Arguments
How reliable are climate models?
What the science says...
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Basic
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Intermediate
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Models successfully reproduce temperatures since 1900 globally, by land, in the air and the ocean. |
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Climate Myth...
Models are unreliable
"[Models] are full of fudge factors that are fitted to the existing climate, so the models more or less agree with the observed data. But there is no reason to believe that the same fudge factors would give the right behaviour in a world with different chemistry, for example in a world with increased CO2 in the atmosphere." (Freeman Dyson)
At a glance
So, what are computer models? Computer modelling is the simulation and study of complex physical systems using mathematics and computer science. Models can be used to explore the effects of changes to any or all of the system components. Such techniques have a wide range of applications. For example, engineering makes a lot of use of computer models, from aircraft design to dam construction and everything in between. Many aspects of our modern lives depend, one way and another, on computer modelling. If you don't trust computer models but like flying, you might want to think about that.
Computer models can be as simple or as complicated as required. It depends on what part of a system you're looking at and its complexity. A simple model might consist of a few equations on a spreadsheet. Complex models, on the other hand, can run to millions of lines of code. Designing them involves intensive collaboration between multiple specialist scientists, mathematicians and top-end coders working as a team.
Modelling of the planet's climate system dates back to the late 1960s. Climate modelling involves incorporating all the equations that describe the interactions between all the components of our climate system. Climate modelling is especially maths-heavy, requiring phenomenal computer power to run vast numbers of equations at the same time.
Climate models are designed to estimate trends rather than events. For example, a fairly simple climate model can readily tell you it will be colder in winter. However, it can’t tell you what the temperature will be on a specific day – that’s weather forecasting. Weather forecast-models rarely extend to even a fortnight ahead. Big difference. Climate trends deal with things such as temperature or sea-level changes, over multiple decades. Trends are important because they eliminate or 'smooth out' single events that may be extreme but uncommon. In other words, trends tell you which way the system's heading.
All climate models must be tested to find out if they work before they are deployed. That can be done by using the past. We know what happened back then either because we made observations or since evidence is preserved in the geological record. If a model can correctly simulate trends from a starting point somewhere in the past through to the present day, it has passed that test. We can therefore expect it to simulate what might happen in the future. And that's exactly what has happened. From early on, climate models predicted future global warming. Multiple lines of hard physical evidence now confirm the prediction was correct.
Finally, all models, weather or climate, have uncertainties associated with them. This doesn't mean scientists don't know anything - far from it. If you work in science, uncertainty is an everyday word and is to be expected. Sources of uncertainty can be identified, isolated and worked upon. As a consequence, a model's performance improves. In this way, science is a self-correcting process over time. This is quite different from climate science denial, whose practitioners speak confidently and with certainty about something they do not work on day in and day out. They don't need to fully understand the topic, since spreading confusion and doubt is their task.
Climate models are not perfect. Nothing is. But they are phenomenally useful.
Please use this form to provide feedback about this new "At a glance" section. Read a more technical version below or dig deeper via the tabs above!
Further details
Climate models are mathematical representations of the interactions between the atmosphere, oceans, land surface, ice – and the sun. This is clearly a very complex task, so models are built to estimate trends rather than events. For example, a climate model can tell you it will be cold in winter, but it can’t tell you what the temperature will be on a specific day – that’s weather forecasting. Climate trends are weather, averaged out over time - usually 30 years. Trends are important because they eliminate - or "smooth out" - single events that may be extreme, but quite rare.
Climate models have to be tested to find out if they work. We can’t wait for 30 years to see if a model is any good or not; models are tested against the past, against what we know happened. If a model can correctly predict trends from a starting point somewhere in the past, we could expect it to predict with reasonable certainty what might happen in the future.
So all models are first tested in a process called Hindcasting. The models used to predict future global warming can accurately map past climate changes. If they get the past right, there is no reason to think their predictions would be wrong. Testing models against the existing instrumental record suggested CO2 must cause global warming, because the models could not simulate what had already happened unless the extra CO2 was added to the model. All other known forcings are adequate in explaining temperature variations prior to the rise in temperature over the last thirty years, while none of them are capable of explaining the rise in the past thirty years. CO2 does explain that rise, and explains it completely without any need for additional, as yet unknown forcings.
Where models have been running for sufficient time, they have also been shown to make accurate predictions. For example, the eruption of Mt. Pinatubo allowed modellers to test the accuracy of models by feeding in the data about the eruption. The models successfully predicted the climatic response after the eruption. Models also correctly predicted other effects subsequently confirmed by observation, including greater warming in the Arctic and over land, greater warming at night, and stratospheric cooling.
The climate models, far from being melodramatic, may be conservative in the predictions they produce. Sea level rise is a good example (fig. 1).
Fig. 1: Observed sea level rise since 1970 from tide gauge data (red) and satellite measurements (blue) compared to model projections for 1990-2010 from the IPCC Third Assessment Report (grey band). (Source: The Copenhagen Diagnosis, 2009)
Here, the models have understated the problem. In reality, observed sea level is tracking at the upper range of the model projections. There are other examples of models being too conservative, rather than alarmist as some portray them. All models have limits - uncertainties - for they are modelling complex systems. However, all models improve over time, and with increasing sources of real-world information such as satellites, the output of climate models can be constantly refined to increase their power and usefulness.
Climate models have already predicted many of the phenomena for which we now have empirical evidence. A 2019 study led by Zeke Hausfather (Hausfather et al. 2019) evaluated 17 global surface temperature projections from climate models in studies published between 1970 and 2007. The authors found "14 out of the 17 model projections indistinguishable from what actually occurred."
Talking of empirical evidence, you may be surprised to know that huge fossil fuels corporation Exxon's own scientists knew all about climate change, all along. A recent study of their own modelling (Supran et al. 2023 - open access) found it to be just as skillful as that developed within academia (fig. 2). We had a blog-post about this important study around the time of its publication. However, the way the corporate world's PR machine subsequently handled this information left a great deal to be desired, to put it mildly. The paper's damning final paragraph is worthy of part-quotation:
"Here, it has enabled us to conclude with precision that, decades ago, ExxonMobil understood as much about climate change as did academic and government scientists. Our analysis shows that, in private and academic circles since the late 1970s and early 1980s, ExxonMobil scientists:
(i) accurately projected and skillfully modelled global warming due to fossil fuel burning;
(ii) correctly dismissed the possibility of a coming ice age;
(iii) accurately predicted when human-caused global warming would first be detected;
(iv) reasonably estimated how much CO2 would lead to dangerous warming.
Yet, whereas academic and government scientists worked to communicate what they knew to the public, ExxonMobil worked to deny it."
Fig. 2: Historically observed temperature change (red) and atmospheric carbon dioxide concentration (blue) over time, compared against global warming projections reported by ExxonMobil scientists. (A) “Proprietary” 1982 Exxon-modeled projections. (B) Summary of projections in seven internal company memos and five peer-reviewed publications between 1977 and 2003 (gray lines). (C) A 1977 internally reported graph of the global warming “effect of CO2 on an interglacial scale.” (A) and (B) display averaged historical temperature observations, whereas the historical temperature record in (C) is a smoothed Earth system model simulation of the last 150,000 years. From Supran et al. 2023.
Updated 30th May 2024 to include Supran et al extract.
Various global temperature projections by mainstream climate scientists and models, and by climate contrarians, compared to observations by NASA GISS. Created by Dana Nuccitelli.
Last updated on 30 May 2024 by John Mason. View Archives
@Tom Dayton 1225
If you look at my original post at 1162 you will see that was the only course I found and it is not currently offered. I was asking for recommendations for a similar course at another university and I haven’t received any recommendation from this group.
Deplore_This: Another example of you writing your own contradictions of yourself, is your statement "And MBA programs use case studies extensively. I earned mine before Amazon but I suspect Amazon is a case study(s) in most current MBA programs." Exactly! One case study within courses that use other case studies as well--courses that address broader topics than any one of those case studies, or narrower topics than any of those case studies. Few if any entire courses devoted to, and titled, "how to make an Amazon-like mega company." Which was exactly Philippe Chantreau's point. GCMs, and "climate models" more generally, are covered in most atmospheric science courses, to some degree. Portions of those models are covered exhaustively, and not just as case studies, in many courses that are devoted to those portions of theory and modeling such as courses devoted to radiative transfer.
@Tom Dayton 1227
You’re speculating. Amazon offers a number of excellent business cases. In any event, Amaxon is a bad analogy to GCM.
ClimateDemon, allow me to make an introduction:
Nature has been trying for millenia to push more and more water vapour into the atmosphere, through a process called evaporation. Maybe you have met. The amount of water vapour that is added each year is huuuge.
Unfortunately, the atmosphere has a nasty habit of condensing that water vapour back to liquid (or freezing to solid) and letting it drop out of the sky as precipitation. It's really, really hard to get it to stay there for anything more than a few days. You can get the atmosphere to hold more if you heat the air up, but that means you need something other than water vapour to force that temperature rise.
Maybe CO2 would work. I wonder. Maybe someone should look into that.
There really aren't any "climate" models. There are models of earth systems, some being "just" atmosphere, some being "just" ocean, some being "just" biosphere, some being "just" land, and so on. Each of those models has sub-models that can and are created and used outside of those bigger models. Any or all of the above models can be combined into really big models that are attempts to model everything.
Any of those models--the big ones all the way down to the little ones--can be used to research climate, by running them over climate-scale simulated durations. They can instead be used to research weather by running them over weather-scale simulated durations. Indeed, "climate models" essentially are identical to "weather models." Of course there are important differences, but many of those differences are in how the models are set up and run rather than in the hearts of the models themselves. In particular, climate models are initiallized by running them for a few hundred simulated years until they stabilize, which means until weather cancels itself out, so that boundary conditions dominate intial conditions. Another notable example is that weather models rarely get run with and without injections of greenhouse gases, because changes in greenhouse gas emissions are too small to matter on the time scales of typical uses of weather models.
@Tom Dayton 1230
Alright, I’ll simplify this. How to I evaluate the following claim without relying on someone else’s opinion? (I’ve already read the IPCC reports).
“There is growing evidence that climate models are running too hot and that climate sensitivity to carbon dioxide is at the lower end of the range provided by the IPCC. Nevertheless, these lower values of climate sensitivity are not accounted for in IPCC climate model projections of temperature at the end of the 21st century or in estimates of the impact on temperatures of reducing carbon dioxide emissions.”
-— Judith Curry, the former Chair of the School of Earth and Atmospheric Sciences at my alma mater
https://www.thegwpf.org/content/uploads/2017/02/Curry-2017.pdf
Deplore_This: It is impossible for you, or anyone else, to evaluate that statement "without relying on someone else's opinion." Because science is a collaborative enterprise. Even, and 100% of, the scientists who create GCMs rely on other people's opinions--critically so. Certainly you can reduce your reliance on someone else's opinion, by learning about climate science. Computer simulated GCMs are only a tiny portion of that climate science. And trying to learn climate science by directly trying to learn computer simulated GCMs is an utterly doomed approach. Several people have given you multiple resources for learning enough climate science for you to start to be able to rely less on other people's opinions. You could stop rejecting those suggestions out of hand.
With regard to the particular claim you mentioned, you could start with the "How sensitive is our climate?" post here on SkS. Read the Basic tabbed pane first, then the Intermediate, then the Advanced. To dig in a bit more, go to RealClimate and type "sensitivity" into the Search box at the top right, then peruse the resulting posts. If you want to jump to cutting edge research on that topic, see the recent RealClimate post about the CMIP6 models.
@Tom Dayton 1232
You’re speculating. You may not be able to “evaluate that claim without someone else’s opinion” but that doesn’t mean someone more capable isn’t able to. And for climate research to be science it must promote hypothesis that can be empirically tested. If scientists are not allowed to challenge the common body of opinion like those I posted in 1193 and 1194 then it is not science, it’s group think.
You don’t need to respond here. I am going to post this philosophical argument under the correct category of SkS. I’ll post a link here.
[DB] Inflammatory snipped.
Deplore_This: Also, you seem to be overweighting the practical importance of the exact value of sensitivity. If you're in a car 200 feet from a rock wall, heading directly toward that wall, it doesn't really matter much if your speed is 50 or 60 miles per hour; the consequences are bad enough in either case that you should be applying the brakes right now. For climate change there is the additional urgency that the problem gets worse as time goes on, so even if sensitivity is on the low end, that merely delays the same bad consequences by an inconsequentially few years. Yet another time urgency comes from the fact that the primary causes (in particular greenhouse gas emissions) and feedbacks (e.g., lower albedo from loss of ice) are impossible to reverse on time scales that will be useful. Ice loss, for example, effectively is permanent on human timescales. Another problem with delaying action is that warming accelerates due to feedbacks, sort of like interest accruing on a loan. The longer you wait to pay, the more money you need to pay.
@Tom Dayton 1232
BTW I've already been through the climate sensitivity part of SkS.
@Tom Dayton 1234
Climate sensitivity is absolutely critical to accurately scientifically predict ACC as are the natural causes of CC. Regulatory policy decisions are based on those predictions. But that is a discussion for another article in SkS.
[DB] Off-topic snipped.
Deplore_This:
It is not enough to read the IPCC or any other material. You also have to understand it. I have seen nothing in your postings here to suggest that you understand anything at all about climatology or climate models.
I have see nothing to suggest that you have understood any of the material that you have been pointed to here, or that you understand any of the materail that you have cut and pasted from denial blogs and sources.
You parrot stuff you don't understand. You accept everything that suits your pre-conceived bias. You reject everything that disagrees with that bias.
DNFTT.
@Bob Lowlaw 1237
You aren't intelligent enough to understand what I know.
[DB] Please note that posting comments here at SkS is a privilege, not a right. This privilege can and will be rescinded if the posting individual continues to treat adherence to the Comments Policy as optional, rather than the mandatory condition of participating in this online forum.
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Egregious personal attack removed.
Deplore_This ,
Firstly, allow me to thank you for bringing entertainment to this thread.
Secondly, allow me to state the obvious ~ being what all readers here are thinking ( including you yourself! ). It is obvious that part of your activity is you indulging yourself in some trolling (but please be calm, because my words are charitable ~ since the alternative diagnosis would be distinctly more unflattering.)
But I see that you are actually here for two purposes (whether you realize it or not). For like many people who start off as climate-science deniers and visit SkS, your mind is split in two. One part knows that it is in the wrong about the science. And actually would like to learn "climate". The other part angrily rejects that self-acknowledgement, and wishes to challenge (and troll) the mainstream science position. [ Here, I won't now go into your subconscious motivations for rejection of the well-established science ~ but you really do owe it to yourself to do some self-examination. It is sad for anyone to live the "unexamined" life. ]
One part of your mind knows that it really ought to learn about such important science. And because in the long run, the science always wins (and history condemns the foolishness of the Flat-Earthers, Geo-centrists, Anti-Evolutionists, et alia.)
The other part of your mind (call it the Denialist part) wishes to fight on, and cause as many waves as possible. Inevitably, this ends up with you embarrassing yourself publicly ~ but the Denialist part is too angry to care about that, and rather enjoys making futile waves.
Ah, we humans are an interesting lot
. . . often Deplorable, yet always Interesting.
Philippe Chantreau @1222
I am not trying to overturn anything. I just want to see the science done correctly. Also, your comment about me arguing that water vapor can serve as a forcing instead of a feedback shows that you are still thinking in terms of the "control knob" model which I have already shown in 1173 and 1190 to be false.
[DB] Making things up is unhelpful.
Sloganeering snipped.
ClimateDemon @1240,
You cite your comments @1173 & @1190 as providing demonstration that the CO2 'control knob' concept of climate is "false".
I would suggest there is no such provided demnstration.
It takes little effort to examine these comments of yours.
@1173 you compare the role of CO2 and H2O when accounting for the energy balance of the atmosphere and jump to the assertion that "there is nothing to indicate that CO2 has any 'control knob' effect." Appended to that rather incomplete analysis, you cite Lacis et al (2010) as describing "the only model that predicts AGW and the CO2 control knob" but that Lacis et al are wrong because this "only model" simplifies the climate system too much. In particular, you describe this "only model" using the Clausius-Clapeyron equation and with "the earth's temperature is represented by a single scalar value T." Your final assertion sets out "It took several false assumptions to make the control knob argument, so there are very likely problems with it."
@1190 you call for people "who claim that I am making evidenceless assertions" to provide "just one example of such an assertion" that you have made. You append to this call three ground rules which you insist all will agree. (i) A world witout a "uniform" surface temperature is not in "thermal equilibruim". (ii) Use of the Clausius-Clapeyron equation cannot be extended to include the large global temperature variations. (iii) An equation should not be used beyond its limits.
(ClimateDemon, do correct me if I misrepresent the intention of your comments @1173 & @1190.)
I find these comments disturbing in many ways but let me here provide a little more than "just one example" of "evidenceless assertions" by naming that "only model."
That "only model" @1173 can only be the one used by Lacis et al (2010) and that is GISS ModleE which nobody in their right mind could ever describe as being:-
Yet that is what I read @1173.
Further, the initial consideration @1173, that CO2 and H2O are treated identically within energy balance equations and that of the two H2O is the more powerful GHG, ignores the obvious point that GISS ModelE models the hydrological cycle (thus setting H2O as a feedback) while the levels of those non-condensing GHGs (of which CO2 is the major component) are simple inputs into the model (thus setting CO2 as the primary GHG forcing agent). And that treatment of CO2 & H2O is the same as that in other GCMs. GISS ModelE is/was never "the only model that predicts AGW and the CO2 control knob."
Bob Loblaw @ 1229
Well how about that! I, too, have a friend whom I would like you to meet — nonequilibrium. At least I believe you are still strangers since you don’t seem to recognize him at all.
Yes, H2O vapor will condense if cooled, but not the entire earth instantaneously. However, if you use a single-temperature earth model constrained to thermal equilibrium at all times (ie. CO2 control knob model), this is exactly what you are assuming. By not handling these atmospheric problems regarding the atmosphere as the nonequilibrium system that it is, you miss all transient effects and temperature changes seem to happen quite suddenly. Here are a couple of quotes from the SkS Climate Myth 36 page that I believe illustrate my point quite well.
Eclectic @268 Climate Myth 36
… Now picture all CO2 suddenly removed from the atmosphere — result: a strong rapid negative feedback. Temperatures plummet, with widespread snow & frost precipitation on land and a fast-spreading layer of ice on the sea [with further sunlight reflection and further spread of sea-ice, to 100% coverage]. Ultimate result: a frozen world (and with minimal H2O in the atmosphere).
KR @284 Climate Myth 36
Non-condensible gases set the thermal equilibrium, condensible gases (water vapor) can only act as feedback because they respond so quickly to a temperature change, even if their overall effect is quite large .
Do the temperature changes and precipitation actually happen that fast? – Not really. What we are seeing here is an artificial discontinuity in temperature due to the neglect of transient effects in the equilibrium model. It’s somewhat like turning on a new refrigerator and expecting the temperature inside to immediately drop to the operating temperature.
At this point, I would strongly suggest that you and your AGW comrades educate yourselves some more on the fundamental physical laws behind the climate models, and recognize when you are working with equilibrium and nonequilibrium systems. Maybe then you won’t be quite so bamboozled by CO2 control knobs and icebound earths.
BTW — I'm actually all grown up now so you can knock off the kid talk!
[DB] Inflammatory baiting and sloganeering snipped. You need to up your game by citing credible sources to support your claims. Assertions are not sources.
ClimateDemon ,
your posts here have been rather off-topic for this thread.
Why not return to the comments section of Climate Myth 36 , where in 2016/2017 you were given frequent & extensive explanations on the subject of H2O vapor and non-condensable GHG's role as climate Control Knob.
That would be the place for you to express any new & convincing arguments which you may have managed to produce since then.
[TD] Uh oh, good memory, Eclectic! Perhaps ClimateDemon is yet another sock puppet of JeffDylan, MartianSky, cosmoswarrior, and so on?
Among the bazillion courses that cover climate modeling (sinisterly hidden so they can be discovered only by searching the intertubes for climate modeling course class university!) is this free one by David Archer that starts today. Obviously Deplore_This will deny it is relevant to climate modeling, but other folks might be interested: Global Warming II: Create Your Own Models in Python.
Although water vapour's role may be better discussed elsewhere, ClimateDemon has made some rather inaacurate claims about climate models. That makes this on topic (I think) for this thread.
Rather than creating a strawman using a simple "single-temperature earth model constrained to thermal equilibrium at all times" (which sounds like ClimateDemon is thinking about zero-dimensional equilibrium models only), let's discuss how precipitation and evaporation work in something like a General Circulation Model (GCM). Such models have full hydrological cycles, and atmospheric dynamics very much like a weather forecasting model. In such a model:
Now, the real world does the same thing, and there are typically three primary ways of getting air to rise and cool. This is covered in pretty much any reasonable introductory weather or climate course or book. The precipitation types related to these processes are used to label the precipitation type;
GCMS include all three of those processes.
Now, ClimateDemon has said "Yes, H2O vapor will condense if cooled, but not the entire earth instantaneously. ", so we need to consider how long we are talking about. So, what amount of time are we talking about for each of those three processes? What is the time lag?
So, in both climate models (GCMs) and the real world, removal of precipitation from the atmosphere is a very rapid process. Not instantaneous in the life of a fruit fly, but pretty close to instantaneous in terms of geologic time.
Mother Nature is unable to drive atmospheric moisture levels up enough to increase the water vapour greenhouse effect for any length of time beyond a few days, because Mother Nature is so good at removing it through precipitation.
The only way to increase long-term global average humidity is to find some other way to warm the global average atmosphere. A way that has more permanance. Then water vapour can increase, and its greenhouse gas properties will act as a feedback on temperature, but it can't do it on its own.
Water vapour will not drive climate change. The models agree with reality on this one.
Tom Dayton @1224 and 1244
Thanks for your responses, and please understand that I am not trying to tear down the general integrity or accuracy of the current models. I do have serious concerns, however, as to how the climate science community is applying these models to conclude that humans are well on the way to toasting the entire earth with their CO2 emissions. Over the last 5-10 years, however, the only analysis I have been able to find that at least indirectly blames humans for the warming trend during the last two decades of the 20th century is the CO2 control-knob theory as explained on the Lacis et. al. paper. I did find several different authors, including John Cook, but they all said pretty much the same thing.
Now, in your statement 1224, you claimed that this was not the only model and paper that predicts the CO2 control knob and AGW. So, what I need to know is what models and papers are out there that do predict AGW, and specifically who or what the AGW community (including politicians as well as scientist) is referring to when they make swooping claims such as "scientists say that humans are causing global warming".
Bob Loblaw @2445
Very good! Now explain how all of this implies that humans are causing global warming.
ClimateDemon, I gave you links to Richard Alley's lectures. There are relevant posts here on SkS as well, which you were given links to, in moderator's comments. There is no point in me or anyone else responding to your requests for information when you refuse to read or watch those resources. It is clear you are merely trolling.
ClimateDemon @ 1247:
Sure. I'll do that as soon as you explain what caused the financial crisis of 2008, and give a detailed explanation of the factors leading up to the Second World War.
What's that? Oh, you mean we're not just playing a game of "ask irrelevant questions?".
I'll take it as a given that you actually have no constructive argument for your previous statements about water vapour.
Tom Dayton @1248
What makes you think I haven't looked at those sources and a whole lot more. If they are so relevant, then howcome they don't even pretend to answer my questions. And no, I am not trolling but it's getting tempting since asking politely isn't working.