# How many people take Global Warming totally on faith? **URL:** \ **Category:** Great Debates\ **Created:** [August 21, 2007, 1:06pm UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356 "2007-08-21T13:06:49Z")\ **Posts on this page:** 20\ **Page:** 27
**Author:** ![brazil84](https://avatars.discourse-cdn.com/v4/letter/b/8491ac/32.png) [@brazil84](https://boards.straightdope.com/u/brazil84)\ **Post date:** [September 4, 2007, 2:13pm UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/521 "2007-09-04T14:13:07Z")
[QUOTE=jshore] Well, I am not saying they should necessarily. But, like I said, it’s a continuum and that is one end (and the end that climate models are pretty close to although probably not completely at). [/quote] Ok, so you believe that there is essentially no benefit to testing a climate model ex ante versus ex post. > [@](#): > > Well, as I explained, in the context you are talking, this doesn’t really make sense. Why doesn’t it make sense? Do you agree that climate modelers sometimes test their models against historical data? (Yes or no) Do you agree that sometimes those tests are positive and sometimes those tests are negative? (yes or no) Do you agree that all results should be disclosed whether positive or negative? (yes or no) Three extremely simple yes or no questions about climate models. ---
**Author:** ![intention](https://avatars.discourse-cdn.com/v4/letter/i/e95f7d/32.png) [@intention](https://boards.straightdope.com/u/intention)\ **Post date:** [September 4, 2007, 11:54pm UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/522 "2007-09-04T23:54:13Z")
[QUOTE=jshore] … All you are proving by talking about this is that you have no idea what you are talking about…which makes it not at all surprising that your beliefs are in conflict with almost all climate scientists and the conclusions of scientific authorities such as the National Academy of Sciences. As far as faster computers go, they allow for higher resolution in the models which means more fidelity in reproducing the actual physical processes, as well as resolving topography, land vs. water, etc. [/QUOTE] Before you tell people that they have no idea what they are talking about, you might learn about it yourself. Regarding the [GISSE](http://pubs.giss.nasa.gov/abstracts/2006/Schmidt_etal_1.html) model, the programmers say (emphasis mine): > [@](#): > > Indeed, some features (such as the stratospheric semiannual oscillation, high-latitude sea level pressure, or the zonality of the flow field) are degraded in higher resolution simulations, indicating that _ **resolution increases alone** _, without accompanying parameterization improvement, _ **will not necessarily create a better climate model.** _ In fact, one of the things that shows that the models don’t represent reality is the fact that as resolution increases, the skill of the model [decreases](http://www.climateaudit.org/?p=1124) . Look, I understand that you have faith in the models … but it’s just faith. From the description of the [GISSE](http://pubs.giss.nasa.gov/docs/notyet/inpress_Hansen_etal_1.pdf) > [@](#): > > _ **2.4 Principal Model Deficiencies** _ > > Model shortcomings include ~25% regional > deficiency of summer stratus cloud cover off the west > coast of the continents with resulting excessive absorption of > solar radiation by as much as 50 W/m2, deficiency in absorbed > solar radiation and net radiation over other tropical regions by > typically 20 W/m2, sea level pressure too high by 4-8 hPa in the > winter in the Arctic and 2-4 hPa too low in all seasons in the tropics, > ~20% deficiency of rainfall over the Amazon basin, ~25% > deficiency in summer cloud cover in the western United States > and central Asia with a corresponding ~5°C excessive summer > warmth in these regions. In addition to the inaccuracies in the > simulated climatology, another shortcoming of the atmospheric > model for climate change studies is the absence of a gravity > wave representation, as noted above, which may affect the nature > of interactions between the troposphere and stratosphere. > The stratospheric variability is less than observed, as shown by > analysis of the present 20-layer 4°×5° atmospheric model by > J. Perlwitz (personal communication). In a 50-year control run > Perlwitz finds that the interannual variability of seasonal mean > temperature in the stratosphere maximizes in the region of the > subpolar jet streams at realistic values, but the model produces > only six sudden stratospheric warmings (SSWs) in 50 years, > compared with about one every two years in the real world. In the GISSE global circulation model, the modeled radiation forcing in the tropics (40% of the world, and where the majority of the radiation is absorbed) is off by a whopping 20 W/m2; cloud cover (arguably the most important factor in climate) is estimated by the model at 58% whereas in fact it’s 69% (about a 35W/m2 error in albedo); the model has never been subjected to V&V or SQA; the potential energy of water vapor/condensate is neglected; angular momentum due to drag and pressure torques at the solid land surface is ignored; the change in ocean radiation emissivity due to wind velocity is not calculated … and yet you actually think the model can be trusted to reliably forecast the effect of a 3.7 W/m2 change in forcing??? The error in the clouds alone is _ **ten times that large.** _ Like I said, it’s lucky you have faith, it gives a warm, fuzzy feeling … I’m just overjoyed that you aren’t in charge of approving the software that controls airplanes or subways. In mission critical software, faith is not sufficient. w. ---
**Author:** ![jshore](https://avatars.discourse-cdn.com/v4/letter/j/b5e925/32.png) [@jshore](https://boards.straightdope.com/u/jshore)\ **Post date:** [September 5, 2007, 1:08am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/523 "2007-09-05T01:08:59Z")
[QUOTE=intention] Regarding the [GISSE](http://pubs.giss.nasa.gov/abstracts/2006/Schmidt_etal_1.html) model, the programmers say (emphasis mine): [/quote] Fine…So, there are exceptions to the rule and it is a little more complicated than what I say. Gavin’s point that resolution increases alone are not the end-all and be-all is well-taken. Still, he is not saying that resolution increases are not overall a good thing…you just want to make sure that you improve the physics in the parameterizations too. And, since the parameterizations are approximations, they sometimes will give a worse result when the model is run at higher resolution. For completeness and because I think remarks such as this always make more sense when seen in the fuller context of what was being talked about, here is the entire paragraph from which you quoted: > [@](#): > > The GISS model philosophy has always been to improve the physics of each modeled component, and to allow as great a degree as possible of flexibility in model configurations. This has led to a great deal of innovative and challenging science (Hansen and Nazarenko 2004; Hansen et al. 1997; Rind et al. 2001a,b, 1999; Shindell et al. 1999, 1998; and many others) although some compromises (such as for horizontal resolution) were necessary. We have chosen not to uniquely pursue higher resolution, since that can severely limit the length and variability of the experiments possible, but rather we have maintained a variety of resolutions that can be used based on scientific need. Our experience has been that while some aspects of a simulation can be improved by increasing the resolution (frontal definition, boundary layer processes, etc.), many equally important improvements are likely to arise through improvements to the physical parameterizations. Indeed, some features (such as the stratospheric semiannual oscillation, high-latitude sea level pressure, or the zonality of the flow field) are degraded in higher resolution simulations, indicating that resolution increases alone, without accompanying parameterization improvement, will not necessarily create a better climate model. As models improve and computer resources expand, there will always be a tension between the need to include more physics (tracers, a more resolved stratosphere, cloud microphysics, etc.), to run longer simulations, and to have more detailed vertical and horizontal resolution. The balance that is struck will be different for any particular application and so a flexible modeling environment is a prerequisite. In this paper, we therefore show results from three different configurations that differ principally in their horizontal and vertical resolution. > [@intention](#): > > In the GISSE global circulation model, the modeled radiation forcing in the tropics (40% of the world, and where the majority of the radiation is absorbed) is off by a whopping 20 W/m2; cloud cover (arguably the most important factor in climate) is estimated by the model at 58% whereas in fact it’s 69% (about a 35W/m2 error in albedo); the model has never been subjected to V&V or SQA; the potential energy of water vapor/condensate is neglected; angular momentum due to drag and pressure torques at the solid land surface is ignored; the change in ocean radiation emissivity due to wind velocity is not calculated … and yet you actually think the model can be trusted to reliably forecast the effect of a 3.7 W/m2 change in forcing??? The error in the clouds alone is _ **ten times that large.** _ And, you know, if quantum electrodynamics had controversial policy ramifications, we’d have people yelling about how one can possibly trust a theory in which you have to subtract two diverging quantities in order to get a real physical quantity like the mass of a particle!!! Welcome to science at the forefront, my friend, where the theories and models are never perfect and where one single piece of evidence is seldom clear-cut when viewed all by itself. The fact is that when at work I model the spectrum of a device, I will often use it to predict changes in the spectrum with device structure that are considerably smaller than the error between what my model predicts for the spectrum of a device and what the experimentally measured spectrum looks like. And, in fact, my predictions will almost invariably be correct. One doesn’t have to get all the radiative processes down to lower than the 3.7 W/m2 change you are looking for. One just has to have reasonable confidence that the errors in those quantities don’t change by very large amounts as the perturbation we are studying (in this case, increasing CO2) is turned on. The fact that a variety of models (and generations of an individual model) with a variety of different parametrization schemes and a variety of different strengths and deficiencies all predict similar climate sensitivities (within an admittedly fairly broad range) is one piece of evidence that we can have confidence that this is so. > [@](#): > > Like I said, it’s lucky you have faith, it gives a warm, fuzzy feeling … I’m just overjoyed that you aren’t in charge of approving the software that controls airplanes or subways. In mission critical software, faith is not sufficient. You may call that faith. Those of us who are actually trained scientists who have worked in other fields (where there is not so much of a politically-charged atmosphere) call it science. ---
**Author:** ![jshore](https://avatars.discourse-cdn.com/v4/letter/j/b5e925/32.png) [@jshore](https://boards.straightdope.com/u/jshore)\ **Post date:** [September 5, 2007, 1:21am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/524 "2007-09-05T01:21:44Z")
[QUOTE=brazil84] Ok, so you believe that there is essentially no benefit to testing a climate model ex ante versus ex post. [/quote] Well, I never claimed that climate modeling was so completely on the extreme that it couldn’t benefit at all from “ex ante” testing to give us more confidence, but I don’t think such a distinction is vital…and I think that there is a lot lf “ex post” stuff you can do (such as looking at the Mt. Pinatubo eruption) that is really essentially “ex ante” because although the data may have existed when the model was being developed or updated, it hadn’t in any way been used in developing the model. > [@](#): > > Do you agree that climate modelers sometimes test their models against historical data? (Yes or no) Yes. > [@](#): > > Do you agree that sometimes those tests are positive and sometimes those tests are negative? (yes or no) Most likely…although I think it is seldom completely black-and-white. > [@](#): > > Do you agree that all results should be disclosed whether positive or negative? (yes or no) As I have said before, I think it is good to discuss both the strengths and deficiencies of the model in reproducing historical results as well as just basic present day climatology. This is what Gavin has done in describing the GISS model and even though it gives people like **intention** with an agenda an opportunity to try to score debating points, I still think it is the right thing to do. I also think it is useful to describe things like, “When we tried this other parametrization scheme…” or “When we varied the parameter over this range…”, “we saw these results instead”. However, as I have also pointed out, it is not like the situation you have in doing purely statistical studies where you actually radically change what one would conclude by whether you include the negative results. I.e., there is nothing akin to the dangers in this sort of modeling as there is in running twenty studies on a drug and only reporting the one study where the drug did statistically-significantly better than the placebo (which would no longer be statistically-significant if you included all the failed study data too). ---
**Author:** ![brazil84](https://avatars.discourse-cdn.com/v4/letter/b/8491ac/32.png) [@brazil84](https://boards.straightdope.com/u/brazil84)\ **Post date:** [September 5, 2007, 1:33am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/525 "2007-09-05T01:33:17Z")
[QUOTE=jshore] Well, I never claimed that climate modeling was so completely on the extreme that it couldn’t benefit at all from “ex ante” testing to give us more confidence, but I don’t think such a distinction is vital [/quote] Ok, but the only benefit is psychological? > [@](#): > > Most likely…although I think it is seldom completely black-and-white. That’s unfortunate for various reasons that I will not get into. > [@](#): > > As I have said before, I think it is good to discuss both the strengths and deficiencies of the model in reproducing historical results as well as just basic present day climatology. This is what Gavin has done in describing the GISS model and even though it gives people like **intention** with an agenda an opportunity to try to score debating points, I still think it is the right thing to do. > > I also think it is useful to describe things like, “When we tried this other parametrization scheme…” or “When we varied the parameter over this range…”, “we saw these results instead”. > > However, as I have also pointed out, it is not like the situation you have in doing purely statistical studies where you actually radically change what one would conclude by whether you include the negative results. I.e., there is nothing akin to the dangers in this sort of modeling as there is in running twenty studies on a drug and only reporting the one study where the drug did statistically-significantly better than the placebo (which would no longer be statistically-significant if you included all the failed study data too). I’m a little confused. Is that a yes or a no? If a model is tested and fails, should the failure be disclosed or not? Or, if you prefer not to see things as “black and white,” let me ask it this way: If a modeler tests a model, should the results of that test be disclosed? Yes or no? Edited to add: My questions refer only to climate models of the type we have been discussing so far. So there’s no need to address other types of models. I realize you would apply different standards to different types of models. My question deals only with climate models. ---
**Author:** ![jshore](https://avatars.discourse-cdn.com/v4/letter/j/b5e925/32.png) [@jshore](https://boards.straightdope.com/u/jshore)\ **Post date:** [September 5, 2007, 1:47am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/526 "2007-09-05T01:47:56Z")
[QUOTE=brazil84] Ok, but the only benefit is psychological? [/quote] I’m not sure I’d say that is 100% completely true, but I think for all intents-and-purposes, I’d pretty much agree with that. > [@](#): > > That’s unfortunate for various reasons that I will not get into. Well, it would be nice if you would actually state things that you believe rather than engaging in this kind of socratic questioning exclusively. > [@](#): > > I’m a little confused. Is that a yes or a no? > > If a model is tested and fails, should the failure be disclosed or not? > > Or, if you prefer not to see things as “black and white,” let me ask it this way: > > If a modeler tests a model, should the results of that test be disclosed? > > Yes or no? Well, I think in general, yes. But I don’t think it is something to be legislated or anything like that. I will leave it in the hands of the individual researcher to decide whether he thinks the results are important and noteworthy enough to warrant discussion and how best to discuss this. (The referees also have a hand here…and I as a referee have suggested tests that I think would be useful before.) However, I would also leave it up to the researcher to decide what is the best way to discuss these issues. A good scientist is always looking for ways to test the limitations of his/her model or theory. ---
**Author:** ![brazil84](https://avatars.discourse-cdn.com/v4/letter/b/8491ac/32.png) [@brazil84](https://boards.straightdope.com/u/brazil84)\ **Post date:** [September 5, 2007, 2:05am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/527 "2007-09-05T02:05:21Z")
> [@](#): > > Well, it would be nice if you would actually state things that you believe rather than engaging in this kind of socratic questioning exclusively. I’m happy to tell you why if you are curious. > [@](#): > > Well, I think in general, yes. Why? ---
**Author:** ![jshore](https://avatars.discourse-cdn.com/v4/letter/j/b5e925/32.png) [@jshore](https://boards.straightdope.com/u/jshore)\ **Post date:** [September 5, 2007, 2:17am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/528 "2007-09-05T02:17:54Z")
[QUOTE=brazil84] I’m happy to tell you why if you are curious. [/QUOTE] Yes. I am. ---
**Author:** ![intention](https://avatars.discourse-cdn.com/v4/letter/i/e95f7d/32.png) [@intention](https://boards.straightdope.com/u/intention)\ **Post date:** [September 5, 2007, 4:29am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/529 "2007-09-05T04:29:15Z")
> [@jshore](#): > > Fine…So, there are exceptions to the rule and it is a little more complicated than what I say. A little more complicated than you say? A _little_ more? I love the “it’s all simple, it’s just basic physics” tack that people take about climate science. The climate is the most complex, and most poorly understood, and largest, system that we have ever tried to model. No, it’s not “a little more complicated” than what you say, it’s immensely more complicated than our tinkertoy models. Nor, as my citation showed, can the problem be fixed simply by improving the parameterization as you and Gavin claim. It is inherent in the models. Read the freakin’ [citation.](http://www.climateaudit.org/?p=1124) Turbulent systems are notoriously difficult to model, and resolution is one of the bugaboos of doing it. [QUOTE=jshore] The fact is that when at work I model the spectrum of a device, I will often use it to predict changes in the spectrum with device structure that are considerably smaller than the error between what my model predicts for the spectrum of a device and what the experimentally measured spectrum looks like. And, in fact, my predictions will almost invariably be correct. One doesn’t have to get all the radiative processes down to lower than the 3.7 W/m2 change you are looking for. One just has to have reasonable confidence that the errors in those quantities don’t change by very large amounts as the perturbation we are studying (in this case, increasing CO2) is turned on. The fact that a variety of models (and generations of an individual model) with a variety of different parametrization schemes and a variety of different strengths and deficiencies all predict similar climate sensitivities (within an admittedly fairly broad range) is one piece of evidence that we can have confidence that this is so. [/quote] And your evidence that gives you “reasonable confidence” that the cloud coverage doesn’t change by even 1% as the temperature changes would be … ??? jshore, a _ **1%** _ change in clouds gives a change in radioactive forcing equal to a doubling of CO2. If you have evidence that there is no feedback that has a 1% effect on the clouds, bring it on. Richard Lindzens “Iris Hypothesis” has recently been supported by [this paper.](http://www.agu.org/pubs/crossref/2007/2007GL029698.shtml) Is his hypothesis true? We don’t know. I know you don’t like to say that, but it’s the truth – we don’t know, just as we don’t know the size and in some cases the sign of a number of climate feedbacks. And not knowing about this or a host of other feedbacks, your foolish assumption that not only the clouds but all of the climate is like your spectrum device, that it just sits stably or reacts predictably enough to ignore the huge model errors, is quite touching … but it is not science. The models get the clouds wrong precisely because we don’t understand all the feedbacks, forcings, and resonances that affect the clouds. The idea that we can hold the clouds constant and thus derive the effect of increasing CO2 is laughable. Yes, as you say, in a simple stable system which is well understood, it’s not necessary to get the details exactly correct. But the climate is a poorly understood, complex, chaotic, driven, constructal, optimally turbulent, multi-stable system, with dozens of forcings, feedbacks, and internal resonances, both known and unknown. It is made up of five subsystems (ocean, atmosphere, lithosphere, biosphere, and cryosphere) which all interact with all of the others in unknown ways. Correct me if I’m wrong, but I doubt very much if the same is true of the devices for which you are calculating spectra. You are analyzing a simple device built by humans, not an incredibly complex natural system. My guess would be that there is no significant turbulence in your system, for example, to take one of the many difference between machines and nature. [QUOTE=jshore] You may call that faith. Those of us who are actually trained scientists who have worked in other fields (where there is not so much of a politically-charged atmosphere) call it science. [/QUOTE] You would not fly in an airplane whose computer system had not been subjected to V&V and SQA. You would not ride in a subway whose computer system regularly had huge errors. But you want me to spend billions of dollars based on an untested, unreliable computer climate models … thanks, but I’ll pass until you subject the models to the _ **normal scientific testing procedure that every other piece of mission critical software has to pass** _. That’s science, and we use it on everything from space probes to submarines. Until the models are tested and verified, it’s not science, it’s just faith. Sorry to break the news, but your being a “trained scientist” doesn’t make you any less susceptible to faith than anyone else. Science is a way of looking at the world, not the result of a course of study. The fact that a person has a PhD in science does not necessarily make them a scientist. w. PS - the fact that a variety of models give us similar results for climate sensitivity only shows that they are tuned to reproduce the past climate record. Given the _ **assumption** _ that the temperature changes are due to CO2, even the simplest model will give that result. Here’s an extremely simple model – we assume that the post 1980 warming of 0.25° is all due to CO2. Given the change in CO2, that works out to about 2°C/per doubling. Does that prove anything about climate sensitivity? No, because we are _ **assuming** _ that all of the warming is due to CO2. ---
**Author:** ![brazil84](https://avatars.discourse-cdn.com/v4/letter/b/8491ac/32.png) [@brazil84](https://boards.straightdope.com/u/brazil84)\ **Post date:** [September 5, 2007, 4:38am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/530 "2007-09-05T04:38:19Z")
[QUOTE=jshore] Yes. I am. [/QUOTE] Because, ideally in a scientific test, the line between success and failure should be drawn before the test is done. Now could you please answer my question: Why do you think that a modeler should disclose the results of all tests, whether good or bad? What’s wrong with just disclosing good results and throwing the bad results down the memory hole? ---
**Author:** ![GIGObuster](https://sea3.discourse-cdn.com/straightdope/user_avatar/boards.straightdope.com/gigobuster/32/421_2.png) [@GIGObuster](https://boards.straightdope.com/u/GIGObuster)\ **Post date:** [September 5, 2007, 7:50am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/531 "2007-09-05T07:50:26Z")
[QUOTE=intention] You would not fly in an airplane whose computer system had not been subjected to V&V and SQA. You would not ride in a subway whose computer system regularly had huge errors. But you want me to spend billions of dollars based on an untested, unreliable computer climate models … thanks, but I’ll pass until you subject the models to the _ **normal scientific testing procedure that every other piece of mission critical software has to pass** _. That’s science, and we use it on everything from space probes to submarines. Until the models are tested and verified, it’s not science, it’s just faith. Sorry to break the news, but your being a “trained scientist” doesn’t make you any less susceptible to faith than anyone else. Science is a way of looking at the world, not the result of a course of study. The fact that a person has a PhD in science does not necessarily make them a scientist. w. PS - the fact that a variety of models give us similar results for climate sensitivity only shows that they are tuned to reproduce the past climate record. Given the _ **assumption** _ that the temperature changes are due to CO2, even the simplest model will give that result. Here’s an extremely simple model – we assume that the post 1980 warming of 0.25° is all due to CO2. Given the change in CO2, that works out to about 2°C/per doubling. Does that prove anything about climate sensitivity? No, because we are _ **assuming** _ that all of the warming is due to CO2. [/QUOTE] The more I look, the more I see that they are indeed tested. [http://www.iop.org/activity/policy/Publications/file\_4147.pdf](http://www.iop.org/activity/policy/Publications/file_4147.pdf) > [@](#): > > How can we evaluate whether these climate > predictions are credible – or to put it another way, > how can we estimate the information content of the > climate forecast? The fact that a weather forecast > model is at the heart of the climate model and this > is independently shown to be valid is an important > feature. Also climate models can be run for current > day climate conditions assuming no further humanproduced > increase in greenhouse gases. This > should reproduce the statistics of current climate > and not drift because of imperfections in the > overall modelled radiation balance. In addition the > model can be run including the known varying > concentration of greenhouse gases over the period > 1850 to present and other external forcing factors > such as volcanic eruptions and variability in solar > output (also used to simulate past climates in the > geological record). The “hindcasts” made in these > ways reproduce many aspects of the (relatively > well) observed climate over that period. Indeed it is > possible to show, by including each forcing > separately, that the solar variations that have > occurred cannot explain the recent few decades of > warming and that human input of greenhouse gases > are most likely responsible for this warming; see > Figure 6. A more complete ensemble may show, > however, that there are a number of different ways > such climate models can balance processes to pass > this test. > > It is sometimes imagined that such tests of the > model are rigged in some way because, as has been > discussed, there are various empirical and other > parameters in the parametrisation components of > the model that are to a degree uncertain and so > perhaps these could be tuned to get the “right” > answer. It is wildly over-simplistic to suppose that > a few parameter values can be adjusted to > reproduce the many diverse attributes that > constitute the complex behaviour of the climate > system. > > If it were possible to do this we would > indeed have emerged with a climate > “theory of everything”! The very complexity of the model > (maybe three-quarters of a million lines of > computer code) tells us that it is almost certain to > be impossible to cheat in this way. > It is clear, however, that climate forecasting does not > have the luxury of the quantity of multiple > independent forecasts to prove its overall level of > accuracy that is available to weather forecasting. In > addition we may need to wait for some time before > we can test fully the predictions of future climate > change. But this does not mean the predictions are > necessarily either inaccurate or not credible as is > sometimes implied. There is little doubt that there is > still some way to go to simulate accurately all facets > of the climate system with such models. The era of > ensemble climate prediction is only just beginning > now. But we will soon be able to say more > quantitatively what level of uncertainty we attach to > predictions of various facets of the climate system – > the fact that some are more uncertain than others > does not mean that all predictions are to be treated as > worthless. > … > So why do commentators imagine that top scientists > are deluded about anthropogenic climate change? > The stakes are high and rarely are scientists under > such scrutiny. Scientists are appalled that they could > be suspected of distorting the evidence to enhance > their reputations or funding opportunities. Of > course scientific hypotheses and analysis can be > refuted by later discoveries but this is not the same > as complicity. The fact that everyone experiences > weather and climate may explain why nonscientists > feel confident in attempting to refute the > scientific evidence. The complexity of the climate > system and its many interacting and compensating > physical processes means that simple arguments > that gloss over this complexity have to be > approached with a significant degree of scepticism. > A common method of arguing starts by identifying > a single cause or physical process that either has not > been included or has been included in an imperfect > way, into climate models. But the climate changes > because of a multiplicity of interacting processes > and any one process alone cannot be the whole > story. The search for the one and only cause of > climate change is doomed to failure. Climate > modellers attempt to include in the models all the > processes that are even remotely likely to have a > detectable effect – any newly discovered process > will quickly find itself incorporated into the > models! - Professor Thorpe. (currently the Director of the Natural Environment Research Council) ---
**Author:** ![intention](https://avatars.discourse-cdn.com/v4/letter/i/e95f7d/32.png) [@intention](https://boards.straightdope.com/u/intention)\ **Post date:** [September 5, 2007, 10:33am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/532 "2007-09-05T10:33:56Z")
[QUOTE=GIGObuster] The more I look, the more I see that they are indeed tested. [http://www.iop.org/activity/policy/Publications/file\_4147.pdf](http://www.iop.org/activity/policy/Publications/file_4147.pdf) - Professor Thorpe. (currently the Director of the Natural Environment Research Council) [/QUOTE] **GIGObuster** , thanks for the citation. If you are convinced that [approximately replicating the historical trend] = [testing a model] there’s not much we can do to help you. However, on the off chance that you’d like to learn something rather than continue with your error, you might start with [Discussions of Application of Verification, Validation, and Quality Assurance Procedures to Climate Modeling Software](http://danhughes.auditblogs.com/files/2007/02/vandvandsqapost.pdf). For a discussion of some of the mathematical problems with models which I alluded to in the discussion with jshore above, you could see [Time Step Sensitivity of Nonlinear Atmospheric Models: Numerical Convergence, Truncation Error Growth, and Ensemble Design](http://www.maths.uwa.edu.au/~kevin/Papers/JAS07Teixeira.pdf), along with [part 1](http://danhughes.auditblogs.com/2007/03/09/an-important-peer-reviewed-paper/) and [part 2](http://danhughes.auditblogs.com/2007/03/22/an-important-peer-reviewed-paper-part-1/) of a discussion of that paper. Finally, there is a bibliography about Verification and Validation (V&V) and Software Quality Assurance (SQA) [here.](http://danhughes.auditblogs.com/2007/02/23/a-start-on-a-vv-and-sqa-bibliography/) The short version is that replicating the past is not testing of a model. There are plenty of stock market models that can replicate the past quite well … but all of them are useless at predicting the future. As the stock brokers famously say, “Past performance is no guarantee of future results” … and the same is true in all chaotic systems, including the climate. My best to all, w. ---
**Author:** ![brazil84](https://avatars.discourse-cdn.com/v4/letter/b/8491ac/32.png) [@brazil84](https://boards.straightdope.com/u/brazil84)\ **Post date:** [September 5, 2007, 11:42am UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/533 "2007-09-05T11:42:26Z")
[QUOTE=intention] The short version is that replicating the past is not testing of a model. There are plenty of stock market models that can replicate the past quite well … but all of them are useless at predicting the future. As the stock brokers famously say, “Past performance is no guarantee of future results” … and the same is true in all chaotic systems, including the climate. . [/QUOTE] This is particularly so if models that do not pass the “hindcast” test can be quietly discarded. And if source code is not 100% disclosed at the time of publication so that popular models can be tested against future data 5, 10, or 20 years after they are published. ---
**Author:** ![BrainGlutton](https://avatars.discourse-cdn.com/v4/letter/b/82dd89/32.png) [@BrainGlutton](https://boards.straightdope.com/u/BrainGlutton)\ **Post date:** [September 5, 2007, 1:50pm UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/534 "2007-09-05T13:50:49Z")
[Loss of Arctic ice leaves experts stunned.](http://www.guardian.co.uk/environment/2007/sep/04/climatechange) ---
**Author:** ![GIGObuster](https://sea3.discourse-cdn.com/straightdope/user_avatar/boards.straightdope.com/gigobuster/32/421_2.png) [@GIGObuster](https://boards.straightdope.com/u/GIGObuster)\ **Post date:** [September 5, 2007, 1:53pm UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/535 "2007-09-05T13:53:12Z")
[QUOTE=intention] **GIGObuster** , thanks for the citation. If you are convinced that [approximately replicating the historical trend] = [testing a model] there’s not much we can do to help you. However, on the off chance that you’d like to learn something rather than continue with your error, you might start with [Discussions of Application of Verification, Validation, and Quality Assurance Procedures to Climate Modeling Software](http://danhughes.auditblogs.com/files/2007/02/vandvandsqapost.pdf). For a discussion of some of the mathematical problems with models which I alluded to in the discussion with jshore above, you could see [Time Step Sensitivity of Nonlinear Atmospheric Models: Numerical Convergence, Truncation Error Growth, and Ensemble Design](http://www.maths.uwa.edu.au/~kevin/Papers/JAS07Teixeira.pdf), along with [part 1](http://danhughes.auditblogs.com/2007/03/09/an-important-peer-reviewed-paper/) and [part 2](http://danhughes.auditblogs.com/2007/03/22/an-important-peer-reviewed-paper-part-1/) of a discussion of that paper. Finally, there is a bibliography about Verification and Validation (V&V) and Software Quality Assurance (SQA) [here.](http://danhughes.auditblogs.com/2007/02/23/a-start-on-a-vv-and-sqa-bibliography/) The short version is that replicating the past is not testing of a model. There are plenty of stock market models that can replicate the past quite well … but all of them are useless at predicting the future. As the stock brokers famously say, “Past performance is no guarantee of future results” … and the same is true in all chaotic systems, including the climate. My best to all, w. [/QUOTE] Old news. Or I should say, incomplete news. The long version is that you are demonstrating that you do not know anything about what NASA is doing with V&V and no, since physics are the main thrust of the modeling, the testing is not just approximately replicating the historical trend. And you seem to have missed the New Scientist’s article already posted: [http://environment.newscientist.com/channel/earth/climate-change/dn11649](http://environment.newscientist.com/channel/earth/climate-change/dn11649) > [@](#): > > A lot of trading in the financial markets is already carried out by computers. Many base their decisions on fairly simple algorithms designed to exploit tiny profit margins, but others rely on more sophisticated long-term models. ---
**Author:** ![brazil84](https://avatars.discourse-cdn.com/v4/letter/b/8491ac/32.png) [@brazil84](https://boards.straightdope.com/u/brazil84)\ **Post date:** [September 5, 2007, 1:56pm UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/536 "2007-09-05T13:56:36Z")
[QUOTE=BrainGlutton] [Loss of Arctic ice leaves experts stunned.](http://www.guardian.co.uk/environment/2007/sep/04/climatechange) [/QUOTE] Are you saying that this is evidence of AGW? ---
**Author:** ![brazil84](https://avatars.discourse-cdn.com/v4/letter/b/8491ac/32.png) [@brazil84](https://boards.straightdope.com/u/brazil84)\ **Post date:** [September 5, 2007, 2:08pm UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/537 "2007-09-05T14:08:37Z")
> [@](#): > > but others rely on more sophisticated long-term models. There’s really no way to verify that this is true. Because obviously if somebody has developed a computer model that predicts the stock market well enough to make money, they will never ever disclose how the model works. ---
**Author:** ![GIGObuster](https://sea3.discourse-cdn.com/straightdope/user_avatar/boards.straightdope.com/gigobuster/32/421_2.png) [@GIGObuster](https://boards.straightdope.com/u/GIGObuster)\ **Post date:** [September 5, 2007, 2:11pm UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/538 "2007-09-05T14:11:00Z")
[QUOTE=brazil84] This is particularly so if models that do not pass the “hindcast” test can be quietly discarded. And if source code is not 100% disclosed at the time of publication so that popular models can be tested against future data 5, 10, or 20 years after they are published. [/QUOTE] > [@](#): > > The fact that a weather forecast > model is at the heart of the climate model and this > is independently shown to be valid is an important > feature. Also climate models can be run for current > day climate conditions assuming no further humanproduced > increase in greenhouse gases. This > should reproduce the statistics of current climate > and not drift because of imperfections in the > overall modelled radiation balance. In addition the > model can be run including the known varying > concentration of greenhouse gases over the period > 1850 to present and other external forcing factors > such as volcanic eruptions and variability in solar > output (also used to simulate past climates in the > geological record). The “hindcasts” made in these > ways reproduce many aspects of the (relatively > well) observed climate over that period. Indeed it is > possible to show, by including each forcing > separately, that the solar variations that have > occurred cannot explain the recent few decades of > warming and that human input of greenhouse gases > are most likely responsible for this warming; see > Figure 6. A more complete ensemble may show, > however, that there are a number of different ways > such climate models can balance processes to pass > this test. By now, I would have expected to see a computer model made by skeptics that follows the physics, or I should say the physical properties, that the early researchers used in their models to show now a repeated pattern that could be reproduced to make everyone aware that the applied physics and formulas were mistaken. ---
**Author:** ![BrainGlutton](https://avatars.discourse-cdn.com/v4/letter/b/82dd89/32.png) [@BrainGlutton](https://boards.straightdope.com/u/BrainGlutton)\ **Post date:** [September 5, 2007, 2:11pm UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/539 "2007-09-05T14:11:32Z")
[QUOTE=brazil84] Are you saying that this is evidence of AGW? [/QUOTE] One of the scientists quoted in the article says so. At any rate, it definitely is evidence of GW, A or not. ---
**Author:** ![GIGObuster](https://sea3.discourse-cdn.com/straightdope/user_avatar/boards.straightdope.com/gigobuster/32/421_2.png) [@GIGObuster](https://boards.straightdope.com/u/GIGObuster)\ **Post date:** [September 5, 2007, 2:15pm UTC](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356/540 "2007-09-05T14:15:24Z")
[QUOTE=brazil84] There’s really no way to verify that this is true. Because obviously if somebody has developed a computer model that predicts the stock market well enough to make money, they will never ever disclose how the model works. [/QUOTE] [http://www.nytimes.com/2006/07/09/business/mutfund/09quant.html?ex=1310097600&en=a4f3558c2486252d&ei=5089](http://www.nytimes.com/2006/07/09/business/mutfund/09quant.html?ex=1310097600&en=a4f3558c2486252d&ei=5089) > [@](#): > > IF movies like “2001: A Space Odyssey” and “The Matrix” are any indication, humans are not comfortable with the idea of artificial intelligence controlling their fate. > > So why ever trust a computer model to run your investments? Because, in the real world, it seems to pay off. > > Many mutual funds that make their trades based on the recommendations of a proprietary computer model, known as quantitative or quant funds, have outperformed their benchmarks in the last three years. And investors have noticed. > > At the Vanguard Group, which created its first such fund in 1985, the amount of money managed by its quantitative group has quintupled in the last three years, to $20 billion at the end of 2005 from $4 billion in 2002. [Previous page](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356.md?page=26) [Next page](https://boards.straightdope.com/t/how-many-people-take-global-warming-totally-on-faith/416356.md?page=28)