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Weather vs Climate

Posted on 26 March 2011 by dansat

The "skeptic" claim "scientists can't even predict the weather right" is based more on an appeal to emotion than fact.  The inference is that climate predictions, decades into the future, cannot be possibly right when the weather forecast for the next day has some uncertainty.

In spite of the claim in this myth, short term weather forecasts are highly accurate and have improved dramatically over the last three decades. However, slight errors in initial conditions make a forecast beyond two weeks nearly impossible.   

Atmospheric science students are taught "weather is what you get and climate is the weather you expect". This is why this common skeptical argument doesn't hold water. Climate models are not predicting day to day weather systems. Instead, they are predicting climate averages. 

A change in temperature of 7 degrees Celsius (°C) from one day to the next is barely worth noting when you are discussing weather. Seven degrees, however, make a dramatic difference when talking about climate. When the Earth's average temperature was 7ºC cooler than the present, ice sheets a mile thick were on top of Manhattan! 

A good analogy of the difference between weather and climate is to consider a swimming pool. Imagine that the pool is being slowly filled. If someone dives in there will be waves.  The waves are weather, and the average water level is the climate. A diver jumping into the pool the next day will create more waves, but the water level (aka the climate) will be higher as more water flows into the pool. 

In the atmosphere the water hose is increasing greenhouse gases. They will cause the climate to warm but we will still have changing weather (waves).  Climate scientists use models to forecast the average water level in the pool, not the waves. A good basic explanation of climate models is available in Climate Change–A Multidisciplinary Approach by William Burroughs. 

Source: AMS Policy Statement on Weather Analysis and Forecasting. Bull. Amer Met. Soc.,79,2161-2163

*Image source: Meehl, G. A., C. Tebaldi, G. Walton, D. Easterling, and L. McDaniel (2009), Relative increase of record high maximum temperatures compared to record low minimum temperatures in the U.S.Geophys. Res. Lett.36, L23701, doi:10.1029/2009GL040736.

NOTE: This post is also the Basic rebuttal to "scientists can't even predict the weather right"

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Comments 1 to 50 out of 131:

  1. A very simple analogy is that if I put a pot of water on my stove and turn the heat to "high", I can say with a great deal of confidence that it will boil. What I can't tell you is the exact minute and second it will boil, nor where in the pot the first bubble will appear nor where and when any of the subsequent bubbles will appear.
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  2. flambeaub at 06:37 AM, your analogy amounts to what might be determined in a laboratory exercise.
    Putting that pot of water onto a campfire might leave you concluding that it is never going to boil, as I'm sure many experienced outdoors might testify to.
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  3. No, no. The stovetop represents climate change due to anthropogenic CO2. The campfire represents climate change due to natural events (ie: solar irradiance, rotational precession, etc...).

    Sorry, feeling the need to be a bit silly.
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  4. You could spend a lot of time thinking up analogies to this absurd argument. How's this one - going in a different direction:

    Saying you can't predict climate change if you can't exactly predict tomorrow's weather is like saying you can't determine who will likely win when the Miami Heat plays the Minnesota Timberwolves (substitute your favorite sports mismatch)unless you know the exact spot on the court where every player will be when there are exactly 8 minutes left in the 4th quarter.
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  5. The "can't predict the weather tomorrow, therefore ..." comment, so often used in what the deniers think is a crushing final killer argument, is very odd indeed, the more you think about it. The weather forecasts in most parts of the world are now extremely accurate. Our local one here will tell you what time it will begin raining, how much rain is likely, when and where a thunderstorm will hit, when clouds will clear, what wind directions and strengths to expect, and so on. On the odd occasions when it is wrong it is only wrong in detail, for example the rain being delayed in its arrival by an hour or two.

    Someone who says that weather forecasts are inaccurate then can only be remembering back to a much earlier time, a time when isobars were based on a few weather stations and drawn by hand in small generalised maps in newspapers; where the forecast of rain could only be refined by what time it rained in the neighbouring town; where a front might peter out and slip away to the south before anyone could be aware of that fact; when conversely a cyclone might arrive out of nowhere; and where the dynamics of interacting weather systems were barely understood. I remember these kinds of forecasts from the 1950s, and I am sure that the deniers are harking back to that time (or even earlier) as well.

    The fact that weather forecasts now are extraordinarily accurate is the result of the huge growth in monitoring stations and weather satellites and computer analysis and well developed theories about rainfall and wind behaviour. All of the same factors that make our understanding of climate change so advanced.

    Time the deniers got to know which way the wind blows and why and when. Oh and if the weather forecast says take an umbrella, take an umbrella, a hard rain is going to fall.
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  6. David Horton at 08:25 AM, I agree with you regarding short term weather forecasts, however when it comes to seasonal forecasts, or looking a year or two ahead, it becomes a different matter.
    The ability to make such forecasts accurately is improving, but in terms of progress the mainstream forecasters are perhaps years behind some of the more progressive ones.
    Generally you get what you pay for, and some of the free services are simply too costly to follow.
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  7. How about "yeah, right, we can't predict individual waves so tide tables are useless, too"?
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  8. I came across a useful way of describing this the other day, but I forget where: The climate trains the boxer, but the weather delivers the punches.
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  9. We can't predict where and when an individual earthquake will occur, but we sure can say where the areas of highest seismic risk are. And there are numerous well-documented cases of anthropogenic influence, notably Healey et al 1968, The Denver Earthquakes, caused by waste water injection wells at the Rocky Mountain Arsenal.

    To go one step further on the absurdity index, small earthquakes are generally harmless; in large quantities (magnitude), not so good.
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  10. johnd, I've asked you this before but maybe you missed it, so I hope you see this : can you give the names of those "progressive" forecasters, so it is possible to compare their results against the "mainstream" ones ?
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  11. JMurphy @10,

    Surely he means groups like IRI or ECMWF when referring to "progressive ones"? ;)

    Very nice post dansat-- succinct and informative. Yet another ridiculous "skeptic" myth busted.
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  12. JMurphy at 10:11 AM, Ian Holton is considered one of the best.
    However I'm not sure how you will be able to compare his forecasts to others without subscribing to his service, or if you are even in the region he provides services to.
    Are you going to subscribe?
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  13. The attempt to find an analogy for this downplays the fact that the driving forces behind changing weather and changing climate are so fundamentally different that it ought to *be* the go-to analogy. That this argument even exists is a travesty for legitimate debate regarding global warming.

    However, good article: succinct, as it should be.
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  14. Darn it Albatross, stole my word.

    A thought, perhaps you could include a hyperlink to where someone might find some info about Burroughs' book? Maybe an abstract or review, not Amazon but something informative.
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  15. johnd, once a forecast has been made by Mr Holton, it must be available online somewhere, so that comparisons can be made between forecast and reality ? Do you know where this can be found, or do you know what his success rate is ?
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  16. I like the terminal cancer patient analogy. No doctor can tell how the patient will feel a week from now, but with certain cancers, they can tell with a high degree of probability, similar to the confidence levels in the IPCC reports, that he will die within a certain time frame. I like this analogy because I think the reasons for the short term uncertainty and the relative long term certainty are similar.
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  17. JMurphy at 10:51 AM, I don't think so, you can only wish.
    Most certainly, his forecasts would not be available on-line, it is a subscriber paid for service, tailored according to individual requirements and distributed directly to each subscriber, updated as necessary.

    He claims about 80% success rate, keep in mind his forecasts are very specific, in both outlook periods and specified coverage,not your usual BOM general forecasts of 50% chance of above and 50% chance of below outlooks produced for whole states.
    Even BOM and CSIRO claim they are several years away from producing useful and reliable forecasts with the government being asked to put up a large sum for purchasing new "super computers", I think that was the they term used.

    If you are not going to subscribe to his service, then you may have to be satisfied with reading testimonials from satisfied subscribers.

    He originally worked for BOM, but his thinking on what data was needed to make forecasts more accurate differed to theirs, so he left to start his own commercial forecasting service.

    His advantage was that he had found that incorporating IO data increased substantially the accuracy of his forecast models putting him about 10 years ahead of BOM in that regard, something I think we have discussed previously.
    He has continually added data from all ocean areas around Australia that wasn't previously being used for modeling.
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  18. "The predictive limitations are the same for climate models as they are for weather models."

    Nonsense. I'll elaborate later, but if someone wishes to debunk this myth please go ahead.
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  19. Weather is like a single roll of a single die (with 1 to 6 dots per face). It’s very hard to predict the outcome, even with a model.

    Climate is like rolling a single die roll 1000 times. It’s quite easy to predict the average outcome using a simple model. The average of all those rolls will be 3.5 +/- 0.17.

    Future climate is predicted by averaging many runs of a model to eliminate noise or some inherent bias towards certain initial conditions. And sometimes averages of different models are used to further eliminate bias.
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  20. I am prepared to concede that short term weather forecasts based on Doppler radar are impressively accurate. When they tell me a storm cell will arrive in my city in 35 minutes I take evasive action.

    As the time window expands, predictions become more and more fuzzy. When the forecast says that it will be raining six days from now I book my golf foursome with better than 50% confidence that the weather will be fine.

    When the BBC predicts that the next winter will be mild I (usually correctly) expect the forecasts to be wrong to an embarrassing degree. Likewise, when various university scholars predict how many hurricanes will hit Florida I realize that their guesses made using super-computers are no better than my guess based on waving a damp finger in the air.

    Predicting the temperature 100 years from now is much tougher than forecasting just a few months ahead.

    This post does say one thing that I believe is probably correct:
    "A change in temperature of 7 degrees Celsius (°C) from one day to the next is barely worth noting when you are discussing weather. Seven degrees, however, make a dramatic difference when talking about climate. When the Earth's average temperature was 7ºC cooler than the present, ice sheets a mile thick were on top of Manhattan!"

    Many of you seem to be in favor of reducing the average global temperature. Do you hate New York so much that you want to restore that ice sheet?
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  21. The article convincingly argues that skill of climate predictions can be different than skill of weather predictions. It does not say anything about any actual comparisons of climate forecasts to actual outcomes.

    In other words, although it is clear that climate prediction is not the same as weather prediction, there is nothing in the way of proof that climate predictions have any accuracy or skill.
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  22. gallopingcamel missed the point of the pool analogy. We can project the average height of the water in the pool with a few simple variables for rate of fill, volume, etc., but we cannot predict the peak of any single wave or trough made by the splash when somebody jumps in. We can do that because predicting local, short-term weather and global average climate over long periods are two very different processes.
    Climate models are NOT a bunch of weather predictions glued together. Anybody trying to use this kind of argument is deeply confused on the subject.

    Charlie A, Skepticalscience has another post dealing with climate models and their accuracy.
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    Moderator Response: [mc] fixed link tags
  23. It's like saying you can't predict that the long term average of dice rolls will be 3.5 because you can't predict the next roll.
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  24. CharlieA @ 23 - "there is nothing in the way of proof that climate predictions have any accuracy or skill.''



    Doesn't look too shabby to me.
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  25. given the fact that the curves are expressed as anomalies (so centered on the same average), and that there is some implicit selection of "good" parameters behind, without precision of how wide the interval of models has been chosen, doesn't like too predictive either. It is rather obvious that with some set of different bad models, centered on the right average, you can always cover a given experimental curve.
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    Moderator Response: Ian has responded to you on the "Models are Unreliable thread.
  26. Correct me if I'm wrong but the image in the article isn't a prediction.
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  27. 27 Rob Painting

    Do you mind explaining, in detail, exactly what scientists were predicting 4 years from the time of the prediction including some sort of uncertainty they were allowing themselves?

    I predict in 4 years time, barring some unpredictable event, that global temperatures will be within 0.3-0.4oC of where they are now. Does this mean I have some skill in climate science?
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    Moderator Response: Ian has responded to you on the "Models are Unreliable thread.
  28. PT#22: "if a model produces different output per run that means something in the model is not known (randomized in some way) and thus inaccurate ... It only takes one unknown variable in a computer model to make the output meaningless. "

    Such summary judgments should be avoided when you don't know what you are talking about. This is exactly how many industries use computer models - to see the range of things that might happen if there is a small change in the input.

    Some call these Monte Carlo methods. Industries that use these type of models (petroleum exploration, nuclear engineering, operations research, military, solid-state physics, fluid dynamics, particle physics, financial analysis, network design, weather forecasting, etc) should immediately cease work because PT says they are inaccurate, irrelevant, worthless and so on. Or due to the consensus that these models are applicable, perhaps PT's assessment is inaccurate, irrelvant, worthless and so on.

    We can decide whether to put civilization back 50 years or ignore PT based on a flip a coin, best 2 out of 3.
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  29. #35 "includes empirical testing as verification"

    And the basis of climate models are empirically tested physical laws and the results are tested by back-casting through known climate conditions.

    "It is interesting you mention financial analysis of which those models are just as worthless."

    I doubt that a corporation would keep throwing money at financial models if they didn't return something useful.
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  30. An easy way to show how good climate models are at predicting weather is to look at climate models predicting weather, in this case ENSO, shown in forecasts from Feb 13th, Mar 16th and Mar 25th (current forecast):






    My conclusion is that climate models can't predict weather. It doesn't mean climate models can't predict climate in some simplified way, but not the critical nuances (i.e. weather) that control sensitivity.

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  31. It's easy to see, in Poptech's arguments, parallels with the old creationist canard that anything less than 100% of the human eye is useless therefor it cannot have evolved.

    His argument is equally as easy to brush aside.
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  32. PT#34: "includes empirical testing as verification."

    Not always. Monte Carlo methods were introduced for the Manhattan Project (and named by physicists with a sense of humor). There was no experimental verification until the Trinity test; if memory serves, there was some doubt as to whether or not it would set the atmosphere on fire - and they went ahead with the test.

    There are no experimental tests in the oil industry, until you pony up and drill a well. A dry hole is merely one of the expected outcomes of a suite of potentially valid models.

    Best advice remains: keep your opinions to yourself unless you actually know what you are talking about.
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  33. PT#41, 42: Your understanding of the process used in the real world is minimal. And your continued use of 'worthless' is another example of your redefinition of words to suit your own purposes. I suggest keeping a dictionary at your computer at all times.

    "any result on a computer system that is not 100% accurate ... not to be trusted"

    OK, run a computer simulation that reports the location and velocity of an electron in a semi-conductor to 100% accuracy. If you can't, you must therefore not trust anything on your computer, or for that matter any piece of electronics you use. Better turn the lights off, because computers run those too.

    Or you could actually try learning about things before you pontificate.
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  34. PT#44: Irrelevant, you did not answer the challenge. You cannot possibly know the exact location and velocity of an electron; no model can defeat the uncertainty principle. By your definition, the output of your computer is thus worthless. Another example: you cannot possibly know when a cosmic ray will alter the state of your computer's memory. Since you cannot build an effective and portable shield from muons, it has happened and will happen again. You must conclude that the output of your computer is thus inaccurate and cannot be trusted.

    But this thread is about weather and climate. Further off-topic digressions should be deleted.
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  35. The fundamental answer to the canard that "we can't even predict the weather N days in advance, so how can we predict the climate M years into the future" is "because climate projection is not based on predicting the weather, but on simulating weather and then taking averages". This sort of statistical simulation is completely standard in statistics and physics, I use them myself in my own research as do countless other statisticians, physicists, computer scientists.
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  36. If climate scientists predict a global warming of 3.8 degrees by 2100 and it turns out to be wrong - it was 3.9 they will feel such fools.
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    Moderator Response: [Dikran Marsupial] Typo fixed; exactly the meaning of GEP Box's quote!
  37. Mods: I have moved my post to the model thread so please remove my previous post here.

    Gilles and HR, I have questions for you here.

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  38. I just started reading this blog a few days ago and find the information useful and more up to date than I can find anywhere else. However, I must say that I find it strange that Poptech seems to have hijacked this discussion and intelligent people are spending lots of time rebutting the same stupid arguments and he is not listening. Is this really the best use of our time and energy?
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  39. Poptech et al provide great examples of the other side. They show off the arguments they have so badly that it is almost reassuring and at times comical.
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  40. flambeaub.... I know it seems futile at times but I think it is a valuable exercise debating Poptech. I always try to put myself in the shoes of the broader readership here. What are they seeing in the conversation? I believe they easily see through PT's distortions and they see the other commenters here being mostly reasonable in their responses to him. People easily see the extremes PT goes to to defend his position. In that I believe the debate with him helps people to understand the larger debate on climate is almost exactly the same.

    On top of that, it's a bit of a car crash every time PT stops by. And like a car crash it's hard for people NOT to watch. It appeals to our more base level instincts.

    I don't think anyone wants to see Skeptical Science become just about this kind of car crash. Many may disagree with this but overall, from time to time, a PT car crash serves it's purposes.
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  41. Moderators, why is Poptech being permitted to troll and derail this thread?

    I agree with Rob @60, SkepticalScience is above this kind of nonsense and typically has a very high signal-to-noise ratio, that is why it is pretty much the only place that I choose to post on climate issues.
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  42. Here is a paper that could be posted in various different threads as it has relevance to a number of topical subjects such as weather/climate modeling, modeling reliability, SST.
    Read and enjoy/learn/weep as so inclined.

    Impact of Global Ocean Surface Warming on Seasonal-to-Interannual
    Climate Prediction
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  43. Two comments: one, where I live, weather predictions are still terrible. I think the "Can't predict weather...can't predict climate" argument is based in enough reality ("Can't predict weather") that it really, truly needs to be addressed. I do think it was well addressed here.

    As to Poptech and Ken Lambart and a few other posters. I hope smart, knowledgeable people will continue to refute the ideas they present when they are wrong. I personally don't have any problem seeing that models work (Hansen 1988 is still mind boggling to me - 23 years ago he knew what would happen to us right now!).

    But the claims that Trenberth's travesty is still with us will give me pause until we can irrefutably (within reason) put it to bed.

    Perhaps others are the opposite - they understand the limitation of ARGO, have read the studies regarding deep ocean temperatures (and a few lakes which give us fascinating insights into ocean heat content and heat transfer behavior) and see no problem with the supposedly missing heat.

    It is for those readers (presumably many X larger than those of us who post - else this is a lot of work for very few eyeballs...) that honest refutations of misinformation (regardless of the sincerity of the poster - wrong is wrong) are so valuable.

    Perhaps the moderators have to be even more hard nosed to move the debate to the right thread? That would ensure that those of us taken in by the false claim would read the background/supporting post and hopefully get a better understanding, so as not to be taken in by the same claim next time.
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  44. actually thoughtfull at 06:49 AM, your comment about terrible weather predictions in your area is quite telling.
    Firstly you probably accept it because it might only impact on whether your take an umbrella or not and so the free, but entertaining forecast attached to the TV news remains useful in providing a topic of conversation, and an excuse to complain.

    But for those whose businesses and enterprises depends on accurate short and long range forecasts, that is not only not good enough, but totally unacceptable.

    So what do they do? They seek out services that have proven track records and provide real value for money. Free is hardly ever free.

    So one of the points that your comment raises is, whilst, as you noted, there are weather forecasters out there that are virtually useless, but probably still retain a large and faithful following, and whilst there are also probably unknown to yourself, weather modelers, that by virtue of providing reliable and useful projections for more astute investors, and are able to charge high fees for their services, is it possible that the same range of expertise might also be within the ranks of those who model climate?

    Just for interest:-
    (1)How many people who read this thread are totally dependent on accurate forecasts for planning the next year or two forward?

    (2)How many people are totally dependent on accurate forecasts to make decisions about umbrellas?
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  45. "Many of you seem to be in favor of reducing the average global temperature. Do you hate New York so much that you want to restore that ice sheet?"

    Gallopingcamel, I cant believe after all this time you can seriously say this. Repeating again, concern over climate science isnt about proposing an optimal global temperature (higher or lower), it about reducing the rate of change in the temperature. From little I know of new york geography, the equilibrium sealevel, last time we had 400ppm would put most of NY underwater. I could ask whether you want that instead?

    Tell, if you put a large kettle on to hot flame, could you will all the computer modelling in the world accurate predict the convective flow within that pot? Not likely, though you might predict the pattern. (the weather) Could you predict when the kettle will boil? (climate) yes.
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    Moderator Response: Wrong thread for rhis conversation.
  46. Just to remind people attempting to argue with Poptech, that he has stated in other threads that no data is capable of changing his mind. He isn't interested in learning anything. Refute the errors but engaging with him directly is a waste of your time.
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  47. @Gilles 18:33 PM on 27 March, 2011

    You're not supposed to ask questions like this here. :-)

    The classical answer back from the AGW camp to your question will always be "deviations are variations in weather and should not be confused with climate that is long term based", combine this with error range that in principle cover every possible future scenario how can one ever be found to have made an incorrect predictions then? ;-)
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  48. @Dikran Marsupia at 01:38 AM on 27 March, 2011

    I read your comment as "Since what I do is a correct procedures, it follows that what climate scientist do is also a correct procedures."

    But surely this is not what you really meant to say or?
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  49. Gilles at 18:33 PM on 27 March, 2011, I see your point (despite the comments of batsvensson!), but to qualify a good theory as one which predicts unlikely events is tricky when we look at climate change. A Pinatubo event for example can be fed into a model once the significant effect it has is appreciated with hindsight and study, but we cannot predict the timing of the next one, or the likely frequency of such events in future decades.

    Back to an “unlikely” event that has been predicted by climate models, if we look at Hansens model from 1988, I repeat what I’ve said on the models are unreliable thread, the global average surface temperature has risen. There were many who predicted the reverse based on overestimates of solar influence, or claimed that any temperature rise to date was not statistically significant, and that this would remain the case (famously for example based on the MSU satellite evidence). Climate science has advanced at least partly as a result.

    It is more telling to look at events not adequately predicted by climate models (and we should remember there are many many types of models and not generalise too much) such as the acceleration in Arctic ice loss and in particular the loss of 2007, which it can be argued is a result of localised combination of “weather” events superimposed on background “climate” warming. There is recent work with higher resolution models which provides insight. There are similar stories to tell about eddy resolving ocean circulation models, sometimes the theory is adequate already, but we need much higher resolution to successfully model or forecast unlikely events (or even realistic variability), such as extreme weather, and then any “knock on” effect that this subsequently may have.
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  50. It would be interesting to see a comparison of Hanson's prediction in 1988 with what MSU and Lindzen predicted in 1988. We have a thread on Hanson's prediction but it does not compare to what other people said. As Peter points out, now everyone knows it got hotter and skeptics say Hanson's prediction was not perfect. A beter question is how good did Hanson do compared to the skeptics (and other scientists) at the time.
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