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 Curtis......please run a calculation based on the table for the error in the model and present it here
Glenn tamblyn similar is a relative term.....ie those two are a lot more similar than say a models that attempts to predict the behavior of atoms...please direct arguments to the 4 items listed in the original posts. Disprove the statements directly
hydrology has nothing to do with weather. It's purpose is to calculate quantities of water and the ability of a system to convey the water
i was watching a video of how the climate models work By a scientist who uses them. He described the math of the model and basic parameters that are used for the model. He discussed how he arrived at values for the Parameters. His method was no different than anything I do to arrive at parameters for the models I operate.
Rhoowl, instead of watching some video, try reading the detail. What you are doing is projecting what you know from hydrology model into a supposed knowledge of how climate models work from simplistic information. It seems to me that what your hydrology models have in common with weather models, is that they are both initial value problems. Climate is not. That is the point both I and Glenn are trying to make. Your 4 points are based around a misunderstanding of the models essentially. The IPCC chapters on modelling are a far better starting point then some video. We are doing our best to point you to useful information which is rather more than can stuffed into a comment reply. Now if you are going to stand by your original suppositions rather than learn new information, I dont think there is much point in continuing the discussion.
Rhoowl, you might also like to consider why there isnt a weather forecast that is going to predict the temperature on say June 25th 2015, let alone Dec 22nd 2015. However, several methods will give you quite accurate predictions for the June average monthly temperature and the December average monthy temperature. Ie. no amount of chaos in weather systems is going to change summer into winter. Summer is different from winter because the energy balance in temperate regions is so different. Adding CO2 is same effect on a global scale.
Scaddenp
please site some data backing your claim.....the program I use are not predicting anything that can not be predicted.....
i will ill give you a real world example of the climate Model
climate models lead to a prediction that sea level will rise from 10 inches to Ive heard some estimates to 20 ft. This is based on the temperature increase. That's a huge error....l
i have to design a sea wall around NYC to prevent losS of the city. Which value to you choose. The 10 inch sea wall will cost about 100million.
20 ft will cost 100 billion....probably not too far off with those figures Loss of the city... 2 trillion.
We we know sea level was about 250 ft higher than now in the past. So the 20 ft is not unreasonable.
Which model do do you choose
[JH] A range of estimates for differing scenarios do not equate to "error".
Rhoowl, please cite the actual sea level rise estimates you are referring to. Are they for the same timeframes? Do they assume the same future emissions paths?
Your claim that there is "huge error" in the modeled range of sea level rise is a provable position... all you need to do is cite the actual source of the estimates ("from 10 inches ... to 20 ft."). You're right... that'd be a huge uncertainty range for a single set of assumptions. So go ahead, cite the source and prove your point.
Rhoowl... I don't want to dogpile here, but I'd like to renew my first question.
If this is a related area of expertise for you, why would you not attempt to engage with people who are actively working with climate models in order to better understand what they're doing? Why are you engaging on SkS instead of talking with someone who builds climate models?
The best I can tell from your comments here, you have a misguided expectation of what climate models are intended to accomplish. But instead of attempting to better understand the matter you're tossing out the entire field of research, deeming it an impossible task.
Not fully understanding something, even for an expert, is no big deal. Most of us are experts in something, and we are all ignorant of the things which we haven't yet learned. But it's not acceptable to be ignorant of something and refuse to learn what other experts already understand. If you actually have the expertise you claim, there is absolutely no excuse for not contacting a professional climate modeler and asking questions.
[I emphasis "if" here because I have a very hard time fathoming why someone with 40 years experience would not first do exactly what I'm suggesting long before posting on this website.]
Rhoowl,
Real Climate is a blog written by climate scientists. The main organizer is Gavin Schmidt who is a climate modeler. They have a lot of background information and old posts that explain all your questions. Perhaps if you read some posts there you would begin to understand how climate models work.
Moderation Request
Please do not respond to future posts by Rhoowl until a Moderator has had a chance to review them. He/she is skating on the thin ice of posting nonsense.
"please site some data backing your claim". Certainly, but which claim? That monthly temperature for a station can be estimated accurately? Or that climate model is boundary value model not initial value model. Or that difference between summer and winter is due to differing energy input? Or which claim? As to sealevel - well in your model you should be able to use it to give response to given storm event. Ie the rainfall for a storm event is an input. I would expect that you could use it to give a range of response to different sized storm events. The sealevel estimates you are looking at are just that - range of estimates for different emission scenarios. Each scenario has its own error estimate but dont confuse the range for different scenarios with error. Climate models certainly do not predict what humans will emit in the future.
JH yes the range of estimates are different scenarios....each scenario had an error. The error equates to a diferrent level of sea level rise.
RH someday an engineer is going to ba asked to design these systems based on the models. when that occurs they they will ask some of the questions I am posing here. I'm not sure that an climate would want to speak me to about these questions. I would respect that their time is valuable.
CBD iposted the graph one of the more extreme scenarios showed 4c warming with 2.4 to 6.4 I believe error. With the way China and India are building coal plants is this implausible scenario? The one post I had which is no longer visible shoe Sea level rise with the worst case bing 11.5m....this probably corresponds to the 6.4 scenario. The 2.3 scenariio should be in the 5m range based on the 2m/degree C value given. That's a pretty big error
Scaddenp I never made any claims about inputs except that I tbought the modellers were entering the best figures. Although the scenarios listed deal with the inputs.....but that's another matter which complicates the design process.
I'm typing this on an Ipad please forgive some of the English it's the spell checker messing some of it up
Rhool... Modelers' time is most certainly valuable, but I think you'd find that many of them would consider explaining their work to be a valuable use of their time. It just requires an open mind and a willingness to learn.
I need to explain something about design. Engineers use an acceptable risk of failure about 1 in 10,000. That's a high standard. Failures can be catastrophic. We absolutely need to know the design parameters within 20 percent. We have safety factors. they range from 1.5 to 4. Something like a sea wall would have overturning sf of 1.5. there would also be free board distance from top of wall to water. Not more than two feet. If the wall gets breached there's a high risk of failure. Water washes out the toe resulting in loss of stability. This is why getting the parameters correct is so important. So having a range if sea level rise would not be usefull. You need to know what it is.
[JH] Is English your first language?
Rhoowl, you are incorrect that "engineers" in the sense of all engineers, use an acceptable risk of failure of "about 1 in 10,000." Perhaps that is true in the very narrow particular engineering field in which you have spent your career, but that absolutely is not a universal rule; it's not even a general guideline. Risk tolerance depends entirely on the particular situation. In my field of spacecraft design, for example, the risk tolerance differs from one spacecraft to another, from one type of risk to another, on the timeframe and other circumstances, and always depends on costs (money, time, labor) for lowering the risk and for dealing with consequences if the bad thing happens. For example, a nanosatellite usually needs to be cheap and fast to develop and launch, so usually the risk of total failure is higher than for big spacecraft, because the funders are not williing to spend enough resources to lower the risk further. For any spacecraft, tolerance for spacecraft failure is lower before the primary mission is accomplished, and higher after that. Much lower risk is tolerated for spacecraft that put human health and life at risk than for mere property risk.
When engineers chose how high to make a seawall, you are correct that they must design to a particular, target, level of sea level. But that particular level is dictated to them by people who take into account the full range of all I've written about, including the range of probabilities of various levels of sea level rise.
" So having a range if sea level rise would not be usefull. You need to know what it is."
There are needs and then there are wants...
Let's compare and contrast this with wind loading: uncertainty abounds and engineers deal with it all the time unlike you suggest!
BOzza wind is a part of the design....Theier a very specific design standards in that regards.....Including standard design to wind tunnel testing. This area has been heavily researched. But again....the only time I hear about failures are due to extreme force events..ie hurricanes, tornados etc. the wind code didn't get very stringent until after hurricane Andrew. Buildings built before then didn't all have the necessary shear elements and hold downs. The design process evolved over centuries of construction. Like climate modeling is still in its infancy. Over time you will see the models refine to produce more accurate results.
TD what type of standards do you design to and what type of safety factors
Rhoowl: The Dutch, who know something about protecting their land from the sea, do not seem to be waiting for futher refinement of Global Climate Models to take action. For example, see the City of Rotterdam's Climate Proof: Adaptation Programme adopted in 2009.
If you are in a low lying city and wondering about building sea walls, then you have two level of uncertainty. One is range of error in a model scenario but far harder is guessing what humans will do about reducing emissions. If you are forced to make the assumption that no political will to tackle the problem exists, then you must use the range of sea level rise values for the upper RCPs. ie 0.81-1.65 in latest papers. A cautious engineer would be going for the larger number at least because sealevel rise doesnt magically stop in 2100.
Unfortunately. sealevel rise has yet another level of uncertainty. The GCMs tell you climate (with a range of uncertainty), but another set of models have to come into play to convert that climate into a rate of ice sheet collapse. This is not a well understood problem and is the major source of the wide range in the numbers.
In my opinion, uncertainty is not your friend. The prudent response is to reduce emissions as fast as it can possibly be done.
Rhoowl, climate modeling is fairly tightly bounded over climate-scale periods. There is no physical reason--barring extremely unusual heavy, persistent volcanic activity or a massive drop in insolation--why the long-term trend should not continue as it has done for the last fifty years and, in fact, increase. On the decadal scale and at medium or high spatial resolution, climate (or, rather, weather) is very complicated, noisy. On the multidecadal scale and at low resolution, the internal variation can be accounted for, and the primary forcings and feedbacks dominate the trend.
Baseball is a good analogy. Given that a team's talent stays generally consistent, projecting the team's chances at the playoffs is pretty easy. However, take any two-week period in the season, and the team's success might not be evident whatsoever--short-term injuries, bad calls, distractions, slumps, etc. It's that "given" that's key. We understand the major "givens" for climate. Indeed, an overwhelming majority of the uncertainty lies in the human response.
We understand the physics well enough. We don't understand the human response. Yet we don't have time to wait for a better understanding of the human emissions pathway. Even if we go to zero emissions tomorrow, we're still looking at a major response from the ice sheets (among many other sub-systems) as they come to equilibrium with the elevated level of forcing. Atmospheric CO2 doesn't just return to pre-industrial once we zero our emissions, and it is extremely unlikely that we'll zero emissions anytime soon.
Rhoowl asked me "TD what type of standards do you design to and what type of safety factors." The answers are NASA standards for mission operations software for JSC to monitor the ISS, Orion, and other vehicles; for mission ops software for JPL to monitor their uncrewed large and small spacecraft including Mars rovers; for ARC nanosat spacecraft flight software and hardware; for rocket guidance, navigation, and control software-hardware packages; for an assortment of hardware-software payloads for an assortment of spacecraft being produced and launched by an assortment of international organizations; and for autonomous aerial drones ground-plus-flight hardware and software.
But I suspect you asked because you believe there are a few books of acceptable risks probabilities to which engineers turn. There is a smattering of such numbers, mostly for small subsystems, and mostly for hardware, but even for those, fundamentally it all comes down to subjective human judgment of acceptable risks for each situation by not just the engineers but the other stakeholders in the project, as I described earlier. The most important design standards for risk are standards for process--for how those design judgments are made, and then how the implementations and testings of those designs and implementations are done.
Rhoowl wrote: "The one post I had which is no longer visible..."
Actually, it's still visible. You just posted it to a different thread.
Yes, the 'gap' between 11.5 meters near maximum (upper 5% uncertainty band) sea level rise assuming the RCP8.5 emissions scenario and 0.13 meters near minimum (lower 5% uncertainty band) on the RCP3PD emissions scenario is big. However, it is not any kind of "error"... because you are looking at two different things. You might as well argue that weather models are useless for predicting the next day's temperature because they show a maximum daily temp of 90 F in Atlanta vs a minimum daily temp of 10 F in Nome... what a "big error"!
Rhoowl claimed "So having a range if sea level rise would not be useful. You need to know what it is."
Suppose you are an engineer hired by the town of NearlySubmerged to design a new seawall to protect it in the year 2100 to the same degree the old seawall protected the town when it was built in 1900. (The town is not in Florida, where for most shores the porous land allows the water to seep under the seawalls.) Think of Superstorm Sandy and New York City.
The town already has made some of the decisions that I described in my previous comment. The town has decided that they want the risk that they had in the year 1900. The town did not look up that risk level in an engineering book. That risk level is not "standard." It is not objectively calculated. It is a choice by the town. They could have decided differently, for example to preserve the risk they have today, in 2015, which is considerably higher than the risk they had in 1900.
Even with that information, you still need to know the projection of sea level rise by 2100. You cannot make that decision by yourself. You must ask the town for their choice of which IPCC emissions scenario they prefer to assume will come to pass. Then given that chosen emissions scenario, you must ask the town whether they want to use that sea level projection's mean value, or its range's 95% upper bound, or its range's 95% lower bound, or some other value. (To simplify this example, let's skip you asking the town to choose a projection of storm surge changes by 2100.)
Only with all that information can you then design the seawall.
But the town will balk at making any of those decisions, because those decisions are subjective. They will ask you, as all savvy shoppers do, to present them with the cost of constructing each design to meet each of those projected sea levels. To shorten your task, probably you will first design for the sea level at the top of the 95% range of the most emissive of the emissions scenarios, and for the one at the bottom of the 95% range of the least emissive of the emissions scenarios. You might discover that the difference in cost of those two extreme designs is so small that the town feels it is well worth the cost to design for the highest projected sea level. But probably that cost difference will be large enough that the town wants you to give them costs for intermediate projections, until the town (not you) decides which sea level projection to use. Now you have enough information to finish designing. That information is not "1 in 10,000"; it is several pieces of information.
In that process, imagine that the minimum projected sea level rise by 2100 was .13 meter, and the maximum was, say, .14 meter. The town might decide they will not build a new seawall but will live with the risk increase, because they think they will spend less money to cope with anything in that range than they would spend on a new seawall. That is the town's decision, not yours. You don't simply look up that decision in your notes from engineering class.
But suppose the town decides that that the least-emissive emissions scenario is impossible--that it will not come to pass. So they tell you to ignore all of the sea level projections from that optimistic emissions scenario. Suppose that the emissions scenarios they tell you to use have 1 meter sea level rise as the lowest end of the 95% range of the least-emissive of those allowed scenarios. Suppose the town decides that they most definitely want to be protected from a 1 meter rise, but they are unwilling or unable to spend the money to protect against anything higher. It does not matter that the upper bound of sea level rise in those within-scope scenarios is 11 meters, because the town has decided not to protect against that much rise, even though it would be catastrophic.
Back to your claim that a range of projected values is useless: You are wrong. The large span of that range does not make the projection useless, if even the minimum value is large enough to demand action. A range is useful for decision makers (requirements deciders) to choose from in picking out the value to hand to you, the engineer, to design to meet.
Rhoowl - "So having a range if sea level rise would not be useful. You need to know what it is."
Knowing a range of risks is sufficient to evaluate risk avoidance - fire insurance is an excellent example. You don't know if your house will or won't catch fire, if it catches fire you don't know how much damage that might cause, yet you buy fire insurance to cover the likely range of damages. That span of damages is not an error, but rather the bounds on risk. The same holds for sea walls, and in fact for every other consideration of risks vs. benefits.
Back on topic - the models are quite good within their stated limits: 30 year or so projections of the average climate response due to stated forcing changes, with bounds determined by climate variability. Your insistence on 1/10,000 risk levels, and in fact your treatment of climate models (boundary problems) as weather models (initial condition problems) are IMO demands of impossible expectations.
Wow so many posts...I see most of you guys are scientists....
JH the Dutch are more susceptible to sea level rise than any other country. something like 1/2 of the country is below sea level...a lot of their dykes, dams and polders have been there for 500 years or more. So they design for those types of timeframes. A 1m sea level would stress all of the dykes and dewatering systems.
[TD: Please keep the conversation going, by directly answering questions and by responding in ways that are directly relevant to the topic of this original post ("Models are Unreliable"). In the above paragraph you have agreed with John Hartz, but have tried to not admit it. Please directly admit you agree with him, but specifically on the topic of the utility of climate models. If you actually disagree with his specific point about the utility of climate models, say so explicitly and explain, directly, why.]
Scaddenp
DSL why do you have to reduce co2 emissions. Co2 emissions have been regularly increasing. You have to figure that the govt of the world will not come to an agreement to reduce co2. Why not focus on other areas like bioengineering plants(specifically algae) to use the increased levels of co2. They'd have such an advantage theyd quickly overtake plants that have evolved to survive a max 300 ppm atmosphere. How much money is spent on this? Why not push for nuclear ( I'm not a huge fan of this But I can live with it
Why not push for technologies to replacing the internal combustion engine. Hydrogen fuel cels are looking promising. Fusion is starting to look promising with ITER Why not push the govt to develop our own tokamak.
it not inconceivable by 2050 having fusion reactors produce hydrogen to power vehicles.
Instead ad the goft want to tax carbon with no specific plan to actually reduce co2. The govt wants to promote solar and wind......solar and wind should be considered dead end.....reliability, storage, ecological problems. I think solar might actually cause more global heating than eqivalent co2. Think about it.....a solar is placed over the ground....the energy is sent into my home. Heats my house. Heat goes into the ground beaneath the house for slow release. Where the panel is it kills the plant life beneath and co2 reduction is reduced.
[TD] The paragraphs I've struck through are very much off topic. You are giving the appearance of deliberately attempting to avoid admitting you are wrong. It's called the Chewbaca defense. There are posts here on Skeptical Science that are relevant to those comments. Use the Search field at the top left of this page.]
Td td the guidelines for the design would never be left at the town level. you'd have an organization ASCE (american society of civil engineers) working working with scientists making the decision. The ASCE is responsible for all structural design building guidelinEs in the coUntry.
[TD: You have avoided addressing the actual point that is relevant to this "Models are Unreliable" post, by skipping off into a different topic.]
[TD] You have veered way off the topic "Models are Unreliable." Please comment on appropriate threads. At the left side of this page, click the "View All Arguments..." link to find relevant arguments, and lower on the left side of this page look at the list of Latest Posts, and then click the Archives link at the bottom of that list. Off-topic comments on this thread will be deleted.
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Rhoowl:
Read my lips...
The Dutch, who know something about protecting their land from the sea, do not seem to be waiting for futher refinement of Global Climate Models to take action. [My bold]
Your propensity to move the goalposts sideways when responding to someone is not an acceptable behaviour on this site.