How do Climate Models Gain and Exercise Authority?

Challenging Models in the Face of Uncertainty - Conference Keynote: Professor Mike Hulme (UEA): How do Climate Models Gain and Exercise Authority?

Bishop Hill writes:

There is video available here of a lecture given by Professor Mike Hulme entitled “How do Climate Models Gain and Exercise Authority?”. Hulme asks whether deference towards climate models is justified and whether we should have confidence in them. I think the answer is “We don’t know”.

http://www.crassh.cam.ac.uk/page/195/media-gallery.htm

NOTE: Chances are the volume of heavy WUWT induced traffic may “crash” the CRASSH server, bookmark for later if you don’t get a response.

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60 thoughts on “How do Climate Models Gain and Exercise Authority?

  1. As someone who works with models I am very concerned by the faith put it them by policy makers.
    As is the case with even IPCC models, each one I work with is usually accompanied by an explanation of the limits and uncertainties of the model. This is not however typically written in a way or explained in a way that policy makers can understand. The question they usually ask is whether I as a professional “believe” or “feel” the model is accurate.
    All to often, their eyes glaze over when I explain that my beliefs or feelings do not increase or decrease the accuracy of the model.
    The best way I have found for explaining models to my managers is to remind them of the models that Wall Street used to create and manage mortgage-backed securities – they work well when conditions the model account for are the dominant ones that are in play, but work very badly when other factors that aren’t factored into the model become important. They still really don’t get it, but it helps.

  2. They should gain authority when they can accurately predict a change in direction – ideally for several cycles. It is depressing how simplistic models built during a relatively benign period for both climate and finance have been seen as more reliable than common sense.

  3. “How do Climate Models Gain and Exercise Authority?”
    Only with considerable semantic and grammatical perversion, it would seem.

  4. The whole question of ‘authority’ is one with a lot of history and philosophy behind it. We used to have authority figures, but whether it be God, priests, our parents, statesmen etc they were (or were claimed to be) living, rational and intelligent. Now we are supposed to vest authority in models: entities that are non-living, non-rational, non-sentient, non-speaking, non-thinking, and beyond scientific demonstration – this is a sociological phenomenon, and deeply troubling.
    Well, I’m not vesting authority in such an entity.

  5. In most cases, I would think that the answer to the question “should we have confidence in the models?” is yes, consistent with our understanding of the uncertainty. However, with the unanswered questions and concerns about the veracity of the climate model builders, I don’t think we have a true understanding of the uncertainty of the climate models, and therefore we cannot trust them.
    If your gut response to the question is “we don’t know,” then isn’t the prudent answer to the question simply “NO?”

  6. Doug’s comments re trying to explain models to his management: ” they work well when conditions the model account for are the dominant ones that are in play, but work very badly when other factors that aren’t factored into the model become important”
    In other words models should not be depended on for complex systems. Is the earth’s Climate complex? Can i develop a reliable equation that represents the heat transfer associated with water moving in variable currents in the vast ocean from the lowest depths at the equator to the surface just under the ice in the arctic and relate it’s heat sink/source interaction with the atmosphere throughout the globe whilst ignoring the affects of variable cloud cover affecting the heat sink/source interaction between the the sun, earth and space?
    Probably not, but it would be a lot of fun if I could get someone frightened enough to pay me to study/model it.

  7. I am sure that avid izaac azimov fans will know what is coming. Before you know it, the programmers will attempt to include a “What is in the best interests of the human race” element into their models and the models will decide that what is in our best interests is, that it (the model) survives in order to protect us from ourselves. We are closer to this senario now than i ever thought we would be.
    I’m for turning them off, whilst we still can.

  8. I used to be in charge of evaluating commercial thermal-hydaulic and reactor fuel models for the government, and I can tell you that although those models were packed up with quite a but of dxperimental data, we insisted that they be used in the most conservative manner possible, and we applied penalty factors whenever the experimental database could not support a model of a particular phenomenon.
    Knowing what sort of experimental database is needed to support modeling of a simple reactor fuel rod, operating in reasonably well defined conditions in a single-phase coolant, I have no confidence whatsoever that the environmentalists can model the entire atmosphere of a planet, assuming that one trace gas is the driver for the entire system. The inability to demonstrate, by comparison to actual observed data, that they can model the behavior of clouds, dooms them to the dustbin.
    It was a common saying in the nuclear TH field that “no one believes the code calculations, except the person running the code, while everyone believes the experimental data, except the person running the experiment”. At least we had a LOT of people running experiments, at different scales, in different facilities, to have some sort of confidence that the data from the experiments was useful. The code results were highly susceptible to “creativity”, which is why they were examined quite closely, and their use was highly constrained.

  9. A theory is something nobody believes, except the person who made it.
    An experiment is something everybody believes, except the person who made it.
    Albert Einstein

  10. IPCC Third Assessment Report:
    “In climate research and modeling, we should recognize that we are dealing with a coupled nonlinear chaotic system, and therefore that long-term prediction of future climate states is not possible.”
    Did they forget about this in AR4 (and now AR5)
    Just because you have bigger and faster computers, doesn’t mean that this does NOT still hold…..

  11. The models gain skill by comparison with instrumental data. This would be a whole lot more credible if the pre-satellite instrumental data was worth a dime. As much as the dendro field is denigrated, the mangling and other issues in the “instrumental period” are more problematic because that’s the calibration period for the models.

  12. Are you seriously proposing that I am gonna use my time to watch what Hulme is saying? Is a member of the Team!

  13. HOW CLIMATE IS CHANGING ?
    Massive Arctic iceisland drifting toward shipping lanes
    The biggest Arctic “ice island” to form in nearly 50 years — a
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    Glacier.Canada.com – Aug 07 10:16am In another research, using Autosub, an
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    Jenkins said, “The discovery of the ridge has raised new questions about
    whether the current loss of ice from Pine Island Glacier is caused by recent
    climate change or is a continution of a longer-term process that began when
    the glacier disconnect from the ridge”.
    http://www.sciencedaily.com/releases/2010/06/100620200810.htm
    Not only warm water, but also concentrated Magnesium Chloride =7,100 p.p.m &
    Sodium Chloride= 31,000 p.p.m. (de-icing agents) trapped under the ice, is
    causing the bottom of the ice shelf to thaw, resulting in continuous thinning
    and acceleration of glacial melt (under water glacier cutting).

    http://www.youtube.com/watch?v=3fGHlEBvKYw&sns=fb
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    “The Climate is changing” said JAY LAWRIMORE, Chief of Climate Analysing at
    the National Climate Data Center in Asheville, N.C. “Extreme events are occuring with greater frequency and in many cases with greater intensity”.
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    1. Mushrooming of Sea water desalination systems in the Middle East:
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    drilling, dynamiting & excavation of sea floor shifted Magnesium Chloride, Sulfur & Sodium Chloride.The geographic position of the Arabian Gulf, Ocean circulations bringing it to Arctic & Antarctic Oceans during Monsoon seasons along with hot water of the Middle East.
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    If we enforce strict Environmental regulations, recover MgCl3 and NaCl3 at
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  14. Hulme deliberately frames the question this way – asking whether or not X has ‘authority’. This is a part of post-normal science, an attempt by people like Hulme to relegate scientific truth as subservient to supposed utilitarian outcomes. No surprise really, as he was deeply influential in shaping the philosophy of the climategate crew.
    There’s no such thing as ‘authority’ when it comes to computer models. What matters is if it is prospectively predictive. Hulme wants to steer debate away from this because once he and his post-normal crew have declared a model as ‘authoritative’ the little people can no longer question it or its’ conclusions

  15. Doug in Seattle- the whole mortgage backed securities fiasco is and example of modeling
    having no idea of what happens if at, random, a certain element(s) does not co-operate
    with the program at hand.
    “What bubble? I don’t see no bubble -this is going to go on for years!”- actually said to
    me at a meeting by my old Real Estate company. I read a paper done by Prudential in 2006, that the Real Estate boom was “unstoppable” and had at least 10 years-according
    to their projections (Modeling, of course) -It was done by the next year….
    The Green Bubble is about to pop…

  16. So as he said climate models are used for political purposes. If that is so, what are scientists doing having any connection with these models. And what are politicians doing using models as proof of the need for legislation and regulation. Have I got it wrong that models are a tool with limits and not in itself proof.
    It’s a good thing my only interest in models is how good she looks.

  17. Actually the climate models don’t exercise any authority, the question is rather how either stupid or mentally disturbed (by evil militant fundamentalist extremist for a tree hugging hippie green communist) you have to be to actually buy all that IPCC like climate model crap?
    Me and my refurbished flame thrower, however, seem to be viewed as very authoritative, even though they damn maniacs at the local petrol shop refuses to refill my tanks (I bought a few extra that now, sadly, are too empty to even have fumes left.) Just look at the tree huggers expressions when I’m near (hmm, do I have to remind you that it is statistical improbable for everyone to not like me, so why all the fear?) :p

  18. In an essay published at
    http://pajamasmedia.com/blog/the-gulf-oil-spill-meets-the-newspeak-dictionary/?singlepage=true
    Theodore Dalrymple wrote
    “In an editorial in the New England Journal of Medicine for 11 August, titled “Moving Mental Health into the Disaster-Preparedness Spotlight,” Drs Yun, Lurie and Hughes (the latter a lawyer, it seems) write:
    “Surveillance systems for mental health and substance abuse must be strengthened through broader intellectual investment in a conceptual framework and technical requirements.”
    Long experience of bureaucracies has taught me to mistrust language such as this. There is a lot of connotation in it without much denotation: intellectual investments, conceptual frameworks and technical requirements escape from verbiage generators like oil from defective wells, and end up being even more expensive. Personally I am not sure that technical investments, intellectual frameworks and conceptual requirements would not be at least as good, if not better.”
    When I heard Professor Hulme saying that climate models “offer access to the future”
    I concluded that his lecture would offer much connotation and little denotation and I stopped listening.

  19. Climate models gain authority in the same way economic models do; because of the ideological incentives of those who use them to promote them, and because they can’t be falsified because their results will always be adjusted ad-hoc to perfectly ‘predict’ the past, and their predictions will always be measured against other possible futures we can never know anyway. And in fine con artist fashion, as with the myriad of rip off psychics out there, when predictions are made it’s the few that pan out that people will remember, and the many that don’t that will be quickly forgotten, and the promoters of the models will have no incentive to stifle this behavior and every incentive to nurture it.

  20. Sorry but I’m new to HTML tags and the post above is in reference to:
    “DISINTEGRATED ICE SHELVES DISINTEGRATION DATES
    Worde Ice shelf March 1986*
    * Larsen A Ice shelf January 1995*
    * Larsen B Ice shelf February 2002*
    * Jones Ice Shelf 2008*
    * Wilkins Ice shelf March 2008*
    If the Ice shelves are disintegrating during WINTER, it is not SUN or CO2.

  21. The most normal thing to do is to fall in love with your own simulation model. This is perfectly understandable of course; you work for so long with your baby equations and the numerical implementation that any objections to your beautiful forecasts become insulting.
    Sometimes numerical simulations are useful, for example when they landed on the moon the first time, they accurately predicted the trajectory of the landing vehicle. However, for simulations to be useful, the model must first be validated, no nuclear engineer would trust reactor simulations that sometimes fail.
    Simulations models are validated when they are able to predict future or unknown empirical observations over and over again. This is not the same as the idea that it is only possible to falsify a theory which is untrue – simulation results that agree reasonably well with the real world are validated, if this happen sufficiently many times.
    The tricky issue is to decide how many simulations that must agree with experiments to decide that we have a valid simulation model. I would say a couple of hundred or thousand simulations would be required. Note, this is with unknown or future data to which the simulation model is not calibrated.
    Most of the thermal mass is in the oceans, the question is then, for how many years would we require that a climate simulation should predict reasonably well the ocean heat content for the model to be validated? Take a close look at this curve:
    http://www.climate4you.com/SeaTemperatures.htm#Sea surface temperatures
    We note that the characteristic time constant for temperature oscillations in the oceans is something like 5 or 10 years, each bump in the curve lasts for about 5 years before the next bump appears. Let us then imagine that we would require 200 predictions to become true before the model is validated. This would mean that we would have to wait at least 1000 years before we can validate a climate model – yes the thermal transients in the oceans are that slow.
    For the simulation engineer this is not easy to realize – the improvements, the modifications, the software quality and the simulation results have become an obsession. Yes it is perfectly normal to become blinded by your own simulation model. In academia this can go on forever, a professor can improve a useless and erroneous simulation model his entire life. However, in a professional commercial company this cannot happen easily and it is common to require that simulation models are validated.
    I think you have figured out what I mean.

  22. Let’s be logical. If the answer is “we don’t know,” then – by definition – we have no business reposing great faith in them.

  23. Climate Science (Roger Pielka Sn) reports on a new study by a group of hydrologists that compares climate models results with observations:
    http://pielkeclimatesci.wordpress.com/
    The abstract of their paper says:
    We compare the output of various climate models to temperature and precipitation observations at 55 points around the globe.We also spatially aggregate model output and observations over the contiguous USA using data from 70 stations, and we perform comparison at several temporal scales, including a climatic (30-year) scale. Besides confirming the findings of a previous assessment study that model projections at point scale are poor, results show that the spatially integrated projections are also poor.

  24. I have yet to find a single Climate Scientist that claims the computer models accurately account for the climate system.
    This alone makes the “Majority of Scientists Agree”assertion transparent.

  25. Computer programs can usually model an object IF its fully defined AND its methods are fully understood AND its properties are completely defined AND its programmed correctly AND its capable of being run in an acceptable timeframe AND its proved correct via testing… this is called object orientated design and programming.
    If you use Windows on your PC, for example, you will know how much “respect” and “authority” you should grant this model operating system which has been evolving for the last 25 years and still requires “fixes” and “patches” as new issues are continually identified.
    Now go back to the first paragraph and look at all those conditions that must be met… now think about all the complexities, uncertainties and unknowns associated with the climate or the economy… now you know how much “respect” and “authority” you should grant a computer model.
    The question: How do Climate Models Gain and Exercise Authority?
    The answer: Not by being correct… so don’t grant them any authority.
    Remember: Garbage In – Garbage Out applies to design, programming and data.

  26. RAVEENDRAN NARAYANAN says:
    October 22, 2010 at 11:22 am
    “HOW CLIMATE IS CHANGING ?
    Massive Arctic iceisland drifting toward shipping lanes…………”
    =============
    I can’t quite make out where your book is coming from, or going,
    but I like the shameless plug.
    If it is bad news, I’m sure it’s my fault.

  27. PS
    There is an established marketing adage used to sell Information Technology: If you can’t convince them then confuse them. This technique works well especially when you incorporate FUD – Fear, Uncertainty and Doubt. These techniques are pivotal when it comes to selling Global Warming and Climate Change… although the more common adage is: Baffle them with science.

  28. deference towards climate models is justified and whether we should have confidence in them
    =====================================================
    Absolutely not…
    …if these slackers could really predict the future, they would put it to better use
    …and pick lotto numbers

  29. Given his background, Hulme went as far as he could in a public setting to say that one should not put all one’s faith in the models as they simply are inadequate and not up to the job.
    This was not a ringing endorsement of the models or the IPCC use of them. Its time that university press releases and the media adopted the same approach.

  30. PPS
    A booted and suited Al Bore always reminds me of a good old fashioned computer salesman who really knows how to sell ice to the Eskimos…. but doesn’t know much about his bits and bytes… although be knows where he wants to stick his digits

  31. In real sciences, a model gains authority by making predictions. Then these predictions are compared to the real world. If the model’s predictions are confirmed by measurement or observation, the model gains authority. If the predictions are not confirmed, the model is discarded or fixed until it comports with reality.
    Unfortunately, climate models have made predictions that have not been confirmed, like increasing temperatures with increasing CO2 for the past 10-15 years, a reduction in snow falls, or accelerating sea level rise.
    The models are useful tools to generate scary press releases and drive power grabbing agendas.
    Sorry-EPIC FAIL !

  32. Doug in Seattle says @ October 22, 2010 at 9:11 am
    As someone who works with models I am very concerned by the faith put it them by policy makers.
    It seems to have slipped under the US radar that there are municipal elections here in Ontario; dunno why that would be 🙂 Anyhow: I notice that those who will be elected are doing and saying nothing to offend no-one. This is one sure way to get elected for a Western politician. However, if they really, really, really must SAY or DO something, then they prefer to wrap it up in the flag of rationalism and inevitability.
    This is why “Policy Makers” put faith in computer models. Not because they believe them, but they offer a fig leave of scientism to their hare-brained schemes. If it all goes pear-shaped, then they are not to blame since they were merely following THE BEST SCIENTIFIC ADVICE AT THE TIME.

  33. This should be made a Friday Funny LOL
    hyper.real says:
    October 22, 2010 at 9:32 am
    “How do Climate Models Gain and Exercise Authority?”
    Only with considerable semantic and grammatical perversion, it would seem.

  34. Billy Ruff’n @ October 22, 2010 at 1:56 pm
    You do realise that Jan-Feb is the height of summer in the southern hemisphere, right?

  35. Richard A: “they can’t be falsified because their results will always be adjusted ad-hoc to perfectly ‘predict’ the past”.
    More than that, past temperatures are ‘adjusted’ because the various models failed to hindcast correctly.

  36. Got to love one of the opening statements by Hulme. At the 5:24 minute mark he says, and I quote:
    “Climate models are essential for the detection and attribution of anthropogenic climate change.”
    Pardon me, perhaps I am a simple lad, but how does a climate model “detect” anything? Back in my day we used instruments in laboratories or even out in the field to “detect” things. Must be my age showing. So these new-fangled models do the entire work of science now…

  37. “Who’d buy a used car from that man [M. Hulme] ?
    Brgds/Sweden
    //TJ”
    I would, but I certainly wouldn’t expect it to be reliable from one day to the next 😉

  38. I found Hulme’s presentation to be more even handed than I had anticipated, though admittedly that was not a high hurdle to top. He did at least leave the question of whether or not climate models deserve respect as an open question and , in laying out the reliability issues, as he sees them at any rate, he left the answers mostly for the audience to provide for themselves. He did however mostly miss the 800 pound gorilla in the room which is that in most modeling applications outside of climate science the models are only deemed useful if their output can be, rather immediately, tested against experimental observations. A quality GCMs don’t possess based both on the timescale of their projections and the relative inadequacy of the observational data they must be judged against.

  39. Confidence in models is a subject I can comment on with some confidence. Any model is only as good as the data and assumptions that are used as input, coupled with the modellers detailed knowledge of how all parameters interact to arrive at a modelled forecast. In the great majority of cases a model is useless at making accurate forecasts unless all preceding paramters are also known accurately.
    What a model is good for is giving an indication of what the future may look like. In this regard it is a tool, but not a decision maker on its own.
    An example is model I produced for forcasting river flows and lake storage in a hydro-electric catchment. It uses known river flows and lake storage, forecast rainfall and temperature changes, modelled snowpack and estimated pseudocatchment storage. So very little of the input is actual data, and some is only guessed. Therefore the resutaltant output can never be relied on.
    It has a very high degree of confidence (better than 99% accuracy) up to 12 hours ahead. It is also very reliable (95% accuracy on average) at up to 48 hours ahead, and a decling degree of accuarcy after that. The model shows a prediction out to 8 days ahead, but as the writer of this model I would say it has very poor confidence that far out.
    So imagine my frutsration when opertors, and even civil engineers, make decisions based on what the model tells them might happen in a week’s time. It is only good for catchment management 12 hours ahead and energy management 48 hours ahead, and on that basis is a very good tool.
    Climate models are also a tool if they are used as an indication of what might happen if the primary component changes, but everything else is constant. Of course we know that everything else isn’t constant, so no reliance can be placed on climate models at all.

  40. Hulme is playing the role of loyal opposition in order to gently bring the outsider criticism to the insider audience.
    This is helpful, but we should not forget how he worked very hard to use his perversion of social science methodology to maintain the exclusion of sceptics and to discredit their arguments in ad hominem attacks.
    (see here:
    http://enthusiasmscepticismscience.wordpress.com/2010/06/25/the-anatomy-of-virtuous-corruption-disagreements-permissible-unmentionable-and-inconceivable/)
    This (unconsious?) strategy is most alarmingly displayed in Hulme’s review of a book by Singer and Avery:
    http://www.guardian.co.uk/society/2007/mar/14/scienceofclimatechange.climatechange
    This Keynote at a conference on modelling and uncertainty elaborates one aspect of another Hulme’s loyal opposition positions, namely his position on the discussion of risk assessments in AGW, especially in the Stern report. Hulme is now as important in perverting the discussion of risk as Schneider was in the late 1980s and 1990s. A fundamental error is his discussion of risk is exemplified in his ‘Five Lessons’ :
    http://www.mikehulme.org/wp-content/uploads/the-five-lessons-of-climate-change.pdf
    There he asks the reader to substitute ‘resource’ for ‘risk’ and I think he is trying to say that we need not value-laden climate change as all negative, as we do when we talk of its ‘risks’. Well indeed! But yet he continues to use ‘risk’ as a contraction of ‘the risk of disasters,’ or as, itself, a euphemism for ‘adversity,’ ‘calamity’ or ‘disaster.’ Thus, risk = risk of an adversity.
    More confusion is introduced in his book Why We Disagree… by conflating the risk of things happening with their happening. Sometimes this is like the risk a hurricane confused with the event of one. Other times you see risk as some objective external thing that we can come to know. With some thought, we can realise that such an objective risk is an illusion.
    This objective risk is invoked in statements like these:
    “When we don’t know for sure what the risks associated with climate change will be” [p114]
    “Because we are uncertain about many of the risks that climate change may cause” [p116]
    “It is actually about whether or not we judge the (largely unknown) risks associated with climate change to be so potentially large and undesirable.. p124
    “..the physical (and hence exonomic) damage caused by climate change, and the risk of catastrophic change, are poorly understood by science.”
    Imagine we were scientifically discussing the risk of a full eruption of a volcano after some rumblings. The risk at any time can be assessed on what is known at any time. The certainty is the event of the eruption – that’s not a risk! If it does not erupt (and all goes quiet) then we cannot say in hindsight that there was, in fact, no risk of eruption at the time the assessment was made. The risk assessment depends on the knowledge (scientia) at the time, including the state of knowledge of the time — thus, risk was assessed differently (due to the state of knowledge) in AD79, in and 1883, than it would be today. It is not that we are ‘not sure of the risks’ – because they are already in what we know — but that risk is about being not sure of the outcomes, and the extent to which we are sure of the outcome is the extent of the risk.
    The most absurd and unscientific invocations of risk are often marked by the expression “potential risk” [eg p223 and common in Schneider]. What proposed outcome, I ask, is not a potential risk? An impossibility? To say that a climate outcome is not impossible is a truth trivial and so almost scientifically useless — and yet this expression has been very useful rhetorically.
    The most insulting and condescending discussion of risk, is where Hulme presumes that, when folks do not respond to claims of risk or ‘potential risk,’ that they are not acting reasonably. In looking for all sorts of psyco-social reasons for ‘ignoring risks’, he discounts the possibility that either folks have assessed the risk and taken it as acceptable, or otherwise that they do not accepted the expert’s opinion of the level of risk.
    Do not swim! Unfiltered water, do not drink! Keep out of reach of children! Is everyone who defies an expert warning doing so unreasonably? How many times have health warnings been wrong? A much more difficult question would be to ask whether folks have good reason to be sceptical of warnings given on the authority of state-instituted science.
    Why does this matter? It matters because this sloppy and confused discussion of risk by Hulme and Schneider, as well as Stern, has been used to obscure a reasonable discussion of the acceptability of various risks to the environment, and especially the risks of CO2 emissions. This obscuring has served the ends of raising alarm beyond what is justified by the evidence. Promoting this confusion is an abuse of science and an abuse of the people’s trust in science. We should hold publically funded scientists such as Hulme accountable for propogating such corrupted reasoning. The value of Lomborg’s scepticism was its sober, clear and balanced discussion of relative risks in an attempt to push aside these puffed-up clouds of confusion, and return us to a clearer view of the (however uncertain) state of what we know by our science.

  41. If this is the best “they” can do, “they” are a sorry lot indeed.
    Quite frankly Hulme is making the point (about 1/3rd) of the way in that “pretty pictures lend public credibility”. Not even deserving PITY. More like complete MOCKING and derision are in order for such an implication.

  42. I’m sure the US Military ran models that showed how the Iraq and Afghanistan wars would run smoothly. And, there was no MWP involved, nor tree rings.
    Just saying.

  43. Boy, did that ever take me back 40 years to university lectures…..
    Analyzing the caffeine dosage required to follow along was more interesting than making sense of the continuous reference to models and how they depend on input parameters to validate the input parameters….
    Recently heard outside the lecture hall:
    “My brain hurts!”
    Prof. Enid Gumby.

  44. Olen says:
    October 22, 2010 at 12:10 pm
    So as he said climate models are used for political purposes. If that is so, what are scientists doing having any connection with these models. And what are politicians doing using models as proof of the need for legislation and regulation.

    Politicians in a democracy need something to hang their hats on, so to speak, in order to lend an air of legitimacy to their actions (increasing government power). I think it’s a fair assumption that ‘useful idiots’ (consciously or not) are helping to create an illusion of legitimacy for sweeping government action.
    The relationship is a bit too cozy from where I sit.

  45. Barry Woods says:
    October 22, 2010 at 10:47 am
    IPCC Third Assessment Report:
    “In climate research and modeling, we should recognize that we are dealing with a coupled nonlinear chaotic system, and therefore that long-term prediction of future climate states is not possible.”

    It is possible for climate models to predict a linear trend line to hit the walls of a non-linear chaotic progression faster than previously imagined. Failure simply comes faster than the press can megaphone it in. Millions are watching intently as Climate Scientists backpeddle.

  46. Get the science debate going on at The Air Vent questionning Models’ response to Condensation as a low pressure effect on weather.

  47. Blimey, listening to Mr Hulme I can feel myself slowly slip into a coma.
    Why use ten words when you can use five hundred really complicated words that make you sound really clever and important?
    I managed about twenty minutes of that twaddle. If he’s got something to say, I wish he’d just say it instead of wiffling on about epistemics and heuristics.
    For me, the guy is an abysmal communicator – life’s just too short to wade through all that ridiculous verbiage.

  48. The weather/climate system is a chaotic one. To model this needs the certain knowledge of all inputs, both magnitude and direction, to get anything like a sane answer. We do not know this system as well as we think we do so our models are wrong.
    We know, from the daily weather forecasts, that after only two days there can be great variation between the forecast and actuality. If a three day forecast is a problem then to forecast the next 50/100 years is crass stupidity.

  49. I think Berniel makes some very astute comments. His own article is worth a read though sadly it also suffers from being too long IMO.
    However, Berniel’s ref to Hulme’s Guardian article is significant. Here, Hulme gives clear evidence of his own false starting point, and I think this is at the heart of the warmists’ ability to adopt BS positions, that is often hidden under their otherwise inexplicable rejections of the sceptics position. Hulme says

    …there are two other characteristics of science that are also important when it comes to deploying its knowledge for the benefit of public policy and society: that scientific knowledge is always provisional knowledge, and that it can be modified through its interaction with society.

    Scientific knowledge is modified through its interaction with evidence, not through its interaction with society! This evidential basis needs to be constantly stated in real scientific work, or the author becomes a hypocrite, talking about scientific method but failing at the same time to practice it himself, in the most basic form of checking, and being seen to check, the crucial evidence. Thus the crucial evidence is loudly missing when Hulme simply says in the preceding paragraph

    Increasing the concentration of greenhouse gases in the atmosphere warms the planet and sets in motion changes to the way the weather is delivered to us, wherever we are. Science has worked hard over a hundred years to establish this knowledge. And new books such as Singer and Avery’s… do not alter it.
    …Deploying the machinery of scientific method allows us to filter out hypotheses – such as those presented by Singer and Avery – as being plain wrong.

    but Hulme has failed badly, and typically for warmists, at this point, because though he TALKS about scientific method, he does not show evidence of PRACTISING it himself ie he parrots the notion that Singer and Avery are “plain wrong” without actually demonstrating their evidence or why he claims it’s wrong.

  50. John Marshall says:
    October 23, 2010 at 2:49 am
    The weather/climate system is a chaotic one. To model this needs the certain knowledge of all inputs, both magnitude and direction, to get anything like a sane answer. We do not know this system as well as we think we do so our models are wrong.
    We know, from the daily weather forecasts, that after only two days there can be great variation between the forecast and actuality. If a three day forecast is a problem then to forecast the next 50/100 years is crass stupidity.

    I call it hubris. Hubris is crass stupidity aimed at the gods 🙂 , there is fear of retribution. In the weather/climate case if the next ice age comes sooner than we hope ; it is really just delayed as far as the ice records show and the warming nonsense carries the day, mankind will be found completely unprepared, and that will be the retribution of the gods.
    I do not tire of saying that the invention of “climate” as something different than “weather” done in order to deny that climate is chaotic, cannot hold as long as the same differential equations are used as are used in the weather calculations.
    And weather iterations hold only for a few days, i.e. a relatively fixed number of iterations. The reason is because programming the solutions of the differential equations requires linearity assumptions that do not exist in the real solutions, thus it is inevitable when non linearities kick in that the programs’ solutions will diverge from the solutions picked by nature , never forget that nature is a huge calculator after all, the only true experiment.

  51. “How do Climate Models Gain and Exercise Authority?”
    Well, the answer is quite simple really.
    The more Complexity they are imbued with , the more a scientifically disconnected public, media & political establishment bestow them with authority, in the mistaken belief that complexity necessarily makes them better.
    The rest is about insulating the non-scientific communities from the realities of modelling.
    Presentations like this ‘though just serve to bore all but the most ardent of sceptics into submission.

  52. Lucy Skywalker says:
    October 23, 2010 at 5:01 am
    Quoting Hulme:
    ” ‘…there are two other characteristics of science that are also important when it comes to deploying its knowledge for the benefit of public policy and society: that scientific knowledge is always provisional knowledge, and that it can be modified through its interaction with society.’ ”
    It is rather scientific ignorance that can be manipulated in this way, ostensibly for the benefit of public policy and society of course.

  53. In the video, Prof Hulme reports on his PhD student, Martin Mahoney’s work on PRECIS. This is a Met Office model, distributed to over 100 countries in last 10 years or so. PRECIS seen as effective for ‘raising awareness’. It ‘can make climate change real’. It can ‘attract public endorsements’. It was said by some player that it had been ‘useful to have the UNDP seal of approval on it’. Clearly PRECIS has been found by activists to be useful for ‘convincing policy makers that they should take a stand’.
    I added this comment to my report of this on Bishop Hill (http://www.bishop-hill.net/blog/2010/10/23/shade-on-hulme.html):
    ‘I suspect the apparent success of PRECIS will one day make a useful study for anthropologists trying to make sense of the late 20th and early 21st century adoration of computer models and the ways in which they seemed to overwhelm policy makers.’
    All is not well with our political system when so much is done based on very unsatisfactory computer models. Hopefully this is just a teething problem ‘the system’ will soon grow out of!

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