Why global climate models do not give a realistic description of the local climate
Global climate
Global climate statistics, such as the global mean temperature, provide good indicators as to how our global climate varies (e.g. see here). However, most people are not directly affected by global climate statistics. They care about the local climate; the temperature, rainfall and wind where they are. When you look at the impacts of a climate change or specific adaptations to a climate change, you often need to know how a global warming will affect the local climate.
Yet, whereas the global climate models (GCMs) tend to describe the global climate statistics reasonably well, they do not provide a representative description of the local climate. Regional climate models (RCMs) do a better job at representing climate on a smaller scale, but their spatial resolution is still fairly coarse compared to how the local climate may vary spatially in regions with complex terrain. This fact is not a general flaw of climate models, but just the climate models' limitation. I will try to explain why this is below.
Regional climate characteristics
Most GCMs are able to provide a reasonable representation of regional climatic features such as ENSO, the NAO, the Hadley cell, the Trade winds and jets in the atmosphere. They also provide a realistic description of so-called teleconnection patterns, such as wave propagation in the atmosphere and the ocean. These phenomena, however, tend to have fairly large spatial scales, but when you get down to the very local scale, the GCMs are no longer appropriate.
Minimum scale
There are several reasons why GCMs do not provide a representative description of the local climate (i.e. exactly where I live). For one, the grid mesh, on which they compute the physical quantities relevant for the climate, is too coarse (typically 200km) to capture the local aspects. The figure on the left shows a typical land-sea mask for a GCM.
The distance between two grid points in a GCM (or an RCM) is the minimum scale (~200km). The coarse resolution typically used in the GCMs till now has implied that the topography has been smooth compared to the real landscape and that some countries (e.g. Denmark and Italy) are not represented in the models (one exception is one Japanese GCM with an extremely high spatial resolution).
Sub-grid processes are represented by parameterisation schemes describing their aggregated effect over a larger scale. These schemes are often referred to as 'model physics' but are really based on physics-inspired statistical models describing the mean quantity in the grid box, given relevant input parameters. The parameterisation schemes are usually based on empirical data (e.g. field measurements making in-situ observations), and a typical example of a parameterisation scheme is the representation of clouds.
Surface processes
Climate models need boundary conditions describing the surface conditions (e.g. energy and moisture fluxes) in order to yield a realistic representation of the climate system. Often simple parameterisation schemes are employed to provide a reasonable description, but these do not capture the detailed variations associated with small spatial scales.
Skillful scale
Shortcomings associated with parameterisation schemes and coarse resolution explain why one gridpoint value provided by the GCMs may not be representative for the local climate. A concept called skillful scale has sometimes been employed in the literature, most of which have been linked to a study by Grotch and MacCracken (1991) who found model results to diverge as the spatial scale was reduced. Specifically, they observed that:
Although agreement of the average is a necessary condition for model validation, even when [global] averages agree perfectly, in practice, very large regional or pointwise differences can, and do, exist.
Although it is not entirely clear whether this study really touched upon skillful scale, it has since been cited by others, and used to argue that the skillful scale is about 8 gridpoints. Nevertheless, since the 1991-study, the GCMs have improved significantly, and the GCMs now are run for longer periods and with diurnal variations in the insolation.
Regionalisation
The figure above gives an illustration of the concept of regionalisation, or so-called downscaling. The left panel shows a typical RCM land-sea mask, giving a picture of its spatial resolution. The middle panel shows a blurred satellite image of Europe, which can illustrate how the sharp details are lost yet providing a realistic large-scale picture. The unblurred image of Europe is shown in the right panel. An analogy for the data from GCMs is looking at a blurred picture (middle above) while regional modeling (RCMs) and empirical-statistical downscaling (ESD) is putting on the glasses to improve the image sharpness (right above).
Both RCMs and GCMs give a somewhat 'blurred' picture albeit to different degrees of sharpness, and RCMs and GCMs are similar in many respects. However, GCMs are not just 'blurred' but also involve some more serious 'structural differences' such as an exaggerated Gibraltar Strait (see land-sea mask above), and the Great Lakes area, or Florida, Baja California are quite different and not just blurred (see figure below). Such structural differences are also present in RCMs (eg. fjords), but on much smaller spatial scales.
(Source: Strand, NCAR)Yet the images shown here for present climate models do not really show features down to kilometer scales that may influence the local climate where I live, such as valleys, lakes, mountains and fjords, even for RCMs (the lower right panel shows an optimistic projection for improved spatial resolution in GCMs for the near future). The climate in the fjords of Norway (can be be illustrated by the snowcover) is very different from the climate on the mountains separating them. In principle, ESD can be applied to any spatial scale, whereas the RCMs are limited by computer resources and the availability of boundary data.
What is the skilful scale now?
My question is whether the concept of a skillful scale based on old GCMs still apply for the state-of-the-art models. The IPCC AR4 doesn't say much about skilful scale, but merely states that
Atmosphere-Ocean General Circulation Models cannot provide information at scales finer than their computational grid (typically of the order of 200 km) and processes at the unresolved scales are important. Providing information at finer scales can be achieved through using high resolution in dynamical models or empirical statistical downscaling.
The third assessment report (TAR) merely states that 'The difficulty of simulating regional climate change is therefore evident'. The IPCC assessment report 4 (chapter 11) and the regionalisation therein will be discussed in a forthcoming post.
27 May 2007 at 6:14 AM
Any comments on this?
James C. McWilliams
Irreducible imprecision in atmospheric and oceanic simulations
PNAS | May 22, 2007 | vol. 104 | no. 21 | 8709-8713
http://www.pnas.org/cgi/content/full/104/21/8709
It emphasises that the problem is not just one of decreasing grid size.
What about the specific proposition that:
“No fundamentally reliable reduction of the size of the AOS dynamical system (i.e., a statistical mechanics analogous to the transition between molecular kinetics and fluid dynamics) is yet envisioned.”
Is this a problem of principle, like sensitive dependence on initial conditions, or something that enough years of hard work might crack?
27 May 2007 at 6:17 AM
Thanks Rasmus,
I did not fully grasp the concept of skilful scale. Are you saying that GCMs do not reliably represent climate to a resolution of 1 grid point and that to achieve accurate representation you need to average over about 8 grid points? Hence the “skilful scale” is 8 grid points.
[Response:This is basically the point, yes. But there has not been much discussion about what the skilful scale has been lately, so I’m not sure if it is still true. -rasmus]
Do climate scientists expect any surprises as resolution increases? Were there “surprises” between the 1980s GISS models and the latest models? I note that in our region (Australia) your minimum scale map leaves out Bass Strait (between Australia and Tasmania) and Torres Strait (between Australia and PNG). These are significant water ways for local climate and ocean currents. They are also about 150 km wide - close to 200 km - so why would they be omitted?
[Response:One Japanese model does have a very high spatial resolution, but I don’t think there are any particular surprises. Perhaps an improved resolution may provide a better rpresentation of the MJO and the monsoon system as well as cyclones. The very high resolution model makes very realistic pictures of the cloud and storm systems, and the guys presenting the results are fond of showing animations which look very much like satellite pictures. Quite impressive. -rasmus]
Do GCMs capture coarse topographic features, eg the Tibetan Plateau?
[Response:apparently not well enough. -rasmus]
27 May 2007 at 7:06 AM
I agree that for quantitative studies GCMs cannot be used at a regional or single gridpoint scale. However, the results can be considered valid at a qualititave level.
[Response:I think this is true too, but downscaling should in general add value to the simulations. -rasmus]
I have used a VERY coarse resolution GCM (8 degrees by 10 degrees) to help plan a vacation, and it worked quite well. The data provided by the GCM was better than any guide book or even the CIA World Factbook. In addition, the GCM provided more than just temp + precip, including other useful variables like cloud cover (tanning), soil moisture and ground wetness (camping) and wind speed and direction (windsurfing).
See my EdGCM writeup on my vacation planning for more details: http://edgcm.columbia.edu/outreach/showcase/cambodia.html
27 May 2007 at 8:37 AM
It would be helpful to provide a useful definition of what is meant by “local”.
27 May 2007 at 8:40 AM
No, no, no. Why doesn’t the AUTHOR OF THE ARTICLE give a useful definition of LOCAL climate!
27 May 2007 at 8:41 AM
What is meant by LOCAL climate?
[Response:I’m getting the message, don’t worry. To me, the local climate is the climatic characteristics which have are directly relevant to my perceptions. This would normally be on a smaller scale than a grid-box for a GCM and smaller than ‘meso scales‘ referred to in meteorology (more like ‘meso-gamma‘) and smaller than minimum scale of most RCMs (which typically have spatial scales of ~50km, although some go down to ~10km). I define regional scales as somewhat larger, that whch characterises a larger region (e.g. at meso scale to synoptic scales). -rasmus]
27 May 2007 at 9:17 AM
How do you manage to convert heat, as in watts m-2, into temperature?
What is the relationship between the steady state input of energy, in watt m2, and total global atmospheric volume, pressure and temperature?
[Response:First law of thermodynamics, but this is done in the models. -rasmus]
27 May 2007 at 9:26 AM
Thanks for this post.
You say:
“Most GCMs are able to provide a reasonable representation of regional climatic features such as ENSO, the NAO, the Hadley cell, the Trade winds and jets in the atmosphere. They also provide a realistic description of so-called teleconnection patterns, such as wave propagation in the atmosphere and the ocean.”
I would like to know, given that these (and other) regional features have not been studied all that long, how stable they are, in the mathematical sense of the term.
A second question is: what do you mean by “*reasonable* representation”? Any links to the primary literature on either question would be appreciated.
Thanks again. I look forward to more on the topic of how GCMs are constructed and parameterised.
P.S. There are a couple of typos in the article: aggrigated, parametereisation
re #5: “local” is an intentionally flexible concept. Often sub-continental, sometimes smaller, somewhere between 100 and 1000 miles.
[Response:The best link is probably to the IPCC AR4 chapter 8. -rasmus]
27 May 2007 at 9:54 AM
There are distributed computing projects for SETI, protein folding, and crypto cracking … but none for global climate change? OK, I’ve Googled after writing that line and I find http://ClimatePrediction.Net … but I don’t have the skill to determine if what they’re doing is valid or not.
What doesn’t RealClimate have a distributed computing initiative? This place certainly has the pull to get people interested in providing computing power.
And thusly (and quite tangentially) the model resolution could improve.
[Response:Climateprediction.net is a SETI-inspired initiative where GCMs are run as screen-savers. These GCMs are coarser than the ‘normal’ GCM run on super-computers, but the vast number of runs provide high ’statistical power’ (a very large ensemble yields a large statistical sample). I don’t know of any initiative where distributed computing has been used to for one high-resolution GCM (i.e. splitting the world into managable chunks of computation), and I think that would be very unpractible as this requires a high rate of data exchange. -rasmus]
27 May 2007 at 10:08 AM
Thanks for this post. You say:
“Most GCMs are able to provide a reasonable representation of regional climatic features such as ENSO, the NAO, the Hadley cell, the Trade winds and jets in the atmosphere. They also provide a realistic description of so-called teleconnection patterns, such as wave propagation in the atmosphere and the ocean.”
I would like to know, given that these (and other) regional features have not been studied all that long, how stable they are, in the mathematical sense of the term. A second question is: what do you mean by “*reasonable* representation”? Any links to the primary literature on either question would be appreciated.
27 May 2007 at 10:11 AM
Don’t some of the GCMs (e.g. NCAR’s CCSM3) try to address coarse grids by having models for different terrain within the grids, and then weighting them according to their area for the grid cell? Does this not help things?
You don’t say much about what “skilful scale” means. Is this the same as some other supercomputer techniques when the grid size is not constant but instead varies as needed?
[Response:I don’t think the literature is very clear on this (try googeling ’skilful scale’; I only got 20 hits!), and I thought it would be interesting to bring it up in this forum. -rasmus]
27 May 2007 at 10:19 AM
Re #5: “local” is an intentionally flexible concept, something smaller in scale than “regional”. The author defines this term in the opening paragraph in human terms, as the spatial extent over which most of us live most of our lives. Seems to me he’s talking about something the size of a state or smaller. Doesn’t much matter, as his point is that GCMs don’t work well at those small scales. Hence the attempt to define the minimum scale over which the models are skillful. “Local” is therefore anything smaller than that.
27 May 2007 at 10:40 AM
Thank you for the great job of this site.
I’ve got a question somewhat related to this article. You gave insights on the spatial resolution of the climate models. I am wondering what you can say on their temporal resolution. More precisely, climate models are predicting the mean temperature evolution. Are there any precision on the evolution of the thermal amplitudes, and on what time scale?
Thank you again.
G. Gay
[Response:One important consideration is the size of the model’s time-step (order of minutes), and then the type of time-stepping (integration) scheme matters. But I’m not sure what the exact answer is to this (others?). -rasmus]
27 May 2007 at 10:44 AM
Re #6: [There are distributed computing projects for SETI, protein folding, and crypto cracking…]
This comes down to a fundamental difference in computational methods. The problems you mention can be broken down into many computationally independent pieces. Each of the pieces can be worked on independently, and the results collected and combined whenever they’re done.
Climate models (and many other problems) work on a grid. At each timestep, values are computed within each cell. Those computations depend on the values of the previous timestep, and the values in adjacent cells. That means there’s a lot of data exchange going on. This might happen in memory on a single processor machine (very fast), or via a dedicated high-speed network on a parallel machine (e.g. IBM BlueGene). But if you tried to do this over the internet, the communication time would be very much larger than the time needed to do the computations themselves.
27 May 2007 at 10:48 AM
I have been interested in the regional and local climate changes partially because as Rasmus writes that is what effects people’s daily lives, but also because regional and climate changes will need to be better predicted to determine the ecological changes caused by climate change.
Are there any barriers that prevent better regional and local climate predictions? For example are there problems in regional vs global models like the difference between climate and weather prediction (ie weather is chaotic and therefore less predictable than climate) that make it impossible to make better local/regional predictions, or is it just a question of researching more and developing better models?
[Response:Good question. I suppose in theory, one could always go down in scale, and when taking it to the extreme, to the scale of atoms (quantum physics). At one point, I expect the downscaling will becom impractical, at least. -rasmus]
27 May 2007 at 11:05 AM
Google: climate distributed computing
First two Results of about 1,130,000 for climate distributed computing. (0.20 seconds)
BBC - Science & Nature - Climate Change …experiment used a technique called distributed computing to utilise users’ spare computing power to predict future climate. www.bbc.co.uk/sn/climateexperiment/theexperiment/distributedcomputing.shtml
Distributed computing tackles climate change. Posted by Stephen Shankland. Oxford University and the BBC have launched a partnership …. news.com.com/8301-10784_3-6041683-7.html
27 May 2007 at 12:23 PM
re: #6
#10 is right, but in addition:
The problems for which @home distribution works have some other characteristics as well:
EITHER:
1) There are a large number of independent input cases, each of which can be analyzed separately, using a modest amount of input, and yielding a simple answer that is easy to verify:
a) YES/NO (”hello Earth. Why aren’t you answering us?”
or INTERESTING/NOTINTERSTING, as particle physicists have long done, i.e., send an event to each free machine, have it crunch for a while, and say whether or not something interesting happened worth further analysis.
b) A few numbers, as in crypto-cracking: “here are the prime factors”, which make take a long time to find, but are trivial to verify by multiplying them back together.
c) A number, which is mainly of interest if it’s the bet found so far, i.e., as in Monte Carlo approaches to protein folding or Traveling Salesman routing problems.
OR
2) One is doing a Monte Carlo simulation where there is no right answer, but one is interested in generating an ensemble of results, and analyzing the distribution, i.e., “Do you have enough money to retire?” A delightful short piece on such is Sam Savage’s “The Flaw of Averages”: http://www.stanford.edu/~savage/flaw/
I think the ClimatePrediction.net effort is of this sort, and it may be useful, but it doesn’t help the topic discussed in the (nice) original posting.
Note that going from a 100km grid to a 10km grid means a 10×10 = 100X more elements (2D), and if it were general 3D, that would be 1000X. In many disciplines, people using such methods have had to do non-uniform-sized subgridding to improve results with a given level of computing. I.e., for some parts of a model, a coarse grid gives reasonable results, but for others, one needs a much finer grid.
27 May 2007 at 12:59 PM
This is all very interesting but as far as I’m concerned fails to give an accurate enough picture of the processes at work behind the differences in predictions.
What I would like to see is a much more detailed run-through of the differences in local predictions by models and concurrently, the unique ways in which they simulate natural processes.
If 8 grid points represents a skillful representation and 1 does not, can you give a relevant example of how regional dynamics cancel each other out at that scale?
[Response:I don’t think it’s necessary a matter of ‘cancelling out’ but rather giving a ‘blurred’ picture or for instance a spurious geographical shift of a few grid points due to e.g. approximations of local grid-point scale spatial gradients. -rasmus]
27 May 2007 at 1:37 PM
I am running a distributed model for climateprediction.net. I would just as happily run one for realclimate. I am not a scientist and real climate has given me the insight and the links to further education which enable me to refute the flat earth rightwingers on the political board I frequent. They are no longer as dismissive and abusive as they were two years ago, when I began studying the information on your website. Thanks and if you need some of my cpu cycles, I will be glad to donate.
[Response: Watch this space… - gavin]
27 May 2007 at 1:45 PM
I’m curious about this example of a regional-local prediction:
Model Projections of an Imminent Transition to a More Arid Climate in Southwestern North America, Seager et al. Science 2007
Abstract: “How anthropogenic climate change will impact hydroclimate in the arid regions of Southwestern North America has implications for the allocation of water resources and the course of regional development. Here we show that there is a broad consensus amongst climate models that this region will dry significantly in the 21st century and that the transition to a more arid climate should already be underway. If these models are correct, the levels of aridity of the recent multiyear drought, or the Dust Bowl and 1950s droughts, will, within the coming years to decades, become the new climatology of the American Southwest.”
This is within the ’skillful scale’. However, if one wants to know the effect on California’s Central Valley (an area of massive agricultural production) and on Sierra Nevada snowpack levels, it seems the models still lag behind the observations - but water districts should probably be focusing on long-term conservation strategies right now.
This paper, based on observations, seems to provide support for Seager et al :Summertime Moisture Divergence over The Southwestern US and Northwestern Mexico, Anderson et al GRL 2001
They note that moisture divergence over the American Southwest increased in 1994, in line with model predictions of persistent drought.
Droughts are a common feature of the ‘unperturbed climate system’ but this change appears attributable to anthropogenic climate change. Seager et al report that the persistent drying is due to increased humidity, which is changing atmospheric circulation patterns and leading to a poleward expansion of the subtropical dry zones. Increases in atmospheric humidity are a long-standing prediction of the effects of increased anthropogenic greenhouse forcing.
27 May 2007 at 2:39 PM
Surely very high resolution experiments were done on smaller time scales covering wide regions, wasn’t there any significant change in results?
27 May 2007 at 6:06 PM
Local drying would be good to predict for urban planning; for example can Las Vegas USA or Adelaide Australia sustain their current populations? A year or two ago AGW was interpreted as ‘wetter everywhere’ but now that doesn’t seem to be the case.
27 May 2007 at 6:58 PM
How do you manage to convert heat, as in watts m-2, into temperature?
What is the relationship between the steady state input of energy, in watt m2, and total global atmospheric volume, pressure and temperature?
[Response:First law of thermodynamics, but this is done in the models. -rasmus]
Is that sarcasm?
How do you calculate the amount of heat in the atmosphere, in terms of volume, pressure and temperature ?
[Response:You can use the ideal gas laws or the radiative balance models, depending on the situation. Besides, you may in some cases need to consider the latent heat associated with vapour concentrations and the condensation processes. But I’m not sure that I understand your point. -rasmus]
27 May 2007 at 11:32 PM
Re: Climate versus weather
One way of thinking about the results of a climate model is that “climate is what you expect, weather is what you get.”
Consider a simple box-model for the Earth: heat goes in, heat goes out. There’s only one number for temperature, and that spans the “grid” of the entire Earth. Everything else, like the difference between Nunavut and Napa Valley, would be “weather” to the model.
As computer models become better, we can see more detail, both in time and space. Parts of “classical” climate, like the ENSO, start showing up accurately — but this would still be “weather” to the whole-Earth-box.
If we had a superfine model, that simulated at whatever timestep and resolution you wanted to name, then we’d be able to refine the definitions. Climate would be what happens over an ensemble of initial conditions, and weather would be what happens if you plug in conditions as-of-now. Until that point, we have to look at averages over both initial conditions and over insufficient resolution.
27 May 2007 at 11:40 PM
Re: Distributed climate models
Unfortunately, climate models are just plain big. The Earth is a big place by itself, and a research-quality climate model needs a relatively fine resolution over the surface.
Even though they’re physically separated, different parts of the Earth also affect each other, climate-wise. In terms of weather, just consider the “butterfly effect.” It’s still present in average climate, albeit (generally) less pronounced.
Combine both of these points, and you have a lot of data (for the globe) that depends on the entire lot of it at prior times. This sort of communication is what distributed systems like SETI@Home are really bad at. That’s why full-resolution climate models are most suited for a single supercomputer or a cluster of tightly-connected machines.
That’s not to say that there’s nothing left for researchers without massive computer budgets. As the article hinted at, there’s a lot of work done in the “subgrid-scale” modelling. That encompasses most of the physics that actually happen, only on a physical scale that would be otherwise invisible to the global model. They’ll never be perfect (because they’re estimated, rather than directly simulated), but improving those models would go a long way to helping the accuracy of global climate models.
28 May 2007 at 5:59 AM
[[How do you manage to convert heat, as in watts m-2, into temperature?
What is the relationship between the steady state input of energy, in watt m2, and total global atmospheric volume, pressure and temperature?
[Response:First law of thermodynamics, but this is done in the models. -rasmus]]]
Don’t forget the ideal gas law.
28 May 2007 at 7:02 AM
Do you have any evidence that the Earths air pressure and volume has remained constant over the last 200 years?
Do you have any evidence that the Earths atmosphere has the same water content over the last 200 years ?
How do you calculate virtual heat, along the atmospheres vertical axis, give the large chages in air temperature and pressure, when you convert from a non-ideal gas when applying the ideal gas law ?
[Response:You mean, do I have any evidence that the mass of Earth’s atmosphere has changed over the last 200 years (the sea level pressure provides a measure of the air masses above and I’m presuming you are not suggesting that Earth’s gravity, i.e. that that Earth’s mass has changed appreciably)? What do you mean by ‘the air volume’. The atmospheric extent? This is irrelevant if you are looking at the air property in a unit volume (m^3). I still don’t get your point; how is this relevant to the GCMs ability to describe small-scale climatic features? -rasmus]
28 May 2007 at 7:15 AM
This scale problem is mirrored in many other disciplines. In transportation modelling, for example, we can run very general models with just a few well-understood parameters, and get results that are generally reasonable matches with observations. So many households, workers etc gives so many trips in a day within a region.
As we move to increasingly disaggregated models (finer scale) we have to consider more detailed parameters (about which we have progressively less confidence as we strive for finer detail) and we produce increasingly more detailed outputs which look very plausible, but which have a progressively higher chance of giving the wrong answer about what is going on in the street outside your house at dinner time on Thursday.
At the end of the model re-fining process we are trying to observe electrons, for which (it seems) we can either know one state or another, but not both at the same time.
Im sure the climatologists are aware of this. Its easy to produce a fancy model that looks good, but as the level of detail increases the rubbish-in-rubbish-out factor increases significantly. Its better to run with a robust broad-scale model, and apply common sense to the interpretation of sub-regional effects, than to run a rubbishy micro-model that cannot be shown to be exactly true anyplace at any given time.
It�s a matter of confidence, and understanding. If you cannot mentally get you head around the input parameters with a high level of understanding and confidence, then its very hard to defend the results. Take it easy.
Besides, we really do know all we need to know already, dont we. Whether its going to rain at your place on 1 July or not makes no difference to the main conclusions. Its going to get hotter, the ice is going to melt, the sea is going to rise - even if we can hit 2050 emission targets. The horse has bolted for the hills, all we can do is figure out how to run after it!
28 May 2007 at 9:59 AM
>Earth’s air pressure
Torricelli
See “expansion tectonics” or “expanding Earth” for the argument that the Earth’s air pressure has changed — along with its mass, and diameter. It’s a religious alternative to geology.
28 May 2007 at 10:25 AM
Nigel Williams (#28) wrote:
Oh, I am not sure you want to compare this to transportation modeling - or at least not highway performance modeling.
In forecasting future traffic patterns with increased populations, traffic modellers fall back on a formula which works quite well except in periods of high congestion - exactly where you would want to have it work the best - assuming you are concerned with vehicle hours of delay or the ratio of freeflow speed versus projected actual speed. The problem is that they calculate speed as a function of volume (vehicles per hour passing a given point). In high congestion, there is a point you hit where the volume will remain constant but the speed drops by several factors for several hours. When congestion finally begins to fall, volume will remain constant with speed gradually rising until a point is hit at which traffic volume begins to fall and a one-to-one relationship between volume and speed is reestablished.
Additionally, if anyone does the post-processing other than the modellers, you might want to be sure that they know how to properly calculate normalized performance measures. In my state, the fellow who implemented those calculations was under the impression that the averages were largely subjective - which didn’t help any. For example, he did a weighted averaging of speed by vehicle miles.
In case some don’t the problem with this, imagine that you are dealing with just a single car where there are two legs to given trip. In the first leg, the car travels 50 mph for one hour, then in the second it travels 10 mph for 5 hrs. Using his weighted averaging, the car’s average speed is 30 mph. However, the car has travelled 100 mph in 6 hrs, giving a real average speed of 16.67 mph.
Thanks to their unusual way of doing math, by the time you aggregated by both time and location, all but one out of over a hundred performance measures were wrong. The only thing they were calculating correctly was length of highway. Even the lane-mile calculations were off: they were calculating it as the maximum of the two directions.
I came in as a temp programmer, identified the problem with their calculations and then reworked the functions. (The rule is to always calculate in aggregates at each level of aggregation, then at the very last step calculate the normalized measures as simple functions of the aggregates - generally through addition and division.) Incidently, I didn’t have any background in the area, either. But I noticed the inconsistencies - and then thought about it. It was clear, for example, that average speed had to be vehicle miles over vehicle hours, and after that the rest started to fall into place. The rework made quite a difference: all of the sudden they could see the congestion in the urban areas at the aggregate level - and the rural areas were looking far better.
28 May 2007 at 11:09 AM
Re #27: [Do you have any evidence that the Earths air pressure and volume has remained constant over the last 200 years?]
The first barometers were invented in the 1700s (or maybe even earlier?) Certainly by the mid-1800s they were extremely sensitive. Not long ago I was reading a book about the erruption of Krakatoa (the title of which I’ve forgotten, alas), which described how recording barometers around the world detected air pressure waves from the explosion for many days afterwards.
Then there’s all sorts of indirect evidence, as for instance gas laws & conservation of mass: you seem to be suggesting that the actual amount of atmosphere might somehow have changed. If so, then where did it come from/go to?
28 May 2007 at 11:38 AM
O.K. I will make it very simple, adding heat to the atmosphere can change the temperature, the pressure and the volume.
When the model an increase in the amount of heat in the atmosphere, what is the relationship bettwen heat input and temperature, pressure and volume?
Secondly, have you manages to observe changes in the volume or pressure of the atmosphere; do thses changes match your models?
Finally, finally, how can you model using the ideal gas law, when the atmosphere is a mixture of gasses, some of which do not follow the ideal gas law even when studied in isolation, much less mixtures?
[Response:The pressure is more or less given in this case by the mass of the atmosphere above the point of interest. However, if you say that the air expands so much (due to an increase in the temperature) that the gravitational forces are reduced for the top of the atmosphere, then possibly there may be an effect. But keep in mind that the atmoshpere is in essence already a very thin shell of gas anyway. I guess this effect would be very minor, if at all noticable. Exactly which gases do not follow the ideal gas law? -rasmus]
28 May 2007 at 12:31 PM
I appreciate the link to Chapter 8, and likely could learn much at that website. Reading the author r’s development here on RC, I thought some fractal math could provide a differential layer for drilling into the overarching model’s output, or, rather, could form the granular infrastructure from which base the model could grow, topologically placing the GCM layer as the outer, visible depiction for the fractally defined substrate. But all this probably is in the math literature for the climate-weather models in existence.
28 May 2007 at 1:31 PM
Thanks to their unusual way of doing math, by the time you aggregated by both time and location, all but one out of over a hundred performance measures were wrong. The only thing they were calculating correctly was length of highway. Even the lane-mile calculations were off: they were calculating it as the maximum of the two directions.
That’s not to say that there’s nothing left for researchers without massive computer budgets. As the article hinted at, there’s a lot of work done in the “subgrid-scale” modelling. That encompasses most of the physics that actually happen, only on a physical scale that would be otherwise invisible to the global model.
anyway,Thank u very much for your sharing
28 May 2007 at 1:50 PM
#32 Atmosphere modelling
Doc, like some others here I am puzzled as to what you’re trying to say.
If all relevant physical (gas) laws are in the GCMs (which they no doubt are), I suppose that these must be some pressure / volume change in the atmosphere if you heat it (probably small, for example 1 deg heating would give 0.3% volume change if pressure is constant). But this does not seem to be very important if we are interested in temperature (which can be verified directly against measurements).
And it seems to me that at pressures of 1 bar max the ideal gas law (PV=RT) is perfectly adequate for the problem at hand.
28 May 2007 at 1:51 PM
“The pressure is more or less given in this case by the mass of the atmosphere above the point of interest. However, if you say that the air expands so much (due to an increase in the temperature) that the gravitational forces are reduced for the top of the atmosphere, then possibly there may be an effect.”
The composition of gas in the vertical cross section of the atmosphere depends on the absolute T and the molecular weight of the gas. It should also be apparent that the atmosphere is “V” shaped, any expansion of the atmosphere (in response to an increase in energy) could have a disproportionate effect on pressure. I have a little sketch calculation looking at what would happen in terms of volume, pressure and temperature of an idealized atmosphere, without water vapor, and found it was very hard to do. I ended up with a system that was rather like a ballon, you can add heat into it and it inflates as the pressure increases. So does the atmosphere act like a ballon? Does it expand and pressurize when you add heat into it in your models?
Another point if it does expand, its surface are should increase and so its radiation into space should also increase.
‘Exactly which gases do not follow the ideal gas law?”
The only gases that follow the ideal gas laws are monoatomic (uniatomic), He, Ne e.t.c. Both di and biatomic gases lose (at least) one degree of freedon along an axis, and triatomic gases like CO2 behave with a large degree of non-ideal character.
The people who really know about this stuff are into air conditioning and refidgeration, the basics is here:-
http://www.zanderuk.com/tech_Centre.asp?chapter=1§ion=2_Compression_3.htm&getIndex=false
there quantum mechanics of simple triatomic gases, like CO2, has also been explored (but is way over my head) and is a little odd to say the least.
On a practical level the ratio of the constant-volume and constant-pressure heat capacities, CV and CP, depends on the degree of freedom and is different in mono,bi and triatmic gases.
http://www.whfreeman.com/college/pdfs/halpernpdfs/part04.pdf
The real problem is that gamma can change at phase transitions, the real fly in the ointment must be the modeling CV/CP ratios at, or near dew points.
So just how do you manage to model it?
[Response:We are not talking about airconditioners and compression in the case of the atmosphere, and most of the atmosphere consists of gases with biatomic molecule s. CO2 is a trace gas with ~380 parts per million in volume (ppm), and doesn’t play a big role in terms of volume and pressure (it’s more important when it comes to radiative properties). So, as far as I know, the ideal gas laws still provide a good approximation to the atmosphere’s behaviour. It seems to work for numerical weather models used in daily weather forecasts
-rasmus]
28 May 2007 at 2:21 PM
JohnLopresti (#33) wrote:
I at least know they have been thinking something along those lines…
… for a while…
Likewise, when it comes to simulating the evolution of past climates, they will use slightly pink noise in the proxies, although it is much closer to white noise - about 15% red or less, if I remember correctly, where red noise would be the 1/f scale-free variety, similar to that found in music and falling rain. This was brought up in a guest commentary not too long ago:
24 May 2006
How Red are my Proxies?
Guest commentary by David Ritson
http://www.realclimate.org/index.php/archives/2006/05/how-red-are-my-proxies
Pink noise realistically mimics the actual noise found in the record, I believe.
28 May 2007 at 3:45 PM
Timothy, your …all but one of over one hundred performace measures were wrong.. comment supports my point. You can make simple models work well and give reasonable answers within their scope, but as the number of parameters increases then the chances of the inputs and hence the outputs being wrong in detail increases. So we start being able to speak quite confidently about one thing, and in the end we are able to say nothing certain at all about absolutely everything. Nuf said.
28 May 2007 at 4:20 PM
#32 and #35. If 0.3% is the expected change in atmospheric pressure for each degree change then it would not be minor and it should be measurable.
28 May 2007 at 4:38 PM
This is an excellent overview of the technology and its limitations. I will suggest that my readers on my site (www.globalwarming-factorfiction.com) jump over here to read this. I have been trying to explain the limitations of climate modeling piece by piece for some time and this article does a great job of explaining the entire spectrum.
I agree with others that have commented that it would be great to have a SETI type distributed process. I understand that the current implementations of this type of project minimize some of that advantage but the SETI techniques are quite old and distributed computing algorithms have evolved quite a bit over the last 3-5 years. If NOAA (or another government agency) would put some effort in this area, I think we would be suprised. Perhaps a campaign to write our elected officials to fund that might make sense. I may do this on my site if I can figure out the details.
28 May 2007 at 5:39 PM
Wait. Adding heat to air makes it heavier?
What’s the source for “0.3% is the expected change in atmospheric pressure for each degree change”?
28 May 2007 at 6:39 PM
Re#27&31. These comments haven’t been adequately answered.
The question concerns whether the mass of the atmosphere has been conserved over a 200 year timeframe. It obviously hasn’t over geological history but that is not relevant here. How sensitive is temperature to pressure and I assume that at ca. 1 bar+/- 0.1 bar the atmosphere behaves ideally as noted PV=nRT.
The adiabatic lapse rates are considerable-
http://commons.wikimedia.org/wiki/Image:795px-Emagram.gif Were The mass of the atmosphere 10% greater at sea level ie. 110kPa one would extrapolate mean temperatures ca. 8 celsius higher than at present.
A direct empirical observation would be the mean temperature regime along the Dead Sea, well below present sea level.
As temperatures rise the oceans and soils will degass according to Henry’s Law and atmospheric pressure will arise not solely because of PVT but also because the mass of the atmosphere is no longer conserved.
I presume that climate models assume only that the mass of the atmosphere is conserved over centuries, ie. ca.5.1*10exp21g and this mass doesn’t change upon degassing.
28 May 2007 at 6:50 PM
Would a butterfly flapping its wings make a model diverge to the point of being useless. that is, a model really can’t go down too small unless there is both computing power and data that would make the model somewhat accurate.
28 May 2007 at 7:06 PM
Paul M. (#38) wrote:
Seek and ye shall find…
I used the website’s search engine, but I had seen it before.
28 May 2007 at 8:22 PM
DocMartyn,
A debating hint: Condescencion is usually much more effective when one has a clue what one is talking about. To a first approximation, most gases behave as ideal gases, so any effects would be 2nd order. And yes, I would expect that the atmosphere does indeed expand due to increasing temperature–you’d expect this just from the fact that the molecules have increased energy. However, the atmosphere does not heat equally, and I’m really don’t see what it has to do with the subject at hand–or much of anything else. As to temperature vs. radiation field, see
http://en.wikipedia.org/wiki/Stefan-Boltzmann_Law
and
http://en.wikipedia.org/wiki/Albedo
28 May 2007 at 9:26 PM
Please, keep in mind that the earth’s atmosphere is NOT in a sealed container. In 1998 when solar heating dramatically warmed the upper atmosphere, the atmosphere expanded and the result was an increase in the drag on orbiting satellites. Solar flares and other events are known to cause changes in the upper atmosphere that affect the thickness of the atmosphere. This has been fairly well studied as satellites require more effort to maintain orbit when solar activity increases.
My guess is that what should be looked at, rather than pressure, is density. I’m sure that PV = nRT hasn’t been repealed just yet …
28 May 2007 at 11:17 PM
Re #38 Higher model resolution and better data on initial conditions do not solve the problem of chaos (sensitivity to small changes in initial conditions) in weather models, if that’s what you’re asking. As far as the climate models go, chaos in the time domain is not the issue - not for something like a global mean, anyways. What is an issue is the related problem of structural instability, which is sensitivity of model output to small changes in model formulation. i.e. Switch one flavor of module for another, say, better one, and there is no guarantee the new ensemble will behave in a predictable manner, let alone better. Not only will the output change metrically, but it will also change topologically. That means that entirely new circulatory features (ENSO, PDO, NAO, etc.) could emerge from the model as a result of highly altered attractor geometry. Same butterfly, totally different impact, all because of a change in one module. If these changes are deemed unacceptable by the modeler then the model will presumably need to be recalibrated by tuning the free parameters available from the non-physics-based portion of the model.
Of course this explanation comes from a non-expert, so I would pass it by someone more qualified before taking any of it on faith.
If you are trying to assert that butterflies can’t alter the global circulation, then I would ask for some hard proof of that assertion. Those that argue that “weather is chaotic, climate is not” would probably agree with you, but then again I’m not sure they’ve really made their case. If I’m wrong I would be happy to review some material from the primary literature. After all, we haven’t been observing the global circulation all that long. How do we know empirically which circulatory features are stable and which are unstable?
29 May 2007 at 3:04 AM
#41 Hank
0.3% just follows from the gas law pV=RT. If T goes from 288 (Earth temperature) to 289 K and p=C, then V must necessarily increase by 1/288 = 0.3%.
Of course it’s more complicated than that (for example: the atmosphere does not heat uniformly, and is colder the higher you go, etc), but this was just to show that atmospheric expansion is probably not a big deal.
29 May 2007 at 3:17 AM
Thanks for this explanation. The way I describe the problems of resolution to the lay person is to relate it to the result of a football match. If Celtic (top of the SPL this season) were to play East Stirling (bottom of the 3rd division)we could all predict the result with some confidence. That’s where I guess GCMs are right now. Some experts might want to hazard the more difficult task of predicting the score. That I guess is where decadal regional models would like to be. But if anyone said that they could forecast not only the score, but also the scorer and the time of each goal with confidence then we’d all say they were nuts.
29 May 2007 at 3:46 AM
From the text above: “We were hoping for important revelations and final proof that we have all been hornswoggled by the climate Illuminati”
As a climate scepticus I’d like to comment that it is never “conspiracy” that we suspect to lay at the basis of the CO2-hype.
It is a time spirit working here, one of rebellion against the industrial revolution, a romantic longing to a virgin world, that brings people to target our capitalist consumption society.
A time spirit, not a conspiracy.
29 May 2007 at 4:31 AM
As if the truth was not enough…! Gavin, I presume you will lead us through this latest seminal paper by J Hansen et al.
Dangerous human-made interference with climate: a GISS modelE study:-
http://www.atmos-chem-phys.net/7/2287/2007/acp-7-2287-2007.pdf
Quote: ‘CO2 emissions are the critical issue, because a substantial fraction of these emissions remain in the atmosphere ‘forever’, for practical purposes (Fig. 9a). The principal implication is that avoidance of dangerous climate change requires the bulk of coal and unconventional fossil fuel resources to be exploited only under condition that CO2 emissions are captured and sequestered. A second inference is that remaining gas and oil resources must be husbanded, so that their role in critical functions such as mobile fuels can be stretched until acceptable alternatives are available, thus avoiding a need to squeeze such fuels from unconventional and environmentally damaging sources.
No problem.
29 May 2007 at 4:31 AM
Timothy Chase in #44 cites the essay by Annan & Connolley as an authority on the subject of chaotic climate. But that essay is curiously written, the first part very good, the latter part containing errors, and curiously chosen qualifiers… [cut]
[Response:If you think there are errors, do feel free to mention them; I’m not aware of any. For a fuller view of my opinions on this, see http://mustelid.blogspot.com/2005/06/climate-is-stable-in-absence-of.html - William]
I think that the jury is still out on this question. Correct me if I’m wrong. We haven’t been observing the climate system long enough at high enough resolution to be able to say with confidence whether abrupt regional shifts can occur unpredictably in response to the internal dynamics of global heat transfer. My hunch FWIW is they can, and I sense this was Pielke’s point in that thread… [cut]
Maybe the experts here can answer me a related question. Are there potentially multiple global circulatory ‘modes’ (for lack of a better word), and if so, would all these modes be equal in their capacity to dissipate global heat to space? My hunch is that different modes are possible, and that there is no reason to expect them to be equal in dissipative efficiency. If so, then abrupt climate change (regional, if not global) can be expected through internal chaotic dynamics alone.
[AGW alarmists, please note I am not denying anything about the 20th c. temperature trend. I am referring to past climate, something we are forced to view through a foggy lens that becomes increasingly foggy the further we look back.]
To be concrete, consider the example of a coastal city whose climate is warmed by a warm ocean current. If the circulation were to shift, and that current now ran cold, that climate would shift abruptly colder and drier. First, I do not believe the occurrence of such shifts is predictable. Second, I believe they can arise dynamically, without the assistance of any forcing agent. Third, if such shifting were to take place at multiple locations at inter-continental scales, there’s no telling in advance how the global temperature might change. I invite you to overturn these belief statements.
Apologies in advance for awkward use of climatological language.
29 May 2007 at 5:03 AM
Attention pressure-change folks — as long as the Earth’s volume is unconstrained, and it is, its surface pressure is not going to vary very much. Basically the surface pressure is going to be:
P = (M / A) g
where M is the mass of the atmosphere (say, in kg), A is the Earth’s surface area (square meters), and g the surface gravity (meters per square second). The answer comes out in Pascals. Working it backwards from sea-level pressure you get a figure of 5.27 x 1018 kg for the mass of the atmosphere. The actual figure is about 5.14 x 1018 kg, because some of the volume that would be atmosphere is taken up by surface relief.
Canonical values for those who want to play with the equation: reference atmospheric pressure is 101,325 Pascals, the Earth’s surface area is about 5.1007 x 1014 m2, and g averages 9.80665 m s-2.
There are pressure variations due to local weather and such physical effects as Bernoulli’s law, which relates pressure and wind velocity. But it’s never very much.
Over geological time, the Earth’s air pressure has probably varied significantly. A primordial hydrogen-helium atmosphere may have given way to a massive steam atmosphere due to the heat of accretion and outgassing, which in turn gave way to a carbon dioxide atmosphere, etc. But the Earth’s atmosphere has had a very consistent makeup for the last several million years at least.
29 May 2007 at 5:34 AM
Bender,
Your whole argument is fundamentally flawed. You are ignoring the fact that the models have already made a number of predictions that have panned out. They predicted global warming, polar amplification, stratospheric cooling, and the magnitude of the cooling from the eruption of Mount Pinatubo, all of which have been confirmed empirically. When we can see that the models work, arguments that they can’t work are out of court from the beginning. As Heinlein put it, when you see a rainbow you don’t stop to argue the laws of optics. There it is, in the sky.
29 May 2007 at 6:12 AM
People just need to realise about this problem
29 May 2007 at 6:21 AM
Re#45 Ray misses the point, the question isn’t about intensive properties.
There is a mean baromatic pressure at my locale, averaged over many years, let’s say exactly 760mm or 1 bar. If I diligently collect daily data for 1 year and the average pressure for that year is 765mm, I would presume that one interpretation might be that there has been fairer weather there than usual for that particular year.
Who measures the possible change in the absolute air pressure globally?
The composition of the atmosphere as ppm by volume may remain constant, apart from the mean increase year on year of ca.delta 2ppm by volume of CO2. Hence, if you refuse to discuss it fair enough. I presume you assume the mass of the atmosphere is conserved.I would be surprised if it were conserved even over a short period such as a century. Were it also increasing, although it wouldn’t figure in the radiation balance, it certainly would further enhance the GHG effect.
[edited]
29 May 2007 at 7:39 AM
B.R. Says in #50:”It is a time spirit working here, one of rebellion against the industrial revolution, a romantic longing to a virgin world, that brings people to target our capitalist consumption society.”
Sorry, this is absolute horse puckey. B.R., do you even know any scientists? I doubt most of these guys even own a copy of Walden Pond! And if they do, it’s probably on their iPod. There is no spirit of rebellion. This is not about ideology, but rather about evidence. The science is pretty much incontrovertible–we are changing the climate. What is less certain is what the effect of these changes will be. However, we will be better able to deal with those changes if we manage the rate at which they occur by limiting our greenhouse gas emissions. If you want to protect our “capitalist society”, you had better act now before draconian measures are needed.
29 May 2007 at 8:22 AM
“Attention pressure-change folks — as long as the Earth’s volume is unconstrained, and it is, its surface pressure is not going to vary very much.”
if P = (M / A) g, will not V, T and P all vary during the day/night cycle?
How do you model the changes in water rich gas V,T and P when the day/night cycle involves water pricipitation?
This is an actual question, a point scoring? What happens to the gas law assumptions when you are dealing with the transition from a single to two phase system, that is water as a gas and then water in the form of droplets. Are the changes manifest in temperature, pressure or volume?
Is a model of the Earth atmosphere as a ballon reasonable?
29 May 2007 at 9:25 AM
DocMartyn, in terms of global properties like whether the atmosphere obeys the ideal gas law etc, consider that ~80% of the atmosphere is N2, with most of the rest being O2, Argon… Most of these molecules are rather inert and stable, so any deviations from ideality are small and mainly only observable at very high or very low pressures.
The atmosphere behaves as a fluid held in place around Earth by the gravitational field. The geomagnetic field is what insulates it from the solar wind so the outer layers are not ripped away. In terms of expansion, I would think that this would be dominated by the outer atmospher–which accounts for most of the volume and little of the mass. The thing is we know how gases behave as a function of temperature and pressure. There’s no new physics here.
29 May 2007 at 9:32 AM
Nigel Williams (#38) wrote:
Hardly.
What it supports is the conclusion that you shouldn’t have a local yahoo and total nitwit in charge of the equations. They work very well when they are the correct ones, - as long as the gravity model does. And people want to save time going from point A to point B, therefore the gravity model works quite well.
However, in modeling traffic they run into a real problem because they are basing their equations off of an equation that calculates speed as a function of volume - which assumes a one-to-one. That assumption breaks down in the context of high congestion where a given volume (cars per hour passing a given point) corresponds to a continuem of speeds.
And what can we conclude from that? Volume isn’t a very good variable for calculating speed in times of high congestion. Unfortunately it is pretty much all they have. Density (vehicles per lane mile) would work far better at all speeds. Unfortunately, it is far more difficult to measure density - you can’t just run a weight sensitive rubber pipe across a road to measure that.
However, in climate modeling, which is admittedly far more complicated, you have a great deal more variables to play with - and a great deal of climate modeling is based upon principles of physics - quite possibly all of it. Of course, one might ask whether there might be some unknown or perhaps even unknowable force which will suddenly cause our models to break down - something that no matter how well they might work reality will take a left when we were expecting a right even though our equations were quite accurate all the way up to that point, accurately describing a whole host of phenomena in large variety of contexts up until that magical point.
But one could say the same thing about physics.
There are problems with the climate models we currently have. We know that their estimates are conservative. We haven’t taken into account all of the positive feedbacks relating to ice or the carbon cycle. But virtually all of the feedbacks that we know we are missing are positive feedbacks, and as such, we are able to say that the models are conservative. Given the positive feedbacks, it is quite likely that projections are rosier than what we will actually face, and therefore the urgency with which we should act is greater than what they currently project. However, the carbon cycle is an area of active research as is the cryosphere, so it is quite likely that models will even more accurate in the future.
This rises above politics, gentlemen. I am uncomfortable with environmentalism, I often think it is taken too far, but this science. Given what is at stake, we must learn to work together despite our differences.
29 May 2007 at 9:50 AM
When you say “skillful scale” do you just mean effective resolution?
Think of a sine wave. Regardless of the grid size (or equivalent grid size for a spectral model), you need two grid lengths (or three grid points) to minimally resolve half of the wave. You need four grid lengths (five grid points) to minimally resolve a full wave pattern. In numerical weather prediction, the effective resolution is typically taken to be about ten grid lengths. Phenomena smaller than that are not well-resolved at grid scale, so they should be parameterized.
So, a regional numerical weather prediction model with grid resolution of 10 km can adequately resolve meteorological phenomena of length scale ~100 km.
GCM’s these days may have resolutions of around 1 deg or 111 km, so their effective resolution would be more than 1000 km. That’s the length scale of features that they can adequately resolve.
29 May 2007 at 11:09 AM
Bzzt! The link behind the name in #55 is another “search engine optimizer” and “global warming awareness” competition counter.
29 May 2007 at 11:31 AM
Re#53 Barton’s quote “But the Earth’s atmosphere has had a very consistent makeup for the last several million years at least.”
By “make up” I presume you mean, firstly, composition eg. O2 20.95% by volume or Ar 0.93% by volume.
The O2 content and N2 contents are biologically controlled, way above thermodynamic values. The Ar isn’t the known cosmic abundance, which is pertinent to 36Ar. 36Ar and the other noble gases Ne up to Xe are million folds depleted on Earth, lost during planetary accretion whereas water H20 was presumably retained as hydrates. Atmospheric 40Ar has been built up slowly by radioactive decay of 40K. This is the one atmospheric gas that one could say, secondly,that “it’s mass balance has been effectively constant over millions of years”.
Where’s the evidence that the M has remained constant for millions of years let alone hundreds? Plenty of scientists make this assertion but where is the empirical evidence to support it? It’s one thing to cite CO2 concentrations, tens of thousands of years ago as ppm by volume but in doing so you make the hidden assumption that mass is conserved.
Geochemical abundances of elements in the Earth’s crust are notoriosly innaccurate in several instances. For instance the molecule water, or water budget, in oceans and lakes etc neglects the more than 10% mass that has been subducted at plate boundaries. Years ago Walker upset the carbon budget by a wild unsubstantiated claim that the mantle contained contained at least seven fold the mass of carbon estimated for the crust, yet granites and basalts are vastly depleted in volatiles.
Does anyone know of anyone who calculates the year on year mean sealevel atmospheric pressure for the globe inorder to check its constancy? Since 40Ar is essentially constant in mass it would be nice to see the other ephemeral gases related to it before paying sole attention to intensive properties. If the mass balance changes, due to N2 and O2 variations, the effect on GHG ppm by volume concentrations certainly will also vary, even though the diatomic gases don’t contribute to GW.
29 May 2007 at 12:08 PM
Re 63. Graham, Sorry, but if there was a point in there I missed it. I rather doubt that the biosphere impacts the 80% nitrogen content of the atmosphere. I don’t even know what you mean when you say the geochemical abundances of elements in Earth’s crust are inaccurate–with respect to what. They can certainly be measured to arbitrary accuracy, don’t you agree? Do you mean that they vary from place to place? As to H2O, it is important in mantle chemistry, but volcanos also give off a lot of water vapor–it’s probably balanced. I can see why O2 might change wrt very large changes in biomass, but not Nitrogen. And as far as conservation of mass, can we at least stipulate the laws of physics?
29 May 2007 at 12:09 PM
There’s one for the standards committee.
“…. a standard atmosphere at sea level is approximately equal to 760 millimeters of mercury, 29.92 inches of mercury, 1.013 bars, 1013 millibars, 14.70 pounds force per square inch, 2116 pounds force per square foot, or 101.325 kilopascals.”
(Quote from a page with one of the better rants I’ve seen about measurement units:
http://ourworld.compuserve.com/homepages/Gene_Nygaard/hectopas.htm )
So, it makes sense to define atmospheric pressure at sea level, because, well, that’s the bottom of the atmosphere, ignoring places like Death Valley that are basins below sea level. What difference will it make when sea level rises? This is where the contemporary rate of change — so much faster than anything anticipated when the standards were defined — can be a puzzle.
Now raising your barometer ten meters is certainly going to show a difference, if it’s a good tool. My old Thommen altimeter certainly detects that change.
But if you then also raise sea level by ten meters to catch up with the barometer — moving the whole atmosphere up the same distance as the barometer — how much difference do you get? The atmosphere’s a thin spherical shell and you’ve increased the inside radius of the atmosphere ten meters.
29 May 2007 at 1:21 PM
Actually, Hank, it’ll get more complicated than that. We’re changing solid H2O to liquid, so it will flow toward the equator to balance centripetal acceleration. Earth may become more oblate and sea level may rise more in the tropics than at the poles; the rate of rotation might change (albeit very slightly). I’ll leave that to my buddies with the atomic clocks and platinum-paladium blocks to figure out.
29 May 2007 at 2:10 PM
Re #65 Hank,
For an increase in altitude of 300 feet the temperature decreases by 1 deg F. So raising sea level by 10 m (approx. 30 feet)will raise the temperature everywhere that land still exists by 0.1 deg. F.
However, barometric pressure depends on the weight of the column of air above that point, and since there is no change to the total air covering the Earth when sea level rises, the barometer readings will increase by the amount of air in a 10 meter column at any fixed point at or above the new sea level.
Cheers, Alastair.
29 May 2007 at 3:08 PM
Re #54 How about Arctic warming in the 1930s-40s?
[Response:See the Delworth and Knutson (2000) article in Science. They use simulations of a coupled model to show that this could easily have arisen from the intrinsic natural variability of the climate at multidecadal timescales. -mike]
29 May 2007 at 3:42 PM
Re: reply in #68
And so the exact same thing - an unusually large realization of internal multidecadal variability of the coupled ocean-atmosphere system - can not possibly be occuring today?
[Response: No. Precisely the same thing could of course be happening today. However, such internal variability (both in this model, and all other current generation coupled climate models) is unable to generate a century-long trend in global mean temperature anywhere close to that observed for the past century. Indeed, it is precisely this issue which is addressed in a rigorous, quantitative manner by model-based detection and attribution studies. See our previous review of the topic. -mike]
Please note: the conclusion here would depend on one’s uncertainty surrounding the interactions among the model’s estimated parameters. (I don’t take these estiamtes as error-free.) So … what’s the chance that the CO2 sensitivty forcing coefficient is off by 10% 20% 50%?
I’ve read AR4. Please don’t assume I haven’t.
[Response: I wouldn’t assume you not to have read the report. However, based on your comments above I might call into question your comprehension of its content. -mike]
29 May 2007 at 3:44 PM
“Alastair
For an increase in altitude of 300 feet the temperature decreases by 1 deg F. So raising sea level by 10 m (approx. 30 feet)will raise the temperature everywhere that land still exists by 0.1 deg. F.”
I was under the impression that ice was less dense than liquid water, so melting ice into liquid water will reduce the surface/water volume of the Earth.
Moving the atmospheres 5.14 x 10^18 kg a distance of 10 meters requires a potential energy of 5×10^16 J.
29 May 2007 at 3:48 PM
Re#64 Ray, we agree where O2 in the atmosphere comes from. It comes partly from the tiny fraction of reduced carbon in biomass that is buried and becomes fossil carbon ie. as coal, kerogen(from which come hydrocarbon gases and oil).The ratio of reduced carbon to carbonate carbon in the crust is thought to be ca. 1 part in 4 or 5. Free O2 also comes from the incorporation of sulphide(and free sulphur from bacterial reduction) as pyrite, also coeval with kerogen formation. At the same time sulphate(as anhydrite or gypsum)is buried but not in similar environments. The ratio of sulphate to reduced sulphur is thought to be ca. 1 to 1. What limits O2 increase is oxidation. Ferrous iron is dominant in the crust,8.6% by mass it rusts through to ferric hydroxide hydrate,(Fe(OH)3.5H20.
In terms of abundances in the crust, oxygen like Si and Al is huge. For every 1 atom of carbon in the crust in general there are ca. 30 each for O, Si and Al. For every 1 atom C there is thought to be ca. 0.5 atoms S in the crust, but the sulphur abundance is imprecisely known(ca. 20% error!). For every carbon atom there are 4 atoms of iron Fe(largely ferrous)and for calcium and magnesium also.
Distribution of elements is not even throughout sedimentary basins, unlike the basaltic crust of the young ocean floors. Thus 10% of the salt(NaCl)content of the oceans is buried beneath the Mediterranean; this figure probably includes associated anhydrites(sulphates), known as sabhkas in the present day Arabian/Persian Gulf. The limited areas of sedimentation are controlled by biomass.
Nitrogen is very low in igneous and basic rocks, it tends to be recycled in kerogens and coals. Whereas atmospheric abundances for O and C are tiny in comparison with the crust, nitrogen accumulates in the atmosphere. It is highly unstable there as every storm produces nitrate, a limited nutrient in the oceans and soils as it is rapidly incorporated as biomass in DNA and proteins. Nitrogen is under as much control by biomass as is oxygen! So for 1 atom of C in the crust how much nitrogen is there in the crust plus atmosphere? No-one knows the error is likely to be several fold. Although not a noble gas, it is depleted relative to cosmic abundance. On a reduced accreting Earth N as ammonia? was lost.
Our Earth, re- climate change, it is often presented as a giant acid/base system(are the oceans becoming more acdic. For millions of years the silicate and borate buffers help maintain ph at ca. 8.2, even with the introduction of volcanic acid volatiles, largely SO2 cf. CO2)). The oceans never become too saline due to evaporite basin formation.
Urey portrayed the acid plus base =salt plus water reaction as the reaction of - calcium carbonate(CaCO3) plus silica(SiO2) to give wollastonite(CaSiO3,igneous at depth) plus CO2 and its reverse.
The Earth’s crust is also a giant oxidation/reduction system-
C + 2Fe2O3 reacts to give 4FeO plus CO2. Those ferric atoms chelate 10 molecules of water, that so happens if you multiply up for the 2.2*10^22kg crust to give 1.46* 10^21kg of water,very close to the known mass of water on Earth.
Up to 36% of the mass of the Earth is free iron(Fe). Homogenise everything and we would return to a highly reduced planet. Brian Mason in the 60’s calculated that since the last 570 million years(Phanerozoic)biomass has recycled a total mass of elements equivalent to more than 50 fold the Mass of the Earth! The mass and composition of the atmosphere is under total control by the biosphere.
Re- mass conservation. Geochemists use an identical atmospheric mass, namely 5.12*10^18kg, dry air, as the rest of you, but we don’t know what it was 100years ago let alone thousands or millions.
Cosmophysicists, cosmochemists and physicists express solar abundances and cosmic abundances as atoms per 1000 atoms Si; climate scientists probably don’t bother.Let’s call these silicon chauvinists. Carbon biomass chauvinists, who aren’t short and vice versa are interested in climate change. Were one to approach the atmosphere,crust and oceans from the biomass point of view it would look like on an atom per atom basis, as I introduced earlier-
C(1)1, S(0.5), Ca4, Fe4,Mg4,H2O(10)……..Si30,O30,Al30
or
S1, C2, Ca8,Fe8 etc.. if you are a sulphur chauvinist.
When I read that the CO2 content of the atmospheree. say in the Younger Dryas at ca. 10000yr was 270ppm by volume, I automatically think but what was its total mass in the atmosphere? Is the atmospheric mass conserved over that time period? I don’t know; I just hope someone wouldstart to measure it with the motivation that Keeling had, and not to continually assert it is conserved without measuring it.
29 May 2007 at 4:15 PM
Re: reply in #69
“models … unable to generate a century-long trend in global mean temperature anywhere close to that observed for the past century”
I understand the reasoning, but why “century-long”?
You have the 1930s-40s warmth - an a posteriori “fit” as an anomaly, the 1960s-70s aerosol cooling (another a posteriori “fit”, uncertainty about which is well-known), and the recent 1998-2007 leveling-off of global mean temperature. That leaves two only *two* decades, not ten decades, that need explaining: 1980s-90s. So why not *probable*, why only “possible” that this was an anomalous warming pulse similar to that of the 1930s-40s? 20 years’ worth of anomaly is not as unlikely as 100 years’ worth. Especially relevant considering PDO went inexplicably positive in 1976. That’s presumably a good chunk of the puzzle?
Anomaly after anomaly after anomaly. That’s chaos, no?
Thanks for the replies. Much appreciated. We need to get this right and there’s not much time.
29 May 2007 at 5:45 PM
Re #71:
Atmospheric pressure times surface area is, by definition, the mass of the atmosphere. There are no magical forces holding it up, and the only force pulling it down is gravity, which exerts a force proportional to the mass. We know that barometric pressure has been reasonably constant (on average, excluding storms, etc.) since the invention of the barometer by Torricelli nearly 400 years ago. Given the climate swings in that length of time, it’s safe to assume that the mass of the atmosphere is reasonably constant over century-long periods and over periods of cooling as well as warming.
29 May 2007 at 6:20 PM
> 1998-2007
How much do you believe a nine-year trend is more reliable than a five-year trend?
Do you believe it’s any different when the first year of the nine years picked is an El Nino year?
http://scienceblogs.com/stoat/upload/2007/05/5-year-trends.png
29 May 2007 at 6:32 PM
“Anomaly after anomaly after anomaly. That’s chaos, no?”
No, anomaly after anomaly after anomaly is called giving up. Persisting in investigating the anomalies until you understand their cause–that’s called science.
Actually there were may atmospheric scientists in the 50s-70s that attributed the lack of warming to aerosols from combustion of fossil fuels–the models now say that was a highly credible hypothesis. The anomalous warming in the late 30s and early 40s is still considered anonmalous. However, I do not consider this a satisfactory “resolution”. It may have been a more or less local effect, but even that is not known at present.
Physicists like me get nervous when people attribute warming to “natural variability”. The energy has to come from somewhere–particularly as much energy as we are seeing dumped into the climate system in the current warming epoch. Again, climate scientists have a self-consistent and highly plausible picture. It cannot be the sun, as solar output has not increased enough. It cannot be water vapor–too variable. Next in line is CO2. If you dismiss that, well, you got a source with a few yottajoules (always wanted to use that prefix!) sitting around?
29 May 2007 at 6:59 PM
ray ladbury (#75) wrote:
Pinatubo basically cinched it for a great many scientists that aerosols could produce global dimming and mask the effects of global warming. Likewise, we know that there was a drop in temperature as the result of flights being grounds after 9/11 - from what I understand. The effects of aerosols is measurable and regular.
After the fact? Nope. Ad hoc? Certainly not.
Then of course, if one takes any one decade of the twentieth century in isolation, few are statistically significant. Any one year by itself is even less “significant.” But the overall trend is quite significant - and in line with the positive feedback relationship we have seen between CO2 and temperature over, what is it now?, one million years? A heckofalot to explain away as coincidence - and that is basically what one is doing when one attempts to explain fairly well-defined patterns simply by reference to “chaos.”
29 May 2007 at 7:55 PM
FurryCatHerder
“We know that barometric pressure has been reasonably constant (on average, excluding storms, etc.) since the invention of the barometer by Torricelli nearly 400 years ago.”
Why should pressure remain constant when temperature changes?
What is the basis for this statement?
29 May 2007 at 8:32 PM
DocMartyn, think about the physics. What is the cause of the pressure? The column of air above the point on the ground. Even if the air expands, you will have the same weight of air above that point, so the pressure (weight of the air column divided by area) will remain the same.
29 May 2007 at 8:45 PM
#74, #75, #76: You guys are parsing the text (#72) and poking holes without attacking the argument - and in doing so you’re, to some extent, making my argument for me. Shall I explain, or are your minds made up already?
29 May 2007 at 8:47 PM
RE#72, bender, As far as the PDO going ‘inexplicably positive’ in 1976, do you want to provide a reference to that?
This argument, that all climate variability is due to various ‘natural cycles’, all of which just happen to be in a positive phase (the AMO, the PDO, etc.), isn’t supported. Every time that there is some unusual warming trend, the skeptics immediately claim it was due to some cycle - warm winter in the US? It must be El Nino, no matter how weak. Record warmth in Russia? It must be the AMO, or the NAO. Warmer sea surface temperatures in the Atlantic? It must be that the AMO is in a positive phase. Or it’s the natural sunspot cycle.
So, how do you tell if you are looking at a trend or at a cyclic phenomena, or a cyclic phenomena superimposed on a trend? You can throw your hands up in the air and claim it’s all chaos - or you can take another look at the link posted in the response to your post: Attribution of 20th Century climate change to CO2.
You run the model without the anthropogenic greenhouse forcing and see what the internal variability is. Then you add in the anthropogenic forcing - then you go and compare the model runs to observations.
From Delworth and Knutson: (you edited their results - the part you left out is in bold: “…the warming of the early 20th century could have resulted from a combination of human-induced radiative forcing and an unusually large realization of internal multidecadal variability of the coupled ocean-atmosphere system.” Bit deceptive, isn’t that?
We now assess whether internal variability alone can account for the observed early 20th century warming, or if the radiative forcing from increasing concentrations of GHGs is also necessary. Over the period 1910-1944 (which encompasses the warming of the 1920s and 1930s), there is a linear trend of 0.53 K per 35 years in observed global mean temperature. If internal variability alone can explain this warming, comparable trends should exist in the control run. Linear trends were computed over all possible 35-year periods, using the last 900 years of the control run (i.e., years 101-135, 102-136, …, 966-1000). For each 35-year segment, the time-varying distribution of observed data over the period 1910-1944 was used to select the model locations for calculating the global mean. The maximum trend in any 35-year period of the control run is 0.50 K per 35 years. This suggests that internal model variability alone is unable to explain the observed early 20th century warming.
If internal variability can’t explain the weaker trend earlier in the century, why would you expect it to now, when the trend is much stronger? Keep in mind also that no amount of internal variation can increase the global temperature - that’s just conservation of energy.
[Response: You’re last statement is not quite correct. Internal variations that lead to either a net change in albedo or to greenhouse effects can lead to a global temperature changes. For instance, El Nino events have a global warming impact, and modelled changes in ocean circulation (such as in the N. Atl.) - even though they mostly redistribute heat - can effect sea ice extent and clouds to produce a net cooling. So, while these changes are small compared to the forced changes, they are not zero. - gavin]
29 May 2007 at 8:59 PM
The basis for the statement? Depends. What are you holding constant, what are you varying, what are you measuring?
http://www.chemistry.ohio-state.edu/betha/nealGasLaw/frb4.3.html
Torricelli’s instrument measures the weight of the atmosphere. http://www.imss.firenze.it/vuoto/index.html
Temperature (and latitude) correction tables for using a mercury barometer anywhere in the world (with interpolation) here:
Handbook of Chemistry and Physics: http://216.149.237.254/ei-chemnet/
Temperature Correction for Barometer Readings 83 Ed., p. 15-23
29 May 2007 at 9:33 PM
Ike Solem (#80) wrote:
Ya gotta remember - parsing an argument into points so that you can respond to them - that is what is really unfair. Parsing quotes into pieces that are useful despite what an author actually wrote - is useful. And we shouldn’t give anyone problems if they find that they have to parse the evidence - so that they never have to acknowledge its full weight. It just isn’t about the evidence. Its about winning - and reality would be an unfair advantage - so it can’t be about that, either.
Come on and give the guy a chance…
29 May 2007 at 10:37 PM
A personal view - for what it is worth…
The denialists aren’t out to destroy the world.
What motivates them is something much more mundane: defending their turf or their tribe against their enemies - in the context of an “us vs. them” view of the world. At root, this seems to be a form of primitive tribalism. But what they seem to have forgotten is that they are part of a larger tribe. To be fully human requires you to recognize the humanity in others - even when they don’t seem to recognize it in themselves. If they are truly honorable warriors, if they honor reality, truth and their own humanity, they will come to the defense of their greater tribe - when it needs them most.
29 May 2007 at 10:39 PM
Layer upon layer upon layer of unsupported presumptions, it’s hard to know where to begin.
-It’s not MY model that can’t explain the 1930s-40s Arctic warmth; it’s Hansen’s. Don’t ask me to explain what they can’t.
-mike in reply to #69 is arguing that the anomalous trend is “century long”; but the only trendy part that’s inexplicable is the 1980s-90s portion. You are parsing #72, taking exception to the wording, but not addressing the argument there.
-Ike thinks one can estimate the system’s internal variability by removing the forcings from the model. That’s the hope. But that presumes the models are structurally appropriate. THAT is what I’m disputing. That’s the argument.
-Hank thinks I’m cherry-picking 1998 to exaggerate my point about recent temperatures plateauing; I’m not. They have flattened by any measure, and whether that’s a cyclic deviation or not Hank hasn’t explained why these deviations from a smooth trend happen. They’re not MY bumps; they’re Hank’s. I’m not claiming they’re “natural variability”; Hank is. Natural variability is not something I like to dismiss. It’s something one is sometimes forced to set aside.
-Ike accuses me of selectively quoting for the purposes of deception - which is not an honorable thing to accuse someone of. I’m trying to keep my arguemnts relatively clean to keep them brief. The extra bit doesn’t refute my argument at all; it just helps puts it in context. I’m ok with that.
-Timothy Chase claims reality is on his side, giving him an unfair advantage. Well, Timothy, if the science is SO settled where does mike’s “could, of course” come from in #69? You do not have a monopoly on the truth. mike sees a small crack there. You do not?
-Many here show an unflappable faith in the models, which suggests to me you have no experience in modeling complex dynamic stochastic systems.
-If the weather system is chaotic, then the climate system is chaotic too. I know you don’t agree with this, but I think you may be wrong. Read the full thread by Annan & Connolley and pay close attention to the comments by Pierrehumbert and Held. (That material, though good, is two years old, so also check the more recent literature.)
-If the climate system is (even “sometimes”) chaotic (yes, I know: you dispute even this), then how do you correctly parameterize the numerically stable models such as to mimic the unstable climate? This is a serious problem; it is no joke. My cartoon name is a joke; these points I raise are not. Get past the labels.
-”anomaly after anomaly after anomaly” is me “giving up”? My friend, ray ladbury, do you know what irreducible uncertainty is? It is the futility of what you are suggesting: never give up. When you hit the wall of chaos, you had better know it, and you had better be ready to give up to save your sanity. Hansen et al 2007 suggest exactly this: giving up on the Arctic warming of the 1930s-40s. Why don’t you criticize them?
-PDO dynamics: google PDO will get you started. Hare coined the term. Start there.
Gentlemen, please examine your assumptions. I’m not trying to win a debate or convince anyone of anything. I just think you are not being sufficiently self-critical when it comes to these models, how they are parameterized and what they do and don’t allow you to infer. Remember that attribution is fundamentally a modeling exercise. This argument that weather is chaotic and climate is not - think about it. Chaos is not just inexplicable ups and downs. Only in temporal models does it take that simplistic form. Chaos in spatiotemporal models is marked by bizarre spatial structures (circulatory pathways) that persist for a while, but fade as inexplicably as they emerged. If your models don’t produce that kind of behavior, are they trustworthy? Open question.
That is enough for now. I apologize for the rambling. I think you are trying hard, but maybe have lost your objectivity. There’s lots to pick at in this comment, I know. Please don’t pick. Please hit the argument square on. Think “home run”.
[Response: Your big question concerns the potential structural instability of models, and by extension the structural instability of the real climate. That’s fine, but none of the variations in climate over the last century fall outside of the envelope of forced+internal variation of the structurally stable system so provide no evidence for a deeper instability. Similarly, over the Holocene, with its large precessional trend, there is no such evidence. We do see evidence for threshold behaviour - the drying of the Sahara around 5500 BP that was likely caused by vegetation/climate interactions, but this is still a forced response to the insolation change. Only during the glacial periods (with the Dansgaard-Oeschgar cycles and Heinrich events) do you have evidence for spontaneous and large changes in climate - and even then, this was centered on the North Atlantic and almost certainly involved ice sheet dynamical instabilities.
Thus for the system we have encapsulated in GCMs today (which don’t generally contain either dynamic vegatation or ice sheet dynamics), there is no strong evidence that this system is chaotic anywhere near the part of phase space where we happen to lie. What about evidence from the models themselves? In my experience, I have never seen a GCM demonstrate significant structural instability for any kind of physically valid tweak (coding errors are another story of course). The closest you get is something like THC hysteresis seen in some of Stefan’s work, but again, there is no evidence that we are near those transitions today. However, probably the best argument for structural stability is simply that where the forcings are the same, the response of the system is very similar. Orbital cycles etc. over the last million years, while they have caused enormous climate change, keep producing pretty much the same climate change.
There is of course no possible ‘proof’ that the climate is not near some structural instability, but there is no need for this hypothesis to explain most of what is seen. However, I would hardly take comfort in than thought, and if anything, it might cause one to be more concerned about our future trajectory. - gavin]
30 May 2007 at 12:17 AM
Ike Solem stated: “You run the model without the anthropogenic greenhouse forcing and see what the internal variability is. Then you add in the anthropogenic forcing - then you go and compare the model runs to observations.”
If the climate model is pre-determined to be a fixed-point equilibrium in the absence of external perturbations (as it was frequently stated or implied by their authors), no internal variability could be possibly observed or exist.
[Response: The GCM equilibrium is in a statistical sense, as you well know, and there is plenty of internal variability. - gavin]
“Keep in mind also that no amount of internal variation can increase the g