Cool for cats

FishThe second climate forecast for the next decade has been published [Advancing decadal-scale climate prediction in the North Atlantic sector, Keenlyside et al, Nature, behind a firewall but available here], and the world’s media – and a fair number of blogs – have jumped all over its suggestion that there might be some regional cooling over the next decade. Richard Black at the BBC headlined his piece “Next decade ‘may see no warming'” , the New York Times‘ Andy Revkin settled for “In a New Climate Model, Short-Term Cooling in a Warmer World”, which becomes “Next decade may see no warming” at frogblog and “Global Warming on hold until 2015 claim Germans” at Kiwiblog. So what’s going on? Is global warming really on hold?

The truth is a little more mundane. There’s a lot of work being done to improve climate models, in particular to allow them to make useful predictions of climate in the relatively near future – over the next decade or two – and to do so at a regional scale. This sort of climate forecast is directly policy relevant because it can provide information on what might happen in a particular place, and give us some time to prepare for it. In other words, this kind of modelling will give us an idea of what we might have to adapt to. It’s an important focus of current research, and will form a key part of the work planned for the next IPCC report. The current generation of global circulation models (GCMs) are pretty good at capturing the large scale features of the climate system and how they might change over the long term, but are not designed for and cannot do “climate forecasts”. [There’s a good discussion of what models can and can’t do here (click on “expand all”), which is being linked to by crank sites as somehow suggesting this is news]. GCMs give us a broad brush picture of likely futures.

At the other end of the business, meteorologists start with a snapshot of the current weather and plug that into their computers. The forecasting software – a complex mathematical model based on the equations that describe how the atmosphere behaves – calculates how atmospheric conditions will evolve over the next few hours and days, and produces a sequence of the charts we get to see in the media. Close to the time the forecasts are made, the predictions are generally pretty accurate, but as they get further out into the future – beyond two or three days – they become steadily more and more prone to error. Small errors in the initial picture of the atmosphere get multiplied as the forecast software chugs away, and the accuracy of the forecast decreases.

The “initial conditions” problem limits the usefulness of traditional weather forecasting models to periods of about two weeks. If you want to produce forecasts for a few months ahead – a seasonal forecast – you have to change the way you build the forecast, and take more factors into account. The most important of these is the behaviour of the oceans, because they hold a lot of heat. They fuel a lot of the weather we experience. If a pool of cold water turns up off the east coast of New Zealand, as it did in late 2006, the weather tends to be cooler than average (remember the icebergs?). So seasonal forecasts have to take into account what’s happening in the oceans. And they don’t produce weather maps. They give us a probabilistic view of what might happen. NIWA’s seasonal forecast for the next three months, for instance, suggests that it will be warmer than average in Northland. It doesn’t try to predict what will happen, and when, because it can’t.

The main features of climate tend to be described over periods of decades – thirty years is the World Meteorological Organisation standard. GCMs are trying to describe future climate states, based on changes in the “forcings” being applied to the system – the increase in greenhouse gases, reduction in ice albedo, and so on. They generate “weather” internally, but that weather isn’t based on a picture of current conditions. It’s realistic, but not real. The results are averages and trends, not specific events, and the drivers are changes in the forcings, specifically the increase in greenhouse gas concentrations. The best models generate an El Niño/La NIña cycle, but they don’t forecast when real La Niñas might happen.

If you want to try use a GCM to make a “forecast” of how the climate system will respond in the near future, you have to first feed in the “initial conditions”, and the most important of these on seasonal and annual timescales is the state of the ocean. This new paper is the second to attempt to run a climate model with information based on actual measurements of ocean temperature and heat content. The first, last year, came from the UK’s Hadley Centre. Both papers – and both forecasts – are very much first attempts. This is state of the art stuff. We have no idea how “good” these forecasts are.

It’s also important to note that although we’re learning a lot more about the heat content of the oceans, from the ARGO float programme, from satellite measurements of surface temperature and many other studies, there is still a great deal more to learn. Modelling how the oceans work and how currents ship heat around the globe is a long way behind where we are with the atmosphere – and good ocean models will be crucial to useful medium term regional climate projections.

So has global warming been put on hold for the next few years? This new paper suggests that some regions might cool, but the overall average will continue to climb. It’s possible that the rate of warming might slow down for a while due to the way oceans behave, but we have no idea how likely that might be. Stoat thinks that the furore is mainly a press phenomenon, with an agressive press release prompting some enthusiastic over-interpretation. James Annan is generally dubious, and RealClimate has a post in preparation. [Edited to add: Climate Progress also has a good post on the subject, and Nature Reports gives a good overview.]

Meanwhile, the Arctic sea ice is melting, and until the models can reflect that in today’s conditions, I will remain agnostic on their abilities on decadal timescales and at regional levels.

29 thoughts on “Cool for cats”

  1. This new bout of Global Cooling Alarmism is plain dumb. Despite all the cries that “evidence” for global cooling is “mounting” and all that, when you get right down to it, what are the actual, peer-reviewed papers out there that can be argued to predict global cooling?

    Rasool and Schneider (which was back in the 1970s). Zhen-Shan and Xian. Keenlyside et al. The end. That’s just 3 papers. And all 3 of them “predict” global cooling only when certain unrealistic conditions are met.

    “Evidence” is “mounting” my foot.

    — bi, International Journal of Inactivism

  2. The Great Global Warming Swindle will be shown on Prime TV at 8:30 pm on the 25th May. I hope everyone will watch it. It is the revised version that has the errors in the first one corrected. I would point out that Al Gore’s AIT – and Al himself – still have the 9 serious scientific errors found by a British Court. And it is still being force fed to our schoolchildren as “good science”.

    Sadly, what I expect to hear is demands that it not be shown. I hope I am wrong.

    Regarding models, I have been looking for evidence that they have accurately predicted the future for many years. If Garth does indeed have this evidence, would he please share it with the world? NIWA don’t have it. I asked them.

  3. If The Great Global Warming Swindle had all its errors corrected it might make for an enthralling – ooh, what – 90 seconds viewing? I hope Prime show some responsibility and don’t allow this to be shown without some prominent disclaimers. And, Bryan, I wonder if you’ve heard about the status of the complaint against Channel 4 and Wag TV (makers of TGGWS) made to the UK OFCOM (broadcasting complaints) body. The OFCOM determination should be out soon. Rather more than 9 “errors” I think we’ll find…

    As to the models, clearly you can’t be bothered to read what I wrote above. Climate models do not make and are not designed to make short term predictions. And I reckon that until they get the Arctic right, they can’t tell us much about the near future.

    But I forgot. According to Bryan, “the Arctic is back to normal”. Do you still stand behind that?

  4. Bryan:

    You mean the errors like the ENTIRE Carl Wunsch interview after he complained he’d been both misled into being interviewed and about the entire premise of the programme and that his interview had been taken out of context?

    Then there was the error that “joined up” bits of a graph to make it look as though sunspots correlated with temperature.

    And the error that said the date at the end of a graph was “today” when it was in fact 20 years ago, conveniently missing the temperature rise in the last 20 years.

    Remind us, Bryan, of which other errors have been corrected? A list would be dead handy.

    Meanwhile the Australian ABC’s Tony Jones interview of the documentary maker is well worth a watch:

    (this is part I; you’ll see part II listed, along with the entire debate after the programme).

    And finally, an ExxonSecrets map of all the interviewees we had listed at the time:

  5. Bryan

    >”Sadly, what I expect to hear is demands that it not be shown. I hope I am wrong.”

    At the very least I would hope that *you* are asking Prime to screen another show with the ‘balance’ viewpoint. Say AIT!


  6. Have you watched TGGWS? I can send you a DVD – but only if you promise to watch it. I have watched AIT – it is a great work of science fiction. TGGWS has scientists speaking not an ex politician whose company will go bust if the AGW house of cards collapses.

    I wouldn’t hold my breath re the outcome of the enquiry into TGGWS. None of the SEVEN complaints are anywhere near e.g. predicting 20 ft of sea level rise when the IPCC prediction is a lot smaller. The hockey stick argument is laughable. Even the IPCC have abandoned it.

    At the time the statement re arctic ice was made, it was accurate. As ice extent depends on currents and wind, I would not attempt to predict it. I am not up to date with the current extent.

  7. At the time the statement re arctic ice was made, it was accurate.

    Bryan, that is simply not true. At no time during the northern hemisphere winter did the sea ice extent or area get anywhere near “normal” (where “normal” is the average over the period of satellite observation). What you said was not true, and deliberately misleading.

    I invite you to write to The Listener retracting that statement.

  8. Hey Bryan,

    still waiting to hear your actual opinion of Beck.
    *not* the implications of what it means if he is right but your opinion of the “science”.

    And as before, if you don’t know enough to say one way or the other then how is you are such an expert on other related issues?

    As I keep saying, if *you* don’t know then ask CdF what he thinks of Beck and post the response here.

  9. Gareth, have you read Dr. Keenlyside’s paper? If you haven’t, then I recommend that you should, since climate change is a topic that you preach about. I have read his paper, which I requested a copy directly from Keenlyside himself. You can request a copy from him here (

    As a skeptic myself, Keenlyside’s paper only confirms to me of what I do understand about climate numerical modeling and that is there is no certainty in the models at all. I am not saying that Keenlyside’s model described in his paper is more accurate than previous (& current) ones, but it clearly established of what science is about, and that is , it has not been settled.

    Err, and please don’t attack & accuse (you and the greenies) some of us skeptics that we don’t understand the science of climate modeling (perhaps others skeptics don’t), because that is not true, I & others (I do know others) do really understand what we’re talking about, because we do read the peer review related publications in climate science. So, we get our knowledge first hand rather than rehashing of what’s being said in the blogosphere & media.

    I think that you & me agree on one thing and that is the NZ Climate Science Coalition should dissociate themselves from Ken Ring, because Ken’s position on climate science is no more than a psychic service.

  10. Gareth said…
    If The Great Global Warming Swindle had all its errors corrected it might make for an enthralling.

    Gareth, I am amazed if you had watched TGGWS and not examine some of the claims it made (excluding the errors). Look, if you want to preach climate change, then you should do better than just concentrating on errors made in the film. I does enhance your status as a climate change ambassador. Did you examine close of how Dr. Patterson (from the TGGWS) described of how he used wavelet analysis, to infer a possible link between temperature & the sunspot cycles? If you haven’t examine that closely, then I think that you should just refrain from making comments about climate science because obviously, you have already made up your mind that the science is settled.

    I wouldn’t say that TGGWS is convincing or not, but it clearly shows that climate science is not settled. As far as I know that there hasn’t been any alternative proposal to explain the wavelet analysis established by Patterson , et al in indirectly linking temperature variations & sunspot cycles and if there has been any work on this, then I am happy to be pointed out to that publication.

    BTW, Patterson was not the first one to use wavelet in climate modeling, there has been numerous applications of wavelet in climate science prior to Patterson’s (et al) work. And here is one think for you to understand, it doesn’t mean that being one of those 1500 IPCC authors, then that person is knowledgeable in all forms of climate numerical modeling. This is a huge area and no single person understands every technique available, and if you doubt this, then try asking those 1500 IPCC authors to find out how many of them understand wavelets? I bet you that it is going to surprise you, that perhaps, 10% or less of that total number do understand wavelets, and the remaining have no clue. It doesn’t confine to only wavelets, but many many other techniques. The point I am trying to make, is, if you use different models, you would arrive at different conclusions, and this is an undeniable fact.

  11. Gareth,

    I find some of your comments here misleading. Since your readers here are largely greenies, they cling to these comments as gospels.

    Let me correct you about the subject of forecasting. It is defined (web & dictionary) as To calculate or estimate something in advance; predict the future. Suppose that now (today, this week, this month, this year, etc…) is at time zero (T=0), if one is to talk about events (quantitative) that occurs beyond time T=0, such at T=t+1, T=t+2, T=t+3, and so forth, where t is a constant time increment quantity, then this projection, estimation, prediction of future states at time T=t+n, is called forecasting. First, you’re wrong to say that forecasting is not to predict future events.

    First, forecasting is meant exactly to do that, and if you argue otherwise, then you’re must admit that you’re being disingenuous.

    Second, you’re wrong to say that forecasting is better long term than short term. Err, wrong! It is an established fact that forecasting is better short term than longer term. This means that the longer time-steps that you forecast into the future, the more inaccurate the prediction is, that is the wider the margin of error.

    This explains why climate modeling & forecasting involves the heavy use of monte-carlo simulation (IPCC also adopts monte-carlo), because of the huge uncertainty brought about by long term forecasts. Monte-carlo is best for long term and not for short term. Monte-carlo tries to cover all possible paths imaginable from initial conditions to any future final value, and these paths are then averaged out to come up with a single projection or forecast for that future time-steps.

    I do use monte-carlo myself for financial market analysis which is used heavily today in that field (Monte Carlo methods in finance).

    If you’re so fond of IPCC monte-carlo, wouldn’t you be so eager to play your hard earned dollar by betting the financial market in using the same monte-carlo? My web-based service (financial market analytics) is just about to go live soon and monte-carlo (including other IPCC models) are included in my service for analyzing the financial market and if you’re interested, then let me know so I can direct you to the site to register when its available. My business model is to take a small percentage cut if the subscribers to the service make a profit, but if they don’t, they only pay the subscription service fees. I hope that the IPCC die harders would endorse my service and subscribed.

  12. Stephen
    thanks for the hockey stick reference. Note that the next page – 468 – of that same IPCC report covers the Medieval warm period discussion which I also found very useful.

    “However, the evidence is not sufficient to support a conclusion that hemispheric mean
    temperatures were as warm, or the extent of warm regions as expansive, as those in the 20th century as a whole, during any period in
    medieval times.”

  13. No worries Cindy.

    So is Leyland just plain lying or what? Bizarrely, I was reading the magazine that the Libertarianz put out a few months ago, and they referred to the same thing. What. Is. Going. On.

  14. FF , I defer in all things statistical to the professional statistician who blogs at Open Mind. He summarises the position on solar climate linkages nicely here.

    There may be some connection between the change in TSI over the 11 year solar cycle and global temperature, but it is small (see discussion linked above). There is no solar connection that can explain the recent warming.

    As for the models, I stand by what I wrote above. They are good broad brush representations of the climate system, but they are not very useful at regional levels or on short timescales. The Keenlyside paper (a full copy of which is linked to in the post) is an interesting first step on the road to near term projections, but it is only a first (in fact, second) step.

    And I have watched TGGWS. Scientifically, it’s crap.

    Note for Bryan: the complaint to the UK broadcasting standards body identifies many serious breaches of the code.

  15. What. Is. Going. On.

    The cranks have their scriptwriters, who come up with the “standard line”. This is then trumpeted and repeated as often as possible in the hope that it will be treated as fact. That’s why it’s important to call them on their deliberate errors.

  16. ho ho

    Any prizes for guessing which of our cowardly denialists uses an offensive pseudonym?

    That sort of behaviour was the wedge for my initial probing of the late AA. Turned out the offensive bit in question – part of a v. dodgy list of things “THEY don’t want you to know” (caps in original) was actually maintained by someone we have yet to see here (using their real name that is).

  17. Doug Mackie said…
    Any prizes for guessing which of our cowardly denialists uses an offensive pseudonym?

    Doug Mackie I know that your post was meant for me. Let me ask you a question, do you understand Tongan language, if you don’t, then shut up and don’t by any mean imply that my name is offensive. If you can’t stomach or counter to my arguments here on this thread, then stop insulting my intelligence & making ridiculous indirect inferences about me, because it is bordering on being a racist. If you have something to say about my post, go ahead and attempt to answer it, rather than your pathetic racist comment. Ko e ngaahi matalemu hange kokoe ‘oku totonu ke taufale’i.

  18. Bryan
    I’ll watch TGGWS on Prime – if I forget you can send me the DVD.

    As for AIT – why bother referring to the 20ft sea level rise. You understand ‘if’ statements I am sure ( what am I saying!, “If Beck is right” – of course you do. Perhaps you learned them off Al Gore).

    20ft came in context of an “if” and was not time constrained, therefore okay! (however I did cringe a bit when he mentioned the evacuation of south pacific islands).

    Maybe AIT is propaganda – but that is what is needed to get the attention of the general public. Propaganda is also what I expect from TGGWS.

  19. Mr FF

    So – let me get this straight…

    a) forecasting is okay for short term but not for long term
    b) Monte Carlo simulation is better for long term than for short term
    c) You use Monte Carlo for forecasting financial markets (long term?)
    d) forecasting is okay for short term but not for long term
    e) Monte Carlo simulation is better for long term than for short term
    f) You use Monte Carlo for………..
    (see where I am going with this?)

    Now consider, climate models are better for long term than for short term because they don’t predict weather (ie annual variability may drown out the climate in the short term), climate models use Monte Carlo simulations (taking your word for it here) because it is better for long term? So what’s the problem?

    Gareth, Good link to Tamino – I hope FF reads it and gives us his thoughts on the wavelets.

  20. 1) forecasting is okay for short term but not for long term

    Correct. The reason is, there is less chance or unlikely (in probabilistic language) that a sudden jump (discontinuity) appears between today and tomorrow. This doesn’t mean it can’t happen, it just mean that the error of estimation is smaller between projecting for tomorrow (assume that the time-step is daily, ie the time increment is one day units of forecasting), than projecting for the next 100 days or so. The longer the time-steps the forecast run estimation to the future, the greater the error. This fact arised from forecasting theory itself which is basically observed in reality (in terms of percentage correct prediction, ie, error rate within margins).

    2) Monte Carlo simulation is better for long term than for short term.

    Yes, because long term almost always encounter jumps (discontinuity), surprises or shocks as others called them. Monte carlo (MC) is used to generate a random path between initial point and a future unknown point. The method is computer memory intensive as the many paths specified by the user for the routine to traverse are in the millions so that to make MC reliable. The many paths are then averaged out to get a final point that is likely to be the final destination, but again it is no guarantee. This power point mentioned a 1 million point monte carlo (IPCC Working Group I Chapter 2 FINAL FIGURES).

    3) You use Monte Carlo for forecasting financial markets

    Monte carlo had been used in the finance industry for over 2 decades. See the following link for its use in finance: Monte Carlo methods in finance. I use it for valuation of american-type option pricing in the financial market.

    4) forecasting is okay for short term but not for long term

    Perhaps I should have clarified myself a bit more. Forecasting is done for both long term and short term, however the catch is, the longer your time-steps into the future, the bigger the error of your margin and that means it is less reliable, if you talk about risk and uncertainty. So, the smaller the uncertainty (short term) the more reliable the forecast is.

    5) You use Monte Carlo for…

    And your point is…?

    …climate models use Monte Carlo simulations (taking your word for it here) because it is better for long term? So what’s the problem?

    The problem is that no one had ever predicted the future correctly. Even using monte carlo doesn’t guarantee accuracy. If that is the case ie, long term forecast is accurate (reasonably), then climate scientists in massive numbers from all over the world would have beat the market regularly and become millionaires or perhaps billionaires when they trade in the Weather derivatives market. But we haven’t seen such scenario have we? I would be happy if you could point me out to a climate scientist who has used his model to beat the market regularly by trading in the Weather derivatives market, then I will become a convert warmist.

    What makes you think that forecasting long term using monte carlo (or other forecasting methods) is more reliable in weather forecasting but not in the financial market forecasting? Does that tell you something about the model? It tells you that models usefulness are limited, but mostly are useless for long term forecast.

    BTW, there are some journals in forecasting where publications found in them are more descriptive and deeper in forecasting methods than I have briefly described here. Here is one that I regularly looked at : INTERNATIONAL JOURNAL OF FORECASTING.

  21. Falafulu
    On another blog someone made the comment that he didn’t believe climate models because he had spent 20 yrs doing finite difference modelling and knew how wrong models could be. To which someone pointed out that a) most GCM’s aren’t finite difference models and more pertinently, b) did he just throw away all the results of his 20 years work or did he actually make some decisions or recommendations based on his models (albeit faulty).

    My point is that you (FF) want people to make some financial decisions on the strength of your financial model and your abilities to drive it.

    Yet you don’t want to accept that AGW is a happening thing because you don’t have faith in the models…….it doesn’t strike me as a good marketing campaign for your business.

    Someone (Tamino or realclimate I think – sorry, can’t find the link right now) has plotted Hansens 1988 projections against actual warming to date and shown that his model has held pretty good for 19 to 20 years – even his allowance for a big volcanic eruption which was provided by Pinatubo. Is that enough proof for you?

    As someone who plans to earn an income from your own modelling why is it so hard to accept that the climate modellers: know how to paramaterise their variables; know the limitations of their models (which will be very different to yours); know of course that whatever result they get it will be wrong (as you do), but; also know overall that it is right enough to warrant action.

  22. Bryan Leyland,

    I’ve watched Swindle, and that is exactly what it is.


    Even if all the climate models on earth were fatally flawed (and they’re not; they do a good job when run over historical data, for example) this would not give us cause to disregard the threat of AGW. We know, thanks to basic physics that, all else being equal, more CO2 in the atmosphere = higher temperatures. We know thanks to carbon isotope measures (along with other work) that we are causing CO2 to rise in the atmosphere. And our knowledge of climate forcings and feedbacks is – while incomplete – adequate to enable us to discount any other combination of forcings+feedbacks as being the cause of C20 warming. We have, in other words, even without models, reason enough to take action.

Leave a Reply