UK-US Workshop Part IV: Limits of climate models for adaptation decision making

by Judith Curry

This post discusses Workshop presentations on the utility of climate models for regional adaptation decisions.

This post is a follow-on to the two previous posts:

This post highlights two presentations on climate modeling.

Tim Palmer – Oxford University:  On seamless prediction and the reliability of climate forecasts

Palmer introduced 5 categories of forecast reliability in context of a reliability diagram: 5 – perfect; 4 – still very useful for decision making; 3 – marginally useful; 2 – not useful; 1 – dangerously useless.  Examples were given of regional variations in reliability in context of ECMWF seasonal forecasts.

Are regression lines of reliability diagrams from seasonal predictions useful to calibrate low-resolution climate change projections?  Preliminary results show that that such regional calibration of climate change projections of precipitation do improve the skill of lower-resolution climate model predictions.

This talk provided an excellent example of the utility of seamless weather-to-climate model predictions, whereby the predictions of short-term high-resolution simulations are used to improve the longer-range low resolution climate model simulations.

In his verbal comments and in discussion, Tim Palmer argued strongly and eloquently for the level of research commitment required to meet the enormous challenges of predicting regional climate, a challenge that he argued was greater than that associated with identification of the Higgs boson.

Leonard Smith – London School of Economics: The user made me do it: seamless forecasts, higher hemlines, and credible computation

Well Lenny certainly gets first prize for best title.  His first slide includes the statement that caught the attention of Uncertain T. Monster: ‘It’s OK to say that we know we don’t know.’   Smith argued that climate models were not up to the standards in relation to other computational fluid dynamics groups in terms of validation, verification, uncertainty quantification, and transparency, stating ‘Trust can trump uncertainty.’

Smith describes the following limits to transparency:  dangerously schematic schematics; showing anomalies versus a real-world quantity (which can hide systematic error that are larger than the observed anomalies); equidismality (rank order beauty contests of climate models, without comparison of some absolute measure of quality); buried caveats; burying the bad news about model performance.

Smith provides the following summary of the demonstrated value of weather/climate forecasts as a function of lead time:

  • Medium-range:  Significant, well into week two +
  • Seasonal:  Yes, in some months and regions
  • Decadal: Not much (global and regional)

With regards to using global climate modes for regional climate variability: “In the long range, simulations which require significant statistical adjustment (or variance inflation) at global scales are NOT rational candidates for local use (e.g. dynamical downscaling.)  This is a key point that was brought out in discussion:  Smith’s presentation basically threw under the bus the widespread practice of dynamical downscaling of global climate model projections using high resolution regional models.

Regarding the credibility of computation.   In climate-like tasks, the impossibility of experiment places heavier burden on analysts.  The burden of demonstrating relevance and credibility is  squarely on the analyst’s shoulders.  In my experience, across all of CFD, climate modelling has been  the slowest scientific field  to embrace this responsibility, whereas other fields are embracing  insightful parallels for structural  model inadequacy.

Smith argues that the climate community has oversold climate models.  ‘How do we ease user pushback when the current oversell becomes clear?’  He then asks the questions:  Can (we) climate modelers stop digging?  Information we are supplying which is not ‘adequate for purpose’ is being interpreted as if it was. A wave of valid criticism of the presentations and interpretation of models may well come from physics, statistics and even (has already come from) honest policy-maker IPCC –questions.  The political/public interpretation might be that the anti-science lobby was right in the first place.  How do we clarify limits of our understanding on more favourable terms?  

Take home points:

  1. There is no rational justification to using “probability distributions” derived from climate model diversity as decision-relevant probabilities
  2. The tools of Decision Theory 101 do not apply. Vulnerability approaches do not require them No probability forecast is complete without an estimate of its own irrelevance.
  3. The values of model simulations must be quantified outside model-land (and will vary with the space and time scales of the task and the lead time relevant to the decision).
  4. Solid insights of climate science may be obscured if the severe limits on our ability to see the details of the future even probabilistically are not communicated clearly.
  5. We need to better distinguish “valid methodology” from “useful tool”, and avoid waffle (“yes, but when the signal comes out of the noise”). When global statistics of GCM distributions require significant correction or inflation, dynamical downscaling is a nonsense.
  6. We can provide seamless forecasts, expose hemlines due do our limited understanding, and support real user needs with more credible computation. Aiming for true transparency and engagement. Other scientific disciplines are doing this now even if they were not when climate modelling started!

In terms of philosophy of climate modeling, there is much in Smith’s presentation that is not included in this summary, along with a useful reference list.

JC reflections

These two presentations were fascinating for someone like me, who both uses climate model outputs and also philosophizes about climate models.   The reactions of the non-climate scientists in the audience was that while they didn’t quite follow the presentations, that this was the first real criticisms of climate models that they had encountered (outside of something that could be dismissed from the ‘anti-science’ crowd).

The limits of climate models for regional adaptation decision making was also highlighted in several other talks (that will be discussed in Part V).  This led Brian Hoskins to speak up in defense of climate models, which he introduced  by saying that normally he finds himself criticizing climate models.  He felt the impression left on decision makers were that climate models are useless for regional adaptation decisions, and was concerned that we were throwing out the baby with the bathwater.  There are two pre-conceived notions that can color how you view this discussion on climate models:  one is that regional decision makers are continuing to use the historical record to drive decision making (e.g. the historical 50 year flood) which does not account for climate change; the second is that international bodies (e.g. the UNFCCC) seem to be operating in a climate model command-and-control mode.

In the discussion, all agreed that global climate models were potentially very valuable and could be made more useful for adaption decision making, but that this potential was not yet realized.  Apart from the important points made by Tim Palmer regarding the importance and challenges of improving climate models, the following strategies would increase the utility of climate models to support adaptation decisions:

  1. Increase the size of the ensemble
  2. Use the climate models to explore possible future scenarios that extend beyond emissions:  e.g. solar forcing, volcanic eruptions.
  3. Develop improved strategies to extract useful information from the climate model simulations, such as suggested by Tim Palmer
  4. Sensitivity studies that help improve the fidelity of decadal simulations and also help improve understanding of model limitations and uncertainty.

Part V (stay tuned) will present some alternative data-driven (and model-data) approaches to supporting regional adaptation decision making.

157 responses to “UK-US Workshop Part IV: Limits of climate models for adaptation decision making

  1. All politics is local, as is adaptation to climate change.

    Warming is net beneficial; cooling is net detrimental.
    =====================

    • What? Is everybody else reading the main post?
      ======

    • Oh, it’s about models. Well I can tell you what’s the matter with them; the climate models get water vapour feedback and clouds wrong. The economic models discount well, shall we say imaginatively?
      ===========

    • Climate models seem the ultimate tautology.

    • James Hansen, in his fraudulent 1988 testimony, blamed the Washington heat wave on AnthroGHGs, claiming regional skill for his climate model. That was not true.

      I suppose it is possible that at the time he did not know his model had no regional skill, but he’s had plenty of time to snap to that insight since. Has he corrected the record?

      Someone oughta. Someone with big, big pants.
      ==============

    • Climate models and tautologies….

      “A tautology is a series of statements that form an argument, whereby the statements are constructed in such a way that the truth of the proposition is guaranteed or that, by defining a dissimilar or synonymous term in terms of another, the truth of the proposition or explanation cannot be disputed. Consequently, the statement conveys no useful information regardless of its length or complexity making it unfalsifiable. It is a way of formulating a description such that it masquerades as an explanation when the real reason for the phenomena cannot be independently derived.”

      Dunno, sounds kinda close.

    • Pervert the null a la Trenberth, and it looks like a prize-winning recipe, until the judges start in tasting.
      ===============

    • “Warming is net beneficial; cooling is net detrimental.” – kim.

      Poor kim, still trying to raise the spectre of catastrophic cooling.

      Leonard Smith has another piece of advice, relevant to the short comings of models – and I’m sure the denizens will take it to heart;

      “Is adaptation cheaper and more feasible than mitigation?
      The answer is that we do not know, and this fact alone means that an
      approach based primarily on adaptation is not realistic or, as it stands,
      rational. Without mitigation, the range and scale of impacts will be much
      greater, and the costs of adaptation—both monetary and otherwise—will
      rise, and eventually our capacity to respond will fall”

    • “and the costs of adaptation—both monetary and otherwise—will
      rise, and eventually our capacity to respond will fall”

      That doesnt follow from his prior claim.

      ‘Is adaptation cheaper and more feasible than mitigation?
      The answer is that we do not know, and this fact alone means that an
      approach based primarily on adaptation is not realistic or, as it stands,
      rational.”

      strange how one argues from a premise that we dont know the costs, to the conclusion that it will rise and our capacity to respond will fail.

    • “fall” not “fail”.

      Strange, how one can suffer from a simple comphrehension failure when it’s convenient.

    • I’d say it’s more of a comprehension fall than fail.
      It’s just a question of degree – doesn’t alter the point.

    • “…someone with big, big pants.”

      (made of fire-proof Nomex)

    • phattie,

      There is a yawning chasm in meaning between,
      “eventually our capacity to respond will fall”
      and
      “eventually our capacity to respond will fail”.

    • “Is adaptation cheaper and more feasible than mitigation?”
      It’s the wrong question. The real question is whether we should pay for mitigation on top of adaptation.
      In 1988, warmists would have called politicians idiots if they drew up plans to handle 14 snowstorms in New York City in the winter of 2014 and near 100% ice coverage of the great lakes.
      But adaptation to heavy snow in Northeast (and ice in Georgia, and floods in England), must be done regardless because they will happen. So we have to do adaptation. The question is how much, if any, mitigation is also needed. Well, that and whether we should ignore the warm and choose mitigation options that actually mitigate anything.

    • Mikey, the issue is with the word ‘will’, which is at odds with the phrase: “we do not know”.
      But I suspect you already knew that.

    • Still doesnt follow Micheal.

      How, when you dont know the costs, do you know our capacity to respond will fall or fail. You don’t. Any more than you know our capacity to mitigate will fail or fall.

      It could well be that adaptation will INCREASE our our capacity to respond.
      primarily through

      A) the learning curve
      B) the technological improvement curve
      C) the changes in demographics in the out years.

    • kim says –

      James Hansen…blamed the Washington heat wave on AnthroGHGs, claiming regional skill for his climate model.

      Is kim’s statement about Hansen’s 1988 testimony accurate? You can check by reading the testimony here.

    • take the simple case of adapting to the case of sea level rise.

      This estimate came in at a couple hundred Billion.. half a trillion
      http://papers.risingsea.net/Holding/NRJ.html

      Subsequent to this The EPA did a similar study. 400B

      400B between now and 2100, is mousenuts. When you consider the knock on effects of infrastructure spending adapting INCREASES your ability and capacity to adapt

      Adaptation costs dont eventually lead to your capacity falling for failing,
      rather just the opposite if you buy the multiplier effect pushed by some folks.. or did you forget that government spending results in $1.50 of increased GDP for every dollar spent

      The best example is the mayor in Japan who adapted to high Tsunami before it happened. His city is spared and he has more capacity to adapt not less. Those who did not adapt have less capacity

    • Steven,

      That sounds like little more than wishful thinking.

      Smith touches on this too;
      “A rational preference for relying on adaptation as the primary response
      requires a deep certainty as to the impacts to be adapted to; today’s science cannot provide that basis. …At present, it is highly misleading to claim that adaptation will be easier or more cost effective then emissions control. Since we do not know what adaptations will be required, we cannot say whether they will be harder or easier—more expensive or less—than emissions control.”

    • Thanks for that, Pat. A quarter of a century later, and still no regional skill. Utterly appalling.
      ==========

    • Michael
      Infrastructure for “adapting” has to be built regardless of whether AGW happens or not. The delta cost of building an infrastructure that will withstand the negative impact of climate change is small compared to the overall cost of that infrastructure’s construction and maintenance.
      You may believe that climate change will be negative, but you really have no reliable data to support your belief. (it will be beneficial in some places and harmful in others and today nobody knows which will happen where) You have no way of knowing that if zero CO2 was ever emitted by humans as of tomorrow that the weather would be noticeably different or better overall.

    • And too much of what is claimed as impacts climate cahnge based on inexact climate models is net BS!

    • “take the simple case of adapting to the case of sea level rise.
      This estimate came in at a couple hundred Billion.. half a trillion
      http://papers.risingsea.net/Holding/NRJ.html
      Subsequent to this The EPA did a similar study. 400B
      400B between now and 2100, is mousenuts” – mosher

      I’m pretty sure that is the EPA paper – and it’s fairly likely to be farcical.

      For starters, that a 1991 costing figure, which even then, was based on 1980’s costings, so there’s 30 yrs out of date, right off the bat.

      We now have some much more recent costings which might futher question those 1991 estimates – US Army Eningeers have estimated relocation costs for 6 Alaskan villages at $30-50 million each. They have identified 160 that will likely need be moved due to sea-level rise/AGW.
      Taking the lower estimate,there’s 5 billion (around 10% of the total estimate you quoted) gone, in just one state, on just one aspect of adaptation. Mousenuts?

      Makes one skeptical.

    • LOL – 1%

    • “You have no way of knowing that if zero CO2 was ever emitted by humans as of tomorrow that the weather would be noticeably different or better overall.” – Rob

      Rob,

      I think we can say that the liklehood of a 30% increase in non-condensing GHGs having no effect is rather slim.

      • I think we can say that the liklehood of a 30% increase in non-condensing GHGs having no effect is rather slim.

        The only evidence you have for this is the extrapolated effects on the planet due to temperature increases that themselves are extrapolations of temperatures based on GCM’s that have proven to be inaccurate.

    • Michael
      Use your example of sea level rise. Since we have had a reasonably reliable means of measurements, there has been zero increase in the rate of sea level rise. It has been rising at a rate which will result in about a foot of rise by 2100. Coastal areas that wish to be protected from the sea will not have a significantly more difficult job in building a sea wall to protect them from a sea impacted by AGW than one not impacted by AGW. It may be slightly higher, but the delta cost for the potential rise due to AGW is minimal. It isn’t like if we stop emitting CO2 that there will not be adverse weather.

    • Mi Cro,

      The observed increased in temp’s have nothing to do with GCMs.

      Rob,

      Opportunity costs.

      • “The observed increased in temp’s have nothing to do with GCMs.”
        True, but they are also only tied to Co2 because of GCM output.

    • I think we can say that the liklehood of a 30% increase in non-condensing GHGs having no effect is rather slim.

      I agree, it will have an effect! This effect will be so tiny that no one will be able to measure it and no one will separate this effect from the noise and no one will ever be able to know or understand if it caused warming or cooling. or anything.

      Yep, it will most likely have a tiny effect. but we will never know for sure. Tiny things are like that. Mostly, we never really know.

    • Max_OK, Citizen Scientist

      Re post by Pat Cassen February 18, 2014 at 3:36 pm |
      kim says –

      James Hansen…blamed the Washington heat wave on AnthroGHGs, claiming regional skill for his climate model.

      Is kim’s statement about Hansen’s 1988 testimony accurate? You can check by reading the testimony here.
      ______

      I thought you were implying kim was fibbing so I checked Hansen’s testimony. OK, that’s not exactly what Hansen said, but kim may have been confused by the testimony or just didn’t remember it all that well. I prefer to attribitute kim’s inaccuracy to incompetence rather than dishonesty.

    • Steven,

      That sounds like little more than wishful thinking.

      Smith touches on this too;
      “A rational preference for relying on adaptation as the primary response
      requires a deep certainty as to the impacts to be adapted to; today’s science cannot provide that basis.
      #####################

      Wrong. It does not require DEEP CERTAINTY whatever the hell that is to understand that a warmer world will mean sea level rise.That is not todays science that is old knowledge. It does not require deep certainty to calculate the costs. It’s pretty straightforward. We’ve done this sort of thing as a species for centuries. We know how to do it, we’ve done so successfully. Second, who ever made the argument that adaptation was the PRIMARY response. We are already mitigating and the suggestion is made over and over that talking about adaptation is akin to denialism. And further here the argument is made that action requires deep certainity. That has never been a part of the story when it comes to mitigation so why suddenly does certainty in fact deep certainty suddenly become a necessity.

      • David Springer

        Adaptation. You mean like New Orleans knowing that a Category 3 hurricane making landfall was inevitable and knowing that the levees wouldn’t hold they fixed them ahead of time?

        Oh wait…

        Figure out why NOLA didn’t pre-adapt, Stevie, and apply it to geopolitical entities larger than cities. The modus operandi of adaption failure scales in both directions. How’s it coming with the US east coast pre-adapting to higher storm surges so underground utilities don’t get decimated by saltwater innundation? Or how is California doing pre-adapting to statistically predictable droughts? Or what pre-adaption to another Sumatra–Andaman earthquake which in 2004 generated a tsunami that killed 230,000 people in 14 countries has taken place?

        The story of failure to pre-adapt just repeats over and over. What happens is they always have more immediate concerns and end up simply dealing with events when they happen if they happen. That perhaps isn’t the smartest thing but it’s the way it plays out time and time again. No amount of wishful thinking by global village moonbats is going to change this. Don’t be a global village moonbat.

    • Mosher is right. The mitigation train left the station a long time ago. This is already a work in progress no matter how many people want to stop it now fearing its expense. Green energy, fuel efficiency, energy efficiency, reduced carbon pollution policies are already being enacted, and research is making mitigation more effective as we speak. As these technologies become even more viable, they will spread through the energy sector. Don’t try to stop it, support it. It is a major area for new commercial ventures and growth, often even with government support and incentives, and a ready-made export market to compete for. It’s like cars replacing horses, part of the future. Don’t cling to the horses.

      • David Springer

        There never was a “mitigation train”, Jimbo. That was imaginary.

        Burdening the global economy with feel-good measures that won’t make a whit of difference in severity of adverse consequences, if there is any net adverse effect at all, will only reduce the capacity to respond to events as they happen. The best strategy is to do whatever is needed to grow economies so that there is a greater capacity to deal with unfolding events. Technology has always come to the rescue in the past but that requires investment in R&D which doesn’t have predictable payoffs for investors. It’s a gamble. When times are good, when economies are vibrant, there’s more money available to gamble on R&D. The bottom line then is to do whatever it takes to get that going and that really can’t be done by making energy more expensive. Making the cost of doing business more expensive depresses R&D spending and R&D spending is what is critically needed.

    • “Is adaptation cheaper and more feasible than mitigation?” Andrew Lilico knows, I quoted him in the previous thread. Capacity-building, growth-promoting, policies win hands down.
      http://www.telegraph.co.uk/finance/economics/10644867/We-have-failed-to-prevent-global-warming-so-we-must-adapt-to-it.html

    • Sreven,

      i thought it was pretty straightfoward, and sea-level is good example.

      Yes, the basic physics of thermal expansion is simple and long known, but sea-level rise islo dependent on sheet-ice dynamics where we area bit more in the dark, so while we may come up with a fair guestimate of the cost of adapting to x cm’s sea-level rise by 2100, we have no firm idea if sea-level will be x cm’s in 2100. That is what Smith is saying, therefore there is no rational argument to be had for the merit of adaptation over mitigation.

      And who’ arguing for the primacy of adaptation? – I have the clear impression our host does. Admittedly her tendancy to talk out both sides of her mouth can lead one’s perceptions astray.

    • The physics of the IPCC’s ‘consensus’ is fundamentally wrong in heat generation and heat transfer, a failure to understand the difference between a Radiation Field, a potential energy flux, and real net IR flux at a plane.

      MODTRAN calculates these RFs because it was designed to explain real observations and uses real molecular absorption/emission data in a brute force and ignorance model that works. You get net IR fluxes at a plane by vector summation of the RFs.

      Climate Alchemists took MODTRANs correct, two-stream approximation radiation transfer and imposed imaginary external energy inputs based on the K-T Energy Budget, a Perpetual Motion Machine of the 2nd Kind.

      This plus Hansen’s 3x exaggerated GHE and imaginary thermalisation in the gas phase (Tyndall has been badly misinterpreted) gives 6.85x + extra ‘GHG-absorbed IR surface energy’, offset by near double real cloud albedo in hindcasting. The sign of the indirect aerosol effect, the real AGW, is reversed because Sagan’s aerosol optical physics is wrong.

      So, none of theIPCC Climate Models can predict climate. Paul Hudson reported recently that 13 of the last 14 UKMO annual global climate predictions have a warming tendency: http://www.bbc.co.uk/blogs/paulhudson/posts/Met-Office-global-forecasts-too-warm-in-13-of-last-14-years

      This is because there is actually near zero CO2-AGW, as shown by the cooling over the last decade in HADCRUT4: http://www.woodfortrees.org/plot/hadcrut4gl/from:2004/plot/hadcrut4gl/from:2004/trend

      In reality, the real AGW was from Asian industrialisation aerosols reducing cloud albedo, and that has slowed down. Therefore you must completely forget about the IPCC: its prognostications are baseless, designed to deceive. We are into global cooling from the weak solar magnetic field, shown here: http://www.newclimatemodel.com/update-2014-visual-proof-of-global-cooling/

    • Alec,

      10 years seems a bit short of a time scale to be judginglong term trends don’t you think? You might end up fooling yourself.

      Being a skeptic,you have probably already thought to take a peak at the last 10 years of OHC, just for confirmation, of course.

    • Obviously decarbonizing energy is happening organically, by subsidy and coercion. The question becomes, how much pressure can we apply to our energy sector without damaging the economy. No matter what we do, climate will change and we need to be ready for drought, flood and wind. There also is the particulate factor that C02 monomania ignores. Deaths now are more valuable than guesstimated deaths in future.

      None of these strategies are informed by climate models except by informing policy makers that we can’t model climate sufficient to direct policy yet. It’s hard to admit ones life work is irrelevant.

    • It’s hard to admit ones life work is irrelevant.

      Especially when one so wants to be the “lone” Scientist hero of the Saturday B-Movie saving the planet against all odds.

    • Thanks for that Max. Hansen says both ‘…our climate model simulations for the late 1980’s and the 1990’s indicates a tendency for an increase of heat wave/drought situations in the Southeast and the Midwest United States.’ and also ‘However, the point that i would like to make is that in the late 1980’s and in the 1990’s we notice a clear tendency in our model for greater than average warming in the southeast United States and the midwest.’ That’s claiming regional skill which his model did not have nor still does. None of them do, that’s part of what the ruckus in Great Britain is about.

      He also says ‘It is not possible to blame a specific heatwave/drought on the greenhouse effect’. So I’ve overstated the egregiousness of his claim about causation of the Washington heat wave. Instead, I’ll pull the Joker Tim Wirth out of my sleeve.

      I’d encourage all to read the 1988 testimony by James Hansen. Words to live by, or down; sometimes it’s hard to tell the difference.
      ================

    • This is for Michael: you must realise that what I have worked out is how the real AGW, the increase of solar SW energy thermalised in the oceans, increased OHC when you can’t do that with imaginary ‘back radiation’!

      We had AGW on top f the warming ENSO, and it is now stabilising as the Sun’s magnetic field has fallen and we enter the new LIA.

      The split Polar Vortex and the heat transfer from the N Atlantic into the Arctic is obvious in the data. CO2-AGW is kept near zero by atmospheric processes.

    • Alec,

      Sure, there’s heat transport going on, which is a significant short term signal.

      But global OHC is going up – this is not heat tranport, but heating.

  2. David L. Hagen

    A welcome start to transparency and reality checks.

    As an engineer/scientist I strongly second:

    Smith argued that climate models were not up to the standards in relation to other computational fluid dynamics groups in terms of validation, verification, uncertainty quantification, and transparency, stating ‘Trust can trump uncertainty.’

    Trust HAS trumped “uncertainty” and real evaluation of errors.

    Re: ” showing anomalies versus a real-world quantity (which can hide systematic error that are larger than the observed anomalies); ”
    We already see >95% of >30 year model projections exceeding actual temperature anomalies – indicating massive systematic Type B error. I find such massive error to put climate models into the “1 – dangerously useless” category as severely misdirecting public funds away from critically important needs.

    Documenting these errors of real-world projections vs actual temperatures would be a very welcome wake up call and reality check.
    Has this been done anywhere yet for all 90 models?
    Strongly recommend this for a major post.

    Re: “UNFCCC) seem to be operating in a climate model command-and-control mode.”
    The UNFCCC is the “anti-scientific” body, having redefined “climate change” to mean “anthroprogenic climate change”, and ignoring obvious evidence that measured temperatures are not obeying the models.

    • Smith argued that climate models were not up to the standards in relation to other computational fluid dynamics groups in terms of validation, verification, uncertainty quantification, and transparency, stating ‘Trust can trump uncertainty”

      Climate Science lacks quality standards everywhere one looks, including models. Are the funding agencies interested in quality? I see no evidence.
      Perhaps everyone is afraid at this point to establish objective standards; such practices would reveal how immature and constrained Climate Science has become. Can’t put the toothpaste back into the tube. Only when the whole system crashes will the funding agencies realign their thinking. In the meantime the money keeps rolling in!

    • David L. Hagen

      UNFCCC needs to restore integrity in the Scientific Method to undergird policy. To begin with, restore the scientific grammatical meaning of “climate change” from its illogical equivocation:
      ARTICLE 1: DEFINITIONS

      2. “Climate change” means a change of climate which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods.

      Smith’s presentation is a step in the right direction towards restoring scientific integrity to climate science, such as described by Richard Feynman:

      It’s a kind of scientific integrity, a principle of scientific thought that corresponds to a kind of utter honesty–a kind of leaning over backwards. For example, if you’re doing an experiment, you should report everything that you think might make it invalid–not only what you think is right about it: other causes that could possibly explain your results; and things you thought of that you’ve eliminated by some other experiment, and how they worked–to make sure the other fellow can tell they have been eliminated.
      Details that could throw doubt on your interpretation must be given, if you know them. You must do the best you can–if you know anything at all wrong, or possibly wrong–to explain it. If you make a theory, for example, and advertise it, or put it out, then you must also put down all the facts that disagree with it, as well as those that agree with it. There is also a more subtle problem.
      When you have put a lot of ideas together to make an elaborate theory, you want to make sure, when explaining what it fits, that those things it fits are not just the things that gave you the idea for the theory; but that the finished theory makes something else come out right, in addition.

      In summary, the idea is to try to give all of the information to help others to judge the value of your contribution; not just the information that leads to judgment in one particular direction or another.

      No matter how many $ billion have been spent on them, why should we believe climate models driven by a parameter (CO2) that only demonstrate R^2 of 0.05, compared to a theory that demonstrates R^2 of 0.92 or higher?
      cf QB Lu 2013, Cosmic-Ray-Driven Reaction and Greenhouse Effect of Halogenated Molecules: Culprits for Atmospheric Ozone Depletion and Global Climate Change.
      Not saying QB Lu is right/validated, that his work needs to be addressed and evaluated vs the current CO2 orthodoxy.

    • Re: “dangerously useless” above by David L. Hagen

      I suggest that U.K. experience supports “deadly“. Two U.K. newspaper articles report (variously) a ratio of death by cold to death by heat of 25:1 over ten years, and 24,000 casualties in the current winter (2013-2014). These are mostly pensioners who could not afford heat.

      This might be seen as an advantage by some troll in the dungeons of Whitehall: tax revenue from carbon taxes and reduced outlay for pensioners. (Just kidding, of course.)

    • Ha,

      you toss your own standards out the window when discussing Scaffetta’s “model”.

      get some principles, clown

    • David L. Hagen

      Mosher
      Try reading.
      I linked to QB Lu, not Scafetta.

      Besides, Scafetta’s “phenomenological” model is still far more accurate than 95% of IPCC’s “climate models”.

      Similarly see the semi automatic data mining Global Warming Prediction Project

      Still confirming forecast of Apr 2011 at 73% accuracy. IPCC forecast at 10%.
      What drives Global Warming? (Update 2)
      This model describes a non-linear dynamic system of the atmosphere for short- to medium-term forecasting consisting of 5 drivers: Ozone concentration, aerosol index, radiative cloud fraction, and global mean temperature as endogenous variables and sun activity as exogenous variable of the system. Note that CO2, though provided as input data, has not been selected as relevant climate driver by self-organizing, inductive modeling. This is a CO2-free prediction model. The model was built from observational data from October 1988 till April 2011 of up to 1000 input variables with time lags of up to 120 months, which is a typical input space dimension for complex dynamic systems modeling.

      As of August 2013, the OUT-OF-SAMPLE prediction accuracy of the most likely prediction (solid red line) of the self-organized model is 73%. The accuracy relative to the prediction range (pink area) is 98% (fig. 1).

      In science, accuracy counts, even if you don’t understand why. e.g. Newton’s laws of gravity are phenomenological.

      I would rather a phenomenological or empirical model any day that gives 73% accuracy, then >95% of the intricate billion dollar global warming models that are > 95% (>2 sigma) wrong.

      PS How accurate are your 3 or 14 year predictions?

    • David.

      Still in denial about the lack of transparency by scaffetta?
      No one has been able to replicate his work
      His model gets SST wrong, rainfall wrong, clouds wrong, ENSO wrong,
      Further the thing he predicts isnt even a physical variable.
      Its a joke of a climate model.

      So, when you compare models using the same standards for both
      when you hold all researchers to the same standards– transparency, openness, replication,
      Then you will unclown yourself.

      There is a reason why scaffetta refused to share his code with Mcintyre.
      and you are worse than the worse mann defender.

    • In science, accuracy counts, even if you don’t understand why.
      SAY WHAT?
      In science, accuracy counts, even if you don’t understand why.

      I read this several times. If you don’t understand, what exactly do you know that is accurate.

      Correlation is not causation. Accuracy, when you don’t know why, is not accuracy, that is just dumb chance. What are you thinking? What are you not thinking?

    • David L. Hagen

      popesclimatetheory
      Newton went from observations (data) to equations to physics to understanding. (That included separating out correlation vs causation.)
      His equations for gravity were very accurate even if he did not understand how force operated at a distance.
      See
      Newton’s Scientific Method: Turning Data Into Evidence about Gravity p 342

    • Max_OK, Citizen Scientist

      Re post by Pooh, Dixie Feb. 18, 2014 at 1:21 pm commenting on Cadman, Emily. “UK Sees Steep Increase in Winter Deaths.” Financial Times, November 26, 2013.
      ______

      Pooh, I am skeptical if you are implying less severe winters in the United Kingdom as a result of rising average global temperature will mean lower mortality rates for the elderly. No doubt sudden and unusual extremes in weather, cold or hot, are harmful to older people no matter where they live. However, I suspect it’s changes people aren’t used to dealing with that result in fatalities rather than extreme temperature levels per se. Scandinavian countries similar to the UK in most ways, but with much colder winters, have lower age-standardized death rates. Sweden, for example, has an older population but a lower death rate than the UK. My guess is older people who live in Scandinavia have learned to adapt to extreme cold that would harm Brits.

      Age standardized death rate (per100,000 population) and percentage of population age 65 and older

      United Kingdom 419 17.3%

      Finland 407 19.2%

      Norway 386 16.7%

      Sweden 375 20.5%

      http://gamapserver.who.int/gho/interactive_charts/mbd/as_death_rates/atlas.html

      http://www.indexmundi.com/finland/

    • David L. Hagen

      Mosh
      While I encourage Scafetta to post his code, I do not see that as required under the scientific method. See my comments at The Blackboard on validating CFD.#28592, #28595; to which JohnV replied:

      I agree with your statements about benchmark testing and testing with synthetic data where the real answer is known. Unit testing is a required practice in good software shops.

      It helps for users to be familiar with analyses methods.
      Note Scafetta’s response to your comments

      . . .Here you find the instructions about the MODWT function in “R”:
      http://rss.acs.unt.edu/Rdoc/library/wavelets/html/modwt.html

      Benestad and Schmidt’s major error was to use boundary=”periodic” instead of using boundary = “reflection” in the modwt function which introduced large errors and severely erroneous border trending. . . .

      Scafetta similarly responded to readers at ClimateAudit 2009/08/09.
      Where the author identifies and clarifies users lack of understanding of advanced analysis methods and problems applying, that is a major step towards the issue of replication.
      I recommend you lay aside the slander and document where you see Scafetta’s papers have not been replicated due to Scafetta’s errors rather than users not being familiar with analysis methods.

  3. Fantastic work Judith. Thank you very much.

  4. Antonio (AKA "Un físico")

    Interesting presentation by Smith. But the main criticism to CMIP5 models is not in those relative errors menctioned in his presentation (p.15/46).
    Instead, I identified these 6 key reasons for disabling CMIP5 models from being reliable in a doc sent to JC (hopefully we could discuss about this in a new post in her blog):
    (1) Global surface temperature linear relation with the concentration variation of greenhouse gases is a non-scientifically demonstrated hypothesis. It is an error to oversimplify complexity like this.
    (2) Total aerosol radiative forcing has no reliable model.
    (3) Despite every IPCC report agrees in setting climate sensitivity into a range between 1.5 ºC and 4.5 ºC, climate sensitivity (or that climate feedback) has no scientifically set value range.
    (4) Top of atmosphere change value, related to energy imbalance, is also not scientifically set.
    (5) Abusing of stochastic, perturbed or multi-model methods: do not provide statistical predictability. {*** close to the above Smith’s critic ***}
    (6) Hierarchy of models only mean that models validate models; but this method is not scientific. Models can only be validated by observation (in the appropriate climate change timescale).

    • “climate sensitivity … has no scientifically set value range.”
      Actually, it has. But not meteorology, oceanography or climatology. Try marketing science or social science.
      The new IPCC range of 1.5 ºC to 4.5 ºC has a low end supporting some claim of responsiveness to observation, and a high end supporting fear mongering.

    • Stating that climate sensitivity falls into a range between 1.5 ºC and 4.5 ºC is pretty meaningless since that range includes both a rate of warming which is of little concern and ranges to a rate of change of great concern.

  5. Can (we) climate modelers stop digging?

    … and stop suing skeptics and stop flinging whatever unfounded supposition after another against the wall of reason — to see what sticks for a while — before slithering on to the next wet dream.

  6. Smith says of model usefulness
    ” ◾Seasonal: Yes, in some months and regions
    ◾Decadal: Not much (global and regional)”
    I note he doesn’t think centennial forecasts even worth discussing.
    In fact the Met Office gave up making even seasonal forecasts a couple of years ago after a series of hopelessly wrong predictions. In spite of their failures the modelers response to the divergence of their forecasts from reality is always to ask. for more money for faster computers as the Met Office did when they acknowledged their decadal forecasts were unreliable a couple of years ago. The IPCC – Met Office models are simply useless for forecasting purposes because they are incorrectly structured by using the input assumption that CO2 is the main driver. Naturally that conclusion is what comes out the other end. A classic case of GIGO . Furthermore models with such a large number of variables are inherently incomputable because they cannot be initialized with sufficient precision or with the necessary data grid mesh size in time or space. The establishment scientists in the USA and at the UK Met office remain incapable of admitting the total failure of the climate models in the face of the empirical data of the last 15 years. It is time for the climate community to move to another approach based on pattern recognition in the temperature and driver data and also on the recognition of the different frequencies of different regional weather patterns on a cooling ( more meridional jet stream ) and warming (more latitudinal jet stream ) world.
    For forecasts of the coming cooling based on the 60 year (PDO) and the 1000 year quasi-periodicities seen in the temperature data and the neutron count as a proxy for solar activity in general see several posts at
    http://climatesense-norpag.blogspot.com
    For a review of a 3 year update of a 30 year forecast see
    http://climatesense-norpag.blogspot.com/2013/07/skillful-so-far-thirty-y
    For an estimate of future NH temperature trends see the latest post at
    http://climatesense-norpag.blogspot.com
    See also @norpag

    • I note he doesn’t think centennial forecasts even worth discussing.

      Thats because you dont need a GCM to do centennial forecasts.

    • Mosher

      Are you suggesting that there have not been “peer reviewed” papers summerizing the potential harms to hamanity of a warmer world based on the outputs of GCM’s???

    • David L. Hagen

      Inaccurate seasonal forecasts
      The Official Forecast of the U.S. Government Never Saw This Winter Coming

      Last fall the Climate Prediction Center of the National Oceanic and Atmospheric Administration predicted that temperatures would be above normal from November through January across much of the Lower 48 states. This graphic shows just how wrong the official forecast of the U.S. government was:

      The big red blotch in the top map represents parts of the country in which the Climate Prediction Center forecast above-average temperatures. The frigid-looking blue blotch in the bottom “verification” map shows areas where temperatures turned out to be below average

  7.  
    Very reasonable–e.g., recognizing the problems of, “systematic error that are larger than the observed anomalies… [and] burying the bad news about model performance,” Smith sees, “the demonstrated value of eather/climate forecasts,” as follows: (1) “significant” in the “medium-range” of about two weeks or less; (2) seasonally for, “some months and regions;” and (3), for either global or regional purposes, not much value at all when looking decades into the future.

  8. If the question is what information should be used regarding the climate for the potential construction of infrastructure, it seems that a combination of historical data and climate model outputs should be considered. If the historical data shows for example that “x” amount of rainfall is expected on an annual basis, but the climate models predict a significantly lower amount then it may make sense to take into account the risk of the lower levels of rainfall. If water retention facilities are being constructed it may be a relatively low cost to make a change during the initial construction. Use all the data available and then make choices based on the funding available.

  9. Wow. When David Hughes and I started talking about IV&V back in 2007 folks thought we were denialists.

    Some of the discussions at Climate Audit may be worthwhile revisiting.

  10. From what I’ve read about GCM’s ability to forecast regional climate, they can’t. It’s only when you average the poorly forecasted regional climates into a global forecast that the major errors cancel out, making them look much more accurate then they really are.
    GISS ICP Evaluation of the GISS GCM ModelE
    GISS ICP Validation of the GISS GCM A Study of Ocean and Climate Modeling

    They all fail because of one construction bias, “Co2 is the control knob”. They will not ever make the leap to the next level, until they remove this error.

    • Mi Cro,
      You write:
      They say:
      CO2 is the control knob. A man-made fraction of trace gas is controlling the temperature of earth.

      You are right, they will never get anything right until the forget this fraction of a trace of a control and look for something MASSIVE to regulate earth temperature in very narrow bounds.

      The IR does most of the cooling for earth, but it has much wider bounds. In has no set point and no means for regulation in the range temperature has been inside for ten thousand years.

      Only Ice and Water, Only the temperature that Polar Sea Ice Melts and Freezes, provides a set point that can turn on massive snowfall when the oceans are thawed and turn off massive snowfalls when oceans are frozen.

      Earth uses snowfall and the resulting albedo to fine tune temperature in the very tight bounds of the most recent ten thousand years.

    • Herman, I think you have part of the regulator well defined, I think you also have to include water’s hot side at the equator, evaporation, rain and clouds. Together with ice, and snow define a key regulation system at our current temperature range.
      I have wondered though about an ice ball earth, where all of the water is frozen out, wouldn’t maybe once we get in the working temperature range of Co2 (-108.4F melting point, -70.6F boiling point), it do the same thing regulating the temp of ice ball earth, at least until enough Co2 builds up, that a bit of warming gets temps at the equator above 32F to kick off the water cycle.

    • CO2 is the control knob.

      You’ll realize too late but there will be no escaping it.

  11. The historic and paleo records are less uncertain sources than the best models to develop adaptation priorities.

  12. I love the irony that Prof. Smith – he of the devastating critique – has a mailing address in Houghton Street, London. Presumably not named after Sir John Houghton, early protagonist of religious based climate scaremongering.

    And that his institution is the LSE – home of the Grantham Institute. Perhaps he will be getting a personal visit from the GI’s climate attack dog, well known geologist RET (Bob) Ward. If so, I’d predict a win for Smith.

  13. The global warming religion is a modern doomsday story about mass superstition that, contains a grain of truth and a mountain of nonsense.

  14. Visiting Physicist

    Judith Curry writes ..

    “all agreed that global climate models were potentially very valuable and could be made more useful for adaption decision making, but that this potential was not yet realized.”

    Well I suppose all would agree if they have a pecuniary interest in maintaining the status quo and continuing to develop and use models that are based on the completely false physics that radiation from a colder atmosphere can actually help the Sun in raising the temperature of Earth’s surface. It cannot do so. Physicists will tell you (if you even bother to ask a specialist in thermodynamics like myself) that such radiation undergoes what they call “pseudo scattering” in which it is immediately re-emitted in a resonating process, without any of its electro-magnetic energy being converted to thermal energy. This provides some of the electro-magnetic energy in the SB calculation for the warmer surface, and thus slows radiative cooling, but it can have no effect on molecules colliding at the interface and transferring thermal energy by conduction and evaporative cooling.

    But none of this is what really determines planetary surface temperatures anyway. The base of the Uranus nominal troposphere is hotter than Earth, and yet it receives no direct solar radiation worth mentioning.

    Valid physics can be used to confirm beyond a shadow of a doubt that a gravitationally-induced temperature gradient will always evolve spontaneously in a vertical plane in any solid, liquid or gas that is exposed to a gravitational field. This happens at the molecular level where molecules swap kinetic energy and gravitational potential energy when in free flight between collisions. No one has correctly rebutted this, and wires outside cylinders also develop thermal gradients so no perpetual motion can occur.

    There is a predetermined thermal profile in Earth’s atmosphere caused by gravity which, without water vapour or greenhouse gases, would intersect the surface in the vicinity of 25C, but then water vapour reduces the gradient (due to inter-molecular radiation, not the release of latent heat) and we end up with a mean of about 15C.

    It is natural cycles, probably regulated by planetary orbits, which are the primary determinants of climate. That’s why it’s not carbon dioxide after all.

    • It is natural cycles, probably regulated by planetary orbits, which are the primary determinants of climate.

      NO!

      When oceans are warm, polar sea ice melts and it snows more.
      When oceans are cold, polar sea ice is frozen and it snows less.

      Earth Temperature and Earth Albedo are always in inverse Phase.

      Consensus Theory says something makes earth warm or cold and that causes ice to advance and retreat.

      Correct Theory says ice advances and cools earth.
      Correct Theory says ice retreats and earth warms.
      Earth Temperature and Earth Albedo are always in inverse Phase. Something that is always in phase is a much better choice than anything that is “sometimes” in phase.

    • Visiting Physicist

      PopesClimateTheory

      We are not necessarily in disagreement on this. Planetary magnetic fields could be causing cycles in cosmic ray emissions which in turn could be affecting cloud formation and thence albedo and ice formation. Note also that ice in the Arctic melts faster when currents beneath it flow faster. There are many things we don’t understand about how and why there appear to be natural climate cycles. I can detect ~1,000 year and ~60 year natural cycles (as can many others) and planetary orbits do at least present a possible reason as to why the cycles are fairly regular.

      But my main point is that there is a very clear and cogent argument based on valid physics that gravity forms and maintains a thermal gradient and, consequently, we can deduce that carbon dioxide actually cools by a minuscule amount, and certainly does not warm.

  15. The 20 or so models that the IPCC supports are but shadows on the wall of credibility. That is because they have no substance outside the IPCC: I have never seen an analysis of any one of those models and as far as I am aware, none has been subject to the of detailed examination, even by physicists capable of understanding the methodology.

    Having 20 different models is only useful if their diversity is sufficient to encompass one good one. The world’s physicists are not privy to such detail, so we don’t know. Yet the US secretary of state is willing to lay the reputation of his country on the line to support the IPCC!

    About 14 years ago I parted company with the Oxford climatologists when I discovered that their “grid” computing scheme included no attempt to explain the Nino phenomena. That was because I knew that Nino had a greater affect on climate in Australia than any other variable. It seems that Oxford has not advanced much since then.

    However I do remain resolute that if the predictability of regional climate is ever solved it will be by mathematical moodelling.

  16. Since we do not know what adaptations will be required, we cannot say whether they will be harder or easier—more expensive or less—than emissions control.”

    We do know one thing for sure. Emissions control will not work. It cannot work. Are we going to declare war on China and India and after winning the war, put in enough windmills for them that they don’t need to burn coal? I don’t think so.
    CO2 Emissions control is impossible for the whole Earth.
    CO2 Emissions control is impossible for the whole world.

    Emissions control for bad stuff is good.
    Emissions control for good stuff is bad.
    CO2 is good stuff that makes green stuff grow better with less water. More is much better!

    • “Do these people read their own stuff…?”

      It’s evident they just make it up as they go along. They really do. Just spew a bunch of self-contradictory crap and no one that matters….that is no one of the Progressive Warmist Kool-Aid drinkers….so much as raises an eyebrow. They all just nod sagely and congratulate each other on how enlightened they are, and how wonderfully good.

      Someone wrote something about being mystified about what goes on inside Slinging Slingo’s head. I’d say not much. At a certain point they all just realized that no matter what they said….and no matter how wrong they were WRT to predictions, they could not lose control of the message. Must be a heady feeling…the sense that one is in effect, infallible.

    • Sorry, wrong place. Lost the thread. Literally.

  17. “This led Brian Hoskins to speak up in defense of climate models…”

    If anything epitomises the axiom “garbage in, garbage out” it is climate models.

    So no surprise that an appartachik like Hoskins defends them.

    • I liked Slingin’ Slingo’s ‘Now that we have credible models’, or words to that effect.
      ===========

    • Oops, that was the Met Office not Slingo. My bad. But really, how can you tell what either of them are saying, so bound up is the matter in mutual contradiction?
      ==================

    • The Bish is of the opinion that the climatologists are hanging Julia Slingo out to dry. I wish I could be that optimistic.
      ==============

    • @kim

      The Bish has shown an increasing tendency towards becoming unduly excited … pity, that

    • “The Bish is of the opinion that the climatologists are hanging Julia Slingo out to dry. I wish I could be that optimistic.”
      ==============

      I don’t see anyone hanging anybody in that group. One goes down, especially their fearless leader, they all do. Then again, those Brits can be hard to read with their upper lips not moving much.

    • Lest we forget the admission that previous climate models were incredible.
      ===========

    • And the wishful thinking that current models are credible.

      Do these people read their own stuff? Or understand what they are saying?
      ================

    • Hoskins comments “that normally he finds himself criticizing climate models” interests me.

      Does anyone have any detailed specific examples they could link to?

  18. All of the above arguments appear to rest on three assumptions:
    1. That future climate is fundamentally predictable on every time scale by means of numerical approximations to ordinary differential equations,
    2. That observed recent increases in atmospheric CO2 concentrations are entirely man made and
    3. That these observed increases must inevitably affect climate.

    The argument then boils down to how to improve the accuracy of these predictions and to what extent we can ameliorate “bad” climate outcomes by curtailing industrial production of CO2. These asumptions are seldom questioned.

    In my view:
    1. Climate is primarily a stochastic process at time scales greater than a month or so and cannot be predicted in other than general terms.
    2. Human production of CO2 of 5.4 Gigatonne per annum is negligably small when compared with the 38,000 Gigatonnes which reside in the ocean-atmosphere system (IPCC TAR figures). Observed variations of atmospheric CO2 concentration are largely due to secular variations in ocean circulation and changing patterns of upwelling and downwelling of deep nutrients and dissolved CO2. One ocean current alone, the Equatorial Counter Current, (which is rich in CO2 and poor in nutrients) contributes 3.0 Gigatonnes of CO2 per annum to the atmosphere.
    3. There is no observational evidence that increases in atmospheric CO2 have any measurable affect on global climate. Any such affect is “lost in the noise” of a very noisy system.

    A stochastic theory of climate was first proposed by Hasselmann in 1976 but was swept under the carpet when OAGCMs came into vogue. Spectral analysis of ice age time series strongly supports the stochastic theory, see:http://www.blackjay.net/papers/bounded-random-walk/index.html.

  19. As a farmer and glider pilot of some 50 years duration and because of the obvious advantages to both my profession and my sport in the predicted and forecast immediate seasonal conditions I got interested in the output and predictions of climate models generally and regional seasonal climate model predictions in the mid 1990’s.

    With good seasonal forecasts we can vary our inputs such as fertilizer levels, seeding rates, even types of crops to match both the seasonal rainfall and temperature predictions with a theoretical considerable financial lifting of the season’s end bottom line.
    There are are seven main grain and oil seed crops types and about another ten minor crop types we can grow here depending on the seasonal conditions.
    As well I tried for some years into the early 2000’s to base some of my farming and even my seasonal soaring predictions on those regional / seasonal model outputs.

    It turned out to be a harsh financial and trust destroying lesson in the utter futility of trying to use those regional models in any sort of useful way in agriculture at least.
    The modeled seasonal predictions were usually so far off the eventual outcomes in the weather and season outcomes as to be beyond totally useless and if followed closely, could and were quite costly to the end of season bottom line.
    All of which shifted me from a very science trusting and believing lay person to a confirmed skeptic and cynic of the claims of what I now think of as a quite grossly oversold, reeking of incompetency and hubris and quite apparently corrupted climate science in the way it is promoted and the claims of accuracy that climate science has never attained nor has ever demonstrated in any manner for the three decades that work on climate models at every level has been going on, that it is ever likely to attain.

    Most other science I still am very respectful of even though from a former position of deep trust in all of science I now know that science is inhabited by the same ratios as the rest of society of really good dedicated highly competent and even brilliant people, of mediocrity, of incompetence and has just as much straight out fraud and thuggery as can be found in any other profession.
    So I ask the question; How much difference or in my view how much better off would the world at large have been today if the climate models had never existed?

    I ask this because based on my personal experience with seasonal model predictions and after following the climate argument for more than a decade I now see that the developed economies such as those of nearly all of western Europe that have placed all their trust in the climate modeled predictions of an oncoming climate catastrophe from the [ non eventuating ] catastrophic CO2 warming of the planet now have by far the greatest economic problems.
    With their multiple increases in energy prices they are now increasingly contemplating with great angst, the de-industrialisation of Europe which from being one of the main power houses until a couple of decades ago of global production and prior to the climate modeled predictions of a catastrophic future global climate were looking at maintaining their very prominent place in the world productivity stakes and in world affairs .

    America was going down the same path of following and countering the catastrophic predictions of the climate models until early in the 2000’s when America’s governmental structure of a whole raft of competitive semi-independent states, very similar in fact to the collection of small highly competitive European principalities of the 17th,18th and 19th centuries which did so much to advance European civilisation, laws and technology through their competitiveness with neighbouring states and like those past European states, the semi-independent American states started to go their own ways in the effort to try and out compete their neighbours.
    In many cases this meant that the predictions of climate catastrophes of the climate models were only given lip service by some states who then got on with fracking and with job creation and etc.
    And so America because of it’s political structure has suffered far less in it’s economy and as a nation by not closely following the predictions of the climate models down to the last dot and T as has western Europe with it’s increasingly EU bureaucratically controlled totalitarian trending EU political structure.

    And that applies even more so to the likes of China, India, the sleeping but awakening giant in SE Asia, Indonesia and numerous other rapidly developing countries around the world who paid no more than lip service to taking action based on the dire predictions of the climate models whether global or regional and / or seasonal.

    So to repeat the question; Just how much in the way of economic destruction of wealth and resources, how much totally unnecessary human suffering and how big a contribution to the destruction of social cohesiveness in so many nations has the climate modeling industry cost the world with it’s false, misleading and ultimately highly destructive and totally wrong predictions of future climate trends at every level?.

    • This ‘Extraordinary Popular Delusion and Madness of the Crowd’ called CAGW has, in fact, been a weapon of mass economic destruction. Our grandchildren will suffer from our folly.
      ========================

    • I believe the “Extraordinary Popular Delusion…” model is perfectly apt for the global warming madness. It’s been a while since I’ve read it…maybe 20 years….but as I recall it focused only on various financial bubbles. Not sure of that. In an case, surely events like the Salem Witch Trials belong on the list. My guess is this era will be looked back on with the same awe and disbelief with which we now think of the days when supposedly perfectly sane people hung a bunch of innocents for practicing ‘witchcraft.

      I don’t see this ending well. I see increasing intolerance, a push toward marginalization and censorship, and an increasing impulse toward authoritarianism. This will likely be exacerbated when the world wide debt bubble explodes once and for all. Look for all hell to break loose.

      We are, for all our IPADS and iPhones quite a primitive civilization still. In the last few years we’ve made remarkable fools of ourselves over and over again. The dot.com bubble, the real estate bubble, and now the Great Global Warming Delusion.

      I have a theory, but no warmists ever want to answer me when I ask, that the same credulous people who bought the reassurances of those with obvious vested interests, that the housing market could never go down now tend to be warmists. I’d be willing to bet that more of today’s warmists fell for that nonsense than those of us who identify as skeptics. No way to prove it though.

    • ROM,

      Maybe we could seek solace by thinking it could have been worse. Modern Western society seems preoccupied with seeking ever more interesting ways to cast us all into abject poverty.

      We live in interesting times. There is an old Chinese curse which may be applicable here. Could those inscrutable Orientals have a point?

      Live well and prosper,

      Mike Flynn.

    • Max_OK, Citizen Scientist

      pokerguy (aka al neipris) said in his post on February 18, 2014 at 7:41 pm

      I have a theory, but no warmists ever want to answer me when I ask, that the same credulous people who bought the reassurances of those with obvious vested interests, that the housing market could never go down now tend to be warmists.
      _______

      Pokerguy, I have a theory too. Mine theory is you are full of it.

      But back to your theory. I can only speak for myself but I knew a real estate bubble was developing when I saw home prices were getting out of line with incomes. What I didn’t know was how long the bubble would grow before it burst. As an investor, “how long” is what you need to know, but that’s hard to know.

    • Jim 2
      I guess as an Australian grain farmer in direct competition with American corn and grain farmers on the global markets I don’t really have much sympathy for those who jumped aboard the government mandated corn to ethanol express in the belief it would never stop until they were ready to get off.
      The American farming industry, with their very significant subsidy system the Europeans are far worse, and it’s Trillion dollar subsidy program over the next ten years which has been just passed in the US Congress has always been a major problem and a real thorn in the flesh for the almost completely unsubsidised Australian grain producers.
      We have to match the American prices for grain on the world markets despite the Americans getting the farm subsidies in addition to their normal globally priced income from the grain they sell.
      Those subsidised prices allow the Americans and the Europeans to sell grain on world markets quite a lot cheaper that if they had no subsidies, and still make a tidy profit and living. All the subsidies do is to crucify those Australian and NZer’s farmers and others whose economies are too small to afford to subside their farming industries but who are nearly all allies of the USA..
      Not a good national policy if you want to keep your friends.

      For American farmers from my lifetimes observations, all the subsidies ultimately do is push up the price of land and farm inputs,. The farmers rarely live any better than those elsewhere with no subsidies.

      When it comes to farm insurance premium subsidies running at around an annual US $14 billion, it just makes the average Australian farmer’s eyes water and boggle at the tax payer largesse being handed out.
      If as for just this one item, we want to insure our crops which unlike the Americans, we cant insure for yield, only for fire or hail damage or loss , then it is up to the individual farmer to cough up himself.
      Nobody else is expected to have to also fork out.

      On Yield we take what we get without any subsidy for what we produce under our almost totally dry land growing conditions, no underground water for irrigation to even think about in our main Ag grain belt, and thats on a lot poorer soils and under a lot harsher and drier and hotter growing conditions compared to the American Ag industry.

      I’ve been across a lot of the American grain belt [ and the old USSR ] and my son has driven combines over there for a couple of seasons as has my nephew now resident in South Dakota plus any number of other young and old farming aussies who have traipsed across the USA so here in Australia we have a fairly good picture of the American grain industry.

      The only real subsidies which Australian farmers get is a very ad hoc drought assistance when drought conditions get to the stage after about 3 years of low rainfall that farmers are about to walk away from their farms, a situation now occurring in central Queensland’s grazing areas where “drought assistance” in the form of very low interest loans, not handouts, is being put in place in the last few days by the Abbot led Federal Government.

      On ethanol, yes we know the American farmers jumped into that boots and all and who could blame them with the government throwing vast amounts of lucrative incentives and filthy lucre into the path of anything that smelt of ethanol.
      But like all government programs that hand out money by the truckloads without much checking on who gets what and how much there comes a day of reckoning where a change of faces in the political and / or bureaucracy brings a sudden end to those hand outs and then the bitching and moaning and “we’ll all be rooned” begins with the volume set to very high.

      [ The old time classic Australian farming lament which is pretty universal in farming circles in every nation ; Hope you can understand the ironic Australian humour which is quite different to the american sense of humour.
      http://www.middlemiss.org/lit/authors/obrienj/poetry/hanrahan.html ]

      When you have a government mandating that everybody will use so much of a specific product in a particular way and governments handing out immense sums to support that mandated program they inflicted onto the populace without any real examination of the effectiveness of their mandated requirements or it’s impact on those forced to use it ie ; ethanol ,and those who will produce it, you get an almighty mess and very expensive and generally a fairly sordid situation where, once the government comes to it’s senses and tries to sort it out or instigate some cutbacks they suddenly find they have a great number of squealing pigs lining up at the trough demanding that the generosity of their swill be continued or they will all perish from a deprived profitability .

      Anybody who followed the climate argument and watched for those straws in the wind which would start to show that the whole scam was starting to wind down would be prepared for the day when the subsidy on ethanol would be at best reduced and at worst removed entirely as the money ran out.
      But like most people and farmers are no different, it’s a case of grab what you can today and hope like hell that tomorrow will be just as lucrative.

      If all you have known is government handouts in large lumps as per the case with American and European farmers, it becomes very hard to imagine life without those handouts.
      If you have never really had any handouts and have been left on your own to make your own decisions and your own mistakes and your own profits from what you actually produce and are allowed to make your own bed without the government telling you every second day when you can wipe your arse because they are paying you, one just smiles and says of the other, it serves you bloody right for trusting the government and even worse if you thought that the government would always rush to your rescue every time you start squealing.

      So cop it sweet mate and get on with it and find your own way just like the rest of us have to do in the cold hard real agricultural world outside of massively subsidised American and European and Japanese agriculture.

      And strangely you will find that life is perhaps a bit harder but the good guys and good operators will still be there in spades when the dust finally settles on the new [ ethanol subsidy free ] regime.

  20. In the nuclear industry we use a model of a high order coupled non-linear system to determine the post large break loss of coolant accident (LBLOCA) peak fuel cladding temperature (PCT) required by 10 CFR 50.46. The methodology is proprietary to Westinghouse but a description of the methodology is publicly available here:

    http://www.westinghousenuclear.com/Products_&_Services/docs/loca_presentation.pdf

    This method uses a non-parametric statistical model to determine the 95/95 PCT. And the system as modeled is not spatially chaotic because only the maximum temperature anywhere is needed.

    My point is that this method requires multiple model runs based on the Wilks formula to ensure the 95/95 criteria is met. No one would ever suggest that any particular model run was the best estimate of what actual PCT would be, and certainly no one would average all of the outputs and claim that this value was a valid estimate of the most likely PCT. This seems to be one of the fatal mistakes climate science makes. If we could accurately model the climate as it really exists each model run might be a valid possibility as an outcome. Then we would need to perform many many runs to establish the 95/95 criteria and we would be left with many many possible outcomes each equally valid. That is all we could say…..is that each model run is an equally valid possible outcome. Of course this would be useless as a policy tool.

  21. The comments in this topic sound like at least some people are getting honest about the climate models. That is an encouraging sign.

  22. Dr. Strangelove

    Judith

    The observed temperature trends from 1950-2013 are best described by the random walk function. See my posts (Feb. 16 at 9:54 pm; Feb. 18 at 3:00 am)
    http://judithcurry.com/2014/02/15/week-in-review-13/#comment-459404

    The climate models cannot accurately describe temperature trends because the models are deterministic. But the behavior of global temperature resembles random variables. My random walk function is proof of this. Another proof is the temperature data approximately follow the normal distribution. This is a well-known probability distribution of random variables.

    Here is a comparison of the frequency distribution of global temperature data (1950-2013) vs. the normal distribution:

    Data Normal
    2s 0% 2.3%

    Note that the data curve is skewed to the left (cooling tendency) and there are no statistically significant deviations (beyond 2 sigma) despite the fact the theoretical probabilities (normal curve) predict two such deviations due to chance alone given the population size.

    However, there is a relevant deviation from the normal curve in the 1-2 sigma range that indicates warming. Is the deviation statistically significant? To answer this, I ran a Monte Carlo simulation using the normal distribution. It only took me 3 runs to replicate the said deviation. LOL The answer is no, it’s trivial. Random variables with the normal probability distribution can easily reproduce the ‘unusual’ deviation. There is nothing in the temperature data that cannot be explained by chance. The null hypothesis stands.

  23. Dr. Strangelove

    Here are the data:

    Range Data Normal
    2s 0% 2.3%

  24. Dr. Strangelove

    Something wrong. The data getting cut. Here again

    Range; Data; Normal
    less than -2s; 0%; 2.3%
    minus 2s; 14.1%; 13.6%
    minus 1s; 42.2%; 34.1%
    1s; 20.3%; 34.1%
    2s; 23.4%; 13.6%
    greater than 2s; 0%; 2.3%

    • DS, no matter how many times you do it, it will be wrong.

      There is likely some component of the global temperature trend that resembles a random walk, but the overall rise is deterministic.

      Volcanic eruptions are the most like a random Poisson process.

    • Dr. Strangelove

      “There is likely some component of the global temperature trend that resembles a random walk, but the overall rise is deterministic.”

      You misunderstood. The overall rise is a product of the random walk. The regression line in any time scale is derived from the random walk graph. The random walk imitates the raw data from observations. Any statistical analyses and conclusions you apply to the raw data are also true for the random walk generated data.

    • Temperature can’t be a random walk because the distance from the starting point grows without limit with time. (As the square root of the number of steps when they are of equal size.) If temperature has drifted about 1 degK in a century by a purely random walk process, how far would it have likely drifted in the last 100 million years? 1000 times as far?

      A random walk is a statistical model that doesn’t make physical sense for a planet that has seen only modest changes changes in mean global temperature (<10 degC) over the last 100 million years.

  25. In the end, it is the data. The models are challenged to reproduce things like this.
    http://www.woodfortrees.org/plot/hadcrut4gl/from:1950/mean:12/plot/gistemp/from:1950/mean:12/plot/esrl-co2/from:1950/mean:1/scale:0.01/offset:-3.3
    It shows that global temperatures and CO2 have been ascending pretty well in step for 60 years. The first test of models is to do this. A nonsensitive model will have trouble with reproducing such behavior, and its credibility is measured, not only by closeness of fit of global temperatures, but also regional variations, like polar and land amplification, and the longer trend since the pre-industrial levels of CO2.

  26. Though it’s unlikely, what would government policy be to deal with conditions if they became similar the Little Ice Age?

    Say we had another year without a summer, and glacier started destroying
    alpine towns in Europe?

    It seems what governments are doing by increasing their debt isn’t a very good plan.
    It seems government constantly preaching disaster- when there is not one-
    and able to increases debt are not going to be able solve any kind serious problem by massive tax increases during a real crisis requiring government action. Instead people going to die, and they are rightly blame the government for making every worst then without lousy governing.

    If you want millions of people to die and want to overthrow governments, it’s a good plan- otherwise not so good.

  27. It’s highly unlikely that we will emerge out of our current Ice Box climate
    within 1000 years. Because the description or definition of Ice Box climate is having permanent polar ice caps and very cold average temperature of the world’s ocean. And there no rational reasons to expect our Oceans which have average temperature of about 3 C to warm as much as oceans were thought to have warmed at warmest time of the last interglacial period- called: Eemian. Wiki: “The warmest peak of the Eemian was around 125,000 years ago, when forests reached as far north as North Cape, Norway (which is now tundra) well above the Arctic Circle at 71°10′21″N 25°47′40″E. Hardwood trees such as hazel and oak grew as far north as Oulu, Finland.”
    http://en.wikipedia.org/wiki/Eemian
    And in which sea levels were 4 to 6 meter higher than current levels- and much of higher sea level was due to a warmer ocean.

    It’s also quite unlikely we return to glacial period [ice age] anytime soon- and normally it requires thousands of years to side back into a period in which call the glacial part of interglacial and glacial cycles which have been occur for millions of years. Exiting from our current Ice Box climate would require us no return returning to the glacial period within tens of thousands of year with the result of melting of all ice caps and the warming of the ocean. To think this is possible within a century or two isn’t just delusional
    but more relevant it’s utter ignorance of science in general.

    Whereas possibility of enter another “little ice age” is possible- it’s reasonable to assume we have entirely left the Little Ice Age, 1850 is said to be the end of Little Ice Age. And there is no doubt there was dramatic shift that justifies saying 1850 was clear shift towards warming, but in future
    looking back at 20th and 21st, it could seem significant warming period
    within the Little Ice Age. Or appearing as almost leaving the Little ice Age, and explainable return to Little Ice Age could explained by long quiet period of the Sun and global volcanic activity returning to levels which occurring during the Little Ice Age. Or the warming last century or so could explained as due to lower volcanic activity and a more active solar period.

    But main point is no one can accurate predict global temperature or climate even within a mere decade into the future, and thinking you know what climate will be in next century is folly. This inability is due to our lack understanding our climate which has displayed by none of IPCC climate models projection as being accurate,

    But it seems most likely we continue the general trend of last century
    which has been a gradual warming with up and downs trends in temperature. And I would say their good chance having similar dip in next couple decades. So such a dip will not be a return to Little Ice Age.
    And I guess that within 50 years, we can much more certain we have entirely left the Little Ice Age.

  28. Berényi Péter

    ’How do we ease user pushback when the current oversell becomes clear?’

    No way.

    We can provide seamless forecasts, expose hemlines due to our limited understanding, and support real user needs with more credible computation. Aiming for true transparency and engagement.

    Flawed frame, sounds like marketing. In science no computation needs to be “credible” ever, just correct.

    Being infatuated with user expectations is an abominable trait in science. Once investigation is not driven by genuine curiosity, all is lost.

    For example, “average global surface temperature” is not even a scientific concept. It may be something, conceivably a marketing buzzword, that “users” are made to be concerned about, but otherwise it simply makes no sense. Local temperature is an intensive property, and sum of intensive quantities is meaningless, while average is the sum divided by number of samples. An inane number divided by anything is of course vacuous itself.

    A proper scientific question would be something like ‘Why true average reflectances of the two hemispheres are similar in spite of an enormous difference in their clear sky albedoes?Users are never concerned about such arcane issues, but scientists should, as no current computational climate model reproduces this property, which is enough to falsify them all.

    With no physical understanding of irreproducible quasi stationary non equilibrium thermodynamic systems at all on the general level, it would be most curious indeed, if a single instance of this wide class, terrestrial climate could be understood to the extent the “science” should be declared “settled”, skeptics labelled “deniers” and any attempt to uncover these flaws stigmatized as “anti science”.

    The thing is a reductionist modelling approach is probably doomed to failure from the beginning, since there is this tiny little closure problem in fluid flow modelling. Reynolds averaged Navier-Stokes equations lend unphysical solutions if the parameter regime needed for closure is not completely covered by experimental data, a goal clearly unattainable in climate studies.

    A wave of valid criticism of the presentations and interpretation of models may well come from physics, statistics and even [whatever]

    Yep, as soon as a field starts to slide down on the slippery slope to become a full fledged pseudoscience, one stops asking experts of that field about the validity of methods applied there and turns to those educated in neighboring disciplines. This is how we know astrology or homeopathy are crap, in spite of considerable user demand for them.

  29. “… whereby the predictions of short-term high-resolution simulations are used to improve the longer-range low resolution climate model simulations.”

    That’s part of the problem right there – using the wrong terms. From a politician, I could understand, but from users in the field, it’s bafflingly inexcusable.
    Climate models are MODELS, NOT SIMULATIONS.

    • Hmm.
      I’ve actually read GCM code.
      I’ve actually written Simulation code.
      GCMs are simulations.

      A simulation requires that you first build a model of the physical process.
      For example, to simulation the flight of an aircraft you first choose a model

      A) a point mass model
      B) a 3Dof model
      C) a 6Dof model

      The model can be simple to complex. Some might include other models that is you might choose to model sub components
      examples, the radar, the missles, the guns, the gear, the engine, the flight controls, the pilots decision process, etc

      A simulation involves stepping through the model in time. you can start on the ground, in mid flight, at approach. A simulation is nothing more than a model operating over time.

      GCMs model the planet. Like all models subcomponents are modelled at various levels of fidelity. Like all models they do not replicate reality exactly.
      The model is executed over time. It is a simulation.

    • Heh, this sounds a bit like the measure/estimate argument, less about the words, and more about the words about the words.
      ==============

    • GCMs model the planet. Like all models subcomponents are modelled at various levels of fidelity. Like all models they do not replicate reality exactly.The model is executed over time. It is a simulation.

      The model is an anthropic algorithmic abbreviation (reduction)of the natural algorithm (reality) hence the simulations are solely an experiment on the program generating it ,and not an experiment on the reality.

      As in reality the solutions are insolvable ie they are infinite(Diophantine), so we have an oxymoronic set of simulators providing simulations for insolvable equations.

    • Hmmm, recursively enumerable. I like that.
      ==========================

    • “GCMs model the planet. Like all models subcomponents are modelled at various levels of fidelity.”

      They model it at a 360 * 180 resolution mostly. The picture of an average aircraft if thus modelled/displayed does leave a little to be desired. I’m not sure I would want to fly in it!

    • “The model is an anthropic algorithmic abbreviation (reduction)of the natural algorithm (reality) hence the simulations are solely an experiment on the program generating it ,and not an experiment on the reality.”

      1. All models are anthropic algorithmic reductions, Unless you know a martian that does one.
      2. Nobody claimed that simulations were experiments on reality. The primary motivation of simulation is that experiments are too big too expensive or too dangerous. We simulate the effects of bullets hitting planes ( Covart and shotline) because actually shooting at them is HUGELY expensive.. although once we did shoot up a couple F/A-18As. talk about a waste.

      ####################

      As in reality the solutions are insolvable ie they are infinite(Diophantine), so we have an oxymoronic set of simulators providing simulations for insolvable equations.

      we successfully simulate insolvable equations all the time.

    • “They model it at a 360 * 180 resolution mostly. The picture of an average aircraft if thus modelled/displayed does leave a little to be desired. I’m not sure I would want to fly in it!”

      #####################

      you probably have flown in it,

      The point was the OP has no idea whatthe difference between a model and a simulation is

    • “The point was the OP has no idea whatthe difference between a model and a simulation is”

      I did rather get that. My point was that the model graduation was frightening coarse.

    • ‘An oxymoronic set of simulators,’ … ‘Oxymoronic,’ hmmm,
      sorta’ virtual reality, unbiased opinion.

  30. I am fascinated by this expensive gem: “Tim Palmer argued strongly and eloquently for the level of research commitment REQUIRED to meet the enormous challenges of predicting regional climate, a challenge that he argued was greater than that associated with identification of the Higgs boson.” (emphasis added)

    The LHC alone cost about $4 billion, not to mention the time of thousands of physicists around the world looking at the data, the data network, etc. Let us start with this REQUIRED cost estimate before we go one step further down this rocky road. I do not see the slightest chance that this kind of money will be provided so the issue is DOA. Let’s save our breath.

    • But according to some of the skeptics,trillions has already been spent on climate science, so what would be the problem with a few billion?

    • Note greater than that associated with the identification of the Higgs-Boson.

      The expense will be greater than and the chance of success will be lesser.

      Face it, regional climate prediction will get done eventually, because it is worth the money. It will be done privately by people for whom the information will be worth the money. Government, such that we have, simply doesn’t value that information highly enough to buy it, or they’d made a better effort to get it already, like asking for verification and validation of models. Granted, government has spent a lot of money on climate models, and they’ve got what they paid for: scary scenarios. Too bad they bought a pig in a poke.
      ============

    • Michael | February 19, 2014 at 3:30 pm | “But according to some of the skeptics,trillions has already been spent on climate science, so what would be the problem with a few billion?”

      Try that cavalier attitude on your wife regarding investments: Honey, we just lost a $1M dollars on Solyndra stock, how about we buy another $4K worth of Solyndra stock.

      And let’s see, another $4 billion spend on more climate research is $4 billion not spend on something else. Maybe bringing potable water to a village without, or feeding a few billion starving people for a day.

    • Berényi Péter

      @kim

      Face it, regional climate prediction will get done eventually, because it is worth the money. It will be done privately by people for whom the information will be worth the money.

      An old joke comes to mind. “Can you jump thirty feet high?” “No.” “And, ehrr, what about it if I paid you handsomely?”

      There is an extensive private horoscope industry for sure, just because there is huge demand for it on the market. Does this fact tell you anything about the intrinsic value of its predictions?

      Jokes aside, current climate modelling paradigm is deeply flawed, it can never lead to useful regional climate predictions at any cost. With improved understanding of irreproducible quasi stationary non equilibrium thermodynamic systems in general that may change, but it is an arcane scientific question, which does not make users particularly enthusiastic in itself, certainly not enough to make a living from it on the market.

  31. Robert I Ellison

    ‘Demand for more accurate predictions of regional climate necessitates a unified modeling approach explicitly recognizing that many processes are common to predictions across time scales.

    The global coupled atmosphere–ocean–land–cryosphere system exhibits a wide range of physical and dynamical phenomena with associated physical, biological, and chemical feedbacks that collectively result in a continuum of temporal and spatial variability. The traditional
    boundaries between weather and climate are, therefore, somewhat artificial. The large-scale climate, for instance, determines the environment for microscale (1 km or less) and mesoscale (from several kilometers to several hundred kilometers) processes that govern weather and local climate, and these small-scale processes likely have significant impacts on the evolution of the large-scale circulation.’ http://journals.ametsoc.org/doi/pdf/10.1175/2009BAMS2752.1

    Initialised models at the appropriate resolution will requite 1000’s of times – and many billions of dollars – more computing power. Even then – the ability to model spatio-temporal ‘dynamical phenomenon’ with temporally chaotic models – models that solve chaotic equations one step at a time – is uncertain. Weather models have a window of about 7 days at best. A window for initialised climate models is quite unknowable.

    ‘Sensitive dependence and structural instability are humbling twin properties for chaotic dynamical systems, indicating limits about which kinds of questions are theoretically answerable. They echo other famous limitations on scientist’s expectations, namely the undecidability of some propositions within axiomatic mathematical systems (Gödel’s theorem) and the uncomputability of some algorithms due to excessive size of the calculation.’
    http://www.pnas.org/content/104/21/8709.long

  32. The only rational way for anyone seriously worried about global warming to adapt climate change is to invest in more air conditioning and more energy.

    • Or move a quarter of a mile poleward every generation.
      ============

    • “Or move a quarter of a mile poleward every generation.”

      Actually, given the ~60 year cycle, have two houses which you swap on alternate generations!

      • Everything is a trade-off. For example, a relatively few years ago elementary schools had incinerators; custodians essentially managed controlled trash fires. But, kids actually got a decent education back then compared to the product of the dropout factories of today where teachers are pushing climate porn on the nation’s children.

  33. I propose the Elevate Everything plan to deal with global warming. Simply put shims/stilts/platforms/hydraulic lifts/piers under every relevant human artifact. This approach neutralizes rising sea levels and simultaneously places human activities in a slightly cooler and windier environment, neatly canceling out most warming impacts. Plus, it creates new “basement” spaces for storage and conduits of all kinds.

    Marketing slogan for this modest proposal: “We put the infra in infrastructure.”

  34. if those ”workshops” were for adaptation when climate changes – people will adopt as the climate is changing, not before; because on every individual plce the climate is changing differently, some places for better, others for worse.

    BUT, when is incorporated in this, the phony ”GLOBAL warming” it’s all con for taxpayer’s cash = workshop for and by the Organised Crime.

  35. Svend Ferdinandsen

    Climate models for adaptation is a dead end, and could be worse than no models. When using models most politicians forget to look at the reality and statistics on that.
    Models can not say what is happening in 10 or 20 years if they can at all, and most adaptation can be done in that timeframe just by observing the weather.
    The fighting against CO2 will not change the possibility of draught or flood for the next 50 years, but it might remove money and attention away from effective adaptation for the next and comming years of variations in the weather.

  36. We do not need adaptation models, we have Holdren and the President announcing that weather is now climate, as long as it’s bad.
    http://thehill.com/blogs/e2-wire/e2-wire/198394-obama-to-announce-1b-climate-change-resilience-fund

  37. Fernando Leanme

    I realize my comments tend to sound a bit disconnected in these forums, because I´m not a climatologist. But I´d like to mention what seems to be a critical issue many are ignoring when they make depositions and reports which can influence decisions:

    The climate models require inputs. As far as I can see one of the most critical inputs is the greenhouse gas concentrations, of which CO2 and methane seem to be the most important. The concentrations are driven by emissions and by the efficiency of removal. I don´t think there´s a full understanding of the carbon cycle, but for now let´s assume it´s modeled adequately.

    This takes me to focus on the emissions. And what I see in studies such as the IPCC´s AR5 (or the CMIP5 model ensembles) is a fairly weak and poorly designed process to arrive at the actual emissions which lead to the concentrations they feed into the CGMs.

    I understand the IPCC chose the concentration pathways based on their surveys of scientific papers prepared by climatologists. When I look over the material I can access I must conclude those model results they surveyed were using faulty inputs because the work flows and processes used to estimate emissions were suspect or poorly defined.

    In other words, these guys and gals were mostly interested in the climate models, the amount of funding and actual work hours devoted to the inputs was insufficient.

    Sincé the IPCC did a survey of preexisting pathways, which yielded forcings which in turn led them to pick the four forcings in watts per squared meter, then all the work done after the IPCC blessed those four forcings was by definition constrained to arrive at the watts per meter squared forcing the IPCC had already set.

    Because climatologists focus on the models and don´t usually “swim upstream” to understand what feeds their models then what we have is a herd following a herd. I´m not saying the herds are all wrong, maybe those emissions pathways are right, but I doubt it.

    For example, when I checked the emissions assumed for AR4, they had a bust in their methane emissions forecast, thus they had a bust in their methane concentrations. And I suspect this is one reason why AR4 models didn´t match real climate data.

    I suppose those who prepared the AR5 inputs (the documented concentrations used in the CMIP5) realized they had missed the call when AR4 was being prepared. So this time they kept the methane emissions curve lower, then kinked it and raised it steeply in the “business as usual” case (RCP8.5) in what appears to be an arbitrary fashion. That curve is…baloney.

    Again, since I don´t have access to the underlying reports, nor can meet with those who prepared the reports, it´s hard for me to follow their logic. But it´s possible the work flow and processes used to create those emissions, which in turn lead to the TARGET FORCINGS the IPCC thinks are representative, don´t pass muster as solid work.

    I don´t want to be seen as unduly criticizing those who prepared the IAMs and generated these inputs. I sense they did what they could with the available resources.

    I would like to finish by adding that a work flow used in a dynamic systems model used to generate those emission flows ought to include well documented decision logic and I would add they CAN be designed a lot better if the people who do that kind of work get much more support .

    You can improve results in areas other than pure climatology. The inputs have such huge spread, error bars, and logic flaws this ought to be a focus area.

  38. Pingback: That old-time religion: Secretary of State Kerry and the Climate Council « DON AITKIN

  39. “Use the climate models to explore possible future scenarios that extend beyond emissions: e.g. solar forcing, volcanic eruptions.”

    Explore the short term solar forcing thoroughly enough and discover that it drives short term regional variations influenced by the AO/NAO fairly irrespective of average global temperature. And that it also drives ENSO and the AMO, meaning that to predict global and regional climate effectively, you need to predict the solar signal at the noise level at long range. Regional forecasts can be deterministic, but the extrapolating the global average from expected teleconnection conditions would have more uncertainty.

  40. Pingback: UK-US Workshop Part V: Broadening the portfolio of climate information | Climate Etc.

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