific method more than any other human endeavour and as far as that goes there is no reason not to believe the climate scientists, their science is as scientific as anyone elses. Maybe its becuase a large number of the lay public (bless them) take an interest in climate science as well as the detractors and obfuscators that the web is full on spurious results and conjecture, all of it wrong in the main.
I for one feel that realclimate was necessary and is needed and I bet that even Al Gore comes here once in a while.
One other good site to vist politically is George Monbiots turnuptheheat.org for the UK listeners. Seems that big business wants to lie to us about climate change to and their green credentials.
6 July 2007 at 12:12
#225
Here’s a little excerpt from an interview of one of the authors:
“We should remain very worried about rising sea levels,” he [Willerslev] said. “We know that during the last interglacial, sea levels rose by 5 meters or more. But this must have come from sources additional to Greenland, such as Antarctic ice. It does not appear the whole [Greenland] sheet will melt.”
(Taken from an article at www.boston.com)
6 July 2007 at 12:25
Vernon, the way that temperature records are made subtracts out the monthly mean over a thirty year period at a station (or a collection of nearby stations). This is called the temperature anomaly and is what GISS and Hadley look at (it would be hard to put temperatures in Washington, DC and Moscow on the same scale otherwise. The second principal virtue of this is that is gets rid of the annumal cycle, so you can compare the anomaly at one location in January with that in June, e.g. how much higher or lower the temperature was than the average. The method also gets rid of any offsets. For the offsets to produce a trend, they too must vary over time in one direction. A much more stringent condition. If the barbeque is sitting out there for 20 years, there will be no effect over 20 years.
6 July 2007 at 13:03
== Post #216 by Ray Ladbury: ==
=”your contention that a bad site speaks of professional neglect is absolutely unsupportable. In many cases, the site was fine, but a city grew up around it.”=
If some of the photographs do not speak of professional neglect, I do not know what does. Sure, cities grow up around sites, but that does not explain BBQ’s, AC units, etc.. And since many of these site have not been properly documented over the years, the neglect possibly goes back a long time.
=”So, do you throw out a long data history and make do with only pristine, brand new stations? Hell no. You learn about the errors introduced by the changed circumstances and find a way to use the data.”=
That is the point that is being made and so strenuously avoided by posters here. Do a thorough, professional review of all sites, or at least core ones, and IMPROVE the data’s integrity.
=”Your post illustrates the reason why this technique raises concerns: It is because the photos give no context to how the data are used. And most who see the photos will lack any knowledge of this context (as you do) and draw conclusions based on that ignorance.”=
As a layman, I have not heard a single solid post that reassures me that some of these sites have been properly QCed or that the data, with adjustments made, is actually of good quality. Clever obfuscations yes, commonsense explanations, no.
Lastly, I would suggest making photographic documentation is not a “technique”, but one of the fundamental steps in documenting, identifying, and validating the data any particular site provides.
6 July 2007 at 13:10
Statistics aren’t the phenomenon, and “natural variability” is not an actual force. There are variations in forcings that can produce variations in world wide climate, and the source of that change can be identified and measured. Sceptics can’t simply expect “variability” to produce a change. There has to be a diminution of some actual force to produce a halt in the increase in global temps.
That seems obvious, but I keep seeing people ascribe a power to “variability” as if there’s an actual missing ingredient out there called “variability”.
6 July 2007 at 13:13
“Any comments on the recent Science paper about evidence for a stable Greenland ice sheet?”
aka evidence for an unstable West Antactic ice sheet.
6 July 2007 at 13:14
Gavin - you didn’t post my last entry, so I don’t expect this one to be posted either. But at least I know you are reading this so here goes. News comes out, potentially good news. The article you are quoted in is titled “Greenland Ice Yields Hope on Climate.” The Globe asks you, the climate expert, to comment. Now granted, god knows you may have been misquoted or taken out of context, but your response does its best to put as negative a spin on the information as possible. Why? It would appear because the data do not support your beliefs. It does not help your credibility when you appear to be less than open regarding new information.
[Response: Things sometimes wait around for responses…. anyway see above. - gavin]
6 July 2007 at 13:19
Re: #61
Google is making a library, here:
http://earth.google.com/outreach/showcase.html
And http://earth.google.com/gallery/
-k.
6 July 2007 at 14:05
Re: #228 (Paul G)
Sounds like a fine idea. Here’s the catch: absolutely NONE of the people claiming problems with the data are doing that. They’re taking pictures of sites for the sole purpose of discrediting the data, not improving it. And contrary to their claims, they are definitely implying that the global surface temperature record is corrupt and the indicated trends are way overblown.
GISS and HadCRU have worked *very hard* to identify bad data, correct them when possible, discard them when not. They apply objective, sound statistical procedures which do not favor warming or cooling, do not credit or discredit the data reputation, just bring us closer to the ever-elusive truth. They have applied their methodology consistently and comprehensively, publishing their results and methodology in the peer-reviwed literature, and their analysis applies to, and can be taken in the context of, the whole network.
The skeptics you seem so enamored of have worked very hard to identify bad sites, without analyzing or even *considering* quantitatively the effect on the data of the siting problems, only making generally snide remarks about the unreliability of the surface temperature record. From what I’ve seen, they’ve photographed fewer than 100 of 1221 stations in the USHCN, have done absolutely no investigation of the many thousands of stations outside the U.S. But they gleefully post pictures of a few dozen or so sites they proclaim to be “proof” the surface temperature record is invalid, on blog sites under such titles as “how not to measure temperature.” Not exactly science at work — yet they’re already convinced they know the answer. I’m convinced that they decided what the answer was, even before they looked.
As a scientist, I have not seen a shred of solid evidence indicating that micrositing problems are anywhere near of enough magnitude to invalidate the present analysis of the surface temperature record. If someone chooses to undertake an objective, statistically sound study of the impact of siting problems on the surface temperature data, great! So far, none of the skeptics has even tried. A smear campaign is not a valid reason to doubt the quality of the data or analysis.
6 July 2007 at 14:09
I’d like to commend mankoff’s GISTEMP Google Earth thingummy:
http://edgcm.columbia.edu/~mankoff/GISTEMP/
Colour coded balloons taking you to temperature records.
Perhaps combine it with a perusal of images of Indiana State Climate Office’s site - with added photos:
http://www.agry.purdue.edu/climate//hcn.asp
A lengthy browse of surfacestations.org does get a bit dull, you quickly realise that not many of the stations are very interestingly located.
It’s rather interesting that the Pielke group managed to visit far flung corners of Colorado for their photos but failed to photo the one at Boulder, on their doorstep: I wonder why that might be…
6 July 2007 at 14:15
very good, Marion (204). You got most of the ad hominems and protagonists talking points and sound bites into only three concisely and well written paragraphs.
6 July 2007 at 14:26
This dustup over monitoring sites reminds me of the “Mann’s PC method mines for hockey sticks” claim. Mann’s critics generate “hockey-stick” leading PC’s from random noise and claim that they are somehow equivalent to Mann’s data-derived “hockey-stick”, all the while neglecting to look at the dynamic ranges of their noise-only hockey-stick PC’s vs. Mann’s PC’s.
Things like Y-axis magnitudes count for something, you know….
6 July 2007 at 14:26
Re #235:
I’d love to include photographs of each station in the popup bubble in Google Earth. I (hesitantly) contacted SurfaceStations.org about this but I have not heard back. I fear they will simply use the GE data to find blue stations near cities and photograph those. Oh well…
If you know of other station photograph data sets, I’d be pleased to contact their maintainers and try to add it to GE. I can’t figure out how to link into that Purdue page, and it would be nice to have a U.S. or global location, rather than having to do 50 times the work for each state…
6 July 2007 at 14:35
Re 223 I have looked at the physics, on both sides; I participated in the NERC debate. Hence my status as a denier, and my concentration on hard data. To quote William Wordsworth “To the solid ground on Nature, trusts the mind that builds for aye.” When you comment on the winters, I assume you are referring specifically to the northern hemisphere. A dichotomy has developed between the temperature anomalies of the northern and southern hemispheres; no-one seems to know why. I assume you have no explanation. The south is cold, and the north warm; and we are supposed to be talking *GLOBAL* effects. Argentinia is having some of the most brutally cold weather on record this year, and it is only just winter. The government has been forced to ration natural gas. Of course temperatures are at historically high levels. Assuming the world is now cooling, when we look back with 20/20 hindsight from the year 2020, we will observe that the the cooling trend started at the maximum of the warming trend. I am sorry, but I do not understand what is meant by “the mass balance is still negative”. If you mean that the trend still shows that ice is disappearing from the arctic, I agree with you. However, again assuming that a cooling trend is upon us, one of these years the amount of ice in the arctic will start increasing. And the harbinger of this trend will probably be precisely what is now being observed.
6 July 2007 at 14:58
re #239
When making claims about *global* effects, one must resist the urge to “cherry pick”. Notwithstanding the selected weather snapshots in Argentina, the southern hemisphere is warming along with the rest of the globe, even if it is lagging the northern hemisphere a bit (think Southern Ocean heat-sink).
http://cdiac.ornl.gov/trends/temp/jonescru/graphics/nhshgl.jpg
6 July 2007 at 15:12
Re: 239. The southern hemisphere has warmed, just not as much as the NH. the answer may be in the sea surface temperatures. The northern oceans have been in a hot phase for the past few decades, perhaps warming the land masses more than occurs in the south. By the way, the northern Pacific appears to be flipping over to a cooler regime. Check out the sea surface data. It is posted three times a week. The data base goes back over ten years. The ‘98 el nino was amazing relative to SSTs. Here is the link:
http://www.osdpd.noaa.gov/PSB/EPS/SST/climo.html
6 July 2007 at 15:13
#238
I found the Indiana link on surfacestations.org. Pictures of well-sited stations are particularly dull - which perhaps explains why no-one has collected them together in one place!
#239
I’m really struggling to see the cooling trend you’re so confidently talking about in these GISTEMP plots for the northern hemisphere, equatorial regions and southern hemisphere:
http://data.giss.nasa.gov/gistemp/graphs/Fig.B.lrg.gif
6 July 2007 at 15:18
Re: #239 (Jim Cripwell)
I suspect you don’t concentrate as much on “hard data” as you claim. The southern hemisphere is hot, the northern is hotter. The hemispheric temperature trends 1975 to present are: northern hemisphere 3.1 +/- 0.5 deg.C/century; southern hemisphere 1.2 +/- 0.4 deg.C/century.
Your claim that “no-one seems to know why” indicates you haven’t really researched the question. The southern hemisphere has a much greater fraction of ocean (as opposed to land) than the northern. Due to the thermal inertia of the oceans, it has been expected for some time that the northern hemisphere would warm faster.
It means that the net change in ice mass is negative, i.e., Greenland is still losing ice, not gaining it.
6 July 2007 at 15:28
Re #235
Recommend following that link to the Purdue Univ Climate page. The review of the Indiana HCN sites was done as part of a Master’s thesis by a Purdue grad student. Her paper is available from the site in pdf format, and reliably answers many of the questions on why a survey is helpful.
6 July 2007 at 15:29
Re: 228 I fail to see how that will remove biased data. I could see if the the nosie was random but the bias would not be removed as noise in the over-sampling. I dont think you understand bias… a biased signal would vary over time, it just would be either higher or low that it should be due to the bias. What your saying works fine for ramdom noise but this sounds just like signal processing and you cannot eliminate a bias that you have not identifed. That is why identing the surface stations so to determine the bias is needed.
6 July 2007 at 15:31
>> “Any comments on the recent Science paper about evidence for a stable Greenland ice sheet?”
> aka evidence for an unstable West Antactic ice sheet.
Yep — the author interviewed on NPR (Ira Flatow, ‘Science Friday’) made the same point.
Previous sea level rise we thought came from melting Greenland — didn’t.
Think: Where else was there ice? Yep. That’s an uh-oh for the ‘no problem’ people, not good news.
6 July 2007 at 16:43
Re 243. You are absolutely right, though I could argue minor points. But as happens in this sort of discussion, we have strayed from the main point. The claim was made that “Winters are still starting later and ending earlier”, in my search for what the trend of temperatures is in July 2007. My point, which I should have restricted my comments to, is that this statement is true for the northern hemisphere in 2007, but not the southern. As to Greenland, my comments referred only to the floating ice mass in the Arctic Ocean. Again I should have been more specific.
6 July 2007 at 16:48
Vernon and Paul G., OK, let’s say that somebody fires up the ol’ barby right under the thermometer just as it is taking a measurement. It registers a high temperature. But the last reading was much cooler, and the reading after that one was also much cooler, and lo and behold none of the several nearby stations shows anything like the temperature of our fricaseed thermometer. Now do you suppose I’m going to blindly include this in my dataset, or am I going to develop techniques that identify and remove that data point? This is true even if somebody sets up a hotdog stand and has the barby going 24/7/365.25. Same thing goes for the air conditioning unit or pretty much any anomaly you care to choose.
That is the point that is being made and so strenuously avoided by denialists here. Before you can do a thorough, professional review of all sites, or at least core ones, and IMPROVE the data’s integrity, you have to UNDERSTAND how the data are being used, what kinds of errors you may encounter, how often and what the likely effect of those errors will be. Understanding before action–what’s so hard to comprehend about that. You’ve been saying it to climate scientists for years when it comes to action on climate change. Now you seem to be deaf to the phrase once climate scientist have incontrovertible evidence that they do understand the climate.
6 July 2007 at 17:11
re 225:
Analysis of the insect mitochondria, cellular components that contain genomes that can be used to date DNA, as well as amino acids, indicate d that the creatures were at least 450,000 years old. Uncertainties with dating, however, leave the possibility that the DNA dated only as far back as the last interglacial period. (from the boston.com article)
It looks to me like this isn’t enough to start talking about overturning climate models.
6 July 2007 at 18:42
Err… On the question of weather station data integrity and whether documenting them with (single) photographs is a worthwhile project, I get a little worried when I read that some of the alleged problems are due to things like barbecue grills or SUVs parked next to the station. Now maybe I have a nasty suspicious mind, but - naming no names, you understand - just how hard would it be for someone, or some group, with a vested interest in casting doubt on temperature records, to stuff their old grill in the back of their SUV, and drive around setting up photos of such problems?
6 July 2007 at 19:44
re: 248
Your missing the point. Some one firing up the barbie would be random noise (I think) but having AC exhaust or more concrete around would not be random. That is what your ignoring. Changing the environment, and not knowing the environment changes would introduce a bias that could be miss read as something else. I am not worried about the random event, that can be filtered, in signal processing terms, but changing the environment with out documenting the change will cause a bias. Undocumented bias is not good, do you see the difference?
6 July 2007 at 19:52
Considering the number of lines of evidence that point to AGW, it’s astonishing that anyone would even bother to attempt discrediting the surface measurements. Sure, they’re probably off by a couple hundredths of a degree, though there’s no compelling reason to think they’re too high instead of too low.
But so what? The tropospheric and stratospheric measurements - unpolluted by UHI - are consistent with AGW. The ocean is acidifying, consistent with rising CO2 levels. Changing snowfall patterns in Greenland are consistent with AGW. And so on, and on, and on, from disappearing arctic sea ice to the new species of insects that have take up residence in my city.
So what possible gain is there from such a breathtakingly myopic inquiry?
Here’s a thought experiment. It’s early December, 1941; you’re an American intelligence officer in the Pacific; and you receive evidence of a large Japanese fleet steaming towards Pearl Harbor. Do you take action? Or do you conclude that we should do nothing until we know exactly how many airplanes are on each aircraft carrier?
(Just to improve the analogy: Taking action against the fleet would slow economic growth. ;-))
6 July 2007 at 20:25
Vernon, OK, let’s take your air con idea. Now presumably, the air con was installed at some point in time, so if there is a sudden change in the data, we know something’s up, and we exclude or downweight that station. Moreover, that change is not reflected in nearby stations, so we identify it that way as well and can average or smooth it out.
Let’s look at increasing pavement. Well, again, the paving took place within a very short window of time (unless you used a paving company in the Chicago area), so over some very short time we see a significant change AND it isn’t reflected in the surrounding data. Hmm, our analyst (or rather our algorithm) says, Something’s up. OK, let’s say we have a paving company that gets paid by the hour and they lay down a square foot of asphalt a day–gradual warming, not good. But it still isn’t reflected in surrounding stations, and so gets downweighted, averaged out or otherwise corrected. See, that’s the thing–to bias the data, you have to have noise that looks at least very much like your signal, and since your signal is both gradual and global, that’s really hard to do. So, can YOU come up with a noise source that looks like the signal? Do you even know what the signal looks like? Do you know what techniques are used to separate signal from noise? If not, then how do you expect to contribute constructively to the data analysis?
6 July 2007 at 20:29
Your missing the point. Some one firing up the barbie would be random noise (I think) but having AC exhaust or more concrete around would not be random.
When I look at global temperature anomaly maps, I see that the most dramatic warming is occurring in places like Alaska, northern Canada, and Siberia. The warming in the continental USA is lagging way behind observed warming of the high northern latitudes. I rather doubt that the the dramatic warming observed up north is the result of Eskimos setting up bbq grills or AC units or whatever next to weather monitoring stations.
To put things into context, check out http://gristmill.grist.org/images/user/6932/global_anomalies.gif
Do you seriously think that a few AC units in the USA is going to have any impact at all on observed global temperature anomalies?
This is just the M&M “noise-only” hockey stick PC with a 0.03 eigenvalue magnitude all over again.
6 July 2007 at 20:29
After posting to realclimate from late 2004 to current with little or no feedback on my post about hydrologic and temperature changes at climate stations in the Upper Midwest and elsewhere in the US including Alaska, and on my not so great treatment by NOAA’s NWS river forecast center for the Upper Midwest, I figured that, given the title of this realclimate blog, there might be some interesting feedback concerning work even though it didn’t meet peer review criteria but I figured wrong, this man is still an Island in urban and unprofessional heat.
6 July 2007 at 21:02
Answer: You audit the instruments, demand more precise information, and throw out anything dubious.
“… Pvts. Eliot and Lockard were manning the radar at Opana Point. They noticed a large blip on the scope and call in to the as-yet not fully functional Fighter Information Center. Pvt. McDonald took the call and located the sole officer at the Center and asked him to call the operators back. Lt. Kermit Tyler, having ending his first tour of training at the newly established Fighter Control Center, received the report and, thinking it was a flight of B-17s due in from the mainland, told the operators to “forget it.” The report went no higher than that. Interestingly enough, the new radars tracked the planes coming and going, but the Army did not tell the Navy about this pointer to the Japanese carriers until the 8th…” http://www.ibiblio.org/pha/myths/index.html
6 July 2007 at 21:17
Re 239: looking at data from Argentina’s large variety of latitudes, that winter may be more atypical than brutal. When Buenos Aires and Mar Del Plata were having snow and slightly below zero temps, Ushuaia (southermost town in the world) had essentially the same temperatures, not colder. Looks like a weather event, not a climate trend. Meanwhile, Australia is not so chilly and its multiyear drought far from relieved by the recent torrential and short lived rains.
7 July 2007 at 0:25
#207 one picture ain’t worth a bucket of warm spit. You need a history of changes over the observing period or something like the Climate Reference Network run in parallel for a period of time. Remember it is the anomalies that count not the absolute temperatures
7 July 2007 at 1:21
Check this US Carbon Footprint Map out, has United States Interactive Carbon Footprint Map, illustrating Greenest States. This site has all sorts of stats on individual State energy consumptions, demographics and State energy offices.
http://www.eredux.com/states/
7 July 2007 at 6:14
Gavin:
Is there a method for changing this long linear list of posts into a tree structure? With so many posts it get really difficult to find anything. Also I notice that multiple subthreads start to develop. Is there some secret hotkey or macro I can use to produce a tree structure?
To Anybody: Is there a software app that can sort all of the responses in this webpage into groups based up an initial post by a poster? Can Google do this?
7 July 2007 at 6:46
Re 257. You are missing the point. Would people who live in Argentina, and places at similar latitudes in the southern hemisphere, agree with the statement that, here in July 2007, “Winters are still starting later and ending earlier”? It is my contention that they would not. The quotation was given was as a reason for believing that, currently, termperatures are still rising as fast as they have been in recent years.
7 July 2007 at 8:17
RE: 242: here is your Indiana data
http://climatesci.colorado.edu/
7 July 2007 at 9:40
Alright, I freely admit I’ve not read all 261 comments, so I’m sure I’ve missed something. But it bothers me that UHI effects are massaged out of the data without taking into consideration where that heat is going. Because it has to go somewhere, it doesn’t just disappear. Right?
And because I’ve got a teenage I must wake up and feed breakfast, I’m just going to throw out an analogy, and then watch the ensuing shredding of said analogy –
To me, ignoring UHI is like ignoring a candle in the middle of the room. Sure. that candle is very hot, but it’s localized (so the argument goes …), so we’ll ignore it. Except that the candle is also warming the room, and having ignored the candle it seems that the cause of the warming is being ignored.
Now, I don’t think that is an argument against AGW. I think it’s part of AGW, and I think that by arguing against the UHI effect, people are playing into climate change deniers hands. The response, to me, should be “Why yes, the UHI effect is real, and it is also contributing to global warming because that heat has to go somewhere.” If you look at power consumption in urban regions, power consumption exceeds all of the solar radiation falling on that area. At ~ 1,360 watts per square meter, a nice multi-story IT-rich building can produce more heat than the sun — and that heat, along with the heat produced generating that power from carbon-based sources, has to go somewhere.
7 July 2007 at 9:45
re #258.
Of course 1 picture is not going to tell anyone anything about the changes that have taken place, but it is a start of a record that can be referenced in the future so that when more pics are taken in the future they have something for comparison.
I wonder if this one will get posted or dumped liket he last one?
7 July 2007 at 10:00
Ray (253), is that how it actually works, or is this just a well thought out idea?? After the anamoly next to the air cond exists for a long period at the same slightly higher temp, is it still adjusted downward (because it’s still slightly off neighboring readings) or does the real algorithm assume it now must be correct and accept it?
7 July 2007 at 10:47
RE: 242: here is your Indiana data
http://climatesci.colorado.edu/
Interesting…. but when I look at http://gristmill.grist.org/images/user/6932/global_anomalies.gif, I see that Greenland has warmed far more than Indiana has. I can only imagine the magnitude of the land-use changes on Greenland that must be responsible for the warming there. Ditto for Alaska, the Northwest Territories, and northern Siberia.
7 July 2007 at 11:08
Re #238
I realize this comment is irrelevant to SurfaceStations.org and/or their use of my Google Earth KML file. As with GISTEMP on the NASA page, anyone can take it and do what they like, and we have to trust they use it appropriately.
I’m actively trying to improve that KML layer, and I think photographs in each bubble would help. I’ve heard back from SurfaceStations.org and they assuaged my fears and are interested in this too. Should we do this we’ll work together to make sure that the photographs are statistically representative (i.e. not only the “How Not To Measure” photos but the “How To” also).
7 July 2007 at 12:57
Rod, I’m not an expert on the algorithms, but I’m also no smarter than the guys who are doing the analysis. If I can figure this out, so can they. Tamino has said they do jackknifing, and several have pointed out that both time series and spatial comparisons figure into the analysis. My data analysis experience is in very different fields, but you never have pristine data, and it’s not worth it usually to try to make the data perfect when you can get the same answer by doing proper cleaning, filtering and error analysis on the data you have.
Again, the most innovative creature on the planet is a graduate student desperate to graduate who has a crappy dataset. The real reason to care about the quality of the stations is because it makes the analysis easier. It’s the difference between a 100 page thesis and a 200 page thesis–and probably an extra year of grad school as well.
7 July 2007 at 13:09
Re 261: It seems to me that you picked a select location that serves your purpose. What really matters is global heat content. Argentina’s climate is mostly influenced by the South Atlantic. Regardless, whether you’re making your assertion based on this particular 2007 winter event or on a trend for the all hemisphere, I am still very much unconvinced that it compensates for what is observed elsewhere. How much would Argentina, Chile, South Africa and Australia have to cool down to counterbalance the later/warmer/shorter Siberian and Canadian winters?
Global climate includes local variations that may be atypical. So far, for Argentina, the big differences are increased precipitation and decreased amplitude (lower highs and higher lows), which may be related. That does not change the whole picture.
7 July 2007 at 14:08
On the subject of UHI and temperature records, I neglected to mention an observation based on data I gather myself — I have 5 minute interval data for two outdoor thermometers and the disagreements between the two can be as great as 10F. The difference appears to be caused by thermal radiation from surrounding structures. The more “accurate” of the two doesn’t show the sharp rises contained in the lesser accurate of the two, but it also doesn’t show the sharp drops of the other.
06.26.07 00:00 76.6 74.4
06.26.07 01:00 76.1 74.4
06.26.07 02:00 76.1 73.9
06.26.07 03:00 75.9 73.7
06.26.07 04:00 75.9 73.7
06.26.07 05:00 75.9 73.7
06.26.07 06:00 75.9 73.7
06.26.07 07:00 75.9 73.7
06.26.07 08:00 76.1 73.9
06.26.07 09:00 77.9 77.3
06.26.07 10:00 79.3 78.0
06.26.07 11:00 77.3 73.4
06.26.07 12:00 77.9 77.1
06.26.07 13:00 81.6 81.6
06.26.07 14:00 86.1 83.4
06.26.07 15:00 85.6 82.4
06.26.07 16:00 86.9 86.3
06.26.07 17:00 88.1 88.1
06.26.07 18:00 88.7 90.8
06.26.07 19:00 85.6 84.0
06.26.07 20:00 84.0 81.6
06.26.07 21:00 81.6 79.5
06.26.07 22:00 80.2 78.2
06.26.07 23:00 79.7 77.5
Rather than relying on a small number of weather stations in an area, whether it’s one or two weather stations at local airports and military bases (what we have here), or stations that get moved over time, I’d argue that a significantly large number of data points are needed to accurately know the surface temperature in developed areas. In my part of the planet the “Weather Data Network” (or whatever they call it) routinely shows temperature variations of several degrees.
7 July 2007 at 15:05
This discussion reminds me of one of the unfortunate ways that I feel the global atmospheric science community lets society down: the surface data being discussed is almost completely proprietary, and not publicy available (except at considerable cost) even though it was collected at taxpayers expense. Bottom of the class are UKMO and Meteo France. The only country (that I’m aware of) that does a good job of making its data available is the US.
I’m not a skeptic, but this is a bit of an achilles heal in the climate change argument: supposing someone from outside the state-funded research community (such as myself) wanted to use observed data to make their own study of the patterns of global climate change (as I would indeed like to). Well, they can’t because they can’t get the data (legally). At that point, they either have to believe you or not: it’s a matter of faith. I *do* believe you, mostly, but I could understand why some people would, at the very least, be a little bit skeptical of your claims, because of this lack of transparency. In the UK, the government’s line on climate change is effectively: “UK climate change is real, but if you want to check for yourself you have to pay the UKMO lots of money”…sounds unfortunately like a snake oil salesman.
If there are any skeptics out there reading this, maybe you could pick up on this issue, until the UK govt, and various other governments around the world, are shamed into making the climate research they fund a bit more transparent. Don’t stop until historic climate data, and meta-data, is freely downloadable for anyone who wants to look at it.
I suspect that in other areas of science it would simply not be acceptable to publish results based on data that isn’t freely available (does anyone know any comparative examples?) but for historical reasons climate science is an exception. This never really mattered in the past, since no-one else was bothered to look at the data anyway, but given the societal important of climate change, it’s now very unfortunate.
(note that I appreciate that the authors of realclimate.org are just cogs in the machine, and not in a position to make decisions or not about the availability of climate data, so don’t take this as a personal attack).
[Response: All of the data being discussed here is available at no cost from NOAA or GISS, regardless of it’s country of origin. There is additional data that comes from higher density observing networks in many countries that is also available (Norway, NZ for instance). However, many National Weather Services have been given mandates to develop commercial products and that has lead them to restrict some analyses to fee paying customers. For the most part that is irrelevant for large scale considerations, but it is obviously a little frustrating at times. Don’t complain here though - complain to the national governments that impose such commercial pressures in the first place. - gavin]
7 July 2007 at 15:38
Furry Cat Herder, your little exercise in #270 is an excellent illustration of the power of an oversampled network–although as you point out, to get a better idea of which thermometer were more accurate, you’d need at least one other thermometer in another nearby location.
Indeed, with such a network we can eliminate or downweight points that are affected by local conditions such as UHI and look for the gradual, global signal due to increased greenhouse gases, or we can concentrate on investigating the UHI effect by emphasizing local and short-term variations. Same dataset, different signals, different analyses to bring down the noise. Or put another way–one man’s signal is another man’s noise.
I believe Pielke protests that local conditions have been given short shrift in the analyses to data. He may be right. However, the chances of local conditions being responsible for even a small portion of the warming attributed to anthropogenic CO2 is virtually nil–and he should realize this.
7 July 2007 at 16:25
re: #261 Jim Cripwell
I’m not exactly sure how to define “winters starting later and ending earlier”, but the state of ski resorts may be a useful surrogate, as it is a topic of intense interest to some people, and so ti gets reported.
I live about 5 hours’ drive from Lake Tahoe, which has many ski resorts, and have skied there (some) almost every year since 1983. A few years ago, we bought ski property in Canad, which requires flying San Francisco -> Seattle -> Kelowna, and then taking an hour bus ride to get to Big White, i.e., about 8-9 hours door-to-door.
Q: Why would somebody regularly do that when they could just drive to Tahoe?
A: Because the ski season around here seems less predictable than it used to be. In fact, the Sierra Ski Resorts are especially worried about global warming:
Google: sierra ski resorts global warming
But, what does that have to do with the Southern Hemisphere?
Many Austrlaians ski at Big White, and I often talk to them on ski lifts. Why are they so far from home?
A: Because they’ve been getting less and less happy with their skiing Down Under.
Of course, some of this is increased crowds, but the most common complaint is that it’s getting harder to pick a good week six months in advance. Of course, good ski conditions not only require reasonable snowfall, but that temperature stay cool, as even a a few days above freezing, with rain, can wreck the conditions.
Here are a few references.
http://www.news.com.au/heraldsun/story/0,21985,21712611-5012935,00.html
http://www.unep.org/geo/geo_ice/PDF/GEO_C4_LowRes.pdf
The second is a nice report called “Snow”, with good maps, which says:
“mean monthly snow-cover extent in the Northern hemisphere has decreased at a rate of 1.3 per cent per decade during the last 40 years.
Of course, in the Southern Hemisphere, outside of Antarctica, serious snow is pretty rare {Chile/Argentina, New Zealand, a few spots in Australia, and a few mountains elsewhere.]
It’s pretty easy to summarize the overall effects:
1) Lower resorts are hurting.
2) Even at higher resorts, the snow depth (which always varies considerably) is trending slowly lower; as in the USA, people are and are planning even more snow-making to stay in business.
3) Individual ski resorts rarely say anything official but “come on out, the snow is great!” which makes it hard to find long-term data from them. However, a lot of Australians are worried about the long-term future of skiing there.
So far, New Zealand, further South, with higher mountains, and more precipitation seems OK on the ski front, and quite happy to take Australian skiers’ money, but quite a few prefer to make the long flight to Canada.
Despite the cool weather in Buenos Aires this year, Argentina and Chile ski resorts mostly got off to a late start due to lack of snow.
Of course, one might argue that skiing is an especially energy-intensive sport (particularly when you have to make snow), and it ought to disappear anyway, but meanwhile, ski resorts provide a useful (albeit somewhat anecdotal) surrogate for the nature of winter around the world.
7 July 2007 at 16:41
Re: #271 (Steve Jewson)
You can find quite a lot of temperature time series on line. There’s the GHCN (google will probably find it for you), which gives easy access to the entire database, and covers the earth. GISS makes their data available. And the European Climate Assessment & Dataset Network has daily data for temperature, pressure, humidity, snow cover, sunshine, cloud cover for many locations throughout Europe. So if you’re serious about your project, you can get started.
7 July 2007 at 17:05
Ray @ 272:
Ray,
I know which one is more accurate because I have another thermometer which doesn’t record temperatures
On the other paw (oh, my name is Julie if you want to stop spelling my ‘nym out longhand, tho I also respond to FCH), my point really isn’t just that small datasets in developing regions have “problems”, it’s also that there is significant heat being produced by these regions and removing urban data points seems like a bad idea to me.
It’s a shame I’m not willing to have a wireless thermometer run over by a car, because I’d really like to find out what the air temperature above asphault is over the span of a day. Even more interesting would be the air temperature above a parking lot full of closed up cars that are each 150oF on the inside. And while most of the planet is still covered with water (and moreso every day …), I’d tend to think that land use changes have the potential to drive surface temperature where people live significantly more than CO2.
Maybe out in the rural areas, where food production will be harmed, and up in glacial regions where runoff will increase sea level, CO2-related warming is going to dominate, but I’m putting my money on UHI effect as the #1 driver of inhabited area temperature increases. I greatly enjoy the 3 to 5oF drop when I drive from downtown out to the ‘burbs. And I dread what’s happening as the 3 adjacent cities all continue to develop around my neighborhood and will likely raise local temps in the ‘hood by 3 to 5oF due to UHI effect over the next 10 to 20 years.
7 July 2007 at 17:29
Steve Jewson,
Just curious. Do you download the data from the human genome before you go to take a test to see if you have a predisposition to a form of cancer? Do you download the wind tunnel data for a jet design before you fly in it? Would you know how to make sense of this data? Please don’t take this as a criticism. I am really curious why this particular subject elicits such incredulity among lay people (especially technically inclined lay people), and I’m curious whether that curiosity sparked by this field would be sufficiently strong that a lay person would persist through the difficulty of analyzing the data. Data rarely yield their secrets to a casual glance. There is always noise, and there are always random and systematic errors. None of this poses insurmountable problems, but it does require a lot of work. What I’ve seen to date among skeptics is a willingness to look through the data until you find a couple of stations whose raw data seem to buck the overall warming trend, and then proclaim climate change a fraud. I wonder whether there might not be a few lay people out there though where this could be a teachable moment–where we might not demonstrate how science is actually done: the perspiration behind the inspiration.
7 July 2007 at 17:37
Far be it from me to lock horns with John Donne,but a man can be a (heat) island. If a human body(assuming he radiates as a blackbody) has a surface area of say 1.5m^2 and a surface temperature of 32deg.C and is in surroundings of 20C,his net heat loss rate to the surroundings is given by sA(T1^4-T2^4) or 5.67×10^-8W/m^2-Kx1.5m^2(305^4-293^4)=109 watts. As the temperature of the environment decreases, heat energy is lost at a greater rate.
There were concerts here in NYC and around the world, today to raise awareness about global warming.Why is it that when climatologists warn us about the potential hazards,the general public mostly doesn’t listen but when someone like,say, Madonna does it everybody perks up their ears?
7 July 2007 at 17:40
Steve, I’m always curious where people get their feelings and beliefs. When you wrote above:
“… I feel the global atmospheric science community lets society down: the surface data being discussed is almost completely proprietary, and not publicy available ….”
Everyone’s entitled to their own feelings, but I wonder how you came by this feeling. Is it from first hand experience, contacting agencies asking for data? Or did you read that statement somewhere, from someone you trusted to tell you the truth?
I often see strongly held beliefs and feelings being stated — often represented as facts —- in postings made here by new readers coming in to RC.
As a longtime reader (and no expert myself) I find it’s really helpful to ask and learn — how did you come by what you believe to be true? What are your sources?
As the cartoon puts it: citation needed http://www.xkcd.com/c285.html
7 July 2007 at 18:37
oops!
7 July 2007 at 18:42
Reading about changes in ski seasons near Lake Tahoe brings to mind the study of changes in the timing of snowmelt runoff on rivers in the Upper Midwest, links below. The study did not rely on air temperatures thus urban heat island was not a concern.
http://www.mnforsustain.org/climate_snowmelt_dewpoints_minnesota_neuman_table_figure1.htm
http://www.mnforsustain.org/climate_snowmelt_dewpoints_minnesota_neuman.htm
Updated figures through 2007 are at: http://picasaweb.google.com/npatphotos
7 July 2007 at 18:51
Ray and Eli,
While you can come up with all the rationalization that you want, if the environment of the stations becomes more urbanized, then bias is being introduced which cannot be told from a warming trend statistically without actually inspecting the site. Arguing against this is sophistry, being so against validation of the underlying data makes no sense to me.
Signal processing I understand and as far as I can tell, tracking the global temperature is nothing more than signal processing. If you don’t identify the biases, then you cannot correct for them and those biases could invalidate your results. Please note I am saying could not will, so have a site inspection and determine your biases, then determine what the signal is without the bias.
7 July 2007 at 19:12
Re 275: What exactly is that oops for? What this article mean is that in the last big interglacial, there was ice where that sample was taken. It does not take into consideration today’s melting due to coating with dark particles, which some say plays a more important role than temperatures (recent SciAm article and corresponding paper). The observed melting is definitely more than what would be expected with current temps. There is also the fact that sea levels have risen more than expected and nobody seesm to really know why. And it is possible that the temperatures will rise much more than the GCMs predict, due to still poorly understood feedbacks. What we are experiencing now is new, I have no doubt that there are surprises in store.
7 July 2007 at 19:14
Erik, it’s been discussed already. Off topic here. Need a pointer?
7 July 2007 at 19:17
gavin> All of the data being discussed here is available at no cost from NOAA or GISS, regardless of it’s country of origin.
Does that apply to raw data and intermediate correction step data? Those are critical for studies of correction accuracy.
7 July 2007 at 19:47
Sorry for the thread hijack here . . .
There is a professor in forecasting who appears to be willing to bet $10000 that he can forecast global temperatures better than Al Gore. Gore turned him down. This story has been gaining traction on conservative sites. Seems like the kind of thing that cries out for a response.
Google “scott armstrong global warming” to learn more.
7 July 2007 at 19:50
Re: 275. No matter what the discovery, there will always be some idiot trumpeting that it proves his pet theory, and usually he will have no understanding of the discovery or even his own theory.
7 July 2007 at 21:11
Eric Baker (#275) wrote “oops!”
Judging from the link you provided, I assume you meant to refer us to the following:
Fossil DNA Proves Greenland Once Had Lush Forests; Ice Sheet Is Surprisingly Stable
July 5, 2007
http://www.sciencedaily.com/releases/2007/07/070705153019.htm
Well, that is interesting.
The dating done on the flora and fauna of Greenland was by means of DNA, radiocarbon and some method involving mineral luminescence. 450,000 years… Well, that isn’t exactly saying how thick the ice was at the time of the last interglacial. What it might suggest is that when the rest of the world had warmed up, Greenland found some way to keep cool… after a while.
But assuming the glaciers of Greenland were as stable as these investigators seem to think, as both Chris and Hank have pointed out, that still leaves open the question of where the water came from that raised the sea levels of the time. They seem to be suggesting it might have been some other large body of ice.
See:
Chris O’Niell’s #231 and Hank Roberts’ #246
7 July 2007 at 22:05
Ray, I can accept that. I suspect, but don’t know at all, the modelers do properly account for the apparent discrepencies, many of which would be of no consequence. Though there is a point where the data can be enough crappy that, while the grad student might get by, the science faults. I just wonder where that point is and if the modelers are forever watchful…..
8 July 2007 at 2:46
I yesterday visited an old friend, a strawberry farmer. His business is suffering. The grandmas had not come in their usual numbers to pick up his main crop, the obvious reason being that the crop was ripe two weeks early.
The grandmas are used to start up their strawberry jam pots mid-July, and probably come at that time, hopelessly too late for the berries. Extra advertising did not help too much. Nor had the grandmas yet understood about the practical impact of global warming on this important aspect of their lives.
Definitely no urban heating on his site.
Similar things happen in the wild nature everywhere. Some organisms wake up when the spring temperatures come, others react to length of day (calendar). Where these organisms are strongly interdependent, disasters follow.
8 July 2007 at 3:27
William Jockusch (#282) wrote:
Armstrong is very good at what he does: self-promotion. From what I understand, he keeps statistics on how often he gets refered to and where. He is promoting a so-called “scientific methodology” of forecasting - something which he invented himself.
If I remember correctly, ten cities are picked at random for which both he and Gore would forecast for, and Gore wouldn’t be able to make his own predictions, but would have to go with the results of a climate model of his choice. By way of contrast, Armstrong would be using a so-called “naive” model of moving averages, with the bet being over a ten-year period, and where he gets to have as his prediction for any given year the behavior from the last year.
Armstrong likes to claim that what we have are ~”scientists making forecasts, not scientific forecasts,” but when he makes this claim, it pays to keep in mind that by “scientific forecasts,” he means nothing more nor less than something which conforms with his personal and oftentimes ambiguously-stated methodology.
… If I remember correctly.
Anyway, if Armstrong gets his name bantied about by the same people who celebrated a German school teacher for screwing up a couple of charts, I guess that is an accomplishment… of sorts.
8 July 2007 at 3:56
PS (to my post above)
The problem with Armstrong’s wager is that his forecast tracks the behavior from the previous year, and thus with a warming trend, it will track that warming trend, building it right into his “naive” forecast. Additionally it is local, specific to each city.
Climatology doesn’t work like that.
Climatology is regional - and whatever models Gore might pick from wouldn’t be making predictions specific to individual cities. Likewise, the purpose of the model would be to predict the behavior as it will be ten, twenty or a hundred years from now based upon the information which we have today, not by building into the forecast what had happened the previous year.
A large part of the power of climatology depends upon its dealing with large averages where the fluctuations matter a great deal less. What will be the behavior for a given decade is answered much more easily than what will happen on a particular day a month from now. No doubt Armstrong knows all of this already. But he hopes to ride the wave of controversy over climate change right into the limelight.
8 July 2007 at 4:21
Re #282. A load of rubbish basically, first of is that cores predictions are over decades whilst this mans assertions and bet are over the next decade which hardly adds up does it.
Just sounds like more obfuscation to me and a deliberate attempt to throw some more confusion on the subject. Its on the TV and hence it must be true.
Personally I doubt that anyone will get the AGW message across in the USA due to right wing interests who are highly organised and funded.
8 July 2007 at 6:15
The ‘Armstrong Challenge’ thing is actually related to weather station data very, um, precisely. If Armstrong is as focused on specific single weather stations as his web page makes it appear, he’s illustrating all the same issues dealt with in this topic.
He’s confusing weather and climate. He’s asking for a climate model that can make ten year weather forecasts for ten specific weather station instrument locations. And he writes “Al Gore is invited to select any currently available fully disclosed climate model to produce the forecasts (without human adjustments to the modelâ��s forecasts). Scott Armstrongâ��s forecasts will be based on the naive (no-change) model; that is, for each of the ten years of the challenge, he will use the most recent yearâ��s average temperature at each station as the forecast for each of the years in the future ….”
Armstrong sums up Gore’s position (I think naively at best) as being that there are ” … scientific forecasts that the earth will become warmer and that this will occur rapidly …. the challenge will involve making forecasts for ten weather stations that are reliable and geographically dispersed. An independent panel composed of experts agreeable to both parties will designate the weather stations. Data from these sites will be listed on a public web site along with daily temperature readings and, when available, error scores for each contestant….”
Wiggle words include “currently available” “fully disclosed” “human adjustment” “rapidly” “reliable” …. Sigh.
Seems quite in line with the general theme of casting doubts on the weather station instruments, one at a time, eh? Oh no, bad paint on that one. Nope, parking lot nearby. Nope, bird sitting on roof. Nope, SUV parked on top. Nope, that’s a WalMart, not a weather box …. Not to mention, oops, we need to wait a decade to see if anything’s happening.
We’re talking about a fraction of a degree C in a decade. No way that’s expected to be uambiguously predictable at ten individual points over ten years. The man’s asking for weather, not climate, prediction.
Heck, he might as well ask for predictions of the interest rate at ten individual banks to be predicted the same way.
Spencer Weart points out in the AIP History that the warming signal, relatively tiny compared to natural variability, is only beginning to emerge from that variability. No one bet on that, in the 1990s. Note 33: http://www.aip.org/history/climate/20ctrend.htm#N_33_
Stoat recently pointed out the problems with inference from five year trends (using large data sources; ten years from ten individual stations would be less reliable than five years from a large network, eh?). http://scienceblogs.com/stoat/2007/05/the_significance_of_5_year_tre.php
Tamino well points out how, counterintuitively, it takes large amounts of noisy data are used to obtain useful information — which isn’t generally understood. This guy’s “challenge” falls flat for all the reasons well discussed, seems to me.
http://tamino.wordpress.com/2007/07/05/the-power-of-large-numbers/
Ok, that’s what a nonscientist can make of the ‘challenge/bet’ thing. At least it’s right on topic, seems to be part and parcel of the attack on the station data.
8 July 2007 at 6:29
Rod B. and Vernon,
First off, Vernon, who’s rationalizing? All I am saying is that
1)all data are less than perfect;
2)there are very good techniques for dealing with imperfect data
3)these techniques are being applied
4)based on the agreement with the result from this data and many other independent lines of data, the techniques are being applied properly
5)the signal they are looking for here is so robust and global, it is hard to imagine how errors at a few individual stations could affect it.
6)you should know how the data are being used and have some idea of what is really a concern before you go off and start futzing with the network.
Now, Vernon, you may understand signal processing, but you sure aren’t thinking about how those techniques apply here or you wouldn’t be getting wrapped so tightly around the axle over a couple of photos of stations that violate siting guidelines. Now, understand that I am in no way saying, “Don’t do this.” I’m just saying you need to understand the network before you embark on your goose chase.
Rod B., yes, there does come a point where a dataset becomes unusable. We’re nowhere near that. Information theory as a guideline suggests that if >33% of the stations were complete crap we might have to start worrying. And yes, the modelers are forever vigilant–nobody wants to put out a crappy product. On the other hand, most of the data filtering algorithms can be implemented completely automatically while still reporting back on any changes. Personally, I think this is one of the most important revolutions in science from the last century–the ability to deal with data that has errors–and most people have never heard of it.
Now, personally, I have to admit that there are a few denialists where I kind of like the idea of them traipsing through poison ivy and blackberry thickets to get to some of the more remote sites. It might be a character-building experience. But again, I strongly recommend understanding the system before you start, or you will likely be wasting your efforts. And if you are seriously concerned, you haven’t understood the system.
8 July 2007 at 6:46
Re 282 and wagers about global warming:
The “professor in forecasting” can find several experts who are ready to bet him on specific issues regarding global warming. See for example Realclimate, “Betting on climate change”, 14 June 2005, by James Annan. The last time I checked no prominent skeptic has been willing to accept well posed wager.
Al Gore continues to do a great job in prublicizing the issue of global warming and the necessity to start now to try to do something about it. It is easy for conservatives to pick on him, but he is not a scientist, nor does he claim to be one.
8 July 2007 at 8:58
Ray,
How do you know if is only a few stations? How widespread is the bias? You can make assumptions but that seems like a denialist stance where you would rather not know the truth. As for your argument:
1. I agree
2. I agree - only if the imperfections are random.
3. I agree - only if the imperfections are random.
4. So, it does not address my argument.
5. Wrong - the whole purpose of this is to properly identify the signal from the noise and accurately measure the delta in the signal in order to see the trend. By say that there is a signal but you don�t know the bias and don�t care means that you don�t know the actual temperature and you don�t know the actual trend.
6. This is the worse statement I have seen you make. The truth is you should know the data collection points to identify bias. Then you should take the bias adjusted data and use that.
If there was no bias then what you�re saying would be correct from a signal processing point of view. Those few pictures indicate that there is possible bias at many stations and the bias appears to be due to urbanization which has all the biases being warming biases. This means that if you do not know and adjust for the bias, then your process could result in a temperature signal that is higher and changing upwards faster than it actually is.
If this is not reason enough to actually validate and profile the individual stations, then what is?
8 July 2007 at 9:27
Attacking Al Gore is akin to killing the messenger. Gore is the trumpet player calling the Cavalry to battle, but by portraying him as a self interested analyst and (former) politician to boot, the deniers,stir their own ideological Cavalry to arms and they’re are able to divert attention toward disrespecting the individual and away from the mostly incontrovertible evidence of the science. Smearing the troubador and even making the cavalry retreat won’t stop the reality of global climate change.
8 July 2007 at 10:20
Hey, I’m a denialist and I read these missives…
Comment by Ken Coffman � 2 Jul 2007 @ 11:53 am
Good. This is another one of my critics Gavin. Nice to firm up data I’ve collected from other stations. Things are much clearer now.
8 July 2007 at 10:26
RE#290: “he means nothing more nor less than something which conforms with his personal and oftentimes ambiguously-stated methodology” … what exactly is this supposed to mean? The guy is an expert in this field, is he not? He has published in peer-reviewed, widely-respected journals, has he not? But, because he goes against the grain he’s all of a sudden a hack of some sort?
8 July 2007 at 11:36
> urbanization which has all the biases being warming biases.
Wrong on that belief stated as though it were a fact, see #20 above.
Who is telling you that story?
8 July 2007 at 12:21
Re: 299
because he goes against the grain he’s all of a sudden a hack of some sort
Irrelevant. Science is science. Hackery is hackery. Nobody’s a scientist all the time.
8 July 2007 at 12:44
Re 295 –
There was someone on that thread who made a wager, and I was more than happy to accept. I don’t recall being contacted by said other party to formalize the wager with any sort of written terms and escrow deposit.
On the short term, someone betting “for” AGW to show its face is betting against any natural events that would depress the climate in the near term, simply because natural events produce greater short term climate change. On the long term, someone betting “for” AGW to show its face is betting against everyone deciding the threat is real and acting on it. In short, the more obvious the threat the less likely the person taking the “for” position is to actually win. Even if one believes in AGW, the area under the probability curve is dominated by a combination of “not going to happen” and “people react and it doesn’t happen”. My intuition tells me that a central “up a little, down a little” position poses the greatest financial risk to someone wagering against AGW.
Given the amount of focus being placed on “Climate Change”, I’d wager against any long term climate change and would have to be given odds to take a 20 or 30 year wager. I’ll likely be dead in 50 years, so 40 and 50 year wagers are straight out as I don’t plan to be well into my 80s and wondering if I’ve won or lost
8 July 2007 at 13:11
“Those few pictures indicate that there is possible bias at many stations and the bias appears to be due to urbanization which has all the biases being warming biases.”
This is a classic false cause fallacy. In my government work I’ve run into these weather stations in all sorts of locations. I place thermographs in streams to get long term profiles, so perhaps they are all biased too by this logical flight of fancy? I doubt it.
“This means that if you do not know and adjust for the bias, then your process could result in a temperature signal that is higher and changing upwards faster than it actually is.”
Every measure there is says the opposite when adjusted for every possible bias. That indicates it isn’t and separates wishful thinking from real science. I’ve done field biology long enough to know that much.
8 July 2007 at 13:18
Vernon, now let me get this straight:
You are actually advocating as helpful sending a bunch of completely untrained individuals with
1)zero understanding of data networks,
2)zero understanding of data processing,
3)zero understanding of the history of the network,
4)zero understanding of the types of errors that are significant,
5)zero understanding of the signal,
6)zero understanding of the noise
And you want to do this when there is
1)zero evidence of any bias in the system
2)the results are consistent with every other line of inquiry
3)the data analysis is being done by skillful professionals who know how to deal with the errors introduced by site variability and degradation
4)the vast majority of the stations in the network are not affected by the biases you allege are there (unless you think polar bears and groundhogs are barbecuing and building parking lots).
And you propose to give your volunteers no training so that they understand how data are analyzed so that they think every little variation from ideality that they find is the smoking gun that disproves that the globe is warming. Hell, you’re not even going to verify that they can balance their own checkbook for fear of compromising their “objectivity”. That about got it?
[edit - please keep personal issues out of this discussion]
8 July 2007 at 14:09
Geez, the guy’s been queried by a real climate scientist — and he went quiet, two weeks ago.
http://julesandjames.blogspot.com/2007/06/more-on-20000-bet.html
8 July 2007 at 14:54
RE #170
One major objective of my project is to determine the range of natural temperature variation at a weather station by reducing the number of factors that effect temperature to as few as possible. For example, by chosing the daily minimum temperature, the effects of clouds on sunlight are eliminated. In general, the daily minimun temperature occurs just before sunrise when the winds are calm and the land quescient. This is why the white-crowned sparrow calls early in the morning, for its call can travel quite a distant without distortion or interference from background noise.
Oil on the oceans should be looked into. Not only do ships deposit huge amounts oil by discharging bilge water, there is enourmous quantities that are flushed from streets of coastal cities. Every parking lot is just slattered with oil and this eventually ends up in the rivers, lakes and oceans. Oil is not biodegarable although it is slowly oxidized by air.
8 July 2007 at 16:11
Re #287: Just to note that the concluding passage from that Science Daily article —
“The dating of dust particles also showed that it has been at least 450,000 years ago since the area of the DYE-3 drilling, in the southern part of Greenland, was ice-free.
“That signifies that there was ice there during the Eemian interglacial period 125,000 years ago. It means that although we are now confronted with global warming, the whole ice sheet will not melt and bring about the tremendous sea-level rises which have been the subject of so much discussion.”
– isn’t supported by the paper. As noted elsewhere above, the dating is not certain with regard to the Eemian. Even if it were, though, the final conclusion about not having to worry about “tremendous” sea-level rise is completely unsupported since the research affirms that more or less complete melting did occur during prior interglacials. Aside from inferring an interesting line of research as to what the differences are between the interglacials that might result in differential melting of the Greenland Ice Sheet, these results should only cause us to be more concerned about a repeat of circumastances under which the Eemian sea-level rise would have come primarily from the West Antarctic Ice Sheet. IOW, there’s no comfort at all here for denialists.
This view is consistent with the press release from Eurekalert.
Re #304: Ray, it’s worth repeating that this surface record documentation business is just the latest chew toy for the “audit” crowd now that the hockey stick has become boring. Once this is over with, it’ll be on to something else.
Some of them are capable of sounding reasonable, but IMHO Mankoff ought to search the surfacestations site for comments made about Jim Hansen prior to firming up plans to work with them.
8 July 2007 at 16:29
The Greenland and Antarctic ice sheets got some extensive news coverage this last week, BTW. (Note to Hank that the Antarctic one includes a juicy ANDRILL teaser.)
8 July 2007 at 17:15
Re#304
Snapping up 4 high-quality images from pre-determined locations requires what sort of statistical and mathematical training?
Re#299
Hardly irrelevant - if you attack a scientist’s methodology, state what part of it constitutes revision and how it should be revised.
For example, read my initial post on this thread regarding the invalid argument made by Parker (2006) and why this paper should not be cited as evidence of a lack of UHI signal on large scales - I don’t simply state that “he means nothing more nor less than something which conforms with his personal and oftentimes ambiguously-stated methodology”. I actually critique his methodology - please separate that from personal attack, which has no business here.
8 July 2007 at 17:21
Harold Pierce — please, try checking your beliefs; Google Scholar will usually give you useful info if you read only the abstracts on the first page of hits. Spelling counts in finding answers; this for example:
H)-21. beta.(H)-hopane as a conserved internal marker for estimating the biodegradation of crude oil
RC Prince, DL Elmendorf, JR Lute, CS Hsu, CE Haith � -
Environmental Science & Technology, 1994 - pubs.acs.org
… Introduction The majority of the components of crude oil are biodegradable (1-41,
but quantifying biodegradation in the field has proven to be a challenge. …
8 July 2007 at 17:57
Modeling your filtering process; will you put your money where your mouth is?
Let us say that a group of skeptics were to be assigned a virtual weather station. They are given a temperature data set which has a clear temperature trend. There are 40-50 such stations, each station has a nominal 100 years histroy (but it may be less).
Each skeptic is allowed to introduce a number (randomly generated) of random events in their station, during its whole history; as in a move, as in a gap of x number of years, as in a UHI effect or even a barbeque next to the instruments.
We will have a strict way that data is allowed to be altered, generally agreed before hand. The actual position of each station in a grid will be chosen at random. We will have the golden envelope that contains the “real” data set and hand the “noised” data to you people.
Could you find the underlaying temperature trend?
What will your error bars be?
I could get 40-50 people who will each handle one site and one site alone. We could easily have someone make up a “real” temperature data-set, who would not be in contact with either group.
Are you prepared to wager on the outcome?
8 July 2007 at 18:06
Matei Georgescu (#298) wrote:
When I say “personal methodology,” I mean essentially that there are methodologies which are used in science for the purpose of forecasting, then there is the methodology which he himself originated and promotes. When I say “ambiguous,” I mean that his methodology is stated in terms of “principles” which at least appear mutually contradictory.
Please see:
His actual field is “marketing,” and he is Professor of Marketing at the Wharton Business School, University of Pennsylvania. In the forecasting of natural phenomena as opposed to market forecasting, I believe he has as much expertise as Bill Dembski in evolutionary biology. Judging from the Kos article above, his greatest skill is self-promotion.
However, “hack” is not the word that I would use to describe him. Hack generally implies lack of skill, and this guy has all the skill of your typical pool hustler or card shark. As for his articles being peer reviewed, plenty of articles in deconstructionism can make the same claim.
8 July 2007 at 18:56
Re #306: “Oil is not biodegarable although it is slowly oxidized by air”.
It may not be “biodegarable” but it is definitely biodegradable. I’ve conducted many lab scale and field scale projects on biodegradation of crude oil and refined products over the past 30 years.
Ian Forrester
8 July 2007 at 19:14
Re 306 “Oil is not biodegarable [sic]”
Of course it is biodegradable - there are plenty of oil-degrading bacteria and fungi, etc. in the ocean. Here is a free electronic book on the subject from the U.S. National Academies of Sciences:
http://books.nap.edu/openbook.php?record_id=314&page=270
8 July 2007 at 19:52
For those who are interested, the NOAA has restored access to surface temperature site data and despite the misgivings of many people here, photographing of sites has resumed.
8 July 2007 at 20:30
DocMartyn, you’re restating the same PR talking point that’s failed above at length. Climate isn’t weather; this is a small signal detectable with a large number of stations.
http://julesandjames.blogspot.com/2007/06/20000-climate-forecast-bet.html
8 July 2007 at 20:49
re: #118 Jim Cripwell
re: #302 FCH
Are either of you up for a Long Bet, ending say around 2020? {I think I might still be around then, see www.longbets.org for the mechanism].
If I read Jim’s post right, it sounds like he may believe the Abdusmatov-like theory (i.e., like “Climate Skeptic?”) that tells us to expect cooling soon. (Is that correct?) I tried to offer CS a Long Bet, but he seemed to disappear shortly thereafter.
FCH: I’d hate to bet against you, but you seem (I’m not sure?) to bet either that the world will not naturally get warmer, or that humans will decide to do something quickly enough. I wish it were otherwise, but since I believe that physics says CO2 will stay a warming influence for a long time, even if we stopped emitting any CO2 tomorrow, I’d guess that a 3 (or preferably 5) year average for 2020 will not be lower than that of 2009 (that’s picked to be 11 years apart to match solar cycles). I’d even take my chances with volcanoes and ENSOs.
Overall on chasing USHCN stations:
according to the CIA Factbook:
510.1 M sq km = Earth total surface area
148.9 M sq km = Earth land surface area
..9.2 M sq km = USA land area, of which (1.8% of total surface)
.-1.5 M sq km = Alaska (other sources), Hawaii small.
..7.7 M sq km = rest of US (1.5% of total surface), since I don’t believe many stations are subject to serious UHI in Alaska.
There could be a substantial amount of uncorrected UHI … and it still wouldn’t matter on the world scale.
In one of my old roles as a computer performance guy [I was one of the architects for SGI Origin/Altix supercomputers with which Gavin would be familiar], I’d have had STRONG words with anybody who:
- started with 100 long-established benchmarks (probably a 3X over-sample) that together yielded a performance number,
- took 1-2 of those, whose results were not outliers, but were in the middle of the distribution, and which had often been scrutinized by experts
- and then proposed to spend a lot of time analyzing those 1-2 to death.
My main worry about UHI isn’t the measurement, it’s the effect on the US Southeast/Southwest especially:
hotter -> run air-conditioners more -> exhaust hotter air outside ->
hotter … chew up more power to run air-conditioners … -> burn more coal ->
fire up least efficient plants for peak electricity usage.
http://communicate.aag.org/eseries/aag_org/program/AbstractDetail.cfm?AbstractID=12661
says Phoenix, AZ already a UHI of 6C … which, still doesn’t make any difference to the overall numbers, but has strong local effects. I was there ~15 years ago in the summer, and it was already ferocious. I’d guess that actions to ameliorate the UHI effect (more trees, rooftop gardens, better building techniques) will prove to be good investments in many places.
8 July 2007 at 21:06
DocMartyn, Let me get this straight. You’re talking 40-50 randomly selected stations–GLOBALLY. What is the range on the number of events, and the duration (or is that random, too)? Are the stations randomly selected? Is there any restriction on the type of error that can be introduced (i.e. does it have to be of a type that could be found in nature)?
If such a proposition were available, I would strongly consider a piece of that action. But before taking your money, as an honest man, I would have to ask you to consider the wager you are making:
You are saying that by introducing some sort of noise some random number of times at 40-50 different stations our of a network with thousands? tens of thousands? of stations that you could significantly alter a GLOBAL trend. OK, let’s say the stations are randomly selected. The chance of any two neighboring stations being affected is very small, and of 3 neighboring stations being affected miniscule, and so on. What if I choose to compare any station’s reading to the 5 nearest it? OK, now say that YOU get to choose the stations. Be careful. If you choose them too close together, the trend you introduce will be local, not global. Now let’s consider the type of noise you introduce. If the noise is large, or it varies in some significant manner from natural noise, GOTCHA. All I have to do drop that station for all time, or downweight it to insignificance. And if your noise looks like a trend I might see in nature, it probably won’t significantly affect the Global results. So, given that I’ll either be able to identify your sabotage or that it won’t significantly affect the global trend, and given that you’re tampering with maybe a percent of the number of stations in the network, yeah, I like those odds. Still interested.
8 July 2007 at 22:45
304 ray ladbury…> so that they think every little variation from ideality that they find is the smoking gun that disproves that the globe is warming.
Why do so many appear to make a straw man of this?
Yes, it is very unlikely that AGW will be disproved by auditing temperature records, but don’t we want to have the most accurate data possible? Resistance to transparency only helps to make a denier case that there is something to hide.
Also, this is mostly not a qualitative argument about whether AGW exists. If the temperature record is in error by 0.1C or so, maybe a climate sensitivity of 2C is more likely than 3C (I know there are other methods of estimating sensitivity, but there is considerable uncertainty).
Also, this is mostly not a qualitative argument about whether AGW exists. If the temperature record is in error by 0.1C or so, maybe a climate sensitivity of 2C is more likely than 3C (I know there are other methods of estimating sensitivity, but there is considerable uncertainity).
8 July 2007 at 23:52
can someone tell me what an “undocumented changerpoint” found in The USHCN Version 2 Serial Monthly Dataset, document referred in the #2 assumption link, is?
9 July 2007 at 0:57
Very interesting thread… keep the debate going guys, there’s still a long way to go before we find out if the arctic will melt. It’s very interesting to see even on a pro-global-warming site such a mix of varying viewpoints on climate change, personally I feel the debate is essential to preserving good science. I also think its important to keep from overwhelming the general public with a certain bias before a general scientific consensus is within reach.
Until this issue is as widely accepted as tectonic plates, the debate is far from over. So please, do try to interpret scientific evidence with one agenda in mind, that is, science.
9 July 2007 at 1:29
The Australian Broadcasting Corporation is showing the climate change swindle show soon. In preparation, The Australian ran a piece Hostages to a hoax by Martin Dunkin who made the show — it features a pair of graphs from Willie Soon’s Geophysical Research Letters 2005 (vol. 32, 27 Aug, L16712) paper in the print edition (Fig. 1 from http://ff.org/centers/csspp/library/co2weekly/20060406/20060406_11.pdf — took me a bit of digging to find it, since Durkin only cited the journal name, volume and year).
I don’t think I’ve yet seen a critical dissection of this particular paper but it strikes me as odd that he can get away with doing a 125-year correlation-based comparison of 2 isolated variables vs. temperature.
How many astrophysicists, I wonder have published papers funded by American Petroleum Institute, and Exxon-Mobil?
A couple more questions … why does he have to use his own carefully massaged temperature measure when there are other accepted measures around? How significant an effect can you expect with solar energy per area varying by less than 0.3%? If he must treat the 2 variables in isolation, why does he compare them over a long-term range, when the CO2 is not increasing as steeply as today? Without doing the stats, if you eyeball the graphs, the CO2-temp trend looks like a much better fit post-1960, when CO2 started to increase more significantly.
Informed comment would be much appreciated.
9 July 2007 at 2:16
Steve Reynolds (#319) wrote:
The figure of roughly 2.9 C comes from the paleoclimate studies for the past 400,000 years. I don’t know of anyone who would be trying to estimate climate sensitivity on the basis of present day temperature records. For one thing, it just wouldn’t make much sense: climate sensitivity isn’t just the temperature change which has occured as the result of the rise in CO2 levels - it is also whatever temperature change is still in the pipeline until the climate system finally re-achieves a quasi-equilibrium.
But there is one thing to keep in mind, something which I personally regard as a great deal more important than any Urban Heat Island effect: the climate sensitivity isn’t what temperature increase will result in the long-run from the carbon dioxide which is in the system at present. The climate sensitivity is ultimately a question of how much the temperature increases relative to the increase in carbon dioxide once the new equilibria for both are achieved. The further this goes, the more positive feedback we are going to be seeing as the result of the carbon cycle.
Recently we discovered that the Southern Ocean has been losing its ability to absorb carbon dioxide. Likewise it appears that plants are losing their ability to take up as much carbon dioxide as they have been in the past - at least during times of heat and drought stress. And now thawing permafrost is releasing methane in the Arctic and Sub-Arctic regions. Then there is the wildcard of shallow water methane hydrates.
Many of the feedbacks which are kicking in from the carbon cycle are a largely a function of temperature. At some point, it is quite possible that the ocean will become a net emitter of carbon dioxide. And even if we were to stop emitting carbon dioxide right now, we would still have a fair amount the temperatures would continue to rise substantially for the next fifty years.
But somehow I doubt that we will even be reducing our net emissions within the next few years. We will probably be fairly lucky if we see them start to fall twenty years from now.
9 July 2007 at 2:26
re 321, Alex
Don’t get this wrong but… arctic is already melting.
http://www.msnbc.msn.com/id/9053898/
“Average arctic temperatures increased at almost twice the global average rate in the past 100 years. Arctic temperatures have high decadal variability, and a warm period was also observed from 1925 to 1945.”
“Satellite data since 1978 show that annual average arctic sea ice extent has shrunk by 2.7 (2.1 to 3.)% per decade, with larger decreases in summer of 7.4 (5.0 to 9.8)% per decade”
http://ipcc-wg1.ucar.edu/wg1/Report/AR4WG1_Pub_SPM-v2.pdf
Secondly, I think this issue is as widely accepted in the climate scientists communauty than tectonics are accepted by geologists (and I’m sure I could find one or two of them to tell you tectonics is just a flat wrong theory
). You said it, none should interpret scientific evidence with an agenda in mind…
9 July 2007 at 2:41
Some responses to people who replied to my original posting.
Thanks for your replies.
Gavin:
Actually I think realclimate.org is a great place to educate people wrt the issue that most state-funded surface weather observations are kept proprietary. Anyone who cares about society’s response to climate change should care about this issue, and the more people who know about it the better. I agree that the governments responsible should also be targeted directly.
The impact of not being able to get data is that many groups of people who need to start responding to climate change can’t do so as effectively as they would otherwise be able to because they can’t quantify their exposures and their risks. That’s bad news for all of us.
Wrt your comment about NOAA data: note that much of the ‘free’ data from NOAA actually comes with legal restrictions, because of the infamous WMO resolution 40. For a lot of the international data NOAA provides, it wouldn’t be legal for me to use it.
My apologies to Norway and NZ for not mentioning that they do make their data available. All credit to them. I’ve dealt with the UK, France, Germany, Holland, Spain, Italy, Belgium, Luxembourg, Sweden, Finland, Denmark, Australia, Japan, Austria, India and Greece. They are all very nice people, but their data is very expensive (at least last time I checked), and this really limits the extent to which it is usable by the people who need to be looking at it.
I agree that *very* large scale climate questions can be addressed using the free data. But I’m interested in smaller scales. How are the patterns of rainfall in the UK being affected by climate change? What are the patterns of temperature change in France? Are there more thunderstorms in Italy? Are typhoon winds in Japan changing? You can’t answer these kinds of questions with the free data.
Tamino:
I agree that you can find a lot of temperature series on line. But it’s a tiny fraction of what’s being measured, and the resolution just isn’t there for the kinds of questions I’ve listed above.
Ray Ladbury:
Sorry, I don’t quite understand your point. I’m a professional meteorologist, and I spend most of my time analysing weather data. I write papers and books on the subject. In my humble opinion of myself, I am qualified to analyse weather data and make sense of it. I want the data to be available so that I can reproduce, check, confirm or refute, and extend, what the state funded researchers are doing. And so that other suitably qualitified people can do the same. I wouldn’t deny that it’s hard work. I don’t have any plans to download the human genome. I wouldn’t have the faintest idea what to do with it.
Hank Roberts:
My comments about the availability of climate data are based on working in a group of people that has contacted many of the NWS’s in the world to try and get their data. If there is any other group in the world who has spent as much time as we have contacting the NWS’s to get data, I’d like to here from them and know what their experiences were. Anecdotally, I talk to a lot of applied meteorologists. They all have the same frustration.
My (rather poor) joke on this subject: for companies in London, UK, it’s easier to get weather data for London, Texas, than it is to get it for their own town.
9 July 2007 at 3:43
Having seen a number (maybe a hundred or so) of official temperature observation stations over 40 years of time and on all continents (ex. Antarctica), I might consider favourably any study results that would report about 0.2 degree underestimate of the global warming in the actual observations.
The reason being that the personnel training and equipment service, maintenance and replacement improvements have substantially reduced the “raw data” temperature measurement errors, slowly but surely. The old and grimy wooden thermometer screens with flaking white paint have gradually become things of the past. The solar radiation heating errors are consequently much less than they used to be.
Another comment I have is that the function of “climate observation” has undergone a profound change over the years. It used to be a local interest. I.e. in the U.S. the “State Climatologist” office system was established to provide climate guidance to the local businesses and the public related to things like which crops and varieties it would be possible to grow in which localities, or on the flooding probabilities of proposed rainwater drains, etc. This did not require 0.1 degC measurement accuracy, and the observation stations were equipped and maintained accordingly with lowest cost instruments meeting those actual needs. This was of course entirely right, local climates in the U.S. show a wide range and the needs were correctly understood.
“Global climate” was then a specialized and narrow academic discipline that was not much of a consideration. It has only recently become an operationally critical main stream interest.
Higher accuracy measurements were required by the weather forecasting services. In that application, a station’s 0,2 degC bias would show up on the national and regional weather maps. Consequently much more was invested in the equipment and training of people working on the (fewer) synoptic stations, in systematic re-calibration of sensors, maintenance of thermometer screens etc.
Various constructions of thermometer screens have been tested in Europe (Netherlands and Norway). In those well controlled and well maintained circumstances impacts are still significant.
http://www.dwd.de/EUMETNET/Berichte/TECO98temp.pdf
U.S. is unique in having a quite separate local climate observation organization. In all other countries climate observation has been an integral part of the national weather service.
Global climate analysis is bound to live with the quantity and quality of past observations, made to the requirements and specifications of other services - inadequate as they may be. As has been said, luckily it is not critical of the science aspect, as the observation statistics are just a diagnostic tool, not a primary input.
As practical advice based on experience, I do propose the following: If a new observation does not come close to a prediction by an established old theory, check carefully the observation. The large errors are very likely found there. Small differences may be on either side.
As to the photo mission, much more useful would be to collect old photos taken on the stations, of which there certainly are great numbers in the family albums.
9 July 2007 at 8:25
RE: T Chase #323
“Recently we discovered that the Southern Ocean has been losing its ability to absorb carbon dioxide.” The oceans are not losing their ability to absorb carbon dioxide, they are just not increasing the absorption. This has been attributed to changes in weather (winds), which are not necessarily permanent.
“Likewise it appears that plants are losing their ability to take up as much carbon dioxide as they have been in the past - at least during times of heat and drought stress.” Really? Losing their ability? Plants thrive in a high CO2 environment, and perform particularly well in wrt drought as they evapotranspire much more efficiently. This efficient use of water overcomes the effect of heat.
“And now thawing permafrost is releasing methane in the Arctic and Sub-Arctic regions.” Permafrost is melting, but why are methane concentrations in the atmosphere leveling off and trending downward?
The case for global warming is strong. Why is there a need to stretch the data and cheer lead for disaster?
9 July 2007 at 8:36
Re: #322 (Phillip Machanick)
One of the big problems with the graph is that the solar data (total solar irradiance, or TSI), is not really right. Durkin, in his piece in the Australian, claims that
But this is just plain wrong. Note that the solar data graphed go back to about 1875; NASA and NOAA have only been measuring TSI since about 1978. In fact the TSI data in Soon’s paper come from a reconstruction, based on proxy data, by Hoyt & Schatten (1993, updated later). But the satellite measurements (the data actually from NASA and NOAA!) distinctly contradict the proxy reconstruction of Hoyt & Schatten. If you want to use a proxy reconstruction for data prior to 1978, the “gold standard” these days seems to be Lean (2000, later updated), which matches the satellite observations quite well during their period of overlap.
It seems to me that what Soon did was to search for some temperature dataset, somewhere, that would match the TSI data he was using. There are certainly enough regions of the earth that one could likely find such a match, whether there is a causal relationship or not! Now that we have better TSI data, the “match” isn’t nearly so good.
You can find more info on TSI in this post and this post on my blog.
9 July 2007 at 8:52
Re: 304 Ray, far be it for me to imply you could be wrong, but since I know so little… please explain how you can adjust for a sampling bias without knowing what it is first. I did a review and could not find this.
I also never discussed how to do a study of possible bias in surface stations.
9 July 2007 at 9:41
Vernon, do you know what “sampling bias” is?
” Sampling bias can occur any time your sample is not a random sample. If it is not random, some individuals are more likely than others to be chosen (more subtly, some combinations of individuals are more likely to be chosen together). Sampling bias occurs whenever those more likely differ in their distribution of one or more of the measured variables from those less likely.”
http://cs.fairfield.edu/~sawin/Stats/Notes/sampling.html
We are not even starting with weather stations randomly distributed across the planet. You’re assuming and stating as a fact your belief that the people running the instruments don’t know as much as you do. You may want to learn more about how they are using the system before deciding for sure that they are wrong.
9 July 2007 at 9:48
OK, Vernon, work through this with me. You claim there is a sampling bias in the data. How would we find it and characterize it. Well, first, “sampling bias” isn’t very specific. The sampling bias could be one that creeped in over time (e.g. through urbanization) or it could have existed from the beginning or it could be a combination of both. (Can you think of any other possibilities?) No matter. We have data going back 100 years or more from some stations, and we have multiple stations near each station that we can cross compare. We can even compare stations far from each other but with similar microclimates (latitude, altitude, geographic setting, weather…). We can compare stations that have different microclimates that vary from each other in well understood ways. We can look at stations and their neighbors where one station is known to have urbanized and compare them to similar stations where all remain rural.
Now the signal we are looking for is gradual AND global. If we see a sudden temporary change, we probably just drop that reading. If we see a sudden permanent change, we probably downweight that station in future analyses. And we can also see if nearby stations are similarly affected. If they are, we can investigate that’s a tipoff that maybe we actually need to look at that little region. It still won’t produce a global signal, but something odd is going on there and we might need more info to understand how to treat it. Or if we don’t have a grad student we want to expose to poison ivy, we can just drop that little cluster–hell, we’re oversampled by ~100x anyway.
Now, I know I’ve made this sound easy. It’s actually a lot of hard work, but it is mostly straightforward, and anyone who has worked with a large geo information network is going to understand how this works. Still the thing that makes it straightforward is the fact that the signal you are looking for is gradual and global, while the errors will tend to be local and often more rapid. It also doesn’t hurt that the biggest signals are in polar high-latitude regions that are still largely unurbanized.
I don’t disagree that as you move from global climate models to regional and local models (e.g. what does climate change mean for the poor souls in Vegas who are enduring 120 degree temperatures and haven’t seen rain this year?), these effects may be important. For the issue of Global climate change, they’re a fart in a windstorm.
9 July 2007 at 10:08
RE 331: Ray, you still have not answered the root question, how do you adjust for a sampling bias when you do not know what it is. Your answer is that there is no bias but by definition you cannot adjust for a bias until you detected it and understand it. All I am saying is that the pictures shown indicate that there is poor siting with many stations that could have a bias but we will not know until the stations are inspected. So I have to ask, how are you going to determine what the bias is, or even if one exists, without a study of the stations and why is doing a study to determine whether there is a bias or not something that you have to be so against? When is collecting better data wrong?
9 July 2007 at 10:25
Sam (#327) wrote:
From what I can see, the amount of methane that we are releasing has leveled off, but it is not declining as of yet, at least not as of 2005.
Please see:
… and more recently, I believe the amount of methane being released from the permafrost has actually increased.
While we have managed to reduce our own methane emissions and it has leveled off as of 2005, it is a factor and it is something we need to take seriously. While I most certainly do not expect a catastrophic release of methane from the permafrost, we have good reason to believe that its release will be increasing in the coming years. And although it has a half-life of only 40 years, even once it decays, it leaves behind an equal amount of carbon dioxide which will remain in the atmosphere much longer.
Please see:
My concern is that we still appear to lack the political will to do something about our own emissions of carbon dioxide, and once permafrost thaws, unlike our emissions, it is something we cannot control. As for shallow water methane hydrates, these too are something which we cannot control - once they become a factor, but they pose a more distant threat.
9 July 2007 at 10:55
Re 324 “I’m sure I could find one or two of them to tell you tectonics is just a flat wrong theory”
Oh, yes, there are few alternative “theories,” some of which have been proposed by geologists :
http://users.indigo.net.au/don/links.html
http://64.233.167.104/search?q=cache:_bOi346yXgsJ:www.ncgt.org/aboutNCGT/aboutNCGT.pdf+plate+tectonics+alternative&hl=en&ct=clnk&cd=9&gl=us&client=safari
9 July 2007 at 11:22
Hank, to be fair, we are sampling temperature at various points around the globe. Perhaps what Vernon is alleging is that the distribution of weather stations around the globe is nonuniform and so would give rise to a sampling bias. However, the answer to this is the same as the answer that I gave: the data will tell you.
Vernon, are you aware of the statistical analysis technique of bootstrapping? It is a technique for looking (among other things) at the dependence of your result on a subset of your data. Now, bootstrapping in a complicated geo-network like the meteorological network can be performed in a variety of ways. You can remove single stations and recompute your result–this tells you if a single station or indeed several stations may introduce a bias. You can remove local clusters of stations–singly or in combination. This tells you where you might have had large-scale local changes. You could remove regions and see if your signal is still robust over the rest of the planet.
Other things you could do:
1)Divide your data in half randomly. Compute your result with each half and see if they agree.
2)Compare your results to multiple other results to see if they are consistent.
Again, Vernon, the signal you are looking at is global. You have to find a problem not just in New York, but in Timbuktu and Novosibirsk–or even more likely, you have to find multiple problems that give rise to a comparable effect in >33% or so of the stations in the network. Even more improbably, it would have to have roughly the same time and spatial dependence as your signal. Do you really think you’ll find anything of that order of magnitude? Do you really think that anything that huge would have escaped notice?
Now notice that I am not saying “Don’t look.” I’m saying “Look where you are most likely to find any issue that exists–in the data,”–and that has already been done with astounding thoroughness.
9 July 2007 at 11:27
re: #322 Phil
Hi Phil!
Since OT, short, see:
http://en.wikipedia.org/wiki/The_Great_Global_Warming_Swindle
which goes through the GGWS controversy, including pointers to reviews.
9 July 2007 at 11:43
RE:333 Tim: thanks for the response on the methane issue. Before getting too pessimistic, please consider that most of the permafrost will remain frozen (only the surface and southern areas will begin melting), and that when melted vegetation will grow and with it carbon will begin to acculmulate in the ground again. This is after all, how the methane got their in the first place.
9 July 2007 at 12:25
RE: 335 Ray, how do we know how many stations are badly sited? Is that not the whole issue. Your going with feelings that it is not likely that enough stations have a problem but your don’t have the evidence to back that assertion.
Now do I think that could escape notice, why not, based on the pictures I have seen so far, it appears that many of the stations presented have problems. I do not know if the pictures represent a valid sample of the network but I would like to see the evidence so we can know, not feel that it is correct.
Once again you ask if I feel on whether this could escape notice and I have to say again, I don’t want to feel it, I want to see the empirical evidence.
Some how I do not think that science is based on feelings but rather empirical evidence.
9 July 2007 at 12:25
I call the temp. quibbling disingenuous because it is analogous in structure and intent to conflating a few electrical meters being inaccurate as evidence that electricity may not exist.
It’s that transparent and phony.
9 July 2007 at 12:49
Vernon, did you reread #20?
Are you saying that you feel, based on looking at those pictures, that the temperature readings from the boxes in the pictures must be biased, and must be biased to give too high a reading?
If you put a comparable box nearby, with fresh paint, or cleaned screens, or positioned outside of the shadow/depression/parking lot/heating exhaust vent, in the picture, would you expect the thermometer result from the nearby box to be different enough in its reading to make a difference?
How would you tell, if not by making the comparisons already described?
Would you want to look at readings from the individual thermometers in the two boxes side by side, and decide if they were different?
How would you decide?
9 July 2007 at 14:14
re: 338. This entire point is a rotten red herring and quite disingenuous with respect to global warming. As has been pointed out numerous times and continually conveniently ignored by the skeptics/denialists, the surface global temperature stations are a very small subset of the larger data set (tree rings, glacier melt, satellite measurements, etc.) indicating the temperature trend. Yet skeptic/denialists keep repeating (and inflating) the red herring issue as if somehow that makes it more important. It is denialist tunnelvision of the worst kind.
9 July 2007 at 15:04
323 Timothy Chase> The figure of roughly 2.9 C comes from the paleoclimate studies for the past 400,000 years. I don’t know of anyone who would be trying to estimate climate sensitivity on the basis of present day temperature records. For one thing, it just wouldn’t make much sense: climate sensitivity isn’t just the temperature change which has occured as the result of the rise in CO2 levels - it is also whatever temperature change is still in the pipeline until the climate system finally re-achieves a quasi-equilibrium.
You are mistaken. 20th century warming (corrected for your objections, I’m sure) and volcanic cooling are also used. See:
http://www.jamstec.go.jp/frcgc/research/d5/jdannan/GRL_sensitivity.pdf
for a brief discussion of the various methods and their sensitivity spreads (see figure 1). Paleoclimate appears to show the smallest sensitivity (peaked around 2.6C).
Also very good discussion at the author’s blog:
http://julesandjames.blogspot.com/2006/03/climate-sensitivity-is-3c.html
9 July 2007 at 16:29
Steve Reynolds (#342) wrote:
Actually the figures from the paleoclimate seem to center around 2.8 C for the past 420 million years, not the 2.9 that I gave or the 2.6 that you gave. And this agrees well with the essay you pointed to which gives 2.9 C. In any case, the argument regarding the long-term nature of carbon emission climate sensitivity wouldn’t apply to the recent volcanic aerosols from Mt Pinatubo as they were essentially cleared within about three years - if I remember correctly.
The again, Urban Heat Island effects would be irrelevant to an estimate based upon Mt. Pinatubo - unless of course people started up their barbeques at just the right moments. It is the delta which is important. So the 3 C from Pinatubo would seem less suspect - if one were worried about the Heat Island effect.
As for the smallest and the largest sensitivity, they come from the joint use of observation and models - not observation alone, and it may very well have been something similar to what was done with Pinatubo and therefore largely independent of anything that would have been affected by the Urban Heat Island effect. I don’t know as the paper which you cite doesn’t say. But anything from 1.5-6 C with a best guess of something around 3 C. The paleoclimate estimate of 2.8 C is above the lower estimate of 1.5.
In any case, we have several largely independent lines of inquiry suggesting something between 2.8-3.0 C. I tend to think if a conclusion is justified by multiple indpendent lines of investigation, the justification which it receives is far greater than that which it would receive from any one given line of investigation in isolation. Likewise a range of 2.8 - 3.0 C seems preferable to 1.5 - 6.0 C, at least if one is interested in narrowing the uncertainty.
As for my original point, sure, they could try to use trends to calculate the sensitivity (given the appropriate mathematical methods) and clearly they have tried. However, in my view the paleoclimatological records are far more likely to give you a narrower range of uncertainty. And that would have been the both the appropriate and correct way of stating my point.
9 July 2007 at 16:41
The wager is for a grid. You get station station psudo-data and I have the real psudo-data and the noised psudo-data. all you have to do it throw away the noise. Could you get the same average in the grid using the noisy-psudo-data compared with the real.
That is the question, psudo-data in a grid. We test your ability to get rid of the noise. Can you do it?
9 July 2007 at 17:00
Anyway, if someone is interested in how the Urban Heat Island effect “distorts” temperature trends, there is relevant literature.
Here is the abstract from one:
9 July 2007 at 17:08
“the surface global temperature stations are a very small subset of the larger data set (tree rings, glacier melt, satellite measurements, etc.)”
So you’re going to show up us skeptic’s prejudice against the accuracy of temperature measurements (to the tenth of a degree, no less) by counting and measuring tree rings??!!? Around the globe???!?
9 July 2007 at 17:12
> We test your ability to get rid of the noise. Can you do it?
The “you” you’re trying to reach would be the data analysts who produce the reports from the weather stations — I’m a reader here just as you are.
You seem to be asking how many stations it takes to derive a small global signal, buried in larger annual variability? If so, the answer from the previous discussion seems to be “about a third of them” — the network is 3x as large as needed to be able to detect a signal.
Why not try this for yourself and show your result? You could use the data set pointed to over at Stoat,
http://scienceblogs.com/stoat/2007/05/the_significance_of_5_year_tre.php
there’s a link from which you can download the original data set — get it all, fudge some of it and run the statistics, and see for yourself how much of a deviation you’d have to introduce before you affected the trend.
If you’re asking whether it’s possible to spit in the pool and then pull back out the spit, the answer would be no. Silly question. If you’re asking whether spitting in the pool is going to cause it to fail the microbiological tests for clean water, the answer would depend on the quantity of spit and its contents and how diluted it becomes.
Seems the first question would be if _you_ can introduce enough bogus information into a data set to affect the trend, and so find out how sensitive it is, eh?
Stoat suggests: “Pick up the HadCRU temperature series from here. Compute 5, 10 and 15 year trends running along the data since 1970″ http://www.cru.uea.ac.uk/cru/data/temperature/
And he shows you his result, http://scienceblogs.com/stoat/upload/2007/05/5-year-trends.png
So you can do that, then alter the data set and doing the math again. Tell us how much you have to change the data to change the trends.
9 July 2007 at 17:15
Re 344. How many stations in the grid vs. how many stations with noise? Are the stations distributed over the entire planet or a reasonable approximation thereof? How close does the reconstruction have to be to the pseudodata?
9 July 2007 at 17:30
Here is another abstract - and the article if one is interested. It is from 2003.
Please see:
9 July 2007 at 17:31
How many stations in the grid vs. how many stations with noise?
All stions will have noise. What type noise depends on many things, things you would not know about, but “realistic”.
Are the stations distributed over the entire planet or a reasonable approximation thereof?
I don’t want you to do a whole planet, just a grid, i will make it square if you like. All you have to do is to find the underlying signal. How you do it I don’t care. If you are given noisy pseudo-data for 40-50 stations, over a 100 year period, can you get rid of the noise.
How close does the reconstruction have to be to the pseudodata?
What do you think is possible? Let us say that if we combine the pseudo-temperature set for your chosen sites and plot them against the same sites “real” pseudo-data. What will be the significance and what will be the R2 factor?
Just how good do you think your programs are?
9 July 2007 at 17:46
Is there something wrong with using the satellite data set (below) to establish global temperature changes over the last 25 years or so? It seems to me that these measurements have been scrutinized and corrected to satisfy the most skeptical observer. Why all this concern with the meteorological station data now that there is a better way to track global temperature changes and a reasonably long record? Just asking.
http://vortex.nsstc.uah.edu/public/msu/t2lt/tltglhmam_5.2
9 July 2007 at 18:05
DocM, here’s an online text on the subject:
“Data Analysis: S&L1 Introduction
http://www.dartmouth.edu/~mss/Volumes%20I%20and%20II%20.pdf
on p.229 (of 636 pages):
“… The moral of the story is that if the variation of values is due to unbiased measurement error, then the distribution of values should be symmetrical and bell shaped.
“As is frequent in data analysis, the application … requires that we use it backward: When your data is not symmetrical and bell shaped, then you can not explain the variation … When the data is not symmetrical and bell shaped, youâ��ve got some work to do to explain why not….”
You’re asking how much noise you need to add to raise a flag? If it’s real noise, it just widens the range. If it’s bias you want to introduce, you can do that in Stoat’s (Hadley) database and see for yourself how much you have to introduce to obscure the five, ten and longer term trend lines.
9 July 2007 at 18:06
re: 351. Verne, this dataset is discussed on this site here:
http://www.realclimate.org/index.php/archives/2005/08/et-tu-lt/
9 July 2007 at 18:19
Re: Noise
Noise comes in many forms.
Truly random noise tends to be unbiased and uncorrelated. This means that it has equal chance to be positive or negative so the “expected value” of the noise is zero, and the noise on any given day/month/year/whatever is unrelated to the noise at any other day/month/year/whatever. This kind of noise has very little effect on the estimated trend, except to make it more “fuzzy” — it generally increases the uncertainty in our estimate of the physical signal, but the error range of our estimate will still include the true value. If you take the “true” signal data, and add noise computed using a random-number generator with mean value zero, you have added unbiased, uncorrelated noise. Unless the noise is huge compared to the signal (so the signal-to-noise level is tiny), or the number of available data is small, it’s generally very easy to remove its impact, and we will be able to recover the signal.
If the noise is biased, so its expected value is not zero, we can still recover the trend, so long as the bias is constant thoughout time. In fact, translating from raw data to anomaly will remove the effect of the noise bias.
Real difficulties in recovering the signal arise when the noise is biased, and the bias is not constant through time. This can happen when the instrumentation, or data-collection procedures or environment, change over time. In such cases we can consider the time-evolving bias to be part of the signal, so the problem becomes one of separating the physical signal from the instrumental signal.
If we have only one reporting station, we can only separate the two kinds of signal if they have different mathematical behavior. For example, if we change from one kind of thermometer to another which has a different bias, the instrumental signal is a step change, a sudden shift from one value to another. If the physical signal is a linear increase/decrease, then these two signals are of different mathematical character, and can be separated by mathematical analysis.
If we have a network of nearby stations, then we have many ways to separate instrumental from physical signals. Due to the very strong spatial coherence of temperature, the same (or very nearly the same) physical signal will exist in nearby stations, but the likelihood that the same instrumental signal will apply to all stations simultaneously is extraordinarily small. In this case, signal which exists in all (or almost all) stations can be safely considered physical, while signal which exists in a single station (or very small number of stations) can be considered instrumental.
Therefore the ability to recover the trend from artificially altered data depends on what kind of alteration is applied. If you artificially add a trend of the same type as the signal (say, adding linear-trending noise to a linear physical signal), and apply it equally to all stations in the “nearby” network, it will not be possible to recover the physical signal. If, on the other hand, the artificially imposed noise is of a different mathematical character (step-change noise added to linear signal), or the noise is applied to a subset of station reports, or to a large set of stations but with significant time staggering, then it will be possible to recover the physical signal.
9 July 2007 at 18:39
Re:353. Ray, thanks but I had read this and articles re the corrections to early data. It is about 2 years old. The article seems to deal with the correlation of the satellite data with models. The conclusion was that the satellites now agreed with the models, so the data must be good - is this still the feeling after two intensive years of examination?
My question is about the current article - reliability of meteroligical station data. It seems a fundamentally superior method to use satellites to directly measure global temperature. Is there something still wrong with relying on this data over the station data?
9 July 2007 at 19:09
343 Timothy Chas