How reliable are climate models?
What the science says...
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Models successfully reproduce temperatures since 1900 globally, by land, in the air and the ocean. |
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.
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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.
Last updated on 30 May 2024 by John Mason. View Archives
NorrisM @1047 , if I may add some background to Tom Dayton's posts :-
When considering climate models, it is well to remember that the models are based on the physical realities of this world.
And the most basic of relevant points, is that the natural greenhouse effect from CO2 etc. has been "artificially" (anthropogenically) pushed higher by the addition of fossil-origin CO2 to the atmosphere. The result is that the world is warming up — it is gaining heat at the rate of approx. 2 watts per square meter. (Which may not sound very much : yet if you think it through planetwide and decades-long, then it represents a major problem for this planet.) Also, if you think it through (regarding where that heat is going and how it moves about within the system of the planet) then you will realize that a pause or hiatus is simply not possible until such time as the system eventually reaches equilibrium (in 2 or 3 centuries' time).
Therefore if Koonin says there is a real "Hiatus", then he talks nonsense.
If you are a Black-Letter lawyer, you will wish to examine "fake-skeptic" comments without considering their provenance or any ad-hominem aspects. Yet as a pragmatic man-of-the-world lawyer, you will wish to take into account the background information regarding the four protagonists you mentioned [Koonin, Christy, Curry, Lindzen], when you come to assess their evidence.
And you will be aware of human frailties — particularly that frailty called "Motivated Reasoning" : where even very intelligent people (such as Koonin) do bend their rationality and end up deceiving themselves. And doing so, very staunchly! And with apparently honest demeanor!
Climate science is a large area, where you can educate yourself considerably — and if you do so, you will find yourself in agreement with the extensive and almost unanimous consensus of experts (e.g. the U.S. National Academy of Sciences; the U.K. Royal Society; the Vatican's Pontifical Academy of Sciences; and dozens more of peak scientific bodies). All in consensus about Global Warming. Indeed, there is only a score or so of Koonins, Christys, Currys, and Lindzens who hold an outlier position in disagreement with the overwhelming preponderance of scientific experts. And as you yourself gain education in climate science, you will understand that these 4 protagonists, despite their intelligence, have all managed to make a very poor judgment of the actual position. And that, as you look beyond their rhetoric, you will find that their apparently scientific arguments are empty and false.
How is it possible for 4 intelligent people to be so very wrong? It is because their emotions have pushed them into motivated reasoning. Motivated reasoning by Koonin / fundamentalist religious bias from Christy and Lindzen / and something less clear, from Curry [about whom you need ask: Cui Bono ].
In the strictest sense, these four are not being scientists — because they have allowed their emotions to override their dispassionate intellects.
They have muddied the waters and confused your understanding of the significance of models (and of the physical realities).
NorrisM @1047,
A big long comment from you setting out a lot of stuff. Can I home in on the things you describe as "what also troubles me in everything that I have read so far on climate change." (As you say it is off topic for the thread but...)
(1) The Mediaeval Warm Period. This you describe as being "at least 200 years in at least Greenland and Northern Europe close to or equal to our present temperature." The temperature at the top of Greenland can be reconstructed from ice cores with some accuracy. GISP2, for instance shows results like this graph and some will take the last few thousand years of this graph as proof that recent warming is trivial when compared with previous centuries, as this SkS post describes. Yet the most recent GISP2 data dates from 1855 and when you graft on modern temperature data things look a whole lot different. The idea that Greenland experienced temperatures "close to or equal to our present temperature" is not borne out by the evidence.
2. "During the 1600's and 1700's there was ... skating on the Thames." We do have the CET Central England Temperature record stretching back into the 1600s, temperatures recorded a few dozen miles up the road from the Thames at London. This shows seriously cold winter month have been occuring occasionally throughout the record with the last occuring in 2010. History tells us that Ice Fairs were rare events and they do coincide (almost always) with these exceptional cold CET months. Ice Fairs stopped not because of a Little Ice Age ending or because of global warming but because the old London Bridge was demolished and the banks of the river were embanked. It's all a bit nerdy, but ancient accounts of the Thames freezing continue back in time and continue through the Mediaeval Warm Period (prior to the bridge being built) and are even found for the centuries called by some the Roman Warm Period.
3. You are on much safer ground suggesting that reconciling the temperature record and climate forcing in the first half of the 20th century is not straightforward but very much less safe with the so-called hiatus. There is a lot of comment on these elsewhere within the SkS site. You do raise the idea that if the hiatus was the product of La Nina sucking the warming from the atmosphere and down into the ocean depths. (It is not controversial to state that the years 2007-13 saw lower global temperatures due to La Nina and withut these years the so-called hiatus is truly a non-event.) From this you speculate whether it was potentially the oceans warming the atmosphere 1975-98. You are not the first with such speculation. Bt if there was such a warming from the oceans, there would be evidence of it in the Ocean Heat Content data as it takes a lot of heat to both warm and keep warm the atmosphere. The level of heat required would certainly have to be evident in the OHC data. It is not evident.
[PS] Thanks for contribution but it would be more appreciated if you had followed the request to put it on the correct place since MWP is offtopic here.
Tom Dayton, Eclectic & MA Rodger. I would like to thank all of your for your comments. I think I have to spend more time reading the full thread both for this topic as well as on questions of MWP etc. I think that I will withdraw from any further comments until I have at least read the full thread on this topic (this could be a long time!).
As a lawyer and not a scientist, I find the best way to come to a conclusion is listen to both sides similar to the process in determining any litigation (I am actually a business lawyer not a litigator). For this reason, my plan is to stay on this website and also the Nigel Lawson GWPF site. I actually have never even looked at the Skeptical Science website. I think I can "filter" things sufficiently to read postings on both sites.
The information on Steve Koonin is quite interesting given his statements in the transcript of the APS panel hearing where he professes surprise a number of times on what he was hearing. I thought I was reading the questions of independent physicists who were trying to get at the facts (I just about said "truth"). But I do commend that transcript to all of you, if only to hear how these significant IPCC climatologists respond to the questions.
But one suggestion to the editor of this website. I think that "ad hominen" comments on the persons contributing to this website should be fully deleted and never appear at all on the website. Just "stroking them out" but allowing everyone to read them just encourages those kind of comments to be made. I do find that the proponents of anthropogenic global warming seem to be much more in "attack mode" than the other side. Can we not come up with a less pejorative term than "climate change denier" with all its connotations when literally none of the Curry, Christy et al group deny that the world is getting warmer.
This term "fake skeptic" is awfully close to "fake news". Is it recently invented since the advent of Trump?
Having said all of this, the recent post today indicating that Stephen Hawking is onside and part of a new organization gives me a significant degree of comfort. Reading his History of Time was a challenge but I got through it. Unless I have missed another YouTube, I was very disappointed with the Neil DeGrasse Tyson video explaining global warming because it is so simplistic and does not explain any of the challenges in trying to "predict" future changes in the climate. I appreciate why he has done this, reaching for the lowest common denominator amongst the public, but I think scientists do have a responsibility to qualify absolute statements. Otherwise, they move into the political arena which then undermines the confidence the public has in their scientific statements.
In any event, thanks very much for all of your comments. Lots of reading ahead of me.
[DB] "This term "fake skeptic" is awfully close to "fake news". Is it recently invented since the advent of Trump?"
The term "fake-skeptic" has been used in this venue since at least 2010. The denial of the science by the venues you note is well-established over the years.
[PS] Your "truth search" understandably seems to be about determining the reliability of witnesses. How many bits of GWPF propoganda, misinformation and denial would we have to demonstrate to you before you decided they were unreliable witnesses?
NorrisM
Firstly, for you as a lawyer, whose principle skill is the use of language...
"Can we not come up with a less pejorative term than "climate change denier" with all its connotations when literally none of the Curry, Christy et al group deny that the world is getting warmer."
This is standard rhetorical technique which I presume you would be adept at slicing through in a legal context. The term 'climate change denier' covers a range of differing 'denials' and by claiming it is being ascribing to one subset of of this 'population', aren't you are engaging in rhetoric.
Next, the purpose and function of climate models. They are, really, no different from weather models. Used to produce the weather forecast.
Climate models work at a coarser resolution than weather models but essentially attempt to produce differing results. A weather model takes what the weather is today and attempts to determine what the weather will be x days from now. In principle, exactly. Well, sort of...
A climate model, being coarser, has a snowflakes chances in hell of doing this. One run of a climate model will be significantly random. And another run of a climate model, with slightly differing starting conditions will also be significantly random.
What if we do many runs of the climate model, each with slightly differing starting conditions? Each run is different. But what does the average of many runs look like? Well this starts to have a pattern, an order to it.
Although each run differs, their average is much less chaotic. Because the underlying climate does vary in a modestly predictable way. The average has predictability.
But that does not mean that the actual day to day evolution of weather over climate timescales will accurately follow this average trend. Because day-to-day weather is chaos superimposed over an underlying order. And since we can't easily predict the chaotic component, the actual weather data will not ever match the climate exactly.
So we can't expect weather to progress with the regularity that the climate averages suggest.
NorrisM:
With a legal background, and experience in trying to assess the credibilty of different sources, one thing for you to look for is inconsitencies in a position. Skeptical Science has a summary page listing contradictions in the so-called "skeptical" view of climate change.
Another issue to keep track of is how often someone expresses complete certainty on something. Generally, you will find that the science of climate change has a lot of "ifs" and "most likelys" - sources of error are discussed at length, and implications of uncertainty are noted. In the so-called "skeptical" view, you will often find very definitive statements (that often contradict other definitive statements). In science, admission of uncertainties is a strength, not a weakness.
Response to NorrisM's comment on another thread: Norris wrote "If I understand your first example, this would suggest that it is appropriate to "average" the various model results and compare them with the actual observations."
No. There is only one observation run, so you cannot average it with other observation runs to obtain the observations mean, so you cannot compare the models mean to the observations mean. Instead, you compare the observations run to the statistics of the model runs, including not just the model runs mean but the model runs spread.
Likewise, we have only one observations run of Earth's temperature because we have only one Earth. You continue to ignore my explanation from weeks ago. As MA Rodger noted, in that comments thread you have merely reiterated your claims from this thread without responding here to the people who gave you information you asked for.
Also following from NorrisM's comment on the thread Tom Dayton refers to:
The model spread is also not an ideal representation of the uncertainty in the prediction, because the number of models is very limited and the type of things they include is different.
RealClimate has set up a page that discusses such things in more detail.
NorrisM @that other thread,
In the context of seeing the results of Multiple Linear Regression adjustment to the global temperature record (Foster and Rahmstorf (2011) adjusting for Sol, Vol & ENSO), you ask:-
The linear assumption for temperature response in F&R2011when Sol,Vol&ENSO are accounted for does leave much unaccounted for while the models in accounting for actual forcings and climatic responses and so have no problem with the 'non-linear', but in so doing fail to reproduce the very important but unpredictable ENSO oscillations.
One approach to coping with ENSO unpredictability adopted by Risbey et al (2014) is to be selective of the model results and only include "those models with natural variability (represented by El Niño/Southern Oscillation) largely in phase with observations are selected from multi-model ensembles for comparison with observations."
And the finding - "These tests show that climate models have provided good estimates of 15-year trends, including for recent periods and for Pacific spatial trend patterns."
Another approach adopted by Huber & Knutti (2014) is to calculate the adjustment required to account for ENSO effects in the models. They conclude from this work "that there is little evidence for a systematic overestimation of the temperature response to increasing atmospheric CO2 concentrations in the CMIP5 ensemble."
Clarifying MA Rodger's excellent reply to NorrisM: Risbey et al.'s approach demonstrated that the models do a good job of producing the sizes and durations of ENSO events. What the models do a poor job of is getting the timings ("phasings") right. Possibly the models never will get better at that, no matter how powerful the computers. Part of the reason for that shortcoming is that climate models are not intialized with the conditions yesterday in order to project the conditions tomorrow. Weather models do that, which is why weather models solve the "initial values" problem. In contrast, climate models are initialized with conditions far enough in the past so that by the time they get to projecting the future, the weather has canceled itself out, thereby wiping out any preferential effect of their particular choice of initial values. What constrains climate models to converge on their long run statistics regardless of their initial values, are the "boundary conditions" of the climate system, such as the net energy entering/leaving the top of the atmosphere. See the post on weather versus climate. After you read the Basic tabbed pane there, read the Advanced tabbed pane, and be sure to watch the video there.
Responding to comment by Mike from here
Further to that - when modellers run one of projections for what humans will do (the RCPs which are about emissions, aerosols), they also have to put in what they think natural forcings will be. (Sun, volcanoes). These are not predictable. If you didnt put in some volcanic eruptions, then the models would always run to hot. However, modellers cannot actually predict when, where, or how big an actual eruption will be - so you put representative volcanic aerosols based on average past history, and vary that with runs. Solar is also hard to tie down precisely.
So if your interest is how well a particular model predicted climate 10 years ago, it is better to rerun the identical code but with actual forcings not the what was projected at the time. This will tell you how well the model will predict climate as opposed to how well modellers predicted forcings. Unless you are pseudoskeptic of course - if so then any distortion that backs your ideologically-based prejudices is just fine, by ideology beats reality, right?
My two cents worth. I'm not a scientist, and not a lawyer, but I have done some stage 1 introductory level university maths, chemistry, physical geography, in the 1980's.
The comments 1054 - 1059 above on models are of course perfectly correct, but would be hard for a lawyer or total lay person to understand.
I would simplify or maybe summarise comments by saying models can predict long term temperature trends, and endpoints, because greenhouse gases and basic, underlying long term solar changes can be quantified as a long term trend. Models cannot predict every wiggle along the way, because ocean processes are slightly random in their timing. These wiggles might be a couple of years or up to ten years, but they don't alter the basic long term trend or track.
This is how I have explained things to denialists. If I'm wrong please tell me.
The pause was significant, but by the time it was properly measured, it was not outside of what models predict could happen.The "pause" looks about 8 years maximum in the nasa giss graph. Models have error bars partly to allow for this short term, random, natural variation.
If you look at the model / real world data comparisons on realclimate.org the models are predicting temperatures over the last 30 years pretty well.
Temperatures are slightly 'under' but not by much, and are certainly within error bars.
The more useful question is to ask why are models still slightly over estimating temperatures. I have read a theory that oceans are delaying warming a little.
Anyway if you look at the realclimate graph, it obviously wouldn't take much for temperatures to jump towards the very top of the error bar.
The bottom line is it seems absurd to me to claim in 2017 that models are way off, or anything like that. Therefore scientists claiming this are grand standing to make inflammatory statements. I dont think that really helps, as it gets picked up by the media.
Also following along the question of removing El NIno effects from the observational record, a simper appraoch is to look at only the years with El Nino, only the years with La Nina, and the remaining "neutral" years as different data sets. Examining the trend in each set individually will help separate the effects in a much simpler manner than the multiple regression or modelling techniques. The simplicity may make it easier to understand.
This has been done by John Nielsen-Gammon, and SkS posted on this in this discussion:
https://skepticalscience.com/john-nielsen-gammon-commentson-on-continued-global-warming.html
Short story: all three sets show basically the same trend.
Thanks everyone above.
Nigelj, I have to admit that 1054-1059 are challenging for a lawyer. I have not had time to go to realclimate.org but I will after we return from holidays. On our sailboat and hoping for wind but I have to admit, I do turn the diesel engine on when there is no wind!
To me the issue of how close the models match observations over whatever necessary period (20 years?) is critical. The "other side" says that there are large discrepancies (I believe that is what they say). If anything, a Red Team Blue Team approach would be the opportunity to show the other side what the models can and cannot do over specified periods of time and how accurate they are. As I noted elsewhere, Santer and Held had the chance to make this point at the APS panel and now have Koonin questioning the models because they did not adequately defend them.
My simplistic understanding of the scientific method is that one comes up with a theory and tests it to see if it is borne out by the tests. Or the model makes predictions and one looks back to see if the models were correct.
If the models cannot show that they are accurate over a 10 year period, then it does get problematic because how are public officials expected to commit massive amounts of funds until the models have shown that it is reasonable to assume they are right on, for example, a 3C rise by 2100 assuming that it is "business as usual"? When I use "predict", I mean a model projection which assumes that no mitigation is taken.
One last point before I head off. I do not think we can rely on "hind casting" to prove that the models can closely match reality because there are too many "fudge" factors used to make the models "fit" the actual history. There is no way of knowing if the same fudge factors work for the future. This is not original, I know. I think this is Freeman Dyson's comment at the beginning of this thread.
i will certainly spend more time on this when I get back. Perhaps by then we will have heard what the Trump administration has decided to do. If all we get is a TV debate as suggested by Scott Pruitt then all we will get is a gong show.
I truly think that a scientific debate along the lines of a legal hearing with both sides going at each other with an independent panel coming to a decision (with dissenting opinions) would be the best way to achieve some form of acceptance by the Republican party. I know this sounds naive but I have to admit I would like to see it!
Moderator: Sorry, just a little "off topic" at the last. Sometimes it does not make sense to fully "stream" these thoughts.
I am very much still a "fence sitter" on this issue because it is so technical and you have intelligent human beings on both sides of this debate saying different things. It is very frustrating. You would think that everyone could at least agree on the facts. Perhaps the Red Team Blue Team traditional approach could achieve some agreement on at least how far apart the models are from observations. That is why I so much trust our adversarial system of justice in Canada and the US compared to the European system. Let each side go at it and have an independent judge or judges render their decision AND provide their reasons for their decision. If there is disagreement amongst the panel, then dissenting opinions are also given.
[DB] "If the models cannot show that they are accurate over a 10 year period"
As Tom Dayton notes, you continue to ignore the explanation he gave you even earlier. You also continue to not investigate the links you were given. You instead resort to sloganeering (repeating claims already invalidated). In a judicial trial, a judge would warn you for this behaviour. In this venue, there is a similar reproach.
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NorrisM @1061 , several points :-
1. Yes, you are beyond even the most extreme naivety, if you feel there's a chance that the political extremists [= Republicans, in this case] would come to any "acceptance" of what the climate science is telling us. And I'm sure that you, as a man of the world, are aware of the situation. It doesn't matter how many hearings occur, at ever higher levels of review and appeal, all the way up to the Supreme Court or beyond . . . . . the extremists will reject authoritative judgment (even if it were issued by the Archangel Gabriel).
2. The Global Warming issue has already already been "Red-Teamed and Blue-Teamed" extensively, for many years — and the result is as you know, a unanimous decision by the only court truly competent to make the judgment (i.e. by the scientists who have the technical knowledge to make the properly-informed decision). Yes, not quite strictly unanimous : there is a minuscule group of "dissenter" climate scientists [ well under 1% ] but their decisions are incompetent owing to the incoherent and mutually contradictory assertions they make. (And a realistic cynic would regard these "few" as composed of crackpots and/or shills for vested interests).
3. The politicians who reject & deny the plain scientific truth, will only change their viewpoint if it seems imminent that they will be voted out by a "fed-up" public — or if their major donors die off or themselves succumb to public pressure (e.g. to shareholder revolt). It is the long-running propaganda campaign of denial, which is the actual influencer or "hamperer" of public opinion : and not any judicial decision or series of judicial decisions.
4. NorrisM, let us be realistic : the question of virtuosity of "models" is unnecessary to the scientific case. The real physical world has already given us the decision, by means of obvious and incontrovertible evidence — sea levels have risen and are rising ever faster; planetary temperature has already risen 1 degreeC above the previous [downward] trend; glaciers and polar ice and permafrost are disappearing at a rapid & increasing rate; the oceans have warmed & acidified; plants and animals have changed their traditional pattern of activity.
Crackpots & shills try to delude themselves and deceive us with graphs which are downright economical with the truth [to use that ironically polite phrase!!]. But in summary :- the world is clearly rising significantly higher in temperature, and with no sign of slowing down any time soon — so to that extent "models" are unnecessary for responsible policymakers (and for us ordinary citizens, too).
Reckless foolhardiness & negligence are the traits of the "deniers".
Correction : that should be addressed to NorrisM @1063.
My apologies for that typo.
Regarding modelling. Even if you forget models, just for one minute, and just project the last 30 years trends forward as a linear trend to end of century, you get very significant warming.
However it will then only take a quite small acceleration to this recent trend, due to constant ramping up of emissions combined with proven positive feedbacks, to cause more warming of about roughly 4 degrees. (Sort of like compound interest). This is what people need to get their heads around.
The Red Blue team court room concept is not the appropriate mechanism to decide science. Courts are already having huge problems making sense of complex financial cases, that are beyond judges, juries and lawyers. Repeating this exercise for science is verging on insanity.
You would be deciding the fate of the planet on who is the best dressed most articulate, and possibly devious speaker and gut reactions of people to all this. Its better to leave such decisions to the people at the IPCC and their more measured processes.
The Europeans grasp this problem and have more of an "Inquisitorial" legal system for complex cases. The IPCC system that we already use is essentially an inquisitorial system!
Honestly I cannot believe the absurd lenths the Republican Party are going to try to deny the climate problem. If only they could see themselves from the outside looking in, and how absurd and desperate they look.
NorrisM,
To me the issue of how close the models match observations over whatever necessary period (20 years?) is critical.
as a lawyer then, perhaps I could ask you whether a person should be judged on the basis of what they have clearly stated (and is recorded), or on the basis of what someone else has reinterpretated them to say?
What climate science expects, is that surface temperature will evolve as a very wiggly line that mostly lies within the range of the multiple model runs ( the grey area in the model projection maps).
Also, I wonder that put so much emphasis on prediction. Models beat reading entrails hands done, but they are not best way to test climate theory, especially such a noisy variable as surface temperature. The normal physics verifications are much better but funnily enough, not skeptic talking points.
Closer to my speciality, I am glad people can take the necessary expensive reforms required from taking earthquake science seriously without demanding prediction models match observations exactly first. Good thing ideological biases havent got in the way there.
I have an important challenge for all climate scientists who feel mathematically inclined.
According to modern climate science theory, H2O vapor concentration is determined only by temperature. This is because H2O can exist on earth in all three phases (solid, liquid, or gas), and therefore the concentration of H2O vapor is determined by the Clausius-Claperyon (C.C.) equation at the given temperature. CO2, however, exists on earth only as a gas (except of course for man-made dry ice), and therefore is subject to no such constraints by the C.C. equation.
The fact that CO2 concentrations can freely vary whereas H2O vapor concentrations are determined by temperature makes CO2 a "control knob" for the greenhouse effect. The argument is that we can increase CO2 concentration without it condensing, which would then increase greenhouse heating causing a rise in temperature. This temperature rise then causes more H2O molecules to enter the vapor state which in turn causes more GH heating. The reverse, of course, holds true if CO2 concentrations decrease. Therefore, CO2 controls the GH heating even though H2O vapor is the stronger GHG, both spectrally and in quantity.
In examining the derivation of the C.C equation, we note that it assumes an isolated system in thermal equilibrium, which the earth and its atmosphere is not. They do, however, form a local thermal equilibrium (LTE) system where temperature and concentrations can be defined locally but not globally, a situation often occurring in fluid mechanics. To a climate scientist, LTE works the same as global equilibrium for use in the C.C. equation. I have some misgivings about that but I won't argue the point now.
Let's take a look at the C.C. equation. It states that for an isolated system consisting of a substance in the gas state in thermal equilibrium with the same substance in the liquid (or solid) state, the partial pressure P of the gas is related to temperature T according to
ln (P/P_ref) = (H_vap/R)((1/T_ref) - (1/T))
where P_ref and T_ref can be any known valid partial pressure / temperature pair, for example P_ref = 1 atm at T_ref = 373 deg K, H_vap = latent heat of vaporization, and R = universal gas constant. Notice that only one value of the partial pressure P and one value of the temperature T is inserted into this equation. So, how do we choose those values for a system consisting of many different partial pressures and temperatures? I believe most climate scientists would say that one merely replaces the values of P and T with their global mean values
and . But is this mathematically correct? This is the challenge I have for all climate scientists who feel mathematically inclined. Given that the above equation is true for all points on the globe (ie. LTE is assumed), prove or show a counter-example to this equation:
ln (
/P_ref) = (H_vap/R)((1/T_ref) - (1/))
Keep in mind, of course, that if this assertion is not true, then the entire CO2 "control knob" theory is in serious trouble.
[DB] Sock puppet nonsense snipped.
Randy C @1069, your assumptions about what climate scientists believe are in error. In particular, while the assumption of constant relative humidity is used as a first approximation of the water vapour feedback, it is not used as an assumption in detailed explorations of the issue. See Minschwaner an Dessler (2004) as an example of more detailed examinations.
I will further note that your assumption that if relative humidity is not maintained, the water vapour feedback is negligible is also not valid.
[DB] Please note that RandyC is just the latest iteration of serial spammer cosmoswarrior and his iterative sock puppets coolearth / diehard / dieharder / moonrabbit / landdownunder / blackhole / WhiteDwarf / GreenThumb / HeatRay / RobJones / JamesMartin / banbrotam / JeffDylan / jcdylan. His compulsion to flood this venue with sock puppets is strong, bordering on pathological.
RandyC - would you accept that if climate science is correct about CC control of water vapour, then Total Precipatible Water should then be highly correlated with surface temperature? Furthermore, you agree that if climate science has it wrong about CC, then climate sensitivity derived from paleotemperature archives would be lower than those derived from models?
scaddenp - Let us consider your first question
Would you accept that if climate science is correct about CC control of water vapour, then Total Precipatible Water should then be highly correlated with surface temperature?
The short, simple answer to your question, of course, is "yes". Given a certain temperature, there is one and only one value of the H2O vapor concentration that satisfied the CC equation. Equivalently, we may regard the CC equation as establishing the H2O vapor concentration as a function of the single independent variable T (ie. temperature). This being the case, we would expect that the amount of H2O vapor in a column of air above a certain area on the surface to be closely tied to the temperature of this area on the surface.
There is also, however, another implication if the CC controls H2O vapor. Remember that the CC equation was derived to determine the equilibrium partial pressure (or equivalently concentration) of a vapor when a reservoir of this same substance in the liquid or solid state is present. This equilibrium concentration (determined by the CC equation) also plays the role of a saturation concentration whether any liquid H2O is present or not. The idea is that if the vapor concentration exceeds this saturation value, then liquid H2O will precipitate until thermal equilibrium is once again established between the H2O vapor and liquid present. Therefore, the CC determines the maximum vapor concentration at a given temperature and not the vapor concentration at this temperature. If we use the CC determined H2O vapor concentration as the atmospheric H2O vapor concentration, the implication would be 100 percent relative humidity everywhere. This would preclude deserts or otherwise dry climates anywhere. Also, the H2O vapor feedback, established as the principal mechanism of AGW, would be way overestimated.
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Moderators - In posting this message, I am not spamming, trolling, nor being a "sock-puppet". I am merely responding to a question specifically directed to me by scaddenp @1071. By definition, spamming and trolling are unsolicited messages which this is not. Now I don't care if you want to delete this paragraph, but please leave everything above it intact. If you object to me posting any messages whatsoever, you will need to take it up with those commentators asking questions directed at me in their postings.
[DB] This is yet another (of almost 2 dozen) iterative sock puppet of serial spammer cosmoswarrior. Posting rights rescinded, per Comments Policy.
Recommended supplemental reading:
The most accurate climate change models predict the most alarming consequences, study finds by Chris Mooney, Washington Post, Energy & Environment, Dec 6, 2017
The Most Accurate Climate Models Predict Greater Warming, Study Shows by Georgina Gustin, InsideClimate News, Dec 6, 2017
Both articles describe the findings contained in:
Greater future global warming inferred from Earth’s recent energy budget, Patrick T. Brown & Ken Caldeira, Nature 552, 45–50 (07 Dec 2017)
doi:10.1038/nature24672
John,
That article is so sad :(.
From reading the article that John Hartz linked free copy it appears that Norrism has been half right about climate models. They have been systematically incorrect. Unfortunately, they have underestimated the expected warming, not overestimated the warming as Norrism suggested. From the discussion:
"Finally, it is sometimes argued that the severity of model-projected global warming can be taken less seriously on the grounds that models fail to simulate the current climate sufficiently. Our study confirms important model-observation discrepancies, indicating ample room for model improvement. However, we do not find that model errors can be taken as evidence that global warming is over projected by climate models. On the contrary, our results add to a broadening collection of research indicating that models that simulate today's climate best tend to be the models that project the most global warming over the remainder of the 21st century." (my emphasis)
This is not the first evidence that models under-project future warming. We are in deeper doo-doo than we thought.