Why weren’t all these records set in 1998, “the warmest year in the last millenium” (according to Mann)?
[Response:New record-breaking events take place as time move on, and the analysis for the time before 1998 cannot include observations have ‘not yet happened’. The latest record for global and annual mean was set 1998, but it may also be slightly different when looking at local temperatures and on a monthly basis. -rasmus]
Another way of putting it is that if the weather record that was broken last week was set last year then we’re probably in the midst of a rapid change in climate.
Just to add to the records – the south west of W.A. had it’s driest July on record (normally the wettest month) which was preceded by the wettest June for some time (although it wasn’t a record). I suspect that the structure of the southern hemisphere climate system is starting to change. By that I mean the series of cells that convey heat from the tropics to the poles.
More pertinently, it worries me that climate scientists have spent so much time ensuring that their predictions are defensible that they may have minimized the risk of dramatic climate change.
In particular, I think that there are signs that severe impacts may be starting to occur in widespread animal and plant communities. It’s worth bearing in mind that living things that can’t migrate only need one year of adverse conditions to go extinct.
The real possibility exists that extinctions may cascade especially where ‘keystone’ species are affected.
It is also worth bearing in mind that (conspiracy theorists notwithstanding) we humans can’t migrate either.
Thanks to another poster here (I don’t think it was you) some time ago, I did some research on the data at your Bureau of Meteorology concerning the “south west of Australia.” I found plenty of contradictory information (especially with regards to variability, as I recall). I would be happy to re-hash when I have some time (privately or otherwise), if necessary. I can also find recent quotes from a Dr. Ian Smith of CSIRO claiming that climate changes in the south-western portion of Western Australia are “most likely due to long-term natural climate variations.”
Comment by Michael Jankowski — 1 Aug 2005 @ 10:22 AM
Would you be so kind as to comment on how such extreme value statistics illuminate a changing mean within cyclical systems, such as NAO or ENSO? Inferrences would seem much more difficult.
[Response:It depends on the length of the data series and time resolution. As long as the criterion that the data are independent, the iid-test can detect a climate change. A cyclical system sets a kind of ‘beat’ and in order to detect a change, the best is to sample at the frequency of the cycle. A cyclical system would furthermore produce autocorrelation structures, and the analysis -i referred to, it was shown that the autocorrelation was low. The NAO is not really very ‘cyclical’ (despite being called an ‘oscillation’ – it has proven very difficult to predict the NAO, and cycles are easy to forecast). In the former paper, we are also talking about the hottest day in a month in a region where ENSO has little impact. In the latter paper, the monthly mean scattered all over the world, most not affected by NAO. Temperature was subsampled once every 3 months, taking different months from adjacent stations. A visual plot showed when the record-event took place, and it was hence possible to show that the sub-sampling removed clustering in time. It’s really easy to tell whether you have a dependency – just plot the times of the record-events. -rasmus]
Your second graph shows an upward trend line. Another possibility is a somewhat horizontal trend line with a widening cone of readings. That would seem to allow for record lows as well as record highs in temperature, rainfall etc. Incidentally it is quite balmy here in southern mid-winter. The local farmers are convinced of a warming trend, so maybe we are all programmed to run tests using fuzzy criteria.
I would like to clarify your usage of the term stationary particularly as it relates to autocorrelation. The second graph you show is, to my mind, trend stationary. This is particularly so given your comment about low autocorrelation in response to the last comment (#5). Have there been any studies that investigate whether ‘global’ temperature (or similar climate indicator) is trend stationary rather than non-stationary? When I look at any of the graphs of global temperature I am struck by an impression of a very high degree of autocorrelation (indeed, tending towards I(1) behaviour) – particularly given the inflection around the turn of the century that seems inconsistent with a deterministic trend.
[Response:When there is a trend, then the distribution function (probability distribution function, pdf, or frequency distribution if you like) is changing. I use the word ‘stationary’ in the meaning of the pdf. By definition, a variable that does not have a constant pdf is non-iid. The test does not discriminate between a linear or a non-linear trend (I think it is this you refer to with ‘stationary trend’ and ‘non-stationary trend’). Many curves for the global mean have been filtered (introduces a higher autocorrelation), but if you use unfiltered data, remove the trend and look at month-to-month variations then you will see that the presistence becomes less important. When we use the iid-test in studying climate-change, then we want to exclude the dependency between successive values related to aspects not related to climate change (i.e. ENSO, NAO), but want to retain the part that explains long-term changes (trend). -rasmus]
I was somewhat put off when Roger Pielke said that here on the eastern front range in Colorado the week where we had +100 degree (fahrenheit) highs for 5 days in a row that the heat did not indicate anything unusual going on. Apparently this had occurred in the late 19th century according to some old temperature records, so we were within some kind of normal pattern — just a 100 year event, I guess. But we set some new temperature records that week and are continuing to set such records some days even now some a few weeks later.
Climate is the statistics of weather over time, I know. But since the probability of such anomalies is greater as time goes on, I expect people to say so instead of giving some reassuring message to the evening news that “It’s All Good”, nothing unusual going on here.
Climate scientists don’t want to get all entangled with day-to-day weather, I understand this. But, when is this backing off on relating the probability of extreme weather events to climate change going to stop?
[Response:Climate can be regarded as ‘weather statistics’, of which the occurrence of record-breaking events is naturally one subject. The longer the series of observations are, the lower the chance of seeing a new record-breaking event given the process is iid. Even so, they will still happen from time to time, and if there are ‘too many’ record-events, then this is improbable given an iid-process. You can have many parallel (contemporary) observations and the chance of seing at least one new record amongst a volume of observables may remain high even after some time. But it’s easy to calculate the probability of seeing a number of new records from binominal law if you know the true degrees of freedom. -rasmus]
[Response:Thanks for the link! It’s important to be cautious and aware of common mistakes. I do like the iid-test bacause of its simplicity: of a batch of N random rational numbers (eg ordered chronologically), the probability one particular (eg the most recent one) has the greatest value is 1/N. The nice thing about it is that you can test it with permutations or create synthetic data and test it (Monte-Carlo simulations). The iid-test makes no assumption about the distribution of the data – the only requirement is that there is no ties. -rasmus]
Rasmus, re your response to my comment #7. By trend stationary I mean this. Thus, I am distinguishing between a deterministic trend (which includes both linear and non-linear trends) and a stochastic trend. I take your research to be establishing the question of whether there is a trend. My question was directed to exploring the nature of that trend (which has profound implications for forecastability).
[Response:Thanks for the clarifications. I think you’re asking whether there might be some kind of ‘time structures’ (types of cycles, etc) present in addition to that of a global-warming trend. A good point! The answer is probably yes (inter-decadal variability, natural external forcings and so on). I’m not sure whether statistical trend models would be sufficient, and in order to examine the ‘residuals’ (the data after the trends have been removed), one really needs to use a fully-flegded climate model with all important forcings and feedback processes accounted for. If the residual is non-stationary, then this will also make the iid-test reject the null-hypothesis (it would be easy to test by applying the iid-test on the residuals). The iid-test does not attribute a behaviour to one specific forcing, but gives the probability of a variable representing independent and identically distributed data. A dependency may influence the test results and therefore must be eliminated (e.g. by sub-sampling) before we can say whether there is an undergoing change in the pdf. It reveals whether the upper tails of the pdf is being ‘stretched’. -rasmus]
Regarding the extreme value fallacy link (provided by Jo):
The awful website to which Jo links speaks informatively about the topic of records in general and then talks about the “myth” of global warming. Rather than asserting this, the author could provide some analysis with data. For example, with global warming, we might predict that record hot events will be more likely than record cold events. A simple sign test could determine if this is true and, since autocorrelations (both spatial and temporal) should act similarly on records at both extremes, I suspect it could be argued that statistical problems would cancel each other out once the test was adjusted for the correct degrees of freedom. More problematic are cases like precipitation and other processes where the prediction is an increase in records at both extremes. In such cases trends in measures for one extreme cannot be used as controls for the evaluation of trends in the other.
Back to the website, if one clicks FAQs at the bottom and goes to the page where the Greenhouse Effect is described one views a reasonable physical description followed by this ridiculous statement: “There are other potential greenhouse gases, such as carbon dioxide and methane, but their atmospheric concentrations are so low that they may be ignored (CO2 at 0.033% and CH4 at 0.0002%).” Better people than me can learn something about extreme events from someone who sees no significance in record-breaking concentrations of CO2. Perhaps CO2 records would be a useful teaching tool for demonstrating the analytical theory.
Let me see if I got it right:
(1) With GW we’re not sure of getting much change in overall global average precip, but when when it rains it pours … & floods, which also means on the flip side we would expect increasing periods of no precip (aka droughts), since the global average precip is not changing.
(2) The reason the changing climate in the second graph does not show more extreme events, is because they are only being compared to the nearby previous timeframe or the new mean (?), not the x=0 point on the graph, because the interest is in finding trends, not absolutes. Right?
(3) If 2 is correct, then from a layperson’s or farmer’s perspective, we might also be interested in absolute changes, comparing the x=10,000 time to the x=0 time, in which case ALL of the y values, say, between x=0 to x=2000 (even the low extremes) would be higher than ALL of the values closer to x=10,000, and all would be extreme in the comparison. And with many other indicators that GW was happening, incl causing the upward trend in extremes, then we might attribute in this absolute analysis all values to GW, or at least all values would have some GW component.
What about any logical HYPOTHESES/THEORIES re heavier precip events, greater dry periods, and same global average precip. Would it have to do with GW causing more water vapor to be held (hoarded) in the air, then when something triggers it, it just pours it out?
I understand scientists cannot attribute a single extreme event to GW; it may in God-only-knows reality be due to GW, but scientists don’t have the tools to make such a claim. The way I handle this (such as a dangerous hurricane) is to say, “We can only expect worse in the future with GW.” But I’d really like to say, “The most dangerous 5% of that hurricane’s intensity has been scientifically proven to be attributed to GW.” But I guess we can’t say that – at least for now. My thinking (perhaps wrong), is that in the future we may be able to come back to these current floods, droughts, hurricanes, etc and attribute portions of them to GW. I know that 1/2 the heat deaths in Europe in 2003 were attributed to GW.
And as I always mention, as a layperson, I don’t need scientific certainty to understand that the drought in Niger & mudslide in India are at least partly due to GW. I think at this point there may be a preponderance of evidence (which means it is more likely than not (more than 50% sure) that GW has a part in these single events). And my standard is even lower than that; “MIGHT be partly (the worst part) due to GW” is for me a clarion call to reduce GHGs.
[Response:Dear Lynn, the answer to (1) is that I have not done the analysis for historical observations. I have analysed several climate model results and find that under a GW regime we would expect to see more record-breaking events at mid- to high latitudes and actually fewer new records than one would expect for the sub-tropics and where there is large-scale subsidence. There are also indications of more record-breaking events in regions with convection (e.g. ITCZ). This study, though is only submitted. (2) There are more record-events (green asterisks) in the lower panel and it is the absolute value that matters. The definition of a record-breaking event is a value greater than any previously recorded (since the recor starts). There are physical reasons to believe that a GW can result in more havy precipitations: a surface warming results in a higher rate of evaporation. Again, this is what the (preliminary) model results suggest. – rasmus]
Comment by Lynn Vincentnathan — 2 Aug 2005 @ 12:56 PM
RE response in #12, what is subsidence? I think it means land sinking or settling. And what in GW is causing that? I think I live in a borderline area btw the mid-lat & subtropics, though people here refer to it as subtropical (my latitude is 26.2 N).
[Response:In this context it means the downward branch of the atmospheric Hadley circulation which exists in the sub-tropics to balance the upward mass flux that occurs near the equator. -gavin]
Comment by Lynn Vincentnathan — 2 Aug 2005 @ 4:14 PM
Re#12-“I know that 1/2 the heat deaths in Europe in 2003 were attributed to GW.”
Who did this?!?!? And does this person (or group of people) also attribute lives saved in European winters to GW? I’ve shown before that the typical European winter gets far more weather-attributed deaths than the extreme heat wave of 2003, so it only stands to reason that GW is saving far more lives in Europe than it is taking, right?
“And as I always mention, as a layperson, I don’t need scientific certainty to understand that the drought in Niger & mudslide in India are at least partly due to GW.”
FWIW, the mean rainfall for Indian in June-Sept (which includes the monsoon season) from 1871-1995 is 85cm…the same as it is from 1871-1950 and 1950-1995 http://tao.atmos.washington.edu/data_sets/india/parthasarathy.html . I went ahead and looked at 1995-2000 at the KNMI Climate Explorer link…range was 79 cm to 87 cm with a mean of 84 cm.
Neither 20th century warming overall nor the warming of recent decades seem to show an effect on India’s rainfall, either taken annually, seasonally, or monthly. But you can dismiss 130 yrs of rainfall data and cry “GW” due to ONE DAY of rain?
Comment by Michael Jankowski — 2 Aug 2005 @ 4:31 PM
As for the typhoon record mentioned in the contribution above…there were 29 Pacific typhoons, just 2 above the annual mean. It’s hard for me to consider one year’s worth of unusual typhoon landfalls in one nation to represent a significant phenomenon. In fact, one might consider a highly increasing landfall count during a roughly average typhoon year overall to indicate less chaotic weather patterns at play. To me, this would contradict the idea of “more extreme, less predictable” climatic events.
[Response:True, the count of one year may not represent a significant scientific evidence (despite otherwise severe consequences for those hit by them), and it is the pattern of occurrences over time that will tell use whether there are strange things going on. If there is a trend that continues with increasingly higher typhoon landfalls over Japan, even if there is a near-constant total number of Typhoons over the Pacific, this would have significance on many levels. This would suggest a systematic change in the storm tracks. Having said that, the record-number of landfalls was ‘only’ 10 and the previous was six, which suggests that either the length of the (official) observations is very short or there so far has not been many record-breaking events. I haven’t dug up the data concerning the landfalls in Japan (many of the Japanese websites are in Japanese, a language that I do not master), so I have not had the chance to make a more thorough analysis on this. -rasmus]
Comment by Michael Jankowski — 2 Aug 2005 @ 4:41 PM
Re #14 Re #12″I know that 1/2 the heat deaths in Europe in 2003 were attributed to GW.”
Who did this?!?!? And does this person (or group of people) also attribute lives saved in European winters to GW? I’ve shown before that the typical European winter gets far more weather-attributed deaths than the extreme heat wave of 2003, so it only stands to reason that GW is saving far more lives in Europe than it is taking, right?
Using a threshold for mean summer temperature that was exceeded in 2003, but in no other year since the start of the instrumental record in 1851, we estimate it is very likely (confidence level >90%) that human influence has at least doubled the risk of a heatwave exceeding this threshold magnitude.
Michael didn’t you quote some figures for low deaths in Scandinavia from cold? Doesn’t this show that people are prepared for what they expect? Isn’t it the case that if GW throws some unusual weather, that is what causes deaths?
Regarding the comment about the driest July in south west Western Australia: the previous record dry July was about 100 years ago; we had already had the Jan 1 – July 31 average rainfall by the first week of the month; the local Bureau of Met person stated that August and September have been getting wetter.
I put it all down to my driving a large V8 from Perth to Bridgetown on a regular basis.
A retiring meteorologist once remarked that a month without a new record would be a record!
[Response:True with some moderations: depending on how long the observational series are and how many independent parallel observations you make, there is an expected number of record-events according to the iid-test. Numbers consistently significantly lower or higher point to a non-iid process. Furthermore, as the length of the observational series become longer, the probability of seeing new record-events diminishes and the expected number of records gradually declines. -rasmus]
Without suggesting that the studies at the centre of this posting are at fault – there is a tendency to generate new ‘records’ with alarming regularity.
It almost seems to be a product of the human condition – we are always looking for something exceptional in recent events and, if you look hard enough, you can find it. You have to work very explicitly to overcome that inherent bias.
I particularly like sporting records – “that was the highest fourth wicket partnership between left- and right-handed batsmen on the second day of a test a Lords between Australia and England” – almost as good as “the driest July in south-west Western Australia”
[Response:You are right, and that was the original motivation of my research into this – I recalled frequent headlines with new record-breakingevents and wondered if this was normal. Now, I know that the iid-test can give some indication about what we would expect if the variable we observe is statistically stationary. -rasmus]
Re #15: The expectation is not for more frequency, but for more strength. The total number of typhoons might actually go up a bit because of the promotion of some tropical storms to typhoons, but of course the distinction between these classes of cyclone is arbitrary. The important issue is the total energy involved. Regarding your last point, I’m not aware of any evidence for such an effect as regards North Atlantic cyclones.
[Response:Thanks! I think we will soon have a new post dealing with this. Stay tuned… -rasmus]
A recent study done by the Australian Bureau of Meteorology (don’t have the link handy, but can post it later if people are interested) showed that Australian high temperature records were being broken at above the rate one would statistically expect for stable temperature, while low temperature records were being broken at below the rate one would expect.
Highly consistent with warming temperatures. The authors themselves said it would be more interesting to look at monthly records rather than daily ones, and they were planning to do this next. Precipitation is much more difficult, and I am not sure if they had plans to move on that. I don’t think the paper was published in a peer reviewed journal, but it was presented at a large conference of meteorologists, so if there were any flaws one would expect it to have been picked to pieces.
That’s precisely why I was jabbering on about the pseudo-control of record low temperatures in #11. As we are now putting more measures into databases and have much greater ability to search for and identify new records, we may need to control for this so that new records say more about weather/climate than they do about our abilities.
On the other hand, if you think of some measure for which there should be a reliable long-term database, this problem should disappear (as suggested in the original contribution). Take your example of moisture in July in south-west Western Australia. Let’s say that this year’s dry July is noticed by someone interested in the statistical method described. He/She can then look at the history of records for dryness in July in Western Australia. Contrast these two differing possibilities:
(i) Immediately after the first measure was taken, a high frequency of records in both dry and wet July conditions gradually gives way to a lower frequency of record dry or wet July conditions that could be expected due to the increasing number of years in the comparison until 2005 which was a dry record.
(ii) The same as (i) except that over the past two decades (1984-2004, say) the rate of record-setting for July conditions is higher than for the two decades prior to that (as opposed to the expectation that records should be harder to attain).
These two scenarios should be informative of a climate change, and very little explicit effort is required to overcome any inherent bias. The only requirement is that all such investigations are recorded [e.g., no publication bias toward scenario (i) or (ii)] so that meta-analyses or corrections for multiple tests [e.g., sequential Bonferroni] are not confounded.
I have a harder time explaining to myself how this would work spatially rather than temporally. In that case, and in the temporal case for that matter, I would think that somehow looking at trends in variance (continuous data) would be more powerful than converting data into rank form or nominal form (“record” or “non-record”). Perhaps Rasmus could explain. Is it because of the more intuitive appeal of results that you have chosen this method?
[Response:I think the analysis probably works best in the temporal case. It is not clear how we could apply this test in a spatial dimension, since we do not expect tempertures to be iid with respect to geographic location. The spatial aspect comes in by aggregating parallel series form different locations. This has to be done with care, since opposite trends in different series will appear consistent with the null-hypothesis. The iid-test is an alternative to trends in variance. -rasmus]
People adapt (or it is genetically predisposed) to average climate/temperatures in their own neighbourhood. A study in Europe by Keatinge ea. (confirmed by a similar one in the USA) found that mortality is lowest in a small (3 degr.C) band, which is 14.3-17.3 degr.C for north Finland, but 22.7-25.7 degr.C for Athens. Above these temperature bands, mortality increases, but below this band, mortality increases much faster: there are some factor 10 more cold related deaths than heat related deaths.
Thus an increase of average temperature, due to global warming (which has most effect in winter), will reduce average mortality, not increase it…
Re #16. Chris, there was also ‘Hot news from summer 2003′ by Christoph Schar & Gerd Jendritzky, Nature, 2 December 2004. It included a startling graph of mortaility rates in one region of Germany that year. The spike during the heatwave is stark and obvious.
Re#16: Yes, I believe I did report low numbers for at leat one nation in Scandinavia (if not the region as a whole). However, the numbers I presented for annual deaths attributed to cold weather for England and Wales combined regularly approach those attributed Europe-wide for the 2003 summer heat wave. I believe I provided a figure someone had come up with which correlated the number of additional deaths to be expected for a one degree drop in avg winter temps, and it stands to reason one could easily reverse that and determine how many lives were saved annually thanks to warmer temps.
Thank you for the link to the article. The question I have with it is that I understand that much of the 2003 heat wave resulted from very unusual pressure system activities. I am not certain whether the Hadley Centre model they used accounts for this. I would like to see their model results of “natural forcing” coupled with these pressure patters. One could, of course, argue that these anomolous pressure patterns were the result of human activities, but that would be another paper, I guess!
Re#21:”Highly consistent with warming temperatures.”
I don’t think anyone disputes that temperatures have warmed since “record keeping” began.
Comment by Michael Jankowski — 3 Aug 2005 @ 8:55 AM
Above link more proof that cloud dynamics have ELECTRICAL forcing… [edited]
[Response:Please try to stay at least vaguely on topic – William]
The period over which figures are looked at is obviously important. The maximum temperature on August 3 at one particular place is going to be far more variable than the average maximum August temperatures etc. But as periods get larger they don’t just become statistically more uniform – consider what happens when a period starts to encompass a seasonal change.
Record high temperatures might be an occurrence before the monsoon, but once it’s started the only records likely to be broken are rainfall. Temperature under cloud cover doesn’t vary greatly. So a period (of three months say)that includes the monsoon will show average temperatures that are dampened by the presence of the monsoon and I think I’m correct in guessing that this would show up as an anomaly within your iid null hypothesis. Of course, the timing of the monsoon may also change!
What I’m trying to get at is that although the problem with records is clearly the arbitrarily large number of degrees of freedom that they invoke. These degrees of freedom can be meaningfully reduced and as that happens information (about events local in time and space) will disappear. The records of annual average global temperature represent the extreme but also carry weight because all other local information has been lost.
Monthly averages to me make the most sense from a time point of view because they are too short for seasonal effects and long enough to reduce noise.
As far as rainfall is concerned – one way of creating a figure similar to temperature(with minima and maxima) is to do what was done by hand in 1948 for most Australian rainfall stations. A meteoroligist(whose name escapses me) calculated the monthly average for all the records then took the difference between the first month actual rain and the average as the first point in a time series. The second point was the same difference for the next month added or subtracted from the previous month.And so on.
He then had a graph of the cumulative deficit or surplus above(or below) the monthly average. This clearly highlighted dry and wet spells extending beyond single seasons. In naturally dry months the graph stays below if there is a preceding rainfall deficit. this enabled one to get a clear view of the length of dry periods.
In a rough analysis of the above data I was able to identify that most short term droughts in coastal Australia were 15 months in length. The inadequacy of relying upon 12 month intervals for rainfall records is clearly problematic.
Interestingly I was able to identify 4 distinct droughts of 7 years duration although this was nowhere near statistically significant given the limit of the records (most stations had between 50 and 100 years of records). The east coast drought in Australia is currently in it’s seventh year.
THe comments regarding the narrow range of temperatures and the importance of habituation influencing European weather related deaths highlights the point I was trying to make regarding the unknown potential for climate change to cause a cascading affect upon biological systems including our own.
[Response:The iid-test ought to be applied to say one fixed day of the year, e.g. for July-01 of each year. Then influences from say a Monsoon will constitute as random noise, unless the Monsoon itself changes systematically. The iid-test becomes more powerful if you apply it to a series of parallel independent series, e.g. January 1st, January 6th, January 11th, and so on. The reason for not using every day, is to reduce the influence of dependencies (day-to-day correlations). -rasmus]
What I’d like to know is what would be the likelihood (best guesstimate), say, of the Venezuela deluge and mudslide of 1999 being partly due to GW. I understand that such events may have happened over 100 years ago, but they would have not been due to AGW in that era, because it wasn’t happening then. Now that we are pretty sure AGW is happening, it might be reasonable to at least suspect that AGW might be partly involved in extreme weather events that are predicted to increase, according to the models, even if scientists cannot prove it for individual events beyond a reasonable doubt. So which might be the best guesstimate for the 1999 Venezuela deluge?
A. AGW most assuredly played at least a small part in the Venezuela deluge (>90% sure).
B. It is somewhat sure (but not certain) or more likely than not that AGW played at least a small part in the Venezuela deluge (>50% sure).
C. It is possible that AGW played at least a small part in the Venezuela deluge, but we cannot be sure (> 0%, but <50% sure).
D. It is impossible that AGW played any part in the deluge (e.g., because … that isn’t even predicted for that area in the models… or ??)
Maybe in the future science will advance to the point (beyond our wildest imaginations) that it can give a more accurate assessment of AGW’s role (or lack thereof) in the 1999 Venezuela deluge. And just think because of AGW (as with war) our science would have advanced so much.
RE #14, I have no problem crying “GW.” I’m not a scientist trying to protect my reputation, but a person concerned about others. In fact I have been crying GW for 15 years & attributing all sorts of harms to AGW (as predicted by climate scientists & their models to happen or increase over time). I say, “Well, that unusual flood looks like it might be due to GW” (and my husband tells me to shut up, though he believes me), and I haven’t seen a dangerous stampede to reduce GHGs yet. People just think I’m crazy. But even if I’m wrong and miraculously people do respond by reducing GHGs, they will save money & help the economy & solve other problems; but if the contrarians are wrong and they persuade people not to reduce GHGs (which seems to me what is happening), then we (at least our progeny & other creatures) will have hell to pay.
Comment by Lynn Vincentnathan — 3 Aug 2005 @ 12:50 PM
Lynn, re #27:
Rainfall in Latin America is heavily tied to the Southern Oscillation (El Nino – La Nina) conditions. These show a large(r) variation in recent decades, which may – or not – be tied to (A)GW. Most models are much too coarse to predict trends on regional scale (and certainly can’t predict extreme events), thus there is no clear answer to your question.
(A)GW can not be excluded, the possibility that it is indirectly involved can not be excluded either. Thus the nearest scientific answer to your question is C.
Btw, you are not crazy by reducing your own use of fossil fuels. Even if CO2 is not a big problem, it will reduce pollutants and our dependence of not so stable countries. But for a lot of energy-dependent industries, there is little way to reduce energy use, as most measures were taken a long time ago (after the first oil crisis), and alternatives (still) are too expensive…
Caracus 1999 was due to dam changes in the region, again, impacting the conductivity of the regions oceans and its ability tho support a surface low sustaining its electrical conductivity over time despite roiling and depressurization depleting ocean carbination. The Bates et al research (Nature) on Hurricane Felix indicates that it takes about 2 weeks for the oceans to ‘recharge’ after a storm. Obviously, if there is more CO2 from human activity, the time it takes to ‘recharge’ is reduced and the equillibrium partial pressure would be greater, allowing for more gas to the surface to run back to ion form and increase conductivity. But IMHO in following the dam constructions and flow and sedimentation delays, it was pretty clear that for several years the Carribean was impacted by the changes to the Orinoco from huge hydroelectric projects in the region.
“In fact I have been crying GW for 15 years & attributing all sorts of harms to AGW (as predicted by climate scientists & their models to happen or increase over time).”
I commend you on your energy and water-conservation methods (although I wonder if not watering your lawn reduces the carbon sink in your yard by restricting growth and whether that should take priority over water conservation). But as for the predictions and models…
We can look a full century into the future of the US climate using some top-flight climate models http://www.usgcrp.gov/usgcrp/Library/nationalassessment/overviewlooking.htm from 2000. There are two models used for this report – the Canadian Centre model and the Hadley Centre model. What do they predict? Warming, of course! Note that the Canadian model projects more warming and that the two conflict with regard to winter warming (Canadian shows max warming in the midwest while Hadley model shows min warming there). Ok, fine…let’s move to precipitation. They agree on increased precipitation in Cali and Nevada – with the specific note that “some other models do not simulate these increases.” So even their agreement here may conflict with the results of other models. The Candadian model projects decreases in precipitation across the eastern half of the US while the Hadley model projects increases. Hmmm…so which is it that climate scientists and their models predict for the eastern half of the US? If these areas are turned into virtual swamps in 100 yrs, will someone be able to say that it was predicted to happen due to AGW? Or what if they instead become virtual deserts – can the same claim be made? Last but not least, we have the combination of rainfall and temperature to produce soil moisture changes in the models. The level of disagreement between the models is quite amazing, isn’t it? So which is it that the climate scientists and their models predict for, say, Oklahoma City? The northwest corner of California? South-Central Texas? The Rust Belt? I think the models have strongly conflicting predictions over a greater area than which they somewhat agree. So what exactly can the climate scientists and their models predict?
Comment by Michael Jankowski — 3 Aug 2005 @ 2:48 PM
The latest onslaught of heat and precipitation records really get very little attention by world press unless someone dies or gets seriously injured. There has been, in my opinion, a trend, not really appreciated by most, which is stable extreme weather, one can name many zones of the world having some extreme fascet of continous drought, rain, heat and mostly changes in dominant wind directions for extended periods of time, which is in itself unusual. I suggest the slowing of Hadley cell circulation caused by weaker differential temperatures between major air masses, this will cause all the phenomenas cited. It is known that there is a pronounced difference in Hadley cell circulation between winter and summer, heat spreading more evenly would mean greater water vapor density, exacerbating AGW effects a great deal more. It would be nice to see if there is active Hadley cell models on the web, in the meantime observing what Hadley, Ferrel and Polar cells are doing must be done through met models, with a particular eye on the meandering jet streams…
I would have thought that there would have been many studies of just this question. Why haven’t there been: is it lack of long term data, or is the work not sexy enough?
Given the data that exists do we have any idea how long it would take to get a reasonable confidence level that extreme events are or are not increasing? Do we have enough data to do the analysis? To be convincing, many locations would nave to be analyzed.
“Caracus 1999 was due to dam changes in the region, again, impacting the conductivity of the regions oceans and its ability tho support a surface low sustaining its electrical conductivity over time despite roiling and depressurization depleting ocean carbonation.”
and “But IMHO in following the dam constructions and flow and sediment delays, it was pretty clear that for several years the Carribean was impacted by the changes to the Orinoco from huge hydroelectric projects in the region.”
I would be interested in some detailed citations supporting these assertions, since they don’t seem very likely to me, for the following reasons:
1) My impression is that it is pretty well established that El Nin~os cause low rainfall in Venezuela and La Nin~as cause heavy rainfall there.
2) The Guri project on the Caroni is one of the world’s largest, but the reservoir started filling in the late 60’s or early 70’s and the project was fully operational in 1978, 21 years before the 1999 floods and mudslides. The Macagua dam is a run of the river project near the confluence of the Caroni and the Orinoco. Carauchi, between Macagua and Guri is partly operational. The two reservoirs below Guri will not have much impact on flow and sediment. What sediment there is is being trapped in the Guri reservoir — and has been for about 25 years. More dams are planned on the Caroni, both above and below Guri and will equally have little incremental impact on sediment entering the Orinoco and less impact on sediment entering the North Atlantic, because …
3) The Caroni and the other right-bank tributaries of the Orinoco are blackwater rivers with a load of dissolved organic carbon (tinting them), but very little suspended material or electrolytes. Almost all of the sediment load in the Orinoco is dumped in the river by the left-bank tributaries, most prominently the Apure, which arise in the Andes and the northern mountains of Venezuela and drain the huge Venezuelan llanos. There has been little or no dam-building on those rivers and no significant reduction their sediment load or in the overall Orinoco sediment and electrolyte load. See (in English) and .
4) From experience of living in Venezuela in the mid-60s and many visits to Caracas, I will assert that the slopes of the Pico Avila chain between the Valley of Caracas and the Caribbean were on their way to being a mudslide waiting to happen, with settlement moving up the slopes and deforestation.
5) I find nothing in the cited Bates et al. paper to support the idea that formation and sustenance of low pressure systems over the ocean depends on electrical conductivity. Do you have some sources for that belief?
(one of the papers has not been placed there as a pdf file, but it will hopefully be available within a few days).
I have also submitted an R-package called iid.test to CRAN: http://cran.r-project.org under contributed packages. It’s not yet posted there, but should hopefully be available soon for people who want to play around with it.
RE #32, you’re right about not watering & letting the grass die back, thus not allowing it to be a carbon sink (though its unclear if there is a net reduction in GHGs if you water your lawn).
However, there’s a solution. Greywater. That is, rigging your bath & washing machine water to be used for your garden (which also saves on your water bill). Water from the kitchen sink is referred to as black water (because it’s a bit dirtier). So you can have a picture perfect garden AND reduce your water bill & water depletion & GW all at once. Who said you can’t have your cake and eat it too?
Comment by Lynn Vincentnathan — 4 Aug 2005 @ 1:08 PM
RE #30, I think you may be wrong re industries not being able to reduce GHGs much. Amory Lovins is continually helping industries to reduce substantially their GHGs in cost-effective/money saving ways (& finding examples of such). He cites an fairly recent example of a business cutting its energy (used for production) by 90% by what he refers to as “tunnelling through.” I would guesstimate that industries on the whole could cut their GHGs cost-effectively by at least 1/4 or 1/3. They just need to seriously put their mind to it, or call in experts.
Comment by Lynn Vincentnathan — 4 Aug 2005 @ 1:18 PM
Re Comment #36
I managed to confuse the software that manages the process of posting comments by citing in the last sentence of paragraph 3 of my Comment #36 a couple of URL, enclosed in angle brackets. The software tried to understand them as one of the small collection of HTML commands it understands, failed to do so, and discarded the offending text. The truncated sentence should read:
Robin McKie reports from Svalbard where scientists have been sunbathing in record temperatures of almost 20C
Sunday July 17, 2005
These are unusual times for Ny-Alesund, the world’s most northerly community. Perched high above the Arctic Circle, on Svalbard, normally a place gripped by shrieking winds and blizzards, it was caught in a heatwave a few days ago.
Temperatures soared to the highest ever recorded here, an extraordinary 19.6C, a full degree-and-a-half above the previous record. Researchers lolled in T-shirts and soaked up the sun: a high life in the high Arctic.
It was an extraordinary vision, for this huddle of multi-coloured wooden huts – a community of different Arctic stations run by various countries and perched at the edge of a remote, glacier-rimmed fjord – is only 600 miles from the North Pole.
That they could bask in the sun merely confirms what these scientists have long suspected: that Earth’s high latitudes are warming dangerously thanks to man-made climate change, with temperatures rising at twice the global average. Clearly, Ny-Alesund has much to tell us.
For a start, this bleakly beautiful landscape is changing. Twenty years ago, giant icy fingers of glaciers spread across its fjords, including the Kungsfjorden where Ny-Alesund is perched.
‘When I first came here, 20 years ago, the Kronebreen and Kongsvegen glaciers swept round either side of the Colletthogda peak at the end of the fjord,’ said Nick Cox, who runs the UK’s Arctic Research Station, one of several different national outposts at Ny-Alesund.
‘Today they have retreated so far the peak will soon become completely isolated from ice. Similarly, the Blomstrand peninsula opposite us is now an island. Not long ago a glacier used to link it with coastline.’
You get a measure of these changes from the old pictures in Ny-Alesund’s tiny museum, dedicated to the miners who first created this little community and dug in blizzards, winters of total darkness and bitter cold until 1962, when explosions wrecked the mine, killing 22 people. The landscape then was filled with bloated glaciers. Today they look stunted and puny.
This does not mean all its glaciers are losing ice, of course. Sometimes it builds up at their summits but is lost at their snouts, and this can be can misleading, as the climate sceptics claim. Recent research at Ny-Alesund indicates this idea is simply wrong, however.
Gareth Rees and Neil Arnold of Cambridge University are using a laser measuring instrument called Lidar, flown on a Dornier 228 aircraft, to measure in pinpoint detail the topography of glaciers. An early survey of the Midre-Lovenbreen glacier at Ny-Alesund ‘shows there has been considerable loss of [the] glacier’s ice mass in recent years,’ said Arnold.
‘Natural climatic changes are no doubt involved, but there is no doubt in my mind that man-made changes have also played a major role.’
This turns out to be an almost universal refrain of scientists working here. They know the behaviour of these great blue rivers of ice can tell us much about the health of our planet. As a result, droves of young UK researchers, armed with water gauges, GPS satellite positioning receivers and rifles (to ward off predatory polar bears) head off from Ny-Alesund to study the local glaciers and gauge how man-made global warming affects them.
It is exhausting work that requires lengthy periods of immersion in glacier melt-water. The outcome of these labours is clear, however. ‘Glaciers are shrinking all over Svalbard,’ said Tristram Irvine-Fynn of Sheffield University. ‘Ice loss is about 4.5 cubic kilometres of ice a year.’
The Arctic is melting, in other words. And soon the rest of the world will be affected, as Phil Porter of the University of Hertfordshire, another UK researcher on field studies in Ny-Alesund, points out: ‘I have studied glaciers across the world, for example in the Himalayas, and we are seeing the same thing there. The consequences for that region are more serious, however. Rivers rise and wash away farming land.’
Humanity clearly needs to take careful notice to what is happening to the beautiful desolate area. ‘This place is important because it is so near the pole, far closer than most Antarctic bases are to the South Pole,’ said Trud Sveno, head of the Norwegian Polar Institute here.
‘We have found that not only are glaciers retreating dramatically, but the extent of the pack ice that used to stretch across the sea from here to the pole is receding. It is now at an absolute minimum since records began.’
Nor is it hard to pinpoint the culprit. On Mount Zeppelin, which overlooks Ny-Alesund, Swedish and Norwegian researchers have built one of the most sensitive air-monitoring laboratories in the world, part of a network of stations that constantly test our atmosphere.
Instruments in the little station – reached by an antiquated two-person cable car that can swing alarmingly in the whistling, polar wind – suck in air and measure their levels of carbon dioxide, methane, other pollutants and gases. It is a set-up of stunning sensitivity. Light up a cigarette at the mountain’s base and the station’s instruments will detect your exhalations, it is claimed.
Carbon dioxide, produced by cars and factories across the globe, is the real interest here, however. Over the past 15 years, not only have levels continued to rise from around 350 to 380 parts per million (ppm), but this rise is now accelerating.
In 1990 this key cause of global warming was rising at a rate of 1 ppm; by 1998 it was increasing by 2ppm; and by 2003 instruments at Mount Zeppelin showed it was growing by 3ppm. ‘Never before has carbon dioxide increased at the rate it does now,’ adds Sveno.
Such research reveals the importance of Svalbard to Europe and the rest of the world, and explains why there is a constant pilgrimage of hydrologists, ornithologists, marine biologists, glaciologists, plant experts and other researchers to the station. The work is hard, although life here has improved a lot since coal was mined at Ny-Alesund.
Buildings are warm and snug, radios and GPS receivers ensure safety in bad weather, and fresh food is shipped in weekly. The base is also kept under careful ecological control. Barnacle geese and their goslings, fiercely territorial Arctic terns, reindeer and Arctic foxes are allowed to wander between the station’s huts.
Apart from the ferocious, unpredictable weather, it is all quite idyllic and very different from Ny-Alesund’s former days. Miners had none of this, nor did the great Norwegian explorer Roald Amundsen.
After beating Scott to the South Pole, Amundsen used Ny-Alesund as his base for his next great triumph, setting sail by zeppelin to cross the North Pole to Alaska in 1926. The mooring gantry for his ship still towers over the settlement as well as a statue dedicated to the great man.
Teams of young researchers now march past these monuments every day, heading out to work on the Arctic landscape he helped to open up and which is now sending humanity a grim warning about our planet.
I don’t imagine the proxies have the temperature sensitivity nor the data accuracy required to do such an analysis with a good degree of confidence. I think you’d have a lot of missed records and false records due to the wide range of error.
[Response:Missing record can lead to an under-count, but not over-count. The iid-test can be run in chronological and reversed chronlogical order and if the former leads to an over-count while the latter an under-count, then the process appearss inconsistent with being iid and there is not a strong effect from missing data, if there were any. Often, we would choose only high-quality series with no missing holes. About noise, as long as these are random and do not undergo a systematic change – i.e. they are also iid, then this does not affect the analysis given a large number of data. It is possible to use mny parallel series to increase the sample size and hence effects from errors will tend to cancel. You can of course test these in numerical execrises with syntetic data. -rasmus]
Comment by Michael Jankowski — 5 Aug 2005 @ 1:24 PM
RE#44 “I don’t imagine the proxies have the temperature sensitivity nor the data accuracy required (Snip)… I think you’d have a lot of missed records and false records due to the wide range of error.”
In my opinion, if this this matters to the final conclusions, it will be exposed by legitimate scientists in the scientific arena in legitimate scientific journals over time. Even the global warming skeptic Richard Lindzen gets published in Geophysical Letters(although his evidence does not stand up). He and others would have a field day if there were holes in this conclusion.
The non-parametric iid test described here is very simple, which is what gives it a lot of its power (although not statistical ‘power’). However, that simplicity means you need to apply a lot of care to the interpretation.
For example, I would be surprised if this test did not find that the ring widths from practically any tree were not iid. Aha! Some people might exclaim – proof of global warming. No, proof that trees grow at different rates during their life. Or, proof that rainfall varied over the life of the tree. Or, proof that CO2 concentrations have changed over the life of the tree. A simple test like this can’t discriminate between all the possible reasons for a change in the distribution of tree-ring widths. Thus, this test will not provide useful results if applied to those sorts of proxies – its just not well designed for the task. It will be useful for examining series that you have a priori reasons for expecting that they will be constant (or in which change is significant of itself). But if you expect that whatever you are examining will have reasons for changing over time that are ‘mundane’ then a positive result from this test will not illuminate you any further.
[Response:You’re correct in that the test is simple and only answers the question of whether the data is likyly to be iid. Thus, it is very important to have a physical insight and compliment with further tests. It does not do the attribution-bit and does not say why data would by non-iid. We can merely say that non-iid is consitent with a climate change in this exercise. -rasmus]
The record highs seem, by eye, to cluster around post-midcentury years, while the record lows around the pre-midcentury years. Does this mean that these statistics are a clear manifestation of the warming trend which has been observed:
and which was illustrated in Table 2 Fig 1? In other words, can I confidently quote these record statistics as being the result of a warming climate?
“The results for such a test on monthly absolute minimum/maximum temperatures in the Nordic countries and monthly mean temperatures worldwide are inconsistent with what we would see under a stable climate.”
Can you weigh in on this or direct me to an appropriate site? I’m looking for some predictions of how the climate will actually change (assuming GW occurring and no major effort made to stop it). Not looking for a denier site or for a worst case site. Just a reasonable best guess. In particular, am interested in broad changes (who gets warmer, colder) over the globe. Am also interested in particular in Virginia. Any chances of palm trees or aligators in my life time?
How good are extreme meteorological events to falsify the greenhouse theory?
The short answer: Very bad. There are too few extreme events to make the statistical testing and estimation to work efficiently.
The long answer: Study the theory of extremes and statistical test theory.
It is fascinating and frightening to observe extreme weather phenomena. From a statistical point of view a lot of information is lost by looking only on extreme events and the statistical test will not be very strong i.e. the probability to reject a false null hypothesis will be small.
If you look at the graph of the average temperature in Denmark from 1873 to 2003, i.e.130 years
and count the number of records, you will find 8 records over 130 years of observations. If one accept the hypothesis of iid temperature measurements one will expect 5.5 records and the probability of observing 8 or more records equals 15%. This is not significant in the statistical sense. Observing 11 or more records would have been significant on a 0.1% level of significance.
Even if it is obvious that the temperature has increased systematically, this can not be verified in this case by testing on the number of records.
Using the number of records is not a good way of testing the existence of global warming. I am afraid of, that this example and other similar examples might be used by the skeptical to prove that no global warming has taken place.
I am very pleased that RealClimate has take “record-breaking events” up for discussion. However, please be carefull not to put to much weight on extreme events in the discussion on global warming and climate change even if extreme events may cause a lot of harm to many people world wide.
I think that we should not be afraid of discussing difficult matters. Extremes is a wide and very complicated topic, and I do agree in general that extremes are not suitable for testing whether there is a climate change. However, the iid-test tests just that: whether the data conform to being independent and identically distributed. It’s very simple, but can also be very powerful. You can test it on other data, and I have been surprised about it being so unversial. But results from the iid-test is certainly not the reason for why we think there is an ongoing climate change: it’s to my mind firstly our physical understanding and secondly the multitude of empirical evidence. When it comes to skeptics, I don’t think we should let them decide what we discuss just because we worry of how they may twist and spin the issue.
Comment by Klaus Flemloese, Denmark — 7 Aug 2005 @ 4:17 PM
I’m just curious about what happened to the Muscheler guest topic posting and threads that were here on the site until yesterday. Was there a system crash?
[Response: Was accidentally deleted due to a technical glitch. We’ve restored it now, though some comments were lost. Our apologies to our readers! ]
Comment by Armand MacMurray — 7 Aug 2005 @ 4:43 PM
Answer me or send me to a good GW site. palm trees and alligators in VA? How long? I’m not talking Florida. Something like Cape Hatteras.
Please don’t ban me. I already got kicked off (and comments deleted) from the climate auditor site. And I wasn’t misbehaving. If anything I was more on their side than yours, but I just wanted to dig a little into the methodology (well wanted them to do a first cut reanalysis…not of your work…but starting from scratch). Even if they are right and you are wrong, it seems a little wierd how much time they spend on someone else’s work. you would think with all the effort exerted, they would get interested and start doing original work.
Anyhow…if you ban me too, I will feel really bad. How about puitting a word in for me instead with your colleagues over there?
And I’m not really a troll. Well…actually I have an AWFUL tendancy to troll. But I thought I didn’t really do any…yet.
There may have been a few record warm days this year on Svalbard, but one need to check the facts, before believing the jumping to conclusions of the journalist…
Glaciers on Svalbard are shrinking, but that is already (at least) since the 1920’s. Yearly average temperatures up to 2004 are app. 0.5 Â°C lower in the last decades than in the period 1930-1960 (be it that there is a non-overlapping switch in stations), but summer temperatures are app. 0.5 Â°C higher than periods in the 1920-1930’s. See the temperature trends of the Svalbard stations.
Thus Svalbard is not “dangerously warming” and the link with man-made greenhouse gases is not evident, as these should have their highest influence in winter, not in summer…
Basically, both models say Virginia will be warmer thru 2100, albeit by differing amounts. The Canadian model suggests a drop in precipitation of about 10% and a drop in summer soil moisture content of 25-50%. The Hadley Centre mode suggests an increase in precipitation of about 30-40% and an increase in summer soil moisture content of up to 25%.
It looks like the gators will have to wait-out and see which model gets the closest.
Comment by Michael Jankowski — 8 Aug 2005 @ 12:53 PM
A story on climate change and its potentially disastrous effects on butterfly species:
The discussion of record weather events and climate change is very interesting and considering the press these events get is very informative.
I am learning more about climate change science and trying to keep up with recent developments. The toughest part is the mathematical/statistical part of the science so the discussion of statistics in this post is very helpful. I did well in the statistics courses when I was an undergraduate but I retained very little of what I learned. I thought those classes were boring. I wished I had taken them more seriously, but since I did not I hope to see more mathematical/statistical explanations on RealClimate!
It is also good to see RealClimate cover topics that could be controversial and twisted by contrarians. I fully agree with the response to #51 about not avoiding discussions of some scientific topics and letting skeptics decide what the discussion should be.
Comment by Joseph O'Sullivan — 8 Aug 2005 @ 8:05 PM
I’m fascinated by the gators. I’ve done some reading on them and googled as much as I can. The very far extent of their northern range is in the north edge of the albemarle sound almost to the VA border). However, I’ve read some other stuff that says that they are only up to SC. And then, other stuff that says that they were only in northern NC in last century. one other site says that they had a historical range up to NJ! But I can’t get any confirmation of that. It seems that they have mostly recovered their natural range (from endangered to millions of them). But I still wonder if there is any chance that they have a natural range up to VA and will come on up to the dismal swamp. There have been a few critters killed in VA recently (Richmond and Chesapeake). but hypothesis is that they were released and would not survive a winter. Wonder how many average degrees warmer a winter would be needed to let gators live in the Dismal Swamp (VA side of the line).
56: I looked at that site now. The good part is the most increase in temp will be nighttime winter lows. That might be enough to swing things into gatorland. I figure if we split the difference on the two, precip will be same. And the Dismal Swamp is pretty damp regardless.
Stephen Luntz (comment #21) appears to be referring to some work done by my colleague David Jones and I. This work was presented at the 16th Australia New Zealand Climate Forum in November 2004. The abstract of our presentation is contained within the volume of abstracts, available here (pages 50-51), or separately here. A media release on this, with a regrettable and inaccurate headline, was issued at the time
(available here), and attracted some local media interest. This work has not yet appeared in any form in the refereed scientific literature,
so our results should be treated with some caution.
We followed the IID null hypothesis approach of Benestad and others (as noted above, there is plenty of relevant statistical literature on rates of record setting outside the fields of meteorology, climatology, hydrology and oceanography), and some of the time series we investigated are available here.
If we look at the global annual mean temperature anomaly time series (as derived from the University of East Angliaâ??s monthly anomaly time series), we find the number of new high records (14) is well above the expected number (5.6) under the IID null hypothesis for a time series of length 148. The results we obtained from various Australian time series were naturally considerably less extreme than this,
but generally consistent with the warming trend observed over Australia during the 20th Century (reported on here).
Maybe my post wasn’t clear. I wasn’t referring simply to gaps in data, but portions where the data exists. If you have a reconstruction of annual average temperatures at a location over the past 1000 yrs with an error range of, say, +/-0.3 deg C in the proxy data, and the net temperature change over that time period is 1.0 deg C from the proxy data, your counts and timing of records are going to be heavily dependent on errors. For instance, you can have a “false high” early in the data that is +0.3 deg C higher in the data reconstruction than it was in actuality, and then you’d have fewer record highs subsequent to that than you should have.
Records are often exceeded by 1/10ths of a degree. If the level of accuracy in the proxies isn’t much smaller than that, there will be plenty of both false and missed records. I don’t think it’s necessarily a good assumption that these would balance out.
[Response:True, but as long as the errors themselves are iid, then you are still testing for a signal if you have many parallel series (the noise cancels in a similar way to taking the mean over many measurements). Try it with a synthetic numerical example and see!(see http://cran.r-project.org for free analytical tool) -rasmus]
Comment by Michael Jankowski — 9 Aug 2005 @ 9:55 AM
Another story from ScienceDaily. This time on the damage caused by ice shelf disintegration:
Michael Jankowski commented: “I can also find recent quotes from a Dr. Ian Smith of CSIRO claiming that climate changes in the south-western portion of Western Australia are “most likely due to long-term natural climate variations.”
That is still the case with regard to the observed winter rainfall decline since about 1970 although, to be precise, I would now add:
” however, we cannot rule out the possibility that that the enhanced greenhouse effect has contributed to the decline.”
In other words, while it is very difficult to demonstrate that the enhanced greenhouse effect could be the sole, or even major, reason for the decline, we cannot rule it out entirely. This simply reflects the fact that our knowledge of how the climate system behaves is not perfect.
Report: Icier Clouds Make More Lightning
By THE ASSOCIATED PRESS
Published: August 11, 2005
Filed at 7:27 p.m. ET
WASHINGTON (AP) — Poet Robert Frost once pondered whether the world would end in fire or in ice. Weather researchers say where you find ice you find fire — at least in the form of lightning.
Whether the storm was over land, ocean or coastal areas, clouds with more ice produced more lightning, researchers studying satellite radar images report in the journal Geophysical Research Letters.
”The new thing is that when you look at different areas of the planet … the hypothesis about the importance of ice holds up,” Walter A. Petersen of the University of Alabama at Huntsville said Thursday.
He said weather scientists have known there was a relationship between ice and lightning, but were learning new details by studying the National Aeronautics and Space Administration satellite images which can look at both the number of lightning strikes and the volume of ice in a cloud at the same time.
Crucial is what is called precipitation-sized ice, particles of a millimeter or so which sometimes can be seen falling as small hail. ”Where you have more of that, you tend to have more lightning,” Petersen said.
These particles crash into smaller ice particles in the swirling winds inside storm clouds, resulting in a separation of electrical charge.
The charge separated between smaller and larger particles, with the smaller carrying a positive charge to the top of the thundercloud and the larger ones with the negative charge sinking to the bottom, he explained in a telephone interview.
”You effectively make a big battery with positive and negative ends,” he said, with the charge building up until it is discharged as lightning.
The relationship between ice volume and lightning held true over such varied locations as the Himalaya Mountains, Central Africa, Madagascar, northern Australia and Florida, the researchers reported.
They found small areas of subtropical South America where lightning flash density seemed slightly less than would have been expected for the measured ice amount. Since they could find no physical reason for this the researchers said it may be a sampling error. They are doing more research on those areas.
The work was funded by the NASA’s Earth Observing System and Earth Science Enterprise programs.
[Response:Thanks! There is little doubt that electric charges play a role in lightning and there is a relationship between ice crystals and charge separation. But this is not the same as to say that the exact state of the ionosphere has strong influence on particular cases. Yes, the ionosphere plays a role, but I believe more as setting the stage (eg the fair weather electric field). -rasmus]
Re 14 and 23:
Here is a very interesting report about ‘excess winter deaths’ in Europe:
It pretty much demolishes the idea that excess winter mortality is linked to people living in countries with particularly low temperatures, or to a wide annual temperature range.
It states that excess winter mortality is particularly high in the UK, but also in Ireland, Italy, Spain and Portugal. It is lower in most parts of northern Europe, ie in countries with a greater annual mean temperature range. A considerable number of those deaths is linked to influenza (and nobody has shown that flu, or infectious diseases will diminish under GW). Influenza alone cannot explain the number of winter deaths in the UK, but it would be interesting to see whether it can explain them in those many northern European countries with much lower winter death rates. Deaths from hypothermia in the UK are rare.
Housing conditions have been blamed widely for those deaths, and given that I used to work for a housing charity in Scotland this is not in the slightest surprising – we have many thousands of properties which are below tolerable standard, hard or impossible to heat, with single-glazed windows in rotting window frames, draughty doors, and above all extreme condensation and rising damp (and they are dreadfully unhealthy in a mild, wet, windy winter too). Over recent years, there has been some (though not enough) progress with regard to housing standards, insulation and fuel poverty and you would expect to see lower winter death rates as a result.
In short, UK mortality rates really give no evidence that GW will mean less deaths worldwide – it is a particular housing and social problem we have which can be fixed quite easily with some decent housing and public health investment and does not require us to heat the whole planet!
Comment by Almuth Ernsting — 14 Aug 2005 @ 4:05 PM
NOAA just reported July 2005 as the warmest in history for the Northern Hemisphere.
Contrairians will easily postulate that this is caused by concrete cities or some likewise lame esoteric explanation. There is no vast big cities in the Arctic (except for a couple in Russia). For students of our world climate this event is extraordinary giving that El-Nino is inactive. I would be interested in reading comments from Climatologists about this phenomena. AGW is certainly the cause, but the driving force behind this years spike is surely the Arctic Ocean, which had much broken ice seen as early as February 05. This transpired in an Arctic Ocean which can be sailed from Nordcapp Norway Eastwards all the way back to Nordcapp by way of the Russian Northeast and Alaska-Canadian Northwest passages.
“The average global temperature anomaly for combined land and ocean surfaces for July (based on preliminary data) was 1.1 degrees F (0.6 degrees C) above the 1880-2004 long-term mean. This was the second warmest July since 1880 (the beginning of reliable instrumental records). The warmest July was in 1998 with an anomaly of 1.2 degrees F (0.7 degrees C) above the mean. There were warmer than average conditions in Scandinavia, much of Asia, North Africa and the western U.S., while below-average temperatures occurred in northern Canada and northern Alaska. Ocean temperatures were also second highest on record.”