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All IPCC definitions taken from Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I, Glossary, pp. 941-954. Cambridge University Press.

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How reliable are climate models?

What the science says...

Select a level... Basic Intermediate

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.

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."


Exxon climate graphics from Supran et al 2023

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

Printable Version  |  Offline PDF Version  |  Link to this page

Argument Feedback

Please use this form to let us know about suggested updates to this rebuttal.

Further reading

Carbon Brief on Models

In January 2018, CarbonBrief published a series about climate models which includes the following articles:

Q&A: How do climate models work?
This indepth article explains in detail how scientists use computers to understand our changing climate.

Timeline: The history of climate modelling
Scroll through 50 key moments in the development of climate models over the last almost 100 years.

In-depth: Scientists discuss how to improve climate models
Carbon Brief asked a range of climate scientists what they think the main priorities are for improving climate models over the coming decade.

Guest post: Why clouds hold the key to better climate models
The never-ending and continuous changing nature of clouds has given rise to beautiful poetry, hours of cloud-spotting fun and decades of challenges to climate modellers as Prof Ellie Highwood explains in this article.

Explainer: What climate models tell us about future rainfall
Much of the public discussion around climate change has focused on how much the Earth will warm over the coming century. But climate change is not limited just to temperature; how precipitation – both rain and snow – changes will also have an impact on the global population.

Update

On 21 January 2012, 'the skeptic argument' was revised to correct for some small formatting errors.

Denial101x videos

Here are related lecture-videos from Denial101x - Making Sense of Climate Science Denial

Additional video from the MOOC

Dana Nuccitelli: Principles that models are built on.

Myth Deconstruction

Related resource: Myth Deconstruction as animated GIF

MD Model

Please check the related blog post for background information about this graphics resource.

Fact brief

Click the thumbnail for the concise fact brief version created in collaboration with Gigafact:

fact brief

Comments

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Comments 201 to 225 out of 291:

  1. Actually, ref, comment #195, please don’t make assumptions about my motives. You are completely wrong about me wanting to delay things. What I’m wanting to do, as hopefully most sceptics do, is my best to ensure that the climate change medicine dispensed by the politicians is not more damaging to humans than any natural or unnatural changes to the global climates. Until I am convinced that the medicine will not make things worse I will continue searching for a better understanding. At least there are some people here who are trying to help me get that better understanding, but you are not one of them. Tom (Dayton) ref. comment #207: I do read Realclimate articles and comments but always in a very sceptical manner because of the pedigree of the main contributors. I do like that quotation you gave - "I use the term validating not in the sense of ‘proving true’ (an impossibility), but in the sense of ‘being good enough to be useful’)” but the question is good enough to be useful for what? For me the validation of computer systems starts with the user requirements. Policy-makers (including politicians) are among the primary users of those climate models. There are others like environmentalists. I leave it to you to work out what “good enough to be useful” means. Must dash, as the boss is calling. Best regards, Pete Ridley
  2. I am having a good chuckle at the discussion about "being good enough to be useful" The parliamentary inquiry last year into the long term weather forecasting capabilities of BOM and the CSIRO received a submission from the federal Department of Agriculture describing the current forecasts as too inaccurate for farmers to use, whilst the submission from the South Australian Farmers Federation described them more to the point as "less then useful". This confirmed that nothing has changed since a University of Melbourne study 5 years ago found the same situation then. However the good news was that if the government could provide "significant further investment" in super computers, reliable usable predictions may be available in at least 3 years, but possibly as far away as 7 seven years.
  3. johnd, I believe you are mixing up your climate forecast models and your weather forecast models. SAFF weren't impressed with the seasonal forecasts they are given, especially as they are not yet detailed enough to give localised information. Weather, not climate.
  4. JMurphy at 02:56 AM , I think it is quite clear that I was referring to "long term weather forecasting capabilities". It is not so much about insufficient localised information, but about forecasts that are so vague that they are meaningless (a 50% chance of above average rains and a 50% chance of below average rains is a common forecast) and despite the vagueness they still have a poor strike rate. In contrast, private forecasters are able to demonstrate an overall much higher degree of accuracy plus provide detailed local information to satisfy their customers requirements. In the meantime as long as the government injects sufficient funds to upgrade to super computers, we still have to wait perhaps 3 to 7 years before we get forecasts that are "good enough to be useful".
  5. Jmurphy, ref. comment #210, I suspect that you aren’t aware of a relevant statement by a senior executive of the Met. Office during the first of the UK’s whitewash enquiries into the Climategate scandal. The question put by a member of the Science and Technology Select Committee was “Is there a problem with scientific software? We have had emails from Professor Darrel Ince and from Professor Les Hatton saying that there are severe problems with scientific software. Do you think that is a general problem in UK or world science?”. Met Office Chief Scientist Professor Julia Slingo (Note 1) said “At least for the UK the codes that underpin our climate change projections are the same codes that we use to make our daily weather forecasts, so we test those codes twice a day for robustness”(Note 2). So the “codes” used for UK weather forecasting are the same as those used for global climate projections - shortly after that that the Met. Office discontinued its long-range forecasts because they were so useless. (The rest of that testimony is worth reading.) It is worthwhile listening to what Professor John Beddington had to say in January (Note 3), which included the gross understatement “..that scientists had perhaps not been as good at communicating the value of uncertainty to the general public .. ”. Professor Barry Brook of Adelaide University and scientific advisor to the Australian Government on climate change was less reticent when saying over a year ago (Note 4) “There are a lot of uncertainties in science, and it is indeed likely that the current consensus on some points of climate science is wrong, or at least sufficiently uncertain that we don’t know anything much useful about processes or drivers”. Brook is a staunch supporter of The (significant human-made global climate change) Hypothesis so then goes on to try to imply that 95% of the science is understood. As Boddington said in January (Note 5) “I don’t think it’s healthy to dismiss proper scepticism. Science grows and improves in the light of criticism. There is a fundamental uncertainty about climate change prediction that can’t be changed”. Phil (Scadden), ref. comment #212, I am not enquiring here into the validity the design of the software or the validity of the underlying science of those climate models. What I am questioning is the extent to which the models have been validated and their starting parameters are “tweaked” and “re-tweaked” before a run produces an output that resembles reality. I do not have enormous confidence that those with a vested interest in convincing others that their research findings or software development skills produce useful models will present an unbiased opinion on the validity of any model forecasts. There are plenty examples in areas where the underlying sciences are much better understood than are those involved in unravelling the complexities of global climate processes and drivers where vested interest has resulted in false claims. There is no good reason to think that things are different for climate forecasting. Let’s not overlook the fact that scientists and software engineers not saints but humans with human failings. As the late Stephen Schneider said Your opinion of me is irrelevant and is bound to differ from mine. You are a staunch supporter of The (significant human-made global climate change) Hypothesis whereas I am a sceptic. Ref. comments #41/48 & 50 on the “Rebutting skeptic arguments in a single line” thread, you (and others here) ought to be aware by now that the IPCC shares Dr. Gray’s opinion that those models do not provide predictions of future global climates, merely projections (based upon that unsound science). If the global mean temperature estimates produced by the Hadley Centre etc. are to be trusted (“lies, damned lies and statistics”) we may have already had over 10 years of “flat or negative temperatures while GHGs rise” so may not have much longer to wait in order to “clearly invalidate AGW”. In your humble opinion “Hansen 1988 did very well for a model so primitive.”. In mine he hit lucky to get closeish with one of his scenarios for 10 years then failed miserably after that. actually (thoughtfull?). does that answer your questions in comment #195? NOTES: 1) see http://www.nerc.ac.uk/about/work/boards/council/biographies.asp 2) see http://www.publications.parliament.uk/pa/cm200910/cmselect/cmsctech/387b/38724.htm 3) see http://www.actoncopenhagen.decc.gov.uk/en/ambition/achievements/february/john-beddington-audio 4) see http://bravenewclimate.com/2009/04/23/ian-plimer-heaven-and-earth/ 5) see http://www.timesonline.co.uk/tol/news/environment/article7003622.ece That’s enough for now. I’ll respond to others soon. Best regards, Pete Ridley
  6. Pete Ridley, if you wish to believe that the 'Climategate' enquiries are all "whitewashes", and that the "scandal" still remains (albeit only in the minds of those who don't wish to face up to the facts), then I cannot write anything that will get through to you : you only see what you want to see. I will, though, disagree with you with regard to the Met Office's Seasonal Forecasts - they had obviously already decided to scrap them before announcing so on March 5, so I doubt whether the House of Commons enquiry had anything to do with it. You, no doubt, would disagree, but, again, you must believe what you want to believe. In the same way, you believe those Seasonal Forecasts were "useless", so, again, nothing I write would be able to change your mind. To end, code written to represent the Physical qualities of the make-up of potential weather would, I would imagine, be useful not only for short-term forecasts but also as a basis for long-term climate forecasts.
  7. Jmurphy, you do what supporters of The (significant human-made global climate change) Hypothesis often do, distort what is said. What I said about the first UK whitewash hearing into Climategate and the Met. Office’s decision to stop its long-rage forecasts was “ .. shortly after that that the Met. Office discontinued its long-range forecasts because they were so useless .. ”. That is not the same thing as saying that the decision by the Met Office was a consequence of what was said at the hearing. That should remove one area of assumed disagreement between us. Others, such as the whitewashes, the validity of The Hypothesis and your belief that “code written to represent the Physical qualities of the make-up of potential weather would .. be useful not only for short-term forecasts but also as a basis for long-term climate forecasts”, will be much more difficult to clear up. Best regards, Pete Ridley
  8. Steady on, Pete. You claim there are inconsistencies and inadequacies in the models and argument of "proponents" of AGW. I'd suggest that if you want to maintain consistency with your claim to be a "sceptic" that you avoid expressions like - 'the first UK whitewash hearing'. That seriously undercuts the position you claim to advance.
  9. Pete Ridley, I am not a "supporter of The (significant human-made global climate change) Hypothesis" (although I don't know how to react to that rather convoluted and bizarre term - doesn't Anthropogenic Global Warming [AGW] do it for you ?) : I am an accepter of the scientific facts behind AGW. Until I see such facts over-turned, or a better theory come along, I will stick with the AGW one.
  10. Pete Ridley - I'm still interested in your response to my question on evaluating Hansen 1988 as a scientific model. I believe this is critical to the thread and the discussion.
  11. Peter Hogarth, ref. #204, I think that Physicist Luboš Motl’s blog thread “John Cook: Skeptical Science” (Note 1) Item 4 should help you. Motl says “It's cooling: Again, Cook's graphs and statements are obsolete and a few years from the moment he wrote the page were enough to falsify his new predictions about the accumulating heat. The reality is that between 1998 or 2001 or other years on one side and 2009 on the other side, the global mean temperature dropped. Sometimes it's cooling, sometimes it's warming. The year 2010 is likely to be much warmer than 2009, approaching the temperatures of 1998, but when the El Nino fully switches to a La Nina, things can be very different. The fact that there's been no significant warming for 15 years has been accepted by both sides of this debate. And since 1998, it's just cooling. Cook has no counter-arguments. He just says that the heat flows influence the temperature and I agree with that. Except that he doesn't show in which way the flows are going to go e.g. in the next 10 years”. Motl also comments at Item 5 about this thread with “Models are unreliable: Cook says that models have made predictions that were successfully compared to observations. Except that this is not enough for the models to be reliable. For them to be reliable, it would have to be the case that the models have produced no predictions that were inconsistent with the observations - because one wrong prediction is enough to falsify a model. Clearly, such falsification has taken place with all of them. In particular, all IPCC-endorsed models predicted a warming since 1998 that didn't occur. They're gone. Again, both sides agree that we can't rely on them. Kevin Trenberth agrees that the disagreement of the models and the data is a travesty. There are hundreds of recent examples showing how deeply flawed the existing IPCC-endorsed models are”. KR, Here are Motl’s comments about those global temperature measurements you were on about in #203 “Temp record is unrealiable: In his counter-point, Cook talks about the urban heat island effects that are "negligible". Well, they're surely not negligible because the estimated urban warming in typical large cities exceeds the whole assumed warming caused by CO2 - something like 0.6 °C. So it matters a lot whether the urban effects are isolated. But the urban effects are far from being the only problem with the surface temperature record. The number of recently found dramatic problems with the surface record is so huge that I can't even enumerate them here”. The rest of Motl’s thread is worth reading too – enjoy. NOTE 1) see http://motls.blogspot.com/2010/03/john-cook-skeptical-science.html Best regards, Pete Ridley
  12. Pete Ridley writes: And since 1998, it's just cooling. I am not aware of any global temperature index that shows a cooling trend since 1998. From Jan 1998 through last month, both satellite series (UAH and RSS) and all three of the major surface series (GISTEMP, HADCRUT, and NCDC) have a positive slope. This is pretty remarkable considering that you've cherry-picked an interval with the largest El Nino on record at the start, and a substantial La Nina near the end. FYI, here's a graph of RSS (satellite) temperatures that I posted in another thread recently: You will note that most of the past decade has been above the 1979-2000 trend line. The apparent "flattening" you refer to is just an artifact of the more-rapid jump of temperatures at the start of this past decade (2000-2002).
  13. Pete Ridley writes: In his counter-point, Cook talks about the urban heat island effects that are "negligible". Well, they're surely not negligible because the estimated urban warming in typical large cities exceeds the whole assumed warming caused by CO2 - something like 0.6 °C. So it matters a lot whether the urban effects are isolated. But the urban effects are far from being the only problem with the surface temperature record. The number of recently found dramatic problems with the surface record is so huge that I can't even enumerate them here”. Comparing the elevated temperature in urban areas to the magnitude of the global increase in temperatures is misleading since urban areas constitute a tiny fraction of the surface area of the earth. The greatest warming is occurring at high latitudes where there are no large urban areas. We have a thread here that addresses many of the alleged problems with the surface temperature record. In my experience, most of the "skeptical" claims about that record have turned out to be groundless once people started looking into them quantitatively.
  14. Pete Ridley - you claim no warming since 1998. That's a frequent, and incorrect skeptic argument addressed here, in "Did global warming stop in 1998?", which you might want to take a look at. You claim no warming since 1998; But there's huge warming since 1997, and huge warming since 1999 - 2 out of 3 wins? Cherry picking your start date, as you do with 1998, to a 2 sigma noise spike can give you any answer you like, but the statistics clearly show continuing warming. As to the accuracy of the surface temperature reconstructions, there are at least four independent data sets producing the same answers, with all variations of UHI and calibration adjustments by any analyst producing answers between 0.15 and 0.175 oC/decade, the two satellite estimates at 0.13 and 0.15. Multiple independent data sets, all adjustment variations, and they come to about the same answer. That's pretty much the definition of reliable measurements. And hence the decent models (including Hansen 1988) actually do match the data, indicating some degree of accuracy in the models. Unless you have a different definition of a scientific model?
  15. Ned, ref. #220, I’m sure you wouldn’t wish to mislead anyone with your “Pete Ridley writes: And since 1998, it's just cooling”. More correctly, Pete Ridley quotes Physicist Luboš Motl who writes: … What I said on the subject (see #213) was:- If the global mean temperature estimates produced by the Hadley Centre etc. are to be trusted (“lies, damned lies and statistics”) we may have already had over 10 years of “flat or negative temperatures while GHGs rise” so may not have much longer to wait in order to “clearly invalidate AGW”. The Hadley Centre “Global average temperature 1850-2009” graph (Note 1) tells me that since 2000 the anomaly (wrt 61-90) has changed by under 0.05C. That’s near enough flat in my book. Correct me if I am mistaken but if the 21-year smoothing is removed then the last decade, according to those same statistics, has experienced virtually no change in mean global temperature The Met. Office commented on this (Note 2) with “ .. Recent Met Office research investigated how often decades with a stable or even negative warming trend appeared in computer-modelled climate change simulations. Jeff Knight, lead author on the research, says: “We found one in every eight decades has near-zero or negative global temperature trends in simulations. Given that we have seen fairly consistent warming since the 1970s, the odds of one in eight suggest the observed slowdown was due to happen.” Our decadal forecast predicts an end to this period of relative stability after 2010. We project at least half of the years after 2009 will be warmer than the 1998 record. Climate researchers are, therefore, reinforcing the message that the case for tackling global warming remains strong. Commenting on the new study, Vicky Pope, Head of Climate Change Advice at the Met Office, said: “Decades like 1999–2008 occur quite frequently in our climate change simulations, but the underlying trend of increasing temperature remains .. ”. Also, “Warming On 11 Year Hiatus” (Note 3) presents a graph on this. You say in #221 that “ .. urban areas constitute a tiny fraction of the surface area of the earth ...”. Equally, the temperature measurements, which are subjected to significant statistical manipulation before being considered suitable for presenting a picture which supporters of The (significant human-made global climate change) Hypothesis through our use of fossil fuels, only take place at a tiny fraction of the surface area of the earth. NOTES: 1) see http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/ 2) see http://www.metoffice.gov.uk/climatechange/policymakers/policy/slowdown.html 3) see http://wattsupwiththat.com/2008/06/20/warming-on-11-year-hiatus/ Best regards, Pete Ridley
  16. Pete, I've given my opinion about the perceived "slowdown" or "flattening" over in the thread about surface temperature reconstructions, particularly this comment. Regarding the last paragraph of your comment, you've created a false parallel. Urban areas are where they are; no extrapolation is needed or appropriate. We don't suspect that there might be a hitherto unknown city in the middle of the North Atlantic, based on interpolation between Boston and London. In contrast, we use a very small subset of the entire surface of the Earth (weather stations) to calculate the broad-scale mean climate. In fact, as mentioned in the other thread this can be done to some degree using as few as 61 stations. At the same time, we can test our temperature reconstructions by comparison to spatially more-extensive measurements from satellite. Finally, you might want to consider toning down the writing style a bit. Sentences like "[...] the temperature measurements, which are subjected to significant statistical manipulation before being considered suitable for presenting a picture which supporters of The (significant human-made global climate change) Hypothesis through our use of fossil fuels [...]" may seem like an amusing way to slip in lots of little digs at climate scientists, but all they really do is lead to turgid prose and a disinclination on the reader's part to keep reading.
  17. I did post a longer comment prior to my #219 but it looks as though admin removed it. I’ll E-mail it to Phil instead, meanwhile this bit may be allowed. Phil, ref. #206, You ask “Where have the models failed?” and I can do no better than quote Vincent Gray “they have failed to predict the temperature in the Lower Troposphere and any future climate event .. “ and “ .. climate models have never been validated in the manner I have stated ..”. Jmurphy. in #217 you ask of my use of The (..) Hypothesis" “.. doesn't Anthropogenic Global Warming [AGW] do it for you ? .. ”. Like you, I and many other sceptics accept “ .. the scientific facts behind AGW ..” but what we don’t accept are the assumptions made about its significance or other assumptions made in the face of the enormous uncertainties about the processes and drivers of global climates. I use my alternative “ .. .. rather convoluted and bizarre term -.. “ to highlight the distinction between “DAGWers” and “Deniers” – that word “significant”. KR, ref. #203/205/218, using your criteria in #203: a) Ability to match previous observations (historic data) b) Ability to predict future observations c) Ability to estimate different future states based on different inputs (Given 'A', predict 'B') d) Match of model internal relationships to known physical phenomena e) Simplicity (no nested 'crystal spheres' for epicycles) my understanding is that because no independent validation has ever been undertaken there is no evidence to refute the argument that: a) can only be achieved through making adjustments to parameters until the desired result is achieved (as you acknowledge “The actual pattern of temperature rise that you get in the model depends on how the model is initialised.”), b) no dependable predictions have ever been made, c) estimates are not dependable predictions, d) it is the significant unknowns that make the models incapable of making dependable predictions, e) it is their simplicity which renders them little more reliable than crystal balls. If you have evidence to the contrary then it would help if you provided a link to it. Regarding the attempt to estimate mean global temperature, your “ .. argument really doesn't hold water .. ”. Reading “The Elusive Absolute Surface Air Temperature” (Note 7) and “NASA GISS Inaccurate Press Release On The Surface Temperature Trend Data” (Note 8) may be of assistance to you. NOTES: 1) see http://data.giss.nasa.gov/gistemp/abs_temp.html 2) see http://pielkeclimatesci.wordpress.com/2010/01/16/nasa-giss-inaccurate-press-release-on-the-surface-temperature-trend-data/ Best regards, Pete Ridley
  18. That's a very tired list, Pete. Before various people here drag themselves through the effort of once again providing some corrections, have you by any chance already discussed this elsewhere? If so, could you quickly list what rebuttals you encountered? That would be most helpful in saving everybody some time and wasted effort.
  19. Pete Ridley - Regarding the model value as discussed here, I would have to disagree with your statements. The Hansen model (and others) map physical phenomena into the computer model (white box modeling) and attempt to replicate previous system behavior. Adjustments to match historic results are certainly made - and if the modelers are doing their job right, this is part of an investigation to understand critical parameters such as feedback levels, time constants, and the like (black box modeling). Both white box (all known, first principles) and black box (estimations of unknowns) are core techniques for modeling. The critical power of a model really lies in estimating future states, the "Given 'A', predict 'B'". The Hansen model did this quite well - Scenario B, which Hansen considered most likely, was actually close to the economic and industrial conditions that have prevailed over the last 22 years, and the predictions made by Hansen were correspondingly close to what has actually happened. When fed the actual industrial numbers (a matter of economics and political decisions, rather than purely physics interactions) it's accurate to well within the weather noise level. See this link for an overview, and quite frankly the Hansen 2006 document describes this most clearly. That's an excellent model - it makes useful predictions that have been shown to be accurate. It certainly doesn't capture every element of chaotic weather overlaid on climate, cannot predict the frequency of volcanic eruptions, and doesn't model down to the cubic millimeter - but the predictions and the interaction estimates certainly hold up. Demanding 100% accuracy means that you will never accept a model. That's certainly your choice, but I believe that will leave you with quite a few tools missing from the toolbox. If you feel that a model, one which given actual industrial activity levels closely predicts temperatures 22 years into the future, and which allows exploring different outcomes based upon our actions, is not worthwhile, well, then I'll have to continue to disagree. As an aside, I must note that I don't consider Luboš Motl a reliable source - he's obviously an expert in string theory, but has no climate background and seems unfamiliar with logarithmic responses to GHG's. He also posts from a clear ideological framework rather than a scientific one in the climate arena. I prefer numbers, myself...
  20. " than quote Vincent Gray “they have failed to predict the temperature in the Lower Troposphere and any future climate event .. “ and “ .. climate models have never been validated in the manner I have stated ..”." I can only assume you mean the denialist canard about tropospheric hot spot because models predict lower tropospheric temperatures very well. For some real information, try tropospheric hot spot As to Gray's validation. Since you apparently understand what he means, can you enlighten the rest of us? And can you please read the Hansen 2006 paper that has been repeatedly pointed out to you. "a) can only be achieved through making adjustments to parameters until the desired result is achieved (as you acknowledge “The actual pattern of temperature rise that you get in the model depends on how the model is initialised.”)," No - you are completely misunderstanding what is meant by 'initialisation of models'. How can you be so critical of models when it appears you know so little about them? This is discussed in depth in IPCC WG1 and in the text of the Keelyside et al paper has more. This Keenlyside paper is criticized and the matter discussed further here You also seem to stubbornly refuse to accept that predictions, accurate to level within the prediction, have been made. Any prediction of any scientific value has error limits associated with it. Demanding a prediction be better than those internal limits is pointless.
  21. There follow a couple of comments that I posted originally on 28th at #226 but was removed by admin, perhaps because I had inadvertently carried over some links from a previous comment. I’ll post it now in two parts in case there was something else that was not found to be acceptable.
  22. PART 1 KR, ref. #222, I know that it is not uncommon for politicians to distort the facts but please don’t misrepresent what I post about The (significant human-made global climate change) Hypthesis. I am not aware that I “ .. claim no warming since 1998 ..”, was “Cherry picking (a) start date, .. 1998” or claiming anything about 1998. If I did then please point me to where and I’ll retract. If you can’t find anything of the sort then try reading my posts again and you may spot where you may have misinterpreted what I actually said. Regarding those attempts to measure global temperatures, perhaps you’d like to help me out and identify those “ .. four independent data sets .. ” but please make sure that they are indeed independent of each other, starting with the raw data then progressing through the statistical manipulations.
  23. PART 2 Ned, ref. #224, perhaps you’d like to advise the extent of the uncertainty of estimating global mean temperature anomaly “.. using as few as 61 stations.” but would you be good enough to provide it in Centigrade degrees. If the attempts at estimation by The Hadley Centre are to be believed, we’ve only had about 1C in 100 years – nothing to get excited about really. I’m not sure that you would agree with KR about four independent data sets but perhaps you do. I don’t get that impression from your article. Vincent Gray has drafted a paper which inlcudes commentary on those temperature measurements so I’ve sent him a link to the “Assessing global surface temperature reconstructions” thread. You might like to try reading “The Elusive Absolute Surface Air Temperature” (Note 1) and “NASA GISS Inaccurate Press Release On The Surface Temperature Trend Data” (Note 2) that I mentioned in #225. As for toning down my writing style, thank you for the advice but I’ll leave it to the blog administrator to decide if my tone is unacceptable. Best regards, Pete Ridley
  24. Pete Ridley writes: Ned, ref. #224, perhaps you’d like to advise the extent of the uncertainty of estimating global mean temperature anomaly “.. using as few as 61 stations.” but would you be good enough to provide it in Centigrade degrees. You're referring to the work of Nick Stokes as described here. Specific questions about his reconstructions should probably be addressed to him. That said, comparing the standard errors listed for the 61-station reconstruction to the full land/ocean reconstruction using all stations (here) suggests that there's about twice as much uncertainty in the reduced set (for which the trends are 0.0855 +- 0.00835 C/decade in 1901-2009, and 0.282 +- 0.0393 C/decade in 1979-2009). It does not seem particularly surprising that the standard error would double when using a much smaller number of stations. PR continues: If the attempts at estimation by The Hadley Centre are to be believed, we’ve only had about 1C in 100 years – nothing to get excited about really. Globally it's a bit less than that, perhaps an 0.75 C increase over the past century. It's important to understand that number in context, however -- a global temperature increase of 0.75 C is actually quite large given the very short time frame involved. (It's roughly 10% of the change in temperature since the last glacial maximum, a time when the location of my house was buried under a couple km of ice). In addition, the real concern is not the impact of the 0.75 C rise from 1900-2010, but of the probable 2-4 C rise from 2010 to 2100. Both the climate and our technological infrastructure have a great deal of inertia, so it is important to figure out what needs to be done and start working on it ASAP. Had we done so 20 years ago, we would have much more flexibility. If we wait another 20 years, we will have much less.
  25. Pete Ridley, perhaps you'd like to dismiss the Japanese Meteorological Agency's temperature figures too. Maybe, because they were under American occupation for so long after the last war, they have been inducted into that great big conspiracy that the rest of us (whoops, have I given the game away ?) are involved in ?

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