Guest Post by Steven Goddard
Global Climate Models (GCM’s) are very complex computer models containing millions of lines of code, which attempt to model cosmic, atmospheric and oceanic processes that affect the earth’s climate. This have been built over the last few decades by groups of very bright scientists, including many of the top climate scientists in the world.
During the 1980s and 1990s, the earth warmed at a faster rate than it did earlier in the century. This led some climate scientists to develop a high degree of confidence in models which predicted accelerated warming, as reflected in IPCC reports. However, during the last decade the accelerated warming trend has slowed or reversed. Many climate scientists have acknowledged this and explained it as “natural variability” or “natural variations.” Some believe that the pause in warming may last as long as 30 years, as recently reported by The Discover Channel.
But just what’s causing the cooling is a mystery. Sinking water currents in the north Atlantic Ocean could be sucking heat down into the depths. Or an overabundance of tropical clouds may be reflecting more of the sun’s energy than usual back out into space.
“It is possible that a fraction of the most recent rapid warming since the 1970’s was due to a free variation in climate,” Isaac Held of the National Oceanic and Atmospheric Administration in Princeton, New Jersey wrote in an email to Discovery News. “Suggesting that the warming might possibly slow down or even stagnate for a few years before rapid warming commences again.”
Swanson thinks the trend could continue for up to 30 years. But he warned that it’s just a hiccup, and that humans’ penchant for spewing greenhouse gases will certainly come back to haunt us.
What has become obvious is that there are strong physical processes (natural variations) which are not yet understood, and are not yet adequately accounted for in the GCMs. The models did not predict the current cooling. There has been lots of speculation about what is causing the present pattern – changes in solar activity, changes in ocean circulation, etc. But whatever it is, it is not adequately factored into any GCMs.
One of the most fundamental rules of computer modeling is that if you don’t understand something and you can’t explain it, you can’t model it. A computer model is a mathematical description of a physical process, written in a human readable programming language, which a compiler can translate to a computer readable language. If you can not describe a process in English (or your native tongue) you certainly can not describe it mathematically in Fortran. The Holy Grail of climate models would be the following function, which of course does not exist.
FUNCTION FREEVARIATION(ALLOTHERFACTORS)
C Calculate the sum of all other natural factors influencing the temperature
…..
RETURN
END
Current measured long term warming rates range from 1.2-1.6 C/century. Some climatologists claim 6+C for the remainder century, based on climate models. One might think that these estimates are suspect, due to the empirically observed limitations of the current GCMs.
As one small example, during the past winter NOAA’s Climate Prediction Center (CPC) forecast that the upper midwest would be above normal temperatures. Instead the temperatures were well below normal.
http://www.cpc.ncep.noaa.gov/products/archives/long_lead/gifs/2008/200810temp.gif
http://www.hprcc.unl.edu/products/maps/acis/mrcc/Last3mTDeptMRCC.png
Another much larger example is that the GCMs would be unable to explain the causes of ice ages. Clearly the models need more work, and more funding. The BBC printed an article last year titled “Climate prediction: No model for success .”
And Julia Slingo from Reading University (Now the UK Met Office’s Chief Scientist) admitted it would not get much better until they had supercomputers 1,000 times more powerful than at present.
“We’ve reached the end of the road of being able to improve models significantly so we can provide the sort of information that policymakers and business require,” she told BBC News.
“In terms of computing power, it’s proving totally inadequate. With climate models we know how to make them much better to provide much more information at the local level… we know how to do that, but we don’t have the computing power to deliver it.“
……
One trouble is that as some climate uncertainties are resolved, new uncertainties are uncovered.
Some modellers are now warning that feedback mechanisms in the natural environment which either accelerate or mitigate warming may be even more difficult to predict than previously assumed.
Research suggests the feedbacks may be very different on different timescales and in response to different drivers of climate change
…….
“If we ask models the questions they are capable of answering, they answer them reliably,” counters Professor Jim Kinter from the Center for Ocean-Land-Atmosphere Studies near Washington DC, who is attending the Reading meeting.
“If we ask the questions they’re not capable of answering, we get unreliable answers.“
I am not denigrating the outstanding work of the climate modelers – rather I am pointing out why GCMs may not be quite ready yet for forecasting temperatures 100 years out, and that politicians and the press should not attempt to make unsupportable claims of Armageddon based on them. I would appreciate it if readers would keep this in mind when commenting on the work of scientists, who for the most part are highly competent and ethical people, as is evident from this UK Met Office press release.
Stop misleading climate claims
11 February 2009
Dr Vicky Pope
Dr Vicky Pope, Met Office Head of Climate Change, calls on scientists and the media to ‘rein in’ some of their assertions about climate change.
She says: “News headlines vie for attention and it is easy for scientists to grab this attention by linking climate change to the latest extreme weather event or apocalyptic prediction. But in doing so, the public perception of climate change can be distorted. The reality is that extreme events arise when natural variations in the weather and climate combine with long-term climate change. This message is more difficult to get heard. Scientists and journalists need to find ways to help to make this clear without the wider audience switching off.
Very few people ever talk about the effect of solar flares or the suns activity as it relates to earth’s temperature. You wonder why? Could it be that this is just a liberal agenda?
http://conservative74.wordpress.com/
I see that the confusion between climate and weather is reflected at the NOAA site, where the National Weather Service has a Climate Prediction Center that offers a 6 Day Outlook.
It is repeatedly said that the climate is an average of the weather observations, so, presumably, a climate prediction is an average of weather predictions.
It’s not surprising that climate models are actually weather models.
In my view, climate is not described by an average of the weather but by a generalisation about the weather. It’s the same sort of distinction that eluded the very enthusiastic proponents of Artificial Intelligence and natural language generation.
Stephen Skinner (13:49:34) : Is this how it was on Easter Island?
My L.I.R. (Large Imaginary Rabbit) model shows, after thousands of runs, that on average a 10′ tall pink rabbit will destroy 10 acres of forest per year given the average deposit of 200 colored eggs per acre per year. I can project this with 95% confidence.
anna v (08:57:30):
Green houses, the real ones, flourish with 1000ppm CO2. The alveoli in our lungs work with something like 8000 ppm, saying something about when lungs evolved: when CO2 was much more abundant. ( unless you do not believe in evolution).
Dear Anna,
Yes, you’re right; and we blow out 53000 ppmV of CO2 in a single breath.
G Alston:
If the most important phenomena are well understood and included in the model then the model can be predictive, as in your “wing” example. However, if many of the phenomena are poorly understood or are known to only pertain to a restricted regime of the phase space, the model is still useful even though it may not be predictive. Often In such cases, the model will be predictive for some portion of the phase space, but not for all possible conditions. So, by studying where the model fails it is possible to understand the limits of the assumptions and to understand how those assumptions break down. It is this understanding of when basic assumptions break down and how much error this introduces that is the underlying goal of science.
As for your comment:
“This begs the question of how politicians etc become aware of models in the first place. Politicians become aware of these models only when they are used as a presentation to make a prediction which impacts policy.”
This might be true if science took place in a vacuum. However, it is usually desirable, especially in such a multi-disciplinary field as climate science, for scientists developing models to communicate. This means presenting models, even incomplete models, at conferences and publishing results and techniques in journals. The problem comes, when policymakers who are providing funding expect to receive predictive models before the science is sufficiently mature to provide them.
In my experience (modeling, but not climate modeling) usually, what ends up happening is that someone (a government official, somebody’s boss or supervisor, etc…) starts asking for predictions based on a model’s results. At first the scientists are pretty good about including caveats about the model’s validity and the accuracy (or lack thereof) of the prediction. However once the predictions are made they take on a life of their own and get used for a variety of purposes both for which they were not intended and for which their validity is extremely uncertain. Often the scientists own disclaimers are ignored by the decision makers and others who propagate his work. At this point the cat is out of the bag and there is little the scientist can do to prevent the misuse of his results.
Computer models tell you the consequences of your premises.
If you can apply them to very well known causal patterns and capacities repeatedly, so that they can be tested again and again against real-world outcomes, you can reach a state where they are accurate tests of real-world outcomes. (In other words they and their constituent elements have been subjected to repeated, controlled, empirical tests.) Engineering models are in that situation.
Climate models, and financial models, are not.
Perhaps I don’t understand how you arrived at the 3% increase/year. If the annual increase in CO2 ppm is 2, wouldn’t the increase as a per centage be (2/390*100=0.5%/year)? Much less than the claimed 3%.
Or, maybe alternatively, you are saying that – of the annual 2ppm – 3% is anthropogenic? If so, then 0.03*2=.06ppm (anthro) and the remanining 1.94 natural?
What?
jrshipley,
No one is doing any experiments with the climate.
Power plants and cars exist because people’s livelihoods depend on them. Our ancestors didn’t like freezing in the cold and dark, and didn’t have time for playing mental games about whether or nor Gaia is happy about their decision not to freeze.
SemiChemE:
“In many cases the purpose of a model is not so much to make accurate predictions as to provide a means to test the basic assumptions upon which the model is based. In short, a model provides a means to relate one set of observables to another set of observables and to understand these relationships.”
How do you test the basic assumptions of the model without making some kind of prediction? It sounds like you are describing a process of predicting a value for one or more “observables” for the purpose of testing a presumed relationship between them. If you intend to say that the accuracy of that prediction is of no import in that even an inaccurate prediction marginally improves your understanding of the modeled system by telling you that something must be wrong, I’d agree, but with the caveat that this argument assumes that you can make sufficiently detailed measurements of the real system along with matching predictions of those measurments so as to determine which aspects of the model might be correct/incorrect. With existing climate models, I don’t believe that that is the case.
Steven. I think that matters are a bit more scientific than “guessing Gaia’s feelings”. Also, I think the alternative to changing the climate is moving into caves. Nevertheless, I understand that your retreat to hyperbole is necessitated by the untenability of your position and that a clever turn of phrase in front of an approving audience can be a source of self esteem. That is, I see why you’d say all that.
However and indeed, a simple notion of “experiment” will suffice to make my point. As has been pointed out, we cannot know with absolute certainty what continuing to increase the amount of CO2 in the atmosphere will mean for sea levels, to focus on one concern. It could be not as bad as the IPCC predicts or as recent research indicating accelerated melt rates may indicate it could be much worse. To do the experiment in this case is just to continue to dump increasing amounts of CO2 in the atmosphere. As curious as I am to find out for-absolute-certain whether [snip] who say sea level will stop rising or the conservative IPCC estimates or the more alarmist predictions are correct, I am not so curious as to risk great harm to my fellow humans.
LOL. I meant of course: “Also, I don’t think the alternative to changing the climate is moving into caves.”
Roger Sowell:
“Could the results be used to better tell you what the thermal conductivity of the pipe wall is, if it were not possible to meause that thermal conductivity in the real world?”
Actually, I believe the answer to that is yes, but only if one is able to measure the outer wall temperature, that is, the edge of the insulation exposed to the atmosphere. If one is unable to measure that outer wall temperature, the problem becomes indeterminant. There would be too many unknown variables, and not enough equations.”
Sorry, I should have been more clear in the hypothetical. Indirect measurements count – if you are able to calclulate the thermal conductivity using an already-proven equation along with measured values for other system elements, surely that counts as an ability to measure the thermal conductivity of the real-world pipe.
Steven Goddard (08:32:41): “The EdGCM Project develops and distributes a research-quality global climate model (GCM)“ This is not what you referred to in your post, just an after the fact Google scrape. It was a GLOBAL CIRCULATION MODEL graphic that you showed in your post and linked to. It is the GLOBAL CIRCULATION MODELS that require massive computational horsepower.
“Obviously you can’t model a physical process which you can’t describe mathematically.” Your post talks about needing to EXPLAIN something before you can model it, now you are falling back to simply needing to be able to DESCRIBE it. This emergence of common sense deflates your whole assault, doesn’t it?
I’d still like to know what the “fundamental rules of computer modeling” you are upholding are. (“Not what those guys are doing” doesn’t count.)
jrshipley (12:44:38) :
. As curious as I am to find out for-absolute-certain whether [snip] who say sea level will stop rising or the conservative IPCC estimates or the more alarmist predictions are correct, I am not so curious as to risk great harm to my fellow humans.
But you are willing on the off chance of IPCC being correct to bring the western economy to its knees, the populations back to the middle ages, ( life expectancy 35yrs) and condemn billions in third world countries to starvation.
An altruist for sure.
The only scenario in Hansen’s graph you linked which showed a seven year cooling trend was Scenario C, which is based on low CO2 increase. The actual CO2 increase has been higher than scenario A.
Steven, did you calculate a trend from scenario B starting around 1990?
Steven, did you calculate a trend from scenario B starting around 1990?
(this sentence shouldn t have been part of the quote)
here is the link again:
http://www.realclimate.org/images/Hansen06_fig2.jpg
1973 is another nice starting point, when looking at the scenario B trend…
@kurt
Well, I was using the hot pipe with insulation merely as an example of why we must at times use trial and error calculations. For boundary layer problems such as the cells and grids in GCMs, one presumably assigns a temperature to each wall of a cell (5 for ground-level, 6 for all others, 1 per face of a cube), and solves the various heat and mass transfer equations. It may be that the ground surface temperature, as measured, is input into the model as the bottom face of appropriate cells. Where calculated temperature values do not match those assumed, iterations are required.
This assumes that the equations behave such that each iteration converges to a temperature, and the temperatures do not instead diverge. I believe this is where the chaos ideas enter the problem, but I do not yet know enough about that to discuss it. But I will.
By the way, glad to see you on WUWT. I am a fellow attorney, chemical engineer, and may soon take the patent bar myself. My work involves climate change law.
anna v (13:17:41) :
Hear, hear! Atta girl. Bullseye. Let him have it with both barrels!
A while back I watched an interesting youtube video http://www.youtube.com/watch?v=xHWTLA8WecI&NR=1 and this post reminded me of a thought I had as I looked at it. Perhaps it would be a more productive use of all that supercomputer computational power now used for running GCMs, seemingly for the sole purpose of reinforcing the prejudices of the programmers, to feed a continuous stream of all the new technical data we produce every day, along with any data we have previously archived, into these machines and have them run pattern recognition algorithms to identify possible cycles, periodicities, and or correlations. The output of this first level of analysis would be fed through further programs designed to isolate cycles that were merely coincident, from those that had possible cause and effect relations. After a cascade of increasingly sophisticated levels of analysis the output would hopefully help us focus on the most productive areas of inquiry. The goal of the system would be to create synthetically that which has always marked the best scientists of the past, but seems to be disappearing in the population of modern scientists, who endlessly proclaim to have the answers to all mankind’s problems. The best scientists of the past recognized, that as they pursued their questions, science would rarely, if ever provide them with answers, but if done properly it would allow them to ask better and better questions and the ones who are now recognized as geniuses shared one quality, the ability to ask the best questions.
Sorry to be quoting myself, but I accidentally posted this on the wrong thread.
kurt (19:49:39) :
Lots of good points in that comment, and one I want to respond to is the idea of having a theory, and a model for that theory, without corresponding observational data.
The example I have in mind is Einstein’s theory of relativity. Specifically, the portion that holds that time dilates as velocity approaches the speed of light. There was no way we knew of to obtain data to test that, until the Apollo program where spacecraft reached high speeds just before re-entry to Earth’s atmosphere. As I remember reading at the time, NASA placed one of two identical, synchronized, and highly accurate clocks in the spacecraft, with the other on the ground. The difference in time readings after the spacecraft landed was exactly what Einstein’s theory predicted, for the velocities achieved.
I am certainly no expert in theoretical physics, but from my readings I am led to believe that physicists made good use of Einstein’s theory before the time dilation tests in the late 60’s.
Another, that you mentioned, is the Bohr theory of the atom. Chemists did good work with that theory, even though the later theories of shells (s, p, d, and f, if I recall correctly) gave better agreement with experimental data.
The opposite is true, of course, as you explained regarding the helio-centric theory of the solar system.
I am not a scientist nor a meteorologist by any stretch of the word. I claim no expertise on these matters beyond common sense and a deep love for my planet.
From what I have read on this blog (and I could be wrong here) it seems to this layman that Watts and his guest writers are attempting to explain away global warming as a bunch of liberal huey.
Perhaps this brouhaha is exagerrated, since when did the media in all it’s spectrums (right, left, conservative, liberal, counter-culture etc.) ever turn down an opportunity to sensationalize a subject? This being said however, I find it hard to accept that there will be no reprecussions for our oil addiction.
I have read both sides of the debate, from natural variant models to human green-house emissions and while not claiming a text-book knowledge of the complex algorithms, feel I have an educated layperson’s understanding.
Either way one looks at the issue, the carbon emissions we pump into our atmosphere, along with the pollution from chemical plants, over-fishing of the oceans and deforestation of old growth forests cannot be beneficial to our quality of life or the balance of the ecosystem.
I admire that this blog is seeking to present the other side of the debate, but I cannot believe that our destructive habits will have no effect upon our Blessed Planet.
nakedwoadwarrior (14:40:22) : said
“From what I have read on this blog (and I could be wrong here) it seems to this layman that Watts and his guest writers are attempting to explain away global warming as a bunch of liberal huey.”
You are wrong here-it is not liberal huey we object to but unscientific liberal huey: There are now so many of us living on the planet that we will cause damage to it at some point-so if you can hatch a clever plan to get rid of around 50% of the population there might be a chance to return it to the pristine state you seek. The carbon emissions-which to this day have never been PROVEN to cause the dramatic warming claimed-are the least of our problems.
Best wishes-keep reading and blogging here
Tonyb
nakedwoadwarrior,
It is wonderful that you are concerned about the environment, but what does overfishing have to do with GCM’s? Do you think a cap and trade scheme will reduce pollution from chemical plants?
By lumping unrelated environmental issues together in one pot with CO2, unscrupulous people are predating on concerned citizens like yourself. Suppose the protesters had of been successful in shutting down the Capitol Power Plant. How much immediate human misery would that have caused?
“…but I cannot believe that our destructive habits will have no effect upon our Blessed Planet.”
I agree that the planet is blessed, but who has it been blessed by? I believe that the planet has been blessed by the appearance of man. Just as we are blessed to have this home. Not one climate realist wants to harm our planet.
Mother Earth loves CO2. The paltry 400PPM or so that exists now is a meager amount for a biosphere that thrives on 1,000PPM and more. Open the floodgates of CO2 and watch our planet return to all her green glory!
Don’t let the politicians take us into a backwards dying earth. Move forward.
“Selfishness is the bedrock on which all moral behavior starts and it can be immoral only when it conflicts with a higher moral imperative. An animal so poor in spirit that he won’t even fight on his own behalf is already an evolutionary dead end; the best he can do for his breed is to crawl off and die, and not pass on his defective genes.”-Robert A. Heinlein
Nakedwoadwarrior (14:40:22) :
Not all man’s activities are harmful to the earth and its inhabitants. See this earlier post on WUWT, specifically my comment at “Roger Sowell (19:06:50) :”
http://wattsupwiththat.com/2009/03/11/gallup-poll-new-high-41-of-americans-now-say-global-warming-is-exaggerated/
In addition, for example, man built dams to prevent rivers from flooding. A side-effect is slower running rivers, with less erosion and scouring of the river bed. It also provides much more water for aquatic species, such as fish. Is that a harm or benefit?
Niagara Falls has much less water flowing, because a good portion of it is diverted to produce hydroelectric power. The result is the soft rock of the falls is not crumbling nearly as fast as it would otherwise. Is this a harm, or a benefit?
Man built bridges over rivers and chasms, allowing no contact with the river below while crossing. Is that a harm or benefit to the environment, from the perspective of the river?
Man cultivated vast areas of land, in the case of the U.S. Great Plains, busting up thick sod root systems to gain access to fertile soil. Such soil became home to billions of micro-organisms while useful crops are obtained. Is that a harm or benefit?
In Southern California and other areas of the dry West, since this was a desert before being settled, there were essentially no trees before building cities. Now, millions of trees, shrubs, and countless acres of grass and crops grow; all were planted by man. Is this a harm, or a benefit?
Please don’t believe all the garbage the environmentalists produce. Man has done, and continues to do, much that is good.