From the point of view of education policy, I would hope that my children are taught that evolution is just a theory; that it may be wrong; and that many people believe in creationism. I would hope that they think critically and make up their own minds, rather than just accept the dictates of authority. I think there’s value in being skeptical, even of generally accepted ideas such as evolution by natural selection.
And there are critical differences between CAGW and evolutionary theory too. So I don’t think your analogy will take you very far.
Perhaps they do - but if the scientists want to take the position that scientific issues are their “turf,” then maybe they shouldn’t use their offices to invade the province of professional policymakers: judges, attorneys, and politicians. Which is arguably what they are doing if they advocate for one policy over another.
Ok, and it follows that if you have a number of climate models predicting climate sensitivities; and there does not exist any values for sensitivity that fall within the range of each climate model, we can be confident that at least one model is wrong.
And I think it could happen pretty easily, for reasons discussed earlier.
And by the way, I’m not claiming that scientists should not advocate for policies. Just that it’s somewhat hypocritical for them to do so if they maintain that non-scientists should not question and evaluate science.
Personally, I believe that professional policymakers (and laypeople too) absolutely should demand disclosure from scientists and put them to skeptical or even hostile questioning. If satisfactory answers and disclosure are not forthcoming, then policymakers have every right to reject what the scientists are claiming.
As Frank Herbert said, law is the ultimate science.
Each GHG must be considered on its own merits as they absorb in different parts of the spectrum and such. The way that climate sensitivity is conventional defined is under the assumption that the other gases remain constant. So, when scientists talk about the amount of radiative forcing from the doubling of CO2, they are talking about this under the assumption that the others are constant. (By the way, the fact that the radiative forcing depends logarithmically on the concentration of the gas is not a rigorous law of nature for all concentrations but is true over a fairly broad range of concentrations, and in particular, for the concentration range of interest for CO2.)
I believe that the effects of the major greenhouse gases of interest (CO2, methane, …) in the range of interests are approximately additive…so that, at least to a good approximation, you can compute each independently and add up the radiative forcings due to each one.
Well, as the saying goes, all models are wrong but some models are useful. The point is, of course, that one should not believe the results of any one model, particularly with any one set of parameter choices, to be the received word…but rather as an estimate. The more groups you have developing climate models more-or-less independently (although obviously there is some communication through papers and the like), the more different estimates you can get.
Well, neither of us is expert enough to really have a very good intuition on this. I might argue that I have more intuition since I have worked extensively with models in the physical sciences, although clearly it would be those people working with climate models themselves who would have the best intuition on this.
I don’t for the most part disagree with you except that I would argue that these people should also have a realistic view of their own expertise and ability to judge the science. I think Rep. Boehlert, the chairman of the House Science Committee when the Republicans were in charge said it very well in his angry letter to Rep. Barton (for launching his investigation in regards to Mann et al.):
The way we have set up the National Academy of Sciences and such to try to de-politicize science has served this nation very well and I see no reason to abandon it each time some political interest doesn’t like the results that are being reached.
By the way, along these lines, here is a new “guest” post at RealClimate on air capture of already-released CO2. The last paragraph summarizes the current state of the technology:
And by the way, if you think you can fix this problem by taking numerous different models and somehow averaging or aggregating their results, you’re wrong for reasons discussed in the temperature record thread.
Richard Feynman analogized this type of situation very well:
Putting aside the question of who has better intuition, it seems to me that you bear the burden of proof. You are the one who claimed as follows:
If that claim is ultimately based on your intuition, it’s hard to put a lot of stock in it.
Everyone should have a realistic view of their own expertise and ability.
jshore, I was very troubled by the neat bit of circular reasoning here:
Say what???
As you have pointed out in this thread, one can do a reasonable job of hindcasting using just a few cyclical variables … does that prove that the cyclical variable method is robust?
The problem is not that the model is so far off on cloud cover, that is a symptom. The problem is that the fact that the model is so far off means that the cloud cover representation is very inaccurate. In particular, since clouds control the throttle on the global climate heat engine, it means that that vital control is parameterized.
Since it (and fifty or so other variables) are parameterized, you can get any historical answer you want. This is clear from the wide variety of models, with different forcings and different climate sensitivities and different model schemes and different dynamic cores and different gridsizes, which are all able to hindcast successfully. This leaves us with two choices:
Hindcasting is so simple, and the problem so well defined, that models are “robust” in the sense that their errors don’t make any difference. As long as you get the major stuff right, the minor stuff (like a ~30 w/m2 error in the cloud cover and all the other errors I listed above) makes no difference
The models are tuned to provide the historical temperature, so that their errors don’t make any difference.
The idea that a model which gives correct historical temperature trends despite having extensive parameterization and huge internal errors exhibits “robustness”, is circular reasoning of the highest order. All it demonstrates is the models lack of sensitivity to reality. In fact, the climate models are not robust, even to such trivial changes as increasing the resolution (decreasing the grid size). And in any case, their robustness is not proven, heck, it is not even tested, by their ability to hindcast temperature trends.
w.
PS - you say “If you had to get everything precisely right in order to be able to [hindcast temperatures] that it would be troubling …”
Perhaps you could provide us with a citation showing that you don’t have to have everything right in a climate model to get correct answers. You have put your finger on one of the most troubling and unsubstantiated claims of the modelers. This is the claim that close is good enough, that although the models contain a host of known errors, they are still robust enough to accurately forecast the climate.
Clearly, you think that this “robustness” is somehow demonstrated by their ability to hindcast the climate. If you don’t see the problem with that claim, let me know, and I’ll explain it.
PPS - you say “it would then show that the [model] results are not robust.” Since you say this with great certainty, I’m sure that you have a citation showing that the model results are in fact robust.
Well, to be frank, if I had views on a scientific matter that were in conflict with the IPCC, the National Academy of Sciences, the American Association for the Advancement of Science, and the councils of the American Geophysical Union, the American Meteorological Society, and the American Physical Society, I’d look long and hard at the question of whether I really have the expertise to know better than them. I am not saying that these organizations are infallible but I am questioning whether all but a very small percentage of those people who disagree with all these organizations on the issue of AGW really have the expertise and ability to have such a contrary opinion…and have it be in any way meaningful (to anybody else but themselves).
intention: Look, this argument really can’t go anywhere until evidence is provided that one can actually do with a climate model what you claim, namely “get any historical answer you want.” If you can provide a citation showing how the model can be tuned to produce the twentieth century historical temperature record in the absence of the anthropogenic forcings, then that would be important. But, I’ve never seen one.
The fact that you can trade off climate sensitivity and aerosol forcing somewhat correctly points out the fact that the current uncertainty in aerosol forcing leaves us with pretty large error bars on the climate sensitivity when you only consider the constraints of the 20th century temperature record. However, it does not go anywhere near showing that you can get any answer you want out of the model by tuning the parameters and arguing this over and over again without demonstrating it is not going to help.
And, you forget that the models are tested against a lot more than just the historical temperature trends. There are all sorts of things regarding the patterns of the climate, the seasonal cycle, etc. that the models can and are tested against.
I would go further than that: I would say that any time a layperson decides that one group of scientists is right and another group is wrong (about scientific issues within the scope of their expertise), he or she should be very careful. No matter which side is in the majority.
By the way, if it turns out that Professor Lindzen’s estimate of 1.0C sensitivity is correct, does that mean that the NAS was dead wrong?
Well, this is the sort of thing that sounds good but I would argue that it is not at all prescriptive for how we use science to inform public policy. After all, on just about any scientific issue, one will always be able to find some scientists who are on the opposite side of the issue from the majority. So, is John Q. Public or Joseph M. Congressperson supposed to just say, “Well, gee, I don’t know what we can conclude about the science. I guess we’ll just have to say that the science can’t give us any information here.”?
Do you really think that is a better way to have science inform public policy than the way that we have been doing it in the past, e.g., by using the National Academy of Sciences to provide the policymakers with their best summary of the current scientific opinion in the field?
Yes, it would mean that the NAS was wrong on the amount of warming that is expected to occur. (Whether it also means the NAS was wrong on its advice to cut emissions would depend on other issues such as how sensitive ecosystems are to the temperature change, how much sea level rise we get from the rise in temperatures due to CO2 emissions, etc.)
Yes indeed, the models are occasionally tested. Mostly it’s by the scientists running the models, but occasionally not. You can read about one such test in a peer reviewed paper here and and a further (non reviewed) discussion of the test here (both are pdfs).
The basic story of the study and commentary is that all climate models forecast a “fingerprint” of anthropogenic GHG global warming, which is a “hot spot” which all the models agree will form in the middle elevations of the troposphere over the tropics.
The problem is … we have three observational datasets (RSS, UAH, and balloon) showing the temperature of the troposphere, and none of them show the hot spot “fingerprint” of global warming forecast by all the models.
Now, when AGW supporters think they’ve found a “fingerprint” of anthropogenic global warming, they tend to follow James Hansen and call it a “smoking gun” … so to keep up with James’s hype, I suppose I should declare this lack of a fingerprint the “smoking gun” showing that the recent warming is not from greenhouse gases.
So, jshore, I can understand your extreme reluctance to have the models properly tested … heck, given these results, if I believed in AGW, I’d shy away from testing the models too.
My best to everyone, sorry I’ve been away, we’re having an audit here at the company and my time is short. More later.
jshore, the problem in this case is we have very little data for the forcings, anthropogenic or otherwise. What the modelers have done is pick what they think are reasonable numbers for things like aerosols. Then they pick numbers for the parameters that apply to those unknown aerosols.
Take, for example, the forcings used in James Hansen’s model, available here. Look at the data they are using for anthropogenic aerosols. They start at zero in 1880. They increase in a straight line until 1950. Then they increase more quickly, but still in a larger straight line, until 1990. And from 1990, they are flat level.
Do you really think that this in any way approximates the changes in the aerosols over the last 130 years? Because if so, I have a bridge in Brooklyn for sale …
The issue is not whether I can force a climate model to do anything. It is that the modelers who run the GCMs are free to pick their forcings and pick their parameters, which allows their models to fit the past. Otherwise, there’s no way that such a wide variety of models, with such a wide variety of forcings, could all fit the historical record.
So yes, given my choice of forcings and parameters, I could easily fit to the historical record.
w.
PS - Could I fit the historical record without anthropogenic forcings? You say that others have not been able to do so, but you seem to be operating under the idea that all significant natural forcings are known and included in the models. Is that the case?
One of the huge natural unknowns are biogenic aerosols. These range from the blue hazy biogenic “smoke” that gave the “Great Smoky Mountains” their name, to the DMS that is produced in megatonnes by the oceanic plankton all over the world.
So, I’ll tell you what - you get me the historical numbers on the change in those natural forcings, and I’ll see if I can fit the historical record … I’m sure you see the problem.
Of course, on the other hand, maybe we don’t need the numbers. I could do with the natural forcings what GISS has done with the anthropogenic forcings, and just pick a curve that fits my needs … easy money.
Finally, the abject failure of the models to predict the changes of the last decade (because they are operating “out of sample” rather than on the last century that they were tuned to) should give you a clue about their abilities regardless of the forcings …
And please don’t tell me “that’s too short a time”. The models were easily able to catch each and every one of the decadal and even shorter length changes when used to hindcast the 1900-2000 temperatures, that’s one of the arguments used to “prove” that they are correct. But they missed this one entirely …
In addition, I would add that the radiative forcings for the various gases are calculated by empirical formulas whose patronage is unclear. The result of the calculations are the instantaneous forcings, F(i).
Of particular interest is the difference between the instantaneous forcing F(i) and the equilibrium forcing F(e). F(e) is the net change in forcing after the system has time to respond, so it includes all feedbacks.
Unfortunately, climate models are the only guide to this, and they disagree. And understandably so. The answer depends subtly on the details of the precise implementation. Not an easy puzzle.
Let me see if I can illustrate the difficulty. Consider the view from my window out on to the deep tropical (9°S) Pacific ocean. In the morning, there’s often not a cloud in view.
The ocean, of course, is warmed by both the sun and the “greenhouse effect” during the day, so the surface waters start to warm. As the day heats up, the ocean evaporates a bit more, and a few clouds appear over oceanic hot spots, small clouds, they don’t do much.
As the day gets hotter, and people and the ocean start to sweat more (evaporative cooling, remember), more water vapor goes into the air. And the few clouds turn into a number of small clouds.
And then, if the day is hot enough, which is most days, an odd thing happens.
First one at at time, and then in bunches, the clouds all start to shoot upwards, growing taller and taller, becoming thunderstorms. Soon there’s the familiar high humidity, that hot and sweaty feeling that means rain’s on the way.
And sure enough, the bowl tips over and cooling rain pours back into the ocean.
Now, each of these thunderstorms that reach up to the high troposphere is one of the most amazing heat engines never invented by mankind. They are an emergent property of the climate system, meaning one moment they are not there, and the next they are there. They are “self-organized”, they form by themselves.
A thunderstorm is a reflective heat pipe moving energy way high into the sky. Shielded inside the towering cloud is a stream of warm moist air moving rapidly upwards, like water through a hose. This air cannot radiate to the outside, because it is in the middle of the cloud.
By means of that heat pipe, all of that surface heat (both latent and sensible) is transported way above most of the CO2, where it spreads out and radiates freely out to space. For heat at the surface, a thunderstorm is a tunnel through the wall of greenhouse gases and out to escape…
In addition, the storm returns the hot water evaporated minutes or hours earlier back to the ocean as cool rain.
Next, of course, it reflects hundreds of watts per square metre of solar energy back into space.
In addition, it whips up a wind around the base that increases a) evaporation, b) albedo , and c) cloud nuclei (microscopic salt spray crystals).
I bring all of this up because it relates to the results of increasing forcing in the tropics. A naive view would be that the temperature would react linearly to the increasing forcing. The whole idea of “climate sensitivity” is based on that idea, that forcing times sensitivity equals temperature change.
But look at what happens every day outside my window as the forcing increases. For a while, the ocean temperature rises. But then, clouds start to form, and the rise slows down. When the thunderstorms start to form, they pipe heat directly past the CO2, plus they shade the ocean, plus they provide cold wind and rain. As the sun increases, the number and size of the thunderstorms increases, driven by the increased forcing.
These thunderstorms are very efficient at what they do. Evaporation is linear with wind speed, so the wind-driven evaporation at the base of the thunderstorm is very high. But the winds don’t waste the water on raising the local relative humidity. Instead, the winds sweep the water vapor into the heat pipe, and it is taken aloft, turned into rain, and sent back to the ocean.
Once the thunderstorms start to form, increasing moisture in the air merely makes more clouds, because the air is near saturation. Nor does the temperature rise much further, because of the variety and efficiency of the thunderstorm’s cooling mechanisms (transport of heat aloft, reflection of incoming energy, wind driven evaporative cooling, and cold wind and water from aloft). More forcing just leads to more thunderstorms.
So in response to a linear change in forcing (the sun getting hotter during the day) we have a linear ocean temperature rise for a while. Then as clouds form the temperature rise slows. Finally, when thunderstorms form, the temperature rise slows substantially. Eventually, as the forcing continues to increase, a point will be reached at which the temperature rise stops. This is why open ocean temperatures, no matter how hot the sun, don’t go above about 32°C. Ever.
So, flex727, in answer to your original question as to whether different kinds of forcings can be added together, heck, no. As my example shows, even different amounts of the same forcing can’t be added together. In the morning, an additional 10 watts/m2 of extra forcing might warm the ocean by six degrees. But in the afternoon, an additional ten watts of forcing might change the temperature a quarter of a degree, with the rest going into evaporation.
To me, the whole idea that there is a linear relationship between forcing and temperature, that mythical number called a “climate sensitivity” that linearly relates a change in forcing to a change in temperature, can be shown to be false just by looking out my window. Increased forcing is not at all linear, and climate sensitivity is not a constant.
Nor can one depend on averages to calculate an “average climate sensitivity”. Take the question of the average relative humidity outside my window. It rises until the time of full cloud formation, and then it doesn’t rise any further, even though the forcing is still rising. All that happens is that more and more water goes up in the clouds and comes down again as rain. The atmosphere doesn’t get any wetter, the cycle just runs stronger.
What’s happening outside my window doesn’t depend on the gridcell average relative humidity. It depends on the relative humidity of the wind-whipped air at the base of the thunderstorm, which is very different from the averate.
See, here’s the crucial thing - climate sensitivity depends heavily on temperature. In the morning, climate sensitivity around here is high. But by the afternoon, it is falling fast, and may actually go to zero.
So before the model can tell me the climate sensitivity, it has to tell me the temperature. But before it can tell me the temperature, it has to calculate the climate sensitivity …