Climate models outperformed by random walks

First, a bit of a primer. Wikipedia describes a random walk is a mathematical formalisation of a trajectory that consists of taking successive random steps. For example, the path traced by a molecule as it travels in a liquid or a gas, the search path of a foraging animal, the price of a fluctuating stock and the financial status of a gambler can all be modeled as random walks. The term random walk was first introduced by Karl Pearson in 1905.

Example of eight random walks in one dimension starting at 0. The plot shows the current position on the line (vertical axis) versus the time steps (horizontal axis). Source: Wikipedia

Computer models utterly fail to predict climate changes in regions

From the Financial Post: A 2011 study in the Journal of Forecasting took the same data set and compared model predictions against a “random walk” alternative, consisting simply of using the last period’s value in each location as the forecast for the next period’s value in that location.

The test measures the sum of errors relative to the random walk. A perfect model gets a score of zero, meaning it made no errors. A model that does no better than a random walk gets a score of 1. A model receiving a score above 1 did worse than uninformed guesses. Simple statistical forecast models that have no climatology or physics in them typically got scores between 0.8 and 1, indicating slight improvements on the random walk, though in some cases their scores went as high as 1.8.

The climate models, by contrast, got scores ranging from 2.4 to 3.7, indicating a total failure to provide valid forecast information at the regional level, even on long time scales. The authors commented: “This implies that the current [climate] models are ill-suited to localized decadal predictions, even though they are used as inputs for policymaking.”……

More here: http://opinion.financialpost.com/2012/06/13/junk-science-week-climate-models-fail-reality-test/

h/t to WUWT reader Crispin in Waterloo

Previously, WUWT covered this issue of random walks here:

Is Global Temperature a Random Walk?

UPDATE: The paper (thanks to reader MT) Fildes, R. and N. Kourentzes, 2011: Validation and forecasting accuracy in models of climate change. International Journal of Forecasting. doi 10.1016/j.ijforecast.2011.03.008
and is available as a PDF here

160 thoughts on “Climate models outperformed by random walks

  1. One of the reasons that climate models fail is that they include CO2 which in fact lags temperature rather than being useful in a forecasting model for temperature, rain, wind etc. The so-called climate scientists basically have no understanding of heat transfer and reaction kinetics. As Willis has been showing they need to look at heat from the sun, and clouds in their various forms. They also need to look at the chemical reactions at the top of the atmosphere such as ozone formation.

  2. One has to admire McKittrick’s clear and direct style.
    I like this long-term precipitation record – Central England & Wales, 1766-now:

    There is some multidecadal oscillation, but nothing exceptional whether it was LIA or modern WP.

  3. This surprises me – and probably most people here – not one bit.
    As long as the input assumptions are flawed, all that the climatologists will manage with larger and more expensive supercomputers (as demanded by the UK MET) will be to compound their errors.

  4. the models are screwed up…we have been saying that for a long time…there are too many factors…many poorly understood…co2 is already absorbing all the infrared it can…adding more will not make any difference…these climatologist guys dont seem to understand basic physics

  5. For some time I have been unable to understand how the UK Met Office models can predict climatic conditions decades in the future, when they are admitted to be of “low skill” (by Richard Betts) in predicting the weather / climate over periods only weeks or months in the future. I asked Richard for references to the modelling procedures and he kindly provided several on various threads at Bishop Hill. This raised more questions and I finally emailed the Met Office with the following:

    “I would be grateful if you could let me know if you think that it is reasonable practice to use numerical models for multi-decadal forecasts that:

    A. Use low pass filters “chosen to preserve only the decadal and longer components of the variability” ( http://www.geosci-model-dev.net/4/543/2011/gmd-4-543-2011.pdf (quote from page 21), and,

    B. Accommodate errors that cause instabilities “by making periodic corrections, rather
    than by fixing the underlying routines (http://www.cs.toronto.edu/~sme/papers/2008/Easterbrook-Johns-2008.pdf (quote from page 7).”

    The Met Office kindly replied with the following answers:

    “(A) The models themselves do not use low pass filters. Indeed they simulate weather on timescales of minutes. Low pass filters are used to analyse the model output in order to focus on timescales of interest.

    (B) The mathematical equations describing the evolution of the atmosphere and oceans cannot be solved analytically. Instead they must be solved numerically using computers. This process frequently involves a compromise between accuracy and stability. During model development much research is undertaken to find the numerical schemes that provide the best accuracy whilst minimising instabilities. At the Met Office the same numerical schemes are employed for weather and climate predictions, and the performance of the forecasts are continuously assessed across a range of timescales from days to decades.”

    I am still struggling to find an answer to my original question, and perhaps my questions to the Met Office were the wrong ones. Is there anybody here who understands how numerical models can be “low skill” over short timescales but could possibly be accurate enough to justify massive intervention over multi-decadal timescales?

  6. LevelGaze: “This surprises me – and probably most people here – not one bit.”

    Yeh no. I’m not simply surprised but mortified. It’s one thing to hold that simply gluing together words ‘climate’ and ‘science’ doesn’t mean there’s much of either in ‘climate science’. It’s quite another to state that the “consensus science” is so stupidly distant from a random walk, on the wrong side of things, that we’re beyond Jonestown and that we’ve gone beyond Ludicrous Speed.

    Each of these models, which the article refreshingly notes, are a scientific theory about the climate. And they are when empirically tested make errors more than twice that achieved by a monkey throwing darts. Under any notion of science every one of those models is a miraculously falsified theory.

    And of course it serves to note that the average stock broker does slightly worse than an actual monkey throwing darts at a dartboard — for those that remember the MonkeyDex. Slightly worse. And it’s a felony for stock brokers to make too much of their own prognostications without a disclaimer to the effect that they are not Delphic Oracles, Palm Readers, or merely reliable. And that’s just for ‘slightly worse’.

    So while I’m unsurprised that the models are terrible, I’m utterly aghast that they are so grotesquely biased as to make the static on an empty television channel the acme of rigorous statistical predictions in climate.

  7. ,b>Helen Ap-Rhisiart says:
    June 14, 2012 at 12:43 am
    Surely a diagram on a flat surface is in two dimensions?

    Yes, but only ONE of the dimensions is length. The other is time. Think of a bead on a string. At time t=0 the bead is at zero, at time t=1 the bead is at -1 (say), at t=2 the bead is at +5, and so on. The graphs shows the position of the bead on the string as a function of time.

  8. Could someone share the title of the paper this was based on? I’ve looked through the 2011 paper in the forecasting journal but couldn’t find any likely titles. Perhaps I just missed it.

    Cheers!

  9. Doesn’t surprise me in the least.

    All the climate models do is project the modellers belief in the net forcing of various factors, primarily CO2, forward into the future. That the models do worse than random chance is proof that some or all of the believed forcings are wrong, and specifically the believed CO2 forcing is wrong.

    No other conclusion is possible, except perhaps serious programming incompetence by the modellers.

  10. In a nutshell a random walk has a finite chance of being correct but if you start with a wrong model it will always be wrong.

  11. @ Roger Longstaff

    “Is there anybody here who understands how numerical models can be “low skill” over short timescales but could possibly be accurate enough to justify massive intervention over multi-decadal timescales?”

    No, because this is not remotely feasible. The climate is a chaotic system so a tiny variation in an initial condition will result in entirely unpredictable (or random) outcomes.

  12. Roger Longstaff says @ June 14, 2012 at 1:03 am

    Hi Roger,

    Pretty certain that what RB has in mind is that (A) short term random noise (white noise) prevents models from making accurate forecasts over weeks and months and (B) the white noise is averaged out over climate time scales (decades) and hence the models should end up providing reasonable average behaviour over the longer time scales.

    The reason that (B) is wrong is simply that the noise in the system does not average out over the decadal time scales. Over these time scales, the pink noise mentioned in the “Is Global Temperature a Random Walk?” link begins to dominate. Models are not currently able to simulate this behaviour, which means that their use in decadal projections is unlikely to be useful globally, let alone regionally.

  13. It’s not too surprising; a random simulation can be right some of the time, but a model rigged to be wrong will consistently be wrong.

  14. GCMs are like communism, they require global venue to succeed as their supporters say; but fail miserably at a local level as reality states.

  15. This is great news! With this breakthrough in modeling, we will be able to improve climate forecasting while at the same time reduce the amount of computational performance needed, making for more sustainable modeling. Simply replace the current climate models with random walk models, do an ensemble run and average over it.

    I can’t wait to see the headlines:
    “Scientists baffled – New Climate Model predicts no change in temperature ever!”

  16. The UK. Met. Office have yet to learn that when you have dug yourself into a hole you stop digging.
    Their reply to Roger Longstaff is typical of QUANGOs which the Met Office has become. At least when it was officially under RAF control it did apologize for errors it made.
    For non UK readers a QUANGO is a Quasi Non Governmental Organization that is formed to advise the government and in doing so get paid money. The Met Office has dreams of operating the worlds biggest climate computer so needs to scare the government into paying more money. It can’t be bothered with members of the public, who actually provide the money through taxation, asking what it considers stupid questions.

    Keep trying Roger.

  17. People here waste too much time in armchair speculation on why climate models can’t work “in theory”. The key issue is validation. Why should I believe what this model tells me? What is the evidence for it’s efficacy? If I have to evaluate the merits of a complex surgical procedure I want to look at the study results. I don’t care if the surgeon is the world’s greatest or that medical science is amazingly good, or if there is a consensus on something related to it, or any other non sequiturs of that type.

  18. Random walk? What random walk? The yellow line and the black line OBVIOUSLY prove my **ULTIMATE THEORY!**

    If you people just can’t see that, well, I hope Schroedinger’s Cat bites you!

    – MJM

  19. Back to discuss about random walks after these ad’s….

    ‘the financial status of a gambler ‘, I spend 4 pounds a week on the lottery and always lose (using this years figures as I ain’t won a penny) and my friend lost the £120,000 given to him when his farther passsed away plus the £40,000 he stole from work, so I promise you gamblers don’t generally have random walks just declines and even when they do win these are generally smoothed out by, yep, the loses.

    Welcome back…..

  20. Yes,, this is exactly how they are supposed to work.
    If you have two climate models, one says ‘rains and floods will increase’ and another that uses the same data says ‘droughts and hot weather will increase’ then depending on the weather at the time you just refer to the model that got it correct and blame it on climate change. I thought you all knew the science behind AGW ? /sarc

  21. The paper is in the International Journal of Forecasting (not the Journal of Forecasting)
    Fildes, Robert and Nikolaos Kourentzes (2011) “Validation and Forecasting Accuracy in Models of Climate Change International Journal of Forecasting 27 968-995.

    http://www.sciencedirect.com/science/journal/01692070/27/4

    Ross McKitrick’s fully referenced article is here (the journal reference is incorrect there too and in the FP article, but the footnote is correct…)

    http://www.rossmckitrick.com/uploads/4/8/0/8/4808045/fp_june12_models_i.pdf

  22. Thanks Philip & Letmethink.

    My problem is that any filtering (between calculation steps), or “re-setting” of variables to preserve stability, inevitably leads to loss of information on the system.

    Filtering is used to increase signal to noise ratio when there is “a priori” knowledge of the signal (for example in a radio receiver that uses a narrowband filter tuned to a specific frequency). With climate models there is only an assumption that there will be a GHG signal. Furthermore, any low pass filtering will remove information generated by the model itself, as signals must be sampled at twice their highest frequency component (Nyquist theory) in order to preserve information.

    If one were to equate accurate information to Shannon entropy, it seems inevitable that climate models will deviate from reality exponentially with respect to time, as a consequence of the logarithmic nature of information theory.

    Is there a flaw in my argument?

  23. Roger Longstaff says:
    June 14, 2012 at 1:03 am

    I am still struggling to find an answer to my original question, and perhaps my questions to the Met Office were the wrong ones. Is there anybody here who understands how numerical models can be “low skill” over short timescales but could possibly be accurate enough to justify massive intervention over multi-decadal timescales?

    =======

    Roger
    In my part of the world there is a dramatic difference between Summer — which can be feature near tropical heat and humidity — and Winter — where weeks can go by with the daytime highs below freezing and snow piling up a meter or more. Thus, a model that predicted daily temperature would follow a sine wave with a period of 365 days and an amplitude of about 30 degrees C might show considerable skill at long term prediction while being more or less useless at predicting whether it will rain tomorrow.

    Let me hasten to say that I see no reason to believe that current climate models are more reliable at predicting future climate than a magic eight ball or monkeys throwing darts.

  24. Suppose, we have an exam test consisting of 30 two-choice items. If you do not know anything about the subject, your expected number of correct answers is 15. Sometimes it may happen that someone answers all items correctly but also that someone does everything wrong. This may happen in a large population of subjects without knowledge. Usually, we interpret 30 items correct as a sign of knowledge. Therefore, all items false may also mean that someone did everything deliberately wrong.

  25. “…consisting simply of using the last period’s value in each location as the forecast for the next period’s value in that location.”

    This reminds me of the standing joke about the accuracy (or otherwise) of weather forecasts amongst professional aviators. We knew that the most accurate forecast was likely to be:

    “Forecast for tomorrow; the same as today. Outlook; no change.”

  26. a “random walk” alternative, consisting simply of using the last period’s value in each location as the forecast for the next period’s value in that location.

    That’s not a random walk, that’s a persistence model, a.k.a a straight line.

    The test measures the sum of errors relative to the random walk.

    Assuming we’re talking about the persistence model above, all the test is doing is scoring the amount of change from the baseline. This says nothing about what is right or wrong. This is at best misleading to try and judge the performance of climate models using a test like this.

  27. So much math this early?

    I need more coffee.

    Thank you for the information. I love Scientific Inquiry. Unfortunately, most of today’s ‘Science’ seems to be more speculative than realistic. Therefore, I like your skepticism.

    At least for now.

    Ghost.

  28. No MT that is not what is assumed. With a simple random walk the last observation represents the instantaneous mean of a probability distribution (at the simplest a normal distribution) of known variance from which the next observation will be randomly drawn.

  29. BTW, the paper is referenced is:
    Fildes, R. and N. Kourentzes, 2011: Validation and forecasting accuracy in models of climate change. International Journal of Forecasting. doi 10.1016/j.ijforecast.2011.03.008
    and is available as a PDF here

  30. Letmethink says:
    June 14, 2012 at 2:25 am

    @ Roger Longstaff

    “Is there anybody here who understands how numerical models can be “low skill” over short timescales but could possibly be accurate enough to justify massive intervention over multi-decadal timescales?”

    No, because this is not remotely feasible. The climate is a chaotic system so a tiny variation in an initial condition will result in entirely unpredictable (or random) outcomes.

    The argument is:::
    A model could show it would not rain in UK in June on the 12th to 15th but on all other days it would – whereas in reality it did not rain on the 22nd to the 25th but on all other days it did. There was no ‘skill’ in the forecast of the 12th-15th or 22nd-25th – but for the overall month of June the model said it rained 26 days out of 30 and that could be claimed to be high skill in aggregate.

    However, the longer a model runs without showing any skill the less likely it is to be skillful in aggregate and at some point it can be said that there is no chance of recovery. Effectively, this is the weather vs climate argument in different clothes.

  31. Hey, no fair, that plot looks almost like my baseball “runnings,” graphical displays of MLB’s standings over the year. For a while the AL East was threatening to have all the teams come back to 0 games from 0.500 they had at the start of the season!

    See http://wermenh.com/runnings_2012.html

    It would be fun to take the lines in the plot above and match them to different baseball teams.

  32. I wonder if anyone can take this further and show that the random walk data put through Michael Mann’s analysis will always show a ‘hockey stick’?

  33. @mt,

    I think you misunderstand what “random walk” is, and you totally ignore the graph at the top of the post.

  34. Mindert Eiting says: June 14, 2012 at 4:23 am

    Suppose, we have an exam test consisting of 30 two-choice items. If you do not know anything about the subject, your expected number of correct answers is 15.
    — — —
    I just so happened to read just hours ago an article by William Briggs on this subject of what we mean by “guessing by chance”.

    http://wmbriggs.com/blog/?p=3583

  35. Low skill has not caused the Obama administration to back off of its AGW agenda. Skyrocket energy costs because the computer told me to do it.

  36. @mt,

    Oh, if you’d like to do your own random walk graph, and have Excel, try this:
    in cell A1, put =randbetween (-1,1)
    in cell A2, put =randbetween(-1,1)+A1
    use the fill option and fill the A2 cell down a few hundred cells.
    select the cells and make a line graph.
    press f9 to refresh, and you’ll get quite a few graphs that look a lot like temperature graphs.

  37. William Briggs had an interesting article on this here:

    http://wmbriggs.com/blog/?p=257

    I just came across it recently. The article motivated me to read up on the “arcsine” rule,
    to go into r-project.org and download the R program, learn something about computing regression using R, and to have some fun running and rerunning Wiliam Briggs’ fun program. ,

  38. Tamsin, please let me offer brief comment that relates both to your weblog’s post “All Models are Wrong: Limitless Possibilities” and to Anthony Watt’s present headline post on WUWT titled “WUWT: Climate Models Outperformed by Random Walks”.

    As a warm-up, let’s consider a non-controversial subject: models of turbulent flow over airframes. As we improve the spatial and temporal resolution of airflow simulations, we find that our ability to predict microscopic details of the flow does *not* improve. The reason is simple: the microscopic dynamics are chaotic, such that no dynamical model (however sophisticated) can predict their future evolution with microscopic accuracy.

    None-the-less, experience shows that fluid dynamical simulations DO successfully predict (typically within errors of order one percent) the flight characteristics that we mainly care about, including (for example) fuel efficiency, stall-speeds, and g-limits.

    How does this happen? It happens because the microscopic dynamics is governed by global conservation laws and thermodynamic constraints, chief among them being strict conservation of mass and energy and global increase in entropy. So instant-by-instant, we don’t know whether a Karman vortex will spin-off an extended wing-flap, and yet minute-by-minute, we can predict the lift, drag, and glide-path of an airliner with considerable accuracy and confidence.

    As with fluid dynamics, so with climate dynamics. Chaotic fluctuations on continental spatial scales and decadal time scales are difficult to predict with confidence. Yet global climate changes are constrained by strict conservation of mass and energy and global increase in entropy, and thus *CAN* be predicted. So year-by-year, we don’t know whether the local weather will be hot or cold, and yet decade-by-decade, we can predict the warming of the earth, and the rise of the sea, with considerable accuracy and confidence.

    Appreciating this, James Hansen and his colleagues have focussed their predictions on the global energy balance, and in particular, upon sea-level rise as an integrative proxy for that global energy balance. In 2011 they confidently predicted an acceleration in sea-level rise for the coming decade. Hansen’s prediction required a certain measure of scientific boldness, since at the time satellites were showing a pronounced decrease in the sea-level rise-rate.

    In coming years we will see whether Hansen’s prediction is correct. Supposing that the prediction *is* proved correct, then the concerns of rational climate-change skeptics will be largely addressed.

    More broadly, it is global conservation of mass and energy and global increase in entropy that explain why simulations of both airflow and climate can be inaccurate on individual space-time gridpoints, yet accurate globally.

    —————————

    LOL … for fun, I’ll post this essay to Judith Curry’s Climate Etc. and to Tamsin Edwards’ All Models are Wrong too.

    It will be fun to see which forums are mainly interested in rational arguments accompanied by scientific links, versus mainly interested in compiling an ideology-first “enemy list.”   :)

  39. Roger Longstaff @ June 14, 2012 at 4:12 am

    Hi Roger,

    I don’t think the models perform any specific filtering between calculation steps. They *simply* solve the discretized differential equations to obtain values over a 3D grid. Important processes like clouds occur within a grid unit, and are represented in the model using heuristics. Such processes may therefore not be realistically modelled, especially over longer time-scales. Is this the kind of issue you are thinking about? Another possible reason for low decadal variability is that some important internal processes are not represented at all.

    Whatever the reason, models do produce decadal variability that is low compared with measured values. If this were not the case, then the short term random fluctuations would cancel out on the average and Richard’s argument would be more reasonable.

    You also wondered whether you were putting the right question to the MO. I think it was a great question you asked, but for myself I’d be rather grateful simply to hear whatever explanation the MO cares to offer about the low decadal variability. I think this is a key question.

  40. mt says:
    June 14, 2012 at 4:47 am


    Assuming we’re talking about the persistence model above, all the test is doing is scoring the amount of change from the baseline. This says nothing about what is right or wrong. This is at best misleading to try and judge the performance of climate models using a test like this.

    Ah, the tussle between “right” and “wrong”.

    If you read closer, the “RW” (for Random Walk) models had less error (E) in predicting what actually happened (“measured”) than ideology-driven “Climate Models”. So ERM < ECM.

    This does indeed say which is (more) right and which is (more) wrong. That is, if your primary concern when building models in the first place is to determine which actually MODELS.

    But for those still unwilling to grasp the concepts or have hockey sticks for spines, continue singing (to any tune you like):

    “Don’t bother me with reality; what I’m looking for is a good fantasy.”

  41. Shevva says:
    June 14, 2012 at 3:13 am

    ‘the financial status of a gambler ‘, I spend 4 pounds a week on the lottery and always lose

    yeahbut … National Lotteries are a tax on people who cannot do mathematics.

    NO sarc….

  42. Philip Richens says:
    June 14, 2012 at 2:27 am
    Pretty certain that what RB has in mind is that (A) short term random noise (white noise) prevents models from making accurate forecasts over weeks and months and (B) the white noise is averaged out over climate time scales (decades)
    =========
    Correct, the climate models make the assumption that climate is normally distributed (constant mean and deviation), that the errors plus and minus average out over time.

    However, what if climate models function more like an inertial guidance system? The models are telling us that temperature will go up and down each day, but there is a small error in this calculation, so that slowly but surely the models will drift away from reality.

    This is what happens in a guidance system. Without some external reference point, like a satellite or radio fix, airplanes, boats and spacecraft drift off course. The errors do not even out, no matter how powerful the computers, no matter how expensive the technology. There is no know solution to this problem.

    The problem is that there is no external reference point for predicting the future. No satellite or radio to tell us where the future lies. You can use history to improve hind casting, but no matter how good your computers, they will slowly drift off course when steering us into the future.

    This is the problem completely overlooked by climate science and the IPCC in their attempt to create an “ensemble” of forecasts to correct for this problem. No matter how many computers you use in a guidance system, it will still drift away from reality without an external reference point, and there is no reference point for the future.

  43. Hi Anthony. Since the purpose of these models is not to predict climate or temperatures so much as change human behavior it makes since a random walk would be more predictable.

    But the schemers are just getting cranked up. I just finished my story on the Belmont Forum and the Belmont Challenge being managed by the US NSF and UK’s NERC. Lots of plans on how to make decadal models that will reliably predict human behavior.

    http://www.invisibleserfscollar.com/the-belmont-challenge-and-the-death-of-the-individual-via-education/

    I have the actual White Paper as well as the downloaded Earth System Analysis and Prediction System. I did not provide links because they will be off the servers immediately. But that is what I am quoting from.

    There is no individual human freedom left in the kind of “coupled human-environmental modeling framework” this informal lobby is pushing.

  44. A fan of *MORE* discourse says:
    June 14, 2012 at 6:22 am
    As with fluid dynamics, so with climate dynamics.

    False analogy.

    Chaotic fluctuations on continental spatial scales and decadal time scales are difficult to predict with confidence. Yet global climate changes are constrained by strict conservation of mass and energy and global increase in entropy, and thus *CAN* be predicted.

    You just need a program sophisticated enough to account for all the variables — which hasn’t been written yet — and a computer powerful enough to run it — which hasn’t been built yet.

    So year-by-year, we don’t know whether the local weather will be hot or cold, and yet decade-by-decade, we can predict the warming of the earth, and the rise of the sea, with considerable accuracy and confidence.

    Sooooo, how do you explain the divergence between predicted and observed this past decade?

  45. In my view any reconstruction of the global temperatures may encounter problems unless two hemispheres are considered separately.
    Recently I looked at the Northern Hemisphere, more complex but still possible to achieve a reasonable degree of correlation using the known natural parameters as shown here:

    http://www.vukcevic.talktalk.net/NH-Recon.htm

    Note: all variables are detrended.
    Despite possibility that the natural oscillations in 1960-70s and 2000-2011 could have been suppressed by man made factors the longer term values or trends are unaffected.
    If this is correct then both the sulphates and CO2 effects are only short term.
    Reasons for anti-phase in the late 1930s are not as obvious.
    (p.s. if there is any interest in method and parameters used, I may put more info on my website some time soon, if there isn’t I’ll do it anyway).

  46. re: Mindert Eiting 4:23 AM 6/14/12

    If you do not know anything about the subject, your expected number of correct answers is 15.

    I suspect this is wrong. First no human is going to be totally clueless of a given subject. Say the subject was the nomenclature used in modern dance. I don’t think I’ve ever read anything about it, but I’ll bet I’d score well above 50% in any actual test constructed in the English language. This is because any human test of knowledge is expressed using the common knowledge embedded in the language it’s constructed in. Depending on whether the test is constructed to be as difficult as possible or to best test the actual knowledge of the test taker, the average score might be 17 or 25 say.

  47. The main climate model forecasts over the years versus the temperature observations (up to April and May 2012).

  48. A fan of *MORE* discourse says:
    June 14, 2012 at 6:22 am
    “Yet global climate changes are constrained by strict conservation of mass and energy and global increase in entropy, and thus *CAN* be predicted”

    If you look at reference B from my first post you will find that the models need to be “corrected” during the numerical integration – the specific reason being given that they violate conservation of mass. Any model thjat needs to be “corrected” in order to restore conservation of mass can not provide useful information.

  49. Philip Richens says:
    June 14, 2012 at 6:36 am

    Hi Philip,

    A similar point was made on Tamsin’s blog: “On filtering, you were given a clear answer in the Met Office’s reply: the low-pass filter described has nothing to do with the workings of the model as it is running. It’s a technique used to aid analysis of a specific climatic phenomenon after the model run has completed.”

    My reply was that any filtering “to aid analysis” must result in loss of information, given that there is no a priori knowledge of the signal.

    Do you agree?

  50. mt says:
    June 14, 2012 at 4:47 am
    That’s not a random walk, that’s a persistence model, a.k.a a straight line.
    ========
    every walk starts from the position of the last step. However, for it to be a straight line, the direction of the next step must remain constant. If the direction changes randomly at each step, it is a random walk.

    In Australia they found it was more accurate to simply forecast yesterday’s weather today than to rely on the zillions of dollars they were spending on weather forecasting.

    In climate, it is much more accurate to forecast that the climate will be pretty much what it was 60 years ago than it is to rely on the IPCC models. This decade will be like the 1950’s and the 1890’s. We are at the beginning of a cooling period that will last 20 more years, just like the 1950’s and the 1890’s. During the next 20 years, until about 2035, the warming we have experienced since the bottom of the LIA will remain halted, and temperatures will be stable to declining.

    After than time, warming should resume. However, there is plenty of evidence that temperatures overall have been declining for 8000 years, and we are likely due to start a rapid slide back into ice age conditions in the not too distant future. At which time you can pretty much be certain that real estate prices outside the tropics with collapse. The money that went to prevent global warming? That money will be gone. Instead you will then be taxed to prevent global cooling. None of which will have any effect except to line some else’s pockets.

  51. Sort of reminds me of an argument between my physics professor and philosophy professor in college. The physics professor was trying to prove a point that (essentially) physics had all the answers and how it was superior to philsophy. To prove it he said to the philosophy professor “you see that pen you’re holding: If you dropped it I could tell you everything about it…it’s velocity at every point in time, it’s momentum, how far it falls, how hard it hits, how high it bounces, etc.” to which the philosophy professor said “but can you tell me if and when I’ll drop it”?

  52. @RockyRoad read the paper. As far as I can tell, they’re giving scores based on looking at future data (2007-2017 and 2007-2027). How is it possible to say what model is “right” and “wrong” versus data that doesn’t yet exist?

  53. Please note there are four papers: the original paper, two critical commentaries, and the authors’s postscript. This is a welcome methodological critique of models, not of the science behind them.

    From the original paper’s conclusions:
    “…there is no support in the evidence we present for those who reject the whole notion of global warming: the forecasts still remain inexorably upward, with forecasts which are comparable to those produced by the models used by the IPCC.”

    From the postscript:
    “Climate change is a major threat to us all, and this requires the IPCC community of climate modellers to be more open to developments and methods from other fields of research.”

  54. Yeah, but if you take a bunch of them and average them together it’s better, right? Oh, I know what the problem is here; These guys aren’t climate scientists, so it’s just too complex for them to understand. I’ll bet they forgot to turn some of the data upside (you have to do that sometimes).

  55. The GCMs are run almost continuously trying to predict weather. They are in general disagreement out after a few days but they keep trying. I have been amazed at their persistence over the years. At 10 days out their guesses at what weather will happen becomes laughable.
    I started paying attention to this in 2006 and so far there has been no improvement. They just keep trying. You can become aware of much of this effort over at weather underground where a bunch of modeler kids try to fathom their rationale for hurricanes and tropical storms. At 3 to five days out they are all pretty accurate but by 10 days out their really fail big time. It remains very disappointing after seven years looking for improvements.

  56. This post and comments include statements with the terms random and chaotic with regard to weather and climate. I wonder who gets to define the terms, outcomes, and miss or match of the results? For example, if the weather forecaster looks at a computer output and it says the High Temp for tomorrow will be X.23 and then posts X and then the actual High comes as X +2, is that forecast considered wrong? In the strictest sense, if the actual High was measured as X.23 but the forecast was X — is it still wrong? On a different level, if, for 999 times out of 1,000, tomorrow (June 15) will be more like today than if will be like January 15, 2013, is it useful to think of weather as random?

    In a similar sense, with climate there seems to be a sense of sameness involved. Sometimes the terms average or normal or climatology enter into the discussions. That a person or model, or tea leaves, cannot say exactly what the high temperature and total precipitation will be for June 15, 2020 may not constitute a FAIL in the sense of climate sameness. Maybe the sameness should be compared to the entire month and not one day. And how close should the numbers be to declare “same/not-same” statements?

    If June 2020 will be more like June 2012 than it will be like January 2013, is the climate chaotic? I cannot recall a June when this comparison – June to June, versus June to January – hasn’t produced the expected result. Yes, I know. There have been instances when it was cold and snowed in June (southern hemisphere folks, please don’t take offence at this NH statement) — but this is within the meaning of “sameness” in my use of the term. I don’t consider that every day has to be very close to the averages for the month for June to be “June” and not some surprising anomaly.

    Consider the statements in the opening paragraph: “ . . . the path traced by a molecule as it travels in a liquid or a gas, the search path of a foraging animal, . . . ”
    One has to define these in a way to make them both “random walks” because the animal is not random in the step-by-step fashion while actually foraging. A horse, say, almost never backs up while foraging in a pasture. They tend to defecate from one end and take in food at the other and they have an aversion to ingesting plant material they have just soiled. To call their movement a “random walk” requires a definition that eliminates the step-by-step movements of the horse. Perhaps, one only plots the position once every half hour. Anyway, a step-by-step movement of a molecule in a gas does not involve the definitional issue as does the foraging horse.

    The people who define the path of a molecule and a horse as equivalent must also be the sort of people who can define weather and climate as random and chaotic. The phrase “The devil is in the details” seems appropriate.

  57. This is my bread and butter — random numbers and stochastic (e.g. Markov chain) models. I can do no better but to refer people to Koutsoyannis — here is a brief post on CA that indicates McIntyre’s opinion of him:

    http://climateaudit.org/2006/01/05/demetris-koutsoyannis/

    In a nutshell, Koutsoyannis asserts that climate is best described by Hurst-Kolmogorov statistics, which is basically a biased random walk. The decadal transitions are locally all nearly random and discrete, with nearly unbiased noise persistent between transitions. The direction of the transitions is nearly random, modulated by truly long term trends and non-Markovian dynamics.

    Personally I think he is brilliant, and brings an extraordinary and much-needed degree of statistical competence to a field (climatology) that operates under the fantasy that simple linear physical models can capture and underlying nonlinear chaotic process. Koutsoyannis builds moderately successful models USING statistics that are closely related to a random walk.

    IMO the right way to approach modeling is via e.g. a Langevin equation — a stochastic integral equation solution to a set of coupled nonlinear ODEs with random terms that model noise, where the noise terms are LARGE (possibly dominant) and not SMALL the way they are now. That’s HK statistics in a nutshell. It’s not that there isn’t long term dynamics and trends driven by physics, it is that resolving this long time scale trend from the short and meso-scale noise is nearly impossible because the noise is actually an order of magnitude greater than the signal. Under these circumstances, understanding response functions to local perturbations of the underlying dynamics is nearly impossible — detecting the “global warming signal” when the noise is an order of magnitude greater on decadal time scales, for example. Doubly so when the underlying dynamical model being “tested” is almost certainly not correct within a factor of three to five…

    rgb

  58. “…The mathematical equations describing the evolution of the atmosphere and oceans cannot be solved analytically. Instead they must be solved numerically using computers. This process frequently involves a compromise between accuracy and stability…”

    If the models uded by the Met are a compromise between accuracy and stability, then that stability must be the proverbial “immovable object”.

    We’ve already seen their accuracy…

    And, as a reply to mt (June 14, 2012 at 4:47 am)

    “…Assuming we’re talking about the persistence model above, all the test is doing is scoring the amount of change from the baseline. This says nothing about what is right or wrong. This is at best misleading to try and judge the performance of climate models using a test like this…”

    And you could say the same about the anomaly charts they pass off as “global temperatures”.

    All they do is show the amount of change from their chosen baseline (averaging period). Not all charts use the same baseline, or even use the same reporting stations.

    So those charts say nothing about what’s “normal”, or if we’re above or below that. This is at best misleading to try and judge “rise” in GLOBAL temperatures (with values less than a degree for most) using charts like this.

  59. Thanks to all of you I am beginning to get a clearer picture of how those on the AGW bandwagon can see things so clearly where, we sometimes we shake our heads and wonder how they can be so dense.

    It’s simple really. If you add one little routine to the random walk that discards all random walks that do not come close to matching the magenta random walk, since after all that one HAS to be right, (since it comes closest to tracking the relentless upward climb of that, that, nasty, evil mosquito of a compound CO2 from the year 18–, no 19whenever) then you can use those logically, correctly selected random walks, since by inference they modeled it rightly, to randomly walk into the future, and voila! within a hundred years we have . . . . . wait for it . . . GLOBAL WARMING! wait no? . . . . ok CLIMATE CHANGE!! See, I told you so! . . .

    /sarc off.

  60. “””””…..Helen Ap-Rhisiart says:

    June 14, 2012 at 12:43 am

    Surely a diagram on a flat surface is in two dimensions?…..”””””

    Not so surely Helen. If you do the exact same random walk yourself out in some safe place so you won’t step off a cliff; how about aschool playing field; you step forward or you step backward, depending on whether the referee calls heads or tails. You can do this till the cows come home, and you will never move sideways. so you either make it to your goal line or you do a wrong way Corrigan score at the enemy’s goal, but you never move sideways.

    If Anthony plotted your path exactly as you walked it, you would see all of your steps on top of each other and you couldn’t tell anything, except the length of the line.

    Time was invented to preventing everything from happening all at once, so the bottom scale on Anthony’s chart is just to time separate the moves so you can see them all. So it is one dimensional steps. In a two dimensional case, you would need to step sideways sometimes depending on some random signal.

  61. to which the philosophy professor said “but can you tell me if and when I’ll drop it”?

    To which the physics professor then replied, “Not even you with all of your philosophy and the pen in hand can do that — but at least I understand why.”

    Who is it, after all, that drops the pen?

    rgb

  62. “””””…..ferd berple says:

    June 14, 2012 at 7:07 am

    Philip Richens says:
    June 14, 2012 at 2:27 am
    Pretty certain that what RB has in mind is that (A) short term random noise (white noise) prevents models from making accurate forecasts over weeks and months and (B) the white noise is averaged out over climate time scales (decades)
    =========
    Correct, the climate models make the assumption that climate is normally distributed (constant mean and deviation), that the errors plus and minus average out over time……”””””

    Well white noise may average out to zero after long time scales; but only in mathematical models, which have a Gaussian distribution. Physical systems don’t have such an ultimate error distribution. Most of them eventally show the presence of 1/f noise, where the amplitude of an error or step, can grow without limit, but at an occurrence frequency that is inversely proportional to the size of the error or step. One can make the argument that 1/f noise is a consequence of Heisenberg’s Principle of Uncertainty. Maybe the Big Bang, was simply the bottom end of the 1/f noise spectrum.

    So in real physical systems, noise does not average out to zero no matter how long you wait, because there is always the chance of a step much greater than anything previously seen. And no; 1/f noise does not violate any thermodynamic limits, such as the total power or energy growing without limit, which it would in a white noise system. It is simple mathematics, to show that with 1/f noise each octave of frequency range contains the same amount of power as any other, no matter how large the amplitude gets.

  63. A 2011 study in the Journal of Forecasting took the same data set and compared model predictions against a “random walk” alternative, consisting simply of using the last period’s value in each location as the forecast for the next period’s value in that location.

    That isn’t a ‘random walk’!

  64. Not to be too pedantic, but Random Walks do not model the motion of foraging animals very well.

  65. Hey, Anthony!

    That’s a nice graph you have there. Very evenly splayed out. Did you pick it yourself? :)

    OK, just teasing. I know it’s only for illustrative purposes.

    Still, I thought it looked suspiciously ‘good’ with that attractive symmetry and those nice convenient outliers either side at about the 2 SD mark at the end, so I ran a few for myself without cherry picking — a straight sequence of runs — just to check my suspicions. Tut tut, Anthony. :)

    They’re not as pretty as yours but you can see the results here:  http://i46.tinypic.com/10rplki.png

    Go on, tell us. How many runs DID you try until you found that nice one?

    Too much exposure to the antics of those delinquents over at RealClimate might be leading you astray. They’re a very bad influence. You need to be careful. I’d stay well away from them from now on if I were you. :)

  66. The climate models are absolute bullshit. And they have failed, all of them. And the scare-mongers predictions of doom, going back over 4 decades, have failed, all of them. And the foundation of trumped up AGW theory, the CO2 / temperature correlation, has been debunked (see algor repeat the lie: http://www.youtube.com/watch?v=WK_WyvfcJyg). The hockey has been shown to be a fabrication. There is nothing wrong with the climate.
    What amazes me is just a few short years ago nearly everybody seemed to be going along with the scam, even conservatives. Now skeptic Senator Inhofe’s position on climate change is the “new normal,” and he is leading the way: http://epw.senate.gov/public/index.cfm?FuseAction=Minority.Blogs&ContentRecord_id=eb26d140-802a-23ad-4a8f-cc2a20647095.
    But, amazing yet so sad quote from the link, Inhofe said: “I was all alone starting in 2001. When you’re an army of one you don’t get much attention.” How was it that the leftist econuts and their liberal political allies duped conservatives, virtually across the board?? Someone needs to tell the story.

  67. Roger Longstaff @ June 14, 2012 at 7:33 am

    I think the problem is that your question asked whether they thought it was reasonable practice to use numerical models that use low pass filters for multi-decadal forecasts. According to both their answer and the paper you mentioned, a filter is used specifically on the model output. This means that even though filtering, smoothing, averaging etc will remove information from the model output, this will only happen after that output has been fully calculated by the model.

    Thanks for pointing out the discussion on Tamsim’s blog – it is very interesting and Tamsin’s style is very nice and friendly. I notice that Judith Curry has a comment at June 14, 2012 – 3:49 pm, which is asking the questions that interest me, plus quite a few others that I should be interested in. Again, I think the crucial issue is the low decadal variability in the models.

  68. John Ray quote from 2009 on the longest temperature record ever, that of Central England:

    “It is clearly a random walk and any trend up or down is a statistical creation rather than anything real.”

    http://www.stoptheaclu.com/2009/11/28/30129/

    His entire series of news digest blogs presents a calmly welcome break from the statistics bickerfest that skeptics risk addiction to, starting with http://antigreen.blogspot.com and branching out to academic politics and medical report skepticism that oft ridicules epidemiology as statistical dredging.

  69. > how numerical models can be “low skill” over short timescales but could possibly be accurate enough to justify massive intervention over multi-decadal timescales?

    Simple really… It’s easy to confirm the (non)accuracy of a model over short timescales. By the time ‘multi-decades’ have passed, no one will remember the model as it will have been replaced a few hundred times. But for now, one can claim the current long-view model to be accurate, secure in the knowledge that no one can prove that it is not.

  70. In regards to:

    A fan of *MORE* discourse says:
    June 14, 2012 at 6:22 am

    Your analogy of fluid dynamics over a wing is not appropriate for predicting climate. To make it more compatible, you would have to have a wing that changed shape in response to the chaotic flow, so that the next calculation of the model was not just applying a new flow, but a new flow over the new shape predicted in the previous calculation. Any error generated in the computation of the new shape of the wing would be carried forward into the next calculation of the wing shape and so on. Soon…you will have a shape that is nothing like a wing, unless you create a function in the program that ‘forces’ a wing shape over time.

    Daily prediction models do this. The further out in time they try to predict, the more powerful climatology becomes in the calculation, otherwise the models would run off into ridiculous solutions beyond 7-10 days.

    It has been argued that climate models are different than forecasting models in that they are not dependent on initial conditions. In other words, forecasting models begin with an initial sampling of the global atmosphere and run it out into the future. Climate models, it is argued, are a snapshot of the atmosphere under different conditions, like a snapshot of the turbulent flow of air over a wing at any given wind speed. But this argument ignores the multiple feedbacks inherent in the climate system, particularly clouds and the water cycle. These feedbacks create a ‘changing wing’ in climate models and any calculation of climate over time will be dependent on the previous calculation and subject to every increasing error.

    So even if all the assumptions about the atmosphere, Earth, Sun, cosmic rays and so on, were absolutely correct, then the models would only be AS accurate as the random walk models, for they would still be subject to escalating feedback errors.

    The fact that the models are so much worse than a random walk is proof that one or more of the assumptions (or equations) are incorrect!

  71. John F. Hultquist says:
    June 14, 2012 at 8:10 am
    “This post and comments include statements with the terms random and chaotic with regard to weather and climate. I wonder who gets to define the terms, outcomes, and miss or match of the results? For example, if the weather forecaster looks at a computer output and it says the High Temp for tomorrow will be X.23 and then posts X and then the actual High comes as X +2, is that forecast considered wrong?”…

    There have been studies into the accuracy of weather predictions and there’s an extensive literature dealing with forecast verification. See for example the paper “Verification of The Weather Channel Probability of Precipitation Forecasts” by J. Eric Bickel and Seong Dae Kim. They used a “distribution-oriented” framework proposed in: Murphy, A. H., and R. L. Winkler,:

    Murphy, A. H., and R. L. Winkler, 1977: Reliability of subjective
    probability forecasts of precipitation and temperature. Appl.
    Stat., 26, 41–47.
    ——, and H. Daan, 1985: Forecast evaluation. Probability, Statistics,
    and Decision Making in the Atmospheric Sciences, A. H.
    Murphy, and R. W. Katz, Eds., Westview Press, Inc., 379–437.
    ——, and R. L. Winkler, 1987: A general framework for forecast
    verification. Mon. Wea. Rev., 115, 1330–1338.
    ——, and ——, 1992: Diagnostic verification of probability forecasts.
    Int. J. Forecasting, 7, 435–455.

  72. Kevin Kinser says:
    June 14, 2012 at 8:02 am

    …This is a welcome methodological critique of models, not of the science behind them.

    From the original paper’s conclusions:
    “…there is no support in the evidence we present for those who reject the whole notion of global warming: the forecasts still remain inexorably upward, with forecasts which are comparable to those produced by the models used by the IPCC.”

    From the postscript:
    “Climate change is a major threat to us all, and this requires the IPCC community of climate modellers to be more open to developments and methods from other fields of research.”

    Kevin…I have seen quotes like these in almost every study that weakens the AGW theory. Some studies have produced evidence that directly contradicts the theory, like the study that indicated Antarctic cooling, and then pronounce in the conclusion that it does not contradict the AGW theory and that AGW is an extremely dangerous situation that needs further study.

    Are these statements derived from the results of their research? No! They contradict the research! Authors make these statements because they like their friends, their jobs and their paychecks.

  73. Pielke Sr. has been pointing this (more or less) out for as long as I’ve been reading his blog – climate models show no skill, over and over again. Unfortunately, if they aren’t listening to him, they aren’t going to listen to anybody. It’s pretty sad.

  74. Mark Bofill says:
    June 14, 2012 at 10:06 am
    Pielke Sr. has been pointing this (more or less) out for as long as I’ve been reading his blog – climate models show no skill, over and over again. Unfortunately, if they aren’t listening to him, they aren’t going to listen to anybody. It’s pretty sad.”

    It doesn’t benefit them one bit to listen to an alternative explanation. That doesn’t pay their bills.

  75. Jim Clarke says:
    June 14, 2012 at 9:59 am

    “Are these statements derived from the results of their research? No! They contradict the research!”

    The study did not address the theory. It addressed the models. The authors are clarifying this so that people would not misunderstand their conclusions. Both published commentaries touch on this, so the authors emphasize it again in the postscript. It would be going beyond their data to conclude that the science behind the models is incorrect. You may infer this, but it is empirically unjustified based on the research they did.

  76. Jim Clarke says: “Your analogy of fluid dynamics over a wing is not appropriate for predicting climate. To make it more compatible, you would have to have a wing that changed shape in response to the chaotic flow, so that the next calculation of the model was not just applying a new flow, but a new flow over the new shape predicted in the previous calculation.”

    Jim, your assertion is just plain wrong-on-the-facts. Existing computational fluid dynamics (CFD) simulations *DO* take into account the nonlinear deformation, both static and dynamic, of wings under aerodynamic loading … this aeroelastic forcing is the CFD analog of climatological forcing.

    As documented on Judith Curry’s weblog, aeroelastic forcing can be exceedingly large and grossly nonlinear, and none-the-less be accurately simulated.

  77. On her blog, Dr. Tamsin Edwards has kindly given me a reference to The UK Met Office code:

    http://cms.ncas.ac.uk/code_browsers/UM4.5/UMbrowser/

    “This version of the Met Office model (v4.5, HadCM3, 1999) was used for the UK Climate Projections: UM 4.5 code.

    [Edit 17:12 – This is also the version we are using in our estimate of climate sensitivity.] Similar versions (such as lower resolution) have been used by climateprediction.net. It is available for academic use, subject to signing a licence agreement. This version is much faster than the current generation so is still used a lot for large groups (ensembles) of simulations, palaeoclimate studies and other areas where you need a lot of, or long, simulations. See for example the Met Office and climateprediction.net model pages.

    The Unified Model is now up to about version 8.2, I think, for operational weather forecasting. IPCC runs for AR5 were done with v6.6 (HadGEM2-ES).”

    I thank Dr. Edwards for this, as it is something that I have requested for a long time.

  78. A fan of *MORE* discourse . You write “Yet global climate changes are constrained by strict conservation of mass and energy and global increase in entropy, and thus *CAN* be predicted.”

    I see others have been ahead of me in pointing out that this is utter garbage. It will be interesting to see whether you try and respond to them, here on WUWT, as you did with me on Climate Etc. I suspect on this forum, you will simply disappear.

  79. That’s a nice graph you have there. Very evenly splayed out. Did you pick it yourself? :)
    Go on, tell us. How many runs DID you try until you found that nice one?

    johnwdarcher,

    The graph that Anthony included in the post is the example graph from the Wikipedia article that he linked to which explains what a Random Walk is.

  80. Anthony and/or mods, you may want to note that the graph in the post is sourced from Wikipedia, to put silly speculation like that from johnwdarcher to rest..

  81. mt says:
    June 14, 2012 at 7:59 am

    @RockyRoad read the paper. As far as I can tell, they’re giving scores based on looking at future data (2007-2017 and 2007-2027). How is it possible to say what model is “right” and “wrong” versus data that doesn’t yet exist?

    Last time I looked at my calendar, “2007” is a number less than “2012”. By 5, to be exact.

  82. Jim Clarke says:
    June 14, 2012 at 9:41 am
    The fact that the models are so much worse than a random walk is proof that one or more of the assumptions (or equations) are incorrect!

    This has not been shown, so this ‘proof’ fails!

  83. George E. Smith; says:
    June 14, 2012 at 9:08 am

    “””””…..ferd berple says:

    June 14, 2012 at 7:07 am

    Philip Richens says:
    June 14, 2012 at 2:27 am
    Pretty certain that what RB has in mind is that (A) short term random noise (white noise) prevents models from making accurate forecasts over weeks and months and (B) the white noise is averaged out over climate time scales (decades)
    =========
    Correct, the climate models make the assumption that climate is normally distributed (constant mean and deviation), that the errors plus and minus average out over time……”””””

    Well white noise may average out to zero after long time scales; but only in mathematical models, which have a Gaussian distribution. Physical systems don’t have such an ultimate error distribution. Most of them eventally show the presence of 1/f noise, where the amplitude of an error or step, can grow without limit, but at an occurrence frequency that is inversely proportional to the size of the error or step. One can make the argument that 1/f noise is a consequence of Heisenberg’s Principle of Uncertainty. Maybe the Big Bang, was simply the bottom end of the 1/f noise spectrum.

    So in real physical systems, noise does not average out to zero no matter how long you wait, because there is always the chance of a step much greater than anything previously seen. And no; 1/f noise does not violate any thermodynamic limits, such as the total power or energy growing without limit, which it would in a white noise system. It is simple mathematics, to show that with 1/f noise each octave of frequency range contains the same amount of power as any other, no matter how large the amplitude gets.

    Perhaps then the exercise should be repeated with a ‘Levy Flight’ random walk with fatter tails to the Gaussian distribution?

  84. Kevin Kinser says:
    June 14, 2012 at 10:32 am

    “It would be going beyond their data to conclude that the science behind the models is incorrect. You may infer this, but it is empirically unjustified based on the research they did.”

    I guess what you and the authors are arguing is that the ‘science’ and the ‘models’ are two very different things, and that the science could be right even if the models are wrong! I guess that is possible, but it also creates quite the conundrum, because the reverse is also true. The models could be right, even if the science is wrong (as was the case with epicycles and celestial movement).

    In order to use the scientific method, however, we have to test the theory with prediction and then see if the prediction holds. In the case of climate change, the models are the prediction. If we can not equate the models with the prediction derived from the theory, then there is no way to falsify the theory and it is not science.

    So we have two choices:

    1. We can adhere to the scientific method, consider the models are giving us a prediction of the theory and, as the models fail to make accurate predictions, conclude that there is a problem with the theory and that it needs to be revamped.

    2. We can conclude that as the models fail to verify, that the theory is still strong and there is something wrong with the mechanics in the software, even though there is no evidence for a robust theory.

    You and the authors are asking all the world to join a cult and pay hefty dues. I feel quite rational and justified in calling the theory into question based on the performance of the models.

  85. Phil. says:
    June 14, 2012 at 12:29 pm

    Jim Clarke says:
    June 14, 2012 at 9:41 am
    The fact that the models are so much worse than a random walk is proof that one or more of the assumptions (or equations) are incorrect!

    This has not been shown, so this ‘proof’ fails!

    But nowhere, Phil, have you been able to show that the [climate] models are BETTER!

    That’s the crux of this whole issue.

  86. It is true that GCMs forecast catastrophe by taking tiny CO2 molecular inputs and amplifying them with water vapor and clouds in mysterious ways. Suggesting ways to further “tune” the models to reality, and to get forecasts which are at least as likely to match regional weather events as a “random walk,” is going to fall on deaf ears. Because they still need to make a mountain out of a molehill-inator.

    http://zekeunlimited.wordpress.com/2012/06/14/dr-doofenschmurtz-evil-inc-unveils-the-mountain-out-of-a-molehill-inator-plans-to-take-over-the-entire-tri-state-area/

  87. CTL,

    The graph that Anthony included in the post is the example graph from the Wikipedia…” [CTL]

    Whoops! Thanks. I missed that. So it was Wiki that cherry picked the graph, not Anthony.

    Not that there’s anything wrong in doing that though. One would naturally choose a ‘nice’ example for illustrative purposes so that the general features were brought out clearly.

    Earle Williams,

    By the way, while walking into my building this morning, I passed a car with a the tag number of FTH 336. What are the odds of that?” [EW]

    Depends. But seeing as it was near your building there’s probably a fair chance that it belongs to one of your colleagues or someone else who works close by so I’d guess the probability was pretty high, and higher if you are habitually late. But it might have been a client’s or customer’s for all I know, so it depends on how often he drops by and what time he likes to arrive. And so on for other possibilities. But you know your environment far better I do.

    Monitor it for a week or a fortnight though. That should give you a rough idea. But it strikes me as little odd that you bother with such distractions. Try to focus on things that are more important to you is my advice.

    …that graph in the post is sourced from Wikipedia, to put silly speculation like that from johnwdarcher to rest…” [EW]

    “Silly”? Never mind my mistaken attribution, there was nothing silly about my speculation. 100 to 1 says that graph was cherry-picked  by whoever did it. There were only 8 random walks in it. That’s far too low a number to get a nice symmetric fan shape like the one shown just by chance. If you don’t believe me, run a few simulations yourself and see how many runs you need to get a ‘nice’ one like Wiki’s.

    Randomness generally produces ugly patterns if left to itself when the number of ‘options’ available is small. For example, if you ever decide to tile a wall with a random pattern made with tiles of, say, only four different colours then you’d be well advised not to actually place them at random but rather to plan ahead and tweak the pattern. If you don’t you’ll end up with noticeably large ugly sub-configurations of the same colour. Again, if you don’t believe me run a simulation yourself on a grid of, say, 20 x 20 cells.

    Finally, a question for you: did you bother to look at the image in the link I gave?

  88. old construction worker says:
    June 14, 2012 at 12:16 am

    Climate Models: If a frog had wings,……….

    Would they be pigs?

  89. [2nd attempt]

    CTL,

    The graph that Anthony included in the post is the example graph from the Wikipedia…” [CTL]

    Whoops! Thanks. I missed that. So it was Wiki that cherry picked the graph, not Anthony.

    Not that there’s anything wrong in doing that though. One would naturally choose a ‘nice’ example for illustrative purposes so that the general features were brought out clearly.

    Earle Williams,

    By the way, while walking into my building this morning, I passed a car with a the tag number of FTH 336. What are the odds of that?” [EW]

    Depends. But seeing as it was near your building there’s probably a fair chance that it belongs to one of your colleagues or someone else who works close by so I’d guess the probability was pretty high, and higher if you are habitually late. But it might have been a client’s or customer’s for all I know, so it depends on how often he drops by and what time he likes to arrive. And so on for other possibilities. But you know your environment far better I do.

    Monitor it for a week or a fortnight though. That should give you a rough idea. But it strikes me as little odd that you bother with such distractions. Try to focus on things that are more important to you is my advice.

    …that graph in the post is sourced from Wikipedia, to put silly speculation like that from johnwdarcher to rest…” [EW]

    “Silly”? Never mind my mistaken attribution, there was nothing silly about my speculation. 100 to 1 says that graph was cherry-picked  by whoever did it. There were only 8 random walks in it. That’s far too low a number to get a nice symmetric fan shape like the one shown just by chance. If you don’t believe me, run a few simulations yourself and see how many runs you need to get a ‘nice’ one like Wiki’s.

    Randomness generally produces ugly patterns if left to itself when the number of ‘options’ available is small. For example, if you ever decide to tile a wall with a random pattern made with tiles of, say, only four different colours then you’d be well advised not to actually place them at random but rather to plan ahead and tweak the pattern. If you don’t you’ll end up with noticeably large ugly sub-configurations of the same colour. Again, if you don’t believe me run a simulation yourself on a grid of, say, 20 x 20 cells.

    Finally, a question for you: did you bother to look at the image in the link I gave?

  90. Why are we referencing Wikipedia? Are we trying to embarrass ourselves? Can we please reference valid sources that cannot be edited by anyone with an Internet connection.

  91. @A fan of *MORE* discourse
    “As documented on Judith Curry’s weblog, aeroelastic forcing can be exceedingly large and grossly nonlinear, and none-the-less be accurately simulated.”

    ++++++++

    Given this fact, what explanation remains for the inability of the models to generally predict temperature over a decade or longer? To me, it seems to be the math that is supposed to be capturing the physical relationships. If complex modelling works (I use it in combustion analysis and heat transfer which is pretty darned hard) then we can take it that the framework as reasonable. Plugging the relationships into the framework is giving the wrong answer. They must some physical understanding fundamentally wrong.

    One plus one = CO2.

  92. Jim, your assertion is just plain wrong-on-the-facts. Existing computational fluid dynamics (CFD) simulations *DO* take into account the nonlinear deformation, both static and dynamic, of wings under aerodynamic loading … this aeroelastic forcing is the CFD analog of climatological forcing.

    As documented on Judith Curry’s weblog, aeroelastic forcing can be exceedingly large and grossly nonlinear, and none-the-less be accurately simulated.

    Why are you linking to “comments” at another site? Your video does not look like a simulation but a real world test. Let me know which passenger airliner was cleared safe to fly based only on computer simulations.

  93. Reblogged this on evilincandescentbulb and commented:
    We are witness to is a classic example of Marshall McLuhan’s the Medium is the Message. The Left can never take back what it has done to Mr. Smith and Mrs. Jones and all of the other victims of the Left’s liberal fascism. Mr. Smith went to Washington to fight the science authoritarians, to save lives. How many lives has the Left saved by saying NO to truth and NO, NO, NO to capitalism? How much misery, poverty and death has the Left caused by sacrificing individual liberty on the altar of the blindingly self-defeatist Climatism of Leftist ideology?

    Expect Us to Take Their Little ‘Red’ Pills Forever

  94. This is all anyone needs to know about the computer illiterates programming the climate models,

    http://www.nature.com/news/2010/101013/full/467775a.html

    “Researchers are spending more and more time writing computer software to model biological structures, simulate the early evolution of the Universe and analyse past climate data, among other topics. But programming experts have little faith that most scientists are up to the task. […]

    …as computers and programming tools have grown more complex, scientists have hit a “steep learning curve”, says James Hack, director of the US National Center for Computational Sciences at Oak Ridge National Laboratory in Tennessee. “The level of effort and skills needed to keep up aren’t in the wheelhouse of the average scientist.”

    As a general rule, researchers do not test or document their programs rigorously, and they rarely release their codes, making it almost impossible to reproduce and verify published results generated by scientific software, say computer scientists. […]

    Greg Wilson, a computer scientist in Toronto, Canada, who heads Software Carpentry — an online course aimed at improving the computing skills of scientists — says that he woke up to the problem in the 1980s, when he was working at a physics supercomputing facility at the University of Edinburgh, UK. After a series of small mishaps, he realized that, without formal training in programming, it was easy for scientists trying to address some of the Universe’s biggest questions to inadvertently introduce errors into their codes, potentially “doing more harm than good”. […]

    “There are terrifying statistics showing that almost all of what scientists know about coding is self-taught,” says Wilson. “They just don’t know how bad they are.”

    As a result, codes may be riddled with tiny errors that do not cause the program to break down, but may drastically change the scientific results that it spits out.

  95. Just out of interest, because I’m a little surprise I missed it, but was that attribution of the graph to Wiki in place when I made my first comment or was it put up afterwards?

    REPLY: I added it because some folks were getting confused. The link to the Wikipedia article on random walks was there originally, but I suppose some folks didn’t follow it to see that the graph also came from there. My mistake for not making it crystal clear in the first place. – Anthony

  96. This paper [Validation and forecasting accuracy in models of climate change] does a poor job phrasing skeptic arguments,

    “From a scientific perspective, disbelief in global warming is found in the work of the Heartland Institute and its publications (Singer and Idso, 2009) and supported by the arguments of a number of eminent scientists, some of whom research in the field (see Lindzen, 2009)”

    It is not “disbelief” in “global warming” but skepticism in “anthropogenic global warming alarm”.

  97. Poptech says: Let me know which passenger airliner was cleared safe to fly based only on computer simulations.

    LOL … Poptech, in aircraft design, computational simulation has replaced “only” 90% of wind-tunnel testing.

    It’s pilot training that is now done 100% on simulators.   :)

    Yes, it’s completely possible — even common nowadays — for a commercial pilot’s first “real” 787 flight to have paying customers aboard.

    The reason makes perfect sense — simulation training is superior in detail-and-depth to flying the real thing.

  98. Poptech,

    This is all anyone needs to know about the computer illiterates programming the climate models…” [Poptech]

    That problem with scientists and programming is decades old as you probably know anyway, but it’s taken Nature that long to find out!? — assuming that’s their first piece on it (but I wouldn’t know).

    I’ve seen this from both sides as for a short while I did a stint as a analyst/programmer in industry when I was very young. (It wasn’t called IT in those days.) You’d get a good bollocking if you broke documentation, coding or annotation standards. Rightly too. And sacked quickly if you showed any hint of persistence at it. But you found out PDQ why they are an absolute necessity. Yes, I learnt that the hard(ish) way, but very quickly. “Programming is easy; anyone can do it.” Well, certainly much of it is but that isn’t the point. The point is can someone else pick up from where you left off (can you yourself?), i.e. without having to read through a load of spaghetti code you wouldn’t feed to a dog trying to work out what the hell is going on and at what stage things are at, or worse, going right back and starting from scratch again, which is the only sensible thing to do under those circumstances. Subsequent changes in specification and the resulting updates are inevitable so the thing needs to be designed with those in mind. Blah blah blah…  And your time is someone else’s MONEY!

    Then jump back into a science environment where everyone is his own god when it comes to systems and programming. What a f..king mess! The worst kind are the prima-donna cleverdicks — they’re the real dummies, and can be very secretive too! Precious, eh? And fun to work with? But it’s impossible to convey to any of them why things need to change. You can explain it all you like but it makes no difference. What they’re doing at the moment is far more important than “mere housekeeping”. If someone leaves and someone else has to pick up the work? “It’s just programming isn’t it?” Right. No. Wrong. In fact, you couldn’t be wronger.

    Get out of that environment as fast as you can before you kill someone. I did.

  99. David L. says:
    June 14, 2012 at 9:52 am
    “There have been studies into the accuracy of weather predictions . . .

    Thanks, David.

    I looked a bit and also found this:

    http://www.climas.arizona.edu/feature-articles/january-2008

    with a link to:

    http://www.cawcr.gov.au/projects/verification/

    . . . that even shows an upcoming meeting for April 2013.

    All more than I have time for today. After several days of winds, with gusts to 40+, they slowed to about 10 mph today. I took the opportunity to clear brush under big old cottonwoods.

  100. Until the “scientists” can input the “butterfly wing beat” and about a million other data points, no climate/weather model, will work further than a week out……

  101. LOL … Poptech, in aircraft design, computational simulation has replaced “only” 90% of wind-tunnel testing.

    That is not what I asked, strawman. Nice video though of an action experiment not done on a computer simulation.

    It’s pilot training that is now done 100% on simulators. :)

    Yes, it’s completely possible — even common nowadays — for a commercial pilot’s first “real” 787 flight to have paying customers aboard.

    The reason makes perfect sense — simulation training is superior in detail-and-depth to flying the real thing.

    This is a red herring to my actual question. So someone never actually flies a real aircraft before becoming a pilot and flying real passengers for the first time? Or are you just talking about pilots already certified to fly other aircraft? There is a big difference.

  102. A fan of *MORE* discourse says:
    June 14, 2012 at 6:40 pm
    The reason makes perfect sense — simulation training is superior in detail-and-depth to flying the real thing.

    Speaking as both a pilot and a sim operator — bullshit. A simulator training program is only as good as its replications of real life. The random factors involved in actual flight are what kill people who have only been trained in simulators.

    Two examples:

    1. Sim training for the A320 don’t include stalls because Airbus insists the computers will prevent the aircraft from stalling — but most accidents in Airbuses were caused by computer malfunctions which resulted in stalls.

    2. Sim training for the V-22 is based on parameters which assume the tilt-props would function like rotors when the aircraft is in “helicopter mode.” Aircraft acceptance was based entirely on sim flights, and it was only after several Class A fatals that someone actually did some digging into the sim program — the program parameters did not match test flight data from the actual aircraft.

    The manufacturers’ solutions in both instances was *not* to correct errors in the training syllabus or the sim program, they were instructions to the pilots to avoid getting into situations which might result in the aircraft crashing.

  103. Poptech says:
    June 14, 2012 at 11:34 pm
    This is a red herring to my actual question. So someone never actually flies a real aircraft before becoming a pilot and flying real passengers for the first time? Or are you just talking about pilots already certified to fly other aircraft? There is a big difference.

    There *is* a big difference.

    In student pilot training, both sims and static flight training devices (FTD) are great tools to teach the fledgling proper engine starting procedures and flight control application and correlation. In rated pilot transitions, they knock a couple of hours off cockpit familiarization drills for pilots transitioning into an advanced aircraft, which allows the instructor pilot to concentrate on maneuver and emergency procedures training.

    Sims have three huge advantages over an actual aircraft — they’re cheaper to operate, they eliminate the “fear factor” of dying if the trainee performs emergency procedures incorrectly or too slowly, and they’re perfect for instrument flight training.

  104. A fan of *MORE* discourse says:
    June 14, 2012 at 6:40 pm
    Yes, it’s completely possible — even common nowadays — for a commercial pilot’s first “real” 787 flight to have paying customers aboard.

    And that commercial pilot will have already accumulated at least 6,000 hours flying a multiengine jet aircraft — the sim is just the stepping-stone to another aircraft transition.

    And the reason the B-787 was delivered years past its original rollout date is because

    1. Boeing discovered airframe and structural problems during flight testing in areas that surprised the hell out of the computer design team,

    2. the aircraft suffered at least two in-flight fires due to excessive heat buildup in the computer-designed wiring bundles, and

    2. the computer-designed Rolls Royce engines didn’t work as specified — none of them were capable of producing the power required and one of them exploded the first time it was run up on the aircraft.

  105. In their paper, Fildes and Kourentzes commit the error of conflating projections with forecasts. The climate models make projections and not forecasts.

  106. Re scientists and programming.

    I should have added the following to my previous post to end on a positive note.

    Years later, but still decades ago now, and when I had more say in things, I had the pleasure of working with a real IT pro far more experienced than I was. I did the the core specifications in outline but he and his team did everything else, and beautifully too. It was an iterative process, as is inevitable, but the number of iterations was minimal. We understood each other perfectly as each knew what the other had to achieve. Everything he did was superb and testing was a delight. We got on like a house on fire and the whole thing was a great success. So, a positive ending.

    Well not quite. That was the first and last time it happened like that, for me anyway. So it was something of an organisational fluke I suppose.

  107. Bill Tuttle says:
    June 15, 2012 at 2:26 am

    I have sim time in B757 and B767. They are easy to ‘fly’ on instruments (with both engines turning). The emergency procedures manual for a seven five contains more information than did the entire flight manual for the high performance single engine retract I once owned. I have far more confidence in a flight simulator than I do in any climate model program. Far more.

  108. John Archer says:
    June 15, 2012 at 7:53 am

    Re scientists and programming.

    I should have added the following to my previous post to end on a positive note.

    Years later, but still decades ago now, and when I had more say in things, I had the pleasure of working with a real IT pro far more experienced than I was. I did the the core specifications in outline but he and his team did everything else, and beautifully too. It was an iterative process, as is inevitable, but the number of iterations was minimal. We understood each other perfectly as each knew what the other had to achieve. Everything he did was superb and testing was a delight. We got on like a house on fire and the whole thing was a great success. So, a positive ending.

    Well not quite. That was the first and last time it happened like that, for me anyway. So it was something of an organisational fluke I suppose.

    More importantly you have just outlined the way scientific research at major universities ought to be setup. They University or R&D consortium should have a professional IT staff on the pay roll to support the research teams. The researchers might cobble out useable test code on their own to develop ideas, then once they are satisfied there is some merit to their methodology they should be “required” as part of their performance objectives of the research to sit down with an IT department software development representative to prepare software requirements documents that formalize the requirements for a professionally coded software module that does the required computations they have outlined.

    Then when the research is complete, they should be “required” to turn in the final research paper, along with the supporting computer code and the final software requirements documents that defined the functionality for their code so it can be tested and validated by any outside researcher to demonstrate that :
    a) The code does what the code requirements document says it should
    b) That the code actually produces the output the research report says they did
    c) That the code does not have some hidden flaw in logic or math that produces the intended output without introducing spurious errors, biases or statistical abuse of the data.

    There obviously also needs to be an in house statistics resource to help the researcher make proper use of complex statistical analysis which should audit and “sign off” on the research that it meets good practice in statistical analysis.

    Will that happen ?
    — not likely but it is a worth while objective to find a mechanism to as in medicine realize that there are sub-specialties which need to be addressed by specialists.

    Today the research task is conducted as if a general practitioner in medicine was doing brain surgery and eye ear nose and throat all at the same time.

    At least in the medical field it is recognized and considered professionally appropriate for doctors to hand off specialized areas of expertise to other colleagues who have the necessary skill sets to properly handle them. Let the researchers do what they do best — be idea men/women, come up with concepts and objectives to investigate a new line of research but hand off the grunt work of best practice computer coding to someone who does that for a living to work as a consultant to the researcher. Let the coder code and the researcher research.

    To use a building trade analogy the researcher should be like the architect who envisions a new building, but he has engineers detail the actual structure and tradesmen skilled in specialties like framing, masonry, plumbing, heating and air conditioning etc. actually do the construction of the structure. The architect gets the awards for developing the concept and shepherding it through to completion, but the actual construction steps were performed by specialists (not unpaid graduate students or interns who are in fact still learning their craft).

    Larry

  109. Babsy says:
    June 15, 2012 at 8:47 am
    I have sim time in B757 and B767. They are easy to ‘fly’ on instruments (with both engines turning). The emergency procedures manual for a seven five contains more information than did the entire flight manual for the high performance single engine retract I once owned. I have far more confidence in a flight simulator than I do in any climate model program. Far more.

    I used to troubleshoot sim glitches in the old Singer-Link mechanical “Blue Canoe” for First US Army, and the basics for writing a good sim program all date from the days when somebody decided that seat-of-the-pants flying in the clouds was suicidal. A well-written flight sim program is a dream to work with — the one for the Mi-8MTV-1 I’m running now is *not* a well-written program.

    And you’re right — even a poorly-written flight sim program will consistently give you acceptable results.

  110. RockyRoad says:
    June 14, 2012 at 2:14 pm
    Phil. says:
    June 14, 2012 at 12:29 pm
    Jim Clarke says:
    June 14, 2012 at 9:41 am
    The fact that the models are so much worse than a random walk is proof that one or more of the assumptions (or equations) are incorrect!
    This has not been shown, so this ‘proof’ fails!

    But nowhere, Phil, have you been able to show that the [climate] models are BETTER!

    That’s the crux of this whole issue.

    They certainly are better than a random walk, which they haven’t been compared with. In his intro Anthony correctly describes a random walk, however the paper doesn’t compare against a random walk. In the linked commentary, as well as getting the name of the journal wrong, McKitrick describes a random walk thus: “consisting simply of using the last period’s value in each location as the forecast for the next period’s value in that location”, this is not a random walk, not even close, compare it with Anthony’s correct description.

  111. Phil. says:
    June 15, 2012 at 10:48 am
    They certainly are better than a random walk, which they haven’t been compared with. In his intro Anthony correctly describes a random walk, however the paper doesn’t compare against a random walk.

    The paper *does* say that plotting random numbers — “using the last period’s value in each location as the forecast for the next period’s value in that location” — resulted in a more accurate forecast than those produced by the models.

  112. “A fan of *MORE* discourse” needs to do better research. It looks like an epic failure for computer modeling (I am not surprised),

    Boeing 787 wing flaw extends inside plane
    Another 787 design flaw
    Electrical fire forces emergency landing of 787 test plane
    Dreamliner’s woes pile up
    ANA 787 lands safely after landing-gear trouble
    What’s Causing Huge Delays for the Boeing 787 Dreamliner?

    Virtual Model Failed

    At times, those issues were design related. One example is the failure of wing joints on both sides of the plane to perform as predicted in virtual models meant to speed the development process, and allow for concurrent engineering.

    “We do testing for a reason. And that’s because models aren’t perfect,” says Scott Fancher, Boeing 787 program general manager.

    Patrick Shanahan, vice president and general manager, Airplane Programs, Commercial Airplanes, adds, “We’ll go back and look at where the model failed to predict this situation (wing stress). And (then) tune them up.”

    Sounds like climate modelers.

  113. I find the following statement by the (admittedly articulate) Jim Clarke to be the perfect culmination (to this point) of the most important exchange in this whole comment thread, and one that simply exemplifies again for me the fundamental cognitive deficiencies in those who reject the science showing the hazards of anthropogenic global warming.

    Jim Clarke says:

    ***Are these statements [where Fildes and Kourentzes affirmed the fundamental science of CO2 as a primary driver of climate change and the dangers inherent from it] derived from the results of their research? No! They contradict the research! Authors make these statements because they like their friends, their jobs and their paychecks.***

    Jim: How the *hell* do you know that?

    What is *really* more likely–that Fildes and Kourentzes are psychically intimidated into denying the conclusions of their research because the “warmist” conspirators will take away their jobs and/or social standing, or that *you* just don’t understand what they are saying? Seriously, which is *really* more likely? I seriously doubt you read their whole article, Jim. (I read as much as I could grasp, which was certainly not all of it, I’ll admit.)

    And your conflation of “theory” and “model” is just . . . (what is a polite word?) . . . unsound. Here’s an analogy:

    I have a “theory” that the gunpowder in the shell of a firearm is a “primary driver” of the round into the target. But I doubt an adequate “model”–computer generated or otherwise–could ever perfectly *predict* exactly where the round will land. But whether it strikes a human in the ear or the temple does not make them any less dead one way or the other.

    It’s the same with climate change: sure enough, it *might* be that prevailing models overestimate climate sensitivity, it ends up being not that big a deal, and increased global temperatures and it’s associated ills are managed fine without any heroic interventions. (Maybe an unforeseen factor such as a gust of wind will take the bullet off target and spare the target’s life.) Great. No one will be happier about it than I.

    Maybe. *Or*, our climate models are wrong in the *opposite* direction–that we are taking an even *bigger* chance with our environment than we realize. Maybe–just maybe Jim–this is why Fildes and Kourentzes affirmed the fundamental science of CO2-induced climate change *and* it’s associated risks–and that this is why we should continue to develop and improve climate models.

    But you seem to know better, don’t you Jim? You can read between the lines of an article you skimmed (at best) and determine where the authors are telling you what they really think (such as when they seemingly debunk climate modeling–the part you like) and when they’re towing a “party line”. An amazing talent, that–and one that a number of self-described climate “skeptics” seem to have.

    And of course the administrator of this site simply (and of course incorrectly) linked to the *Journal of Forecasting*, blithely assuming the 2011 article proved his point, but course it was the wrong journal, showing that AW, whatever his merits as an individual, did not read the original article. He just saw, believed, and linked.

    Why did I bother posting this? Not entirely sure, really. It’s just a question of time before AW censors me.

  114. Poptech says:
    June 15, 2012 at 11:07 pm
    A fan of *MORE* discourse” needs to do better research. It looks like an epic failure for computer modeling (I am not surprised),
    Patrick Shanahan, vice president and general manager, Airplane Programs, Commercial Airplanes, adds, “We’ll go back and look at where the model failed to predict this situation (wing stress). And (then) tune them up.”
    Sounds like climate modelers.

    Ay-up. A bud at the NTSB once told me an aero engineer complained to him that the CG schematics for one particular airplane required attaching sections of composite skin to the aluminum airframe without using rivets, because the composites would de-bond at the rivet holes. Problem was, an adhesive with the requisite temperature + strength + bonding characteristics didn’t exist.

    The modeler told him, “You’re the engineer — invent it.”

  115. Next up on WUWT: Afo*M*d checks in with an exposition of how the improved graphics in Flight Simulator XXI demonstrate continuing improvement in climate modeling…

  116. rgbatduke says:

    June 14, 2012 at 8:50 am

    “To which the physics professor then replied, “Not even you with all of your philosophy and the pen in hand can do that — but at least I understand why.”

    Who is it, after all, that drops the pen?”

    That’s excellent! I wish I could travel back in time and use that on the philosophy prof.!

  117. snaparooni says:
    June 16, 2012 at 3:39 am
    rgbatduke at June 14, 2012 at 8:50 am: “To which the physics professor then replied, “Not even you with all of your philosophy and the pen in hand can do that — but at least I understand why.”
    Who is it, after all, that drops the pen?”
    That’s excellent! I wish I could travel back in time and use that on the philosophy prof.!

    Actually, the “why” he drops the pen is the province of philosophy. The “how” he drops the pen is the physics prof’s bailiwick.

    Unless, of course, the physics prof had previously observed the philosophy prof eating popcorn and realized his fingers were still coated with butter…

  118. skip says:
    June 16, 2012 at 1:35 am
    Maybe–just maybe Jim–this is why Fildes and Kourentzes affirmed the fundamental science of CO2-induced climate change *and* it’s associated risks–and that this is why we should continue to develop and improve climate models.

    You first have to *prove* CO2-induced climate change exists before you can affirm it.

  119. Bill Tuttle says:
    June 15, 2012 at 11:33 am
    Phil. says:
    June 15, 2012 at 10:48 am
    They certainly are better than a random walk, which they haven’t been compared with. In his intro Anthony correctly describes a random walk, however the paper doesn’t compare against a random walk.

    The paper *does* say that plotting random numbers — “using the last period’s value in each location as the forecast for the next period’s value in that location” — resulted in a more accurate forecast than those produced by the models.

    That isn’t a ‘random walk’, it’s persistence.

  120. ***You first have to *prove* CO2-induced climate change exists before you can affirm it.***

    I confess I do not even really understand what your point is. Aside from the pointlessness of the distinction between “proof” and “affirmation” in this context, you’re missing the *key* point that Fildes and Kourentzes are more in *dis*agreement with Anthony Watts than Watts realized when he posted the comment about their article.

    This of course stems from the fact that Watts *never read* the article but instead relied on secondhand sources–as shown by the fact that he didn’t even get the link right initially.

    The subsequent gang-tackling by the readership of this blog–none of whom had read the article either–was simply an all-too-common example of what happens when people rely on (a) a singular source with (b) an agenda, and (c) never critically evaluate that source. This, unfortunately, is what happens to the readership of Wattsup all the time.

    But soon enough the “moderator” will begin to detest my exposure of this ugly truth, and I’ll be shortly censored. You all can go back to believing Anthony Watts again undeterred by people who actually investigate the evidence.

    [Reply: Anyone that paranoid about WUWT moderation should check under the bed every night. Just in case. ☺ ~dbs, “moderator”]

  121. The most obvious problem, is no one should ever reference Wikipedia since it is a completely unreliable resource that can be edited at will by anyone with an Internet connection. Almost every time I read a Wiki page I find something wrong.

  122. Bill Tuttle says:

    “You first have to *prove* CO2-induced climate change exists before you can affirm it.”

    Excellent point. CO2=AGW is only a conjecture, not a hypothesis. To affirm it requires empirical evidence verifying that human emitted CO2 causes global warming. No such evidence exists.

    And in order to be elevated to the status of a scientific hypothesis, CO2=AGW must be testable. But so far, CO2=AGW is not testable. It may be true [I happen to think that CO2 causes slight – and entirely beneficial – warming]. But it is still only a conjecture.

    As for CO2=CAGW, that is the province of lunatics like Algore, and certifiable nutjobs like Joe Romm.

  123. “Wattslings”?? Strike two.

    Another pejoritive insult like that and your comments will be deleted. -mod]

  124. [snip]

    But I’ll keep reading this blog anyway. Unlike y’all, I actually *care* what the other side says . . ..

    [Reply: You are not a mind reader, and despite your claims to that effect you have no understanding about what Anthony thinks. From your very first comment on this site you have been saying you expect to be deleted, then you push the envelope to get what you want in every subsequent comment. I suggest you read up on the site Policy, and abide by it. Scientific comments are always welcome here at the internet’s “Best Science” site, from any point of view. But your deliberately insulting of our host and our readership is not acceptable. Learn some manners or go elsewhere. ~dbs, mod.]

  125. Skip, we all “care” what the other side says, we just make sure to verify their claims which frequently turn out to be bogus.

    I also know you believe yourself to be the great “moderate” one. Someone rational in a sea of irrationality. The one who can see what others are missing. You are so “objective” in your mind it defies imagination. You are so above all of us peons. There are a select few popular commentators here who share your delusions of grandeur and follow the pied pipers no matter where it leads,

    http://www.populartechnology.net/2012/05/truth-about-judith-curry.html

    http://www.populartechnology.net/2012/06/truth-about-richard-muller.html

  126. skip says: June 16, 2012 at 7:45 pm

    Let’s see… as near as I can tell, your first post here at WUWT, ever, was around 1:30 this morning and you were already complaining about moderation. You spent a lot of time criticisizing Anthony for linking to an article you seem to think he didn’t read because you interpreted it as not supporting his point of view. Let’s put this in perspective: Anthony posted an article published in the popular press by Dr. Ross McKitrick, who is not exactly a fool, by the way, and then posted a link to the article that McKitrick was discussing but failed to link to in his own article. You seem to think that Anthony should have vetted the article first to be sure that it presented a nice tidy picture. He doesn’t do that. Read the article yourself and form your own opinion. I would suggest that you failed to read the article, “skip”, or failed to understand what it actually said… not un-typical for the semi-educated public that feels compelled to bray its ignorance. Sheesh. Anthony linked to the paper that Dr. McKitrick was apparently referring to in his article, so his readers could judge for themselves, and YOU criticize him for it?

    This site attracts commenters with far better qualifications than yours, whatever those may be. My CJ majors, (oh yeah… I am a college professor) who are a rather rigid and narrowly-focused lot, generally exhibit a more liberal view. In my experience, Anthony and his moderators treat thoughtfui comments with respect… and ignorant, provocative comments like yours with more respect than they deserve.

  127. Phil. says:
    June 16, 2012 at 11:14 am
    Bill Tuttle says, June 15, 2012 at 11:33 am: “The paper *does* say that plotting random numbers — ‘using the last period’s value in each location as the forecast for the next period’s value in that location’ — resulted in a more accurate forecast than those produced by the models.”
    That isn’t a ‘random walk’, it’s persistence.

    I didn’t say that was a random walk, I said “plotting random numbers resulted in a more accurate forecast than those produced by the models.” You haven’t refuted or rebutted that statement, you’ve merely nattered on about the definition of a random walk.

  128. skip says:
    June 16, 2012 at 7:45 pm
    But I’ll keep reading this blog anyway. Unlike y’all, I actually *care* what the other side says . . ..

    You forgot the “/sarc” tag.

  129. skip says:
    June 16, 2012 at 2:36 pm
    ***You first have to *prove* CO2-induced climate change exists before you can affirm it.***
    I confess I do not even really understand what your point is.

    The point is that someone who makes an unsubstantiated allegation and then draws a conclusion based on the assumption that the allegation has been substantiated merely because he stated it is indulging in a logical fallacy.

    Aside from the pointlessness of the distinction between “proof” and “affirmation” in this context,

    You consider it pointless because you have no rebuttal to it.

    you’re missing the *key* point that Fildes and Kourentzes are more in *dis*agreement with Anthony Watts than Watts realized when he posted the comment about their article.

    You’re introducing an external argument in an attempt to nullify my statement, which is further evidence that you can’t think of an effective rebuttal — because you have none. And Robert E. Phelan (June 16, 2012 at 10:45 pm) effectively eviscerated you on your “key point” —
    “Anthony linked to the paper that Dr. McKitrick was apparently referring to in his article, so his readers could judge for themselves, and YOU criticize him for it?”

  130. Incredible.

    So I am supposed to respond to a multitude of posts even as I am being censored?

    The point is that someone who makes an unsubstantiated allegation and then draws a conclusion based on the assumption that the allegation has been substantiated merely because he stated it is indulging in a logical fallacy. –Bill tuttle

    Is this what you are claiming I did? OMG . . ..

    Bill Tuttle also wrote, in response to my, “you’re missing the *key* point that Fildes and Kourentzes are more in *dis*agreement with Anthony Watts than Watts realized when he posted the comment about their article,” the following:

    You’re introducing an external argument in an attempt to nullify my statement, which is further evidence that you can’t think of an effective rebuttal — because you have none.

    You’re referring, Bill, I assume, to your statement that there is no evidence that “CO2-induced climate change exists.”

    Bill, even so called *skeptics* agree that CO2-induced climate change exists. All they dispute is it’s magnitude.

    Bill, you are simply an amazing exemplar of the mindset of the contributors to this blog. You think your arguments are brilliant, when in fact they are boorish. Of *course* I have a response to that, and I would love to go at it with you some time, but you have wildly missed the point of Anthony Watt’s original post–that the Fildes and Kourentzes article supposedly showed that climate models are no better than “random walks”. But in fact the article vigorously *disputes* Anthony Watt’s positions on climate change. Fildes and Kourentzes *agree* with the fundamental science of anthropogenic climate change induced largely by CO2 *and* that there are real risks associated with it. You understand the article so poorly that you seem to think the it should provide evidence of CO2-induced climate change, and proudly “nail” me with the point. This, again, stems from relying on blogs like this instead of original sources.

    And as for you, Professor Phelan:

    . . . you were already complaining about moderation.

    Based on an undeniable history of censorship: If you ask AW a question for which the only truthful answer is an embarrassment and any non-embarrassing answer is a lie, you’re post is toast. It’s a fact.

    You spent a lot of time criticisizing Anthony for linking to an article you seem to think he didn’t read . . . .

    He didn’t read it. And he did not “link to it”. He linked to the wrong journal. That’s how I know he didn’t read it. And I am not “criticizing” him for it. Mr. Watts, on his own blog, can link to any number of legal *porn* sites for all I care. My point is simply that it shows he is not credible as a source of information on climate. He links based on what he *thinks* an article says. If he really knew that the authors of this article do not agree with him on the larger questions of climate change, he would *not* have brought attention to the article.

    because you interpreted it as not supporting his point of view.

    Do you have an alternative interpretation of the article? Please share it.

    Let’s put this in perspective: Anthony posted an article published in the popular press by Dr. Ross McKitrick, who is not exactly a fool, by the way, and then posted a link to the article that McKitrick was discussing but failed to link to in his own article.

    That is not what happened. The not-exactly-a-fool Ross McKitrick *also* had the journal title wrong (yes I did read his editorial), which is what screwed Anthony Watts up. McKitrick himself had just quote mined the part of the original research article he liked and Watts simply replicated McKitrick’s double error. Am I “criticizing” either of them for this? Not so much, but I am certainly criticizing anyone who would invest any credibility in either of these men.

    This site attracts commenters with far better qualifications than yours, whatever those may be. My CJ majors, (oh yeah… I am a college professor)

    A question. Are you suggesting that your status as a professor of criminal justice is a qualification to comment on this blog? Another question: do you think we should base our opinions of climate on what experts say? Finally, if you don’t know what my qualifications are, then how do you know they are inferior relative to other posters?

  131. skip says:

    “Incredible. So I am supposed to respond to a multitude of posts even as I am being censored?”

    You’re not ‘supposed’ to do anything, and I don’t see you being censored, Crybaby. You don’t know what censorship is. At RealClimate, Mann and Schmidt censor points of view they disagree with, while they’re being on the government payroll. That is official government censorship. All I’ve seen here is a part of your comment being snipped with a warning to abide by the site Policy. Why should Anthony allow a rude pig like you to come barging into his home on the internet, and tell him what he’s thinking? It is to Anthony’s credit that he still allows you to comment here. I would have evicted your obnoxious butt after your first comment.

    As for your pseudo-scientific belief system, there is no measurable, quantifiable evidence showing that human CO2 emissions are drivers of global climate change, or even a small part of it. Your citation of a couple of pal reviewed clowns playing with models lacks rigor and proves nothing. Just because those feeders at the public grant trough got their nonsense hand-waved into a journal doesn’t mean they understand what scientific ‘evidence’ means any more than you do.

    “Evidence” in science means verifiable, reproducible, testable data, replicable per the scientific method. It does not mean computer models, or IPCC assessment reports, or pal reviewed papers. Evidence has a very specific, rigorous meaning.

    There is no ‘evidence’ showing that anthropogenic CO2 is altering global temperatures, because no such testable, reproducible data exists. If it did, the climate sensitivity number for 2xCO2 would be definitively established, and the question of the quantifiable effect of human emissions on global temperature would be decisively resolved and predictable.

    But it is not resolved or predictable, and that is why there is endless debate about it: no such verifiable, empirical, testable evidence exists. SWAGuesstimates range from the UN/IPCC’s preposterous and debunked 3+ºC, to ±1º C, down to ≈≤0.5ºC, down to Dr. Misckolcgi’s 0.00ºC. There is no agreement at all. Why not? Because there is zero evidence that human CO2 emissions have any measurable effect on temperature. All such claims are conjecture, nothing more.

    Obviously you get your pseudo-science talking points from the thinly-trafficked alarmist blogs you inhabit. Big mistake, because unlike WUWT, all you ‘learn’ at those propaganda outlets are one-sided pseudo-science ‘facts’. Here, you get both sides of the argument. That’s why WUWT has such high traffic numbers. The government-censoring RealClimate panders to a small handful of true believing head-nodders, and gets very little traffic as a result. You need to run along back to them for some new talking points, because what you’re posting is old and busted.

    You won’t get away with your appeals to authority here. Either produce real evidence, per the scientific method, showing that X amount of CO2 emissions verifiably cause Y global temperature increase, or admit that you’re just winging it, and hoping nobody will notice.

    Or you can snivel about being set straight by commenters, and throw your juvenile tantrums for being snipped or deleted when you violate Policy and insult the rest of us. Argue the science to the best of your ability instead, and you won’t have to worry about being snipped.

  132. Your comments are as insightful as ever, Smokey.

    censored?”

    I don’t see you being censored, Crybaby.

    Clever as ever, aren’t you, Smokey? Of course you’re not “seeing” censorship, because what I attempted to post was being *censored*.

    You don’t know what censorship is . . . .

    I dare *anyone* on this site to reprint an example of a thoughtful comment Real Climate censored. Anyone, starting with you, Smokey. If I verify that RC won’t print it, and you’re right, I’ll concede it. On the other hand, I can *prove* that Anthony Watts has personally censored me–for no other offense than asking a *question* for which he had no good answer. I *dare* him to deny it.
    rude pig . . . obnoxious butt . . . pseudo-scientific . . .

    Insults from you are a compliment, Smokey. Please don’t relent.
    There is no measurable, quantifiable evidence showing that human CO2 emissions are drivers of global climate change, or even a small part of it.
    I just wonder if Anthony Watts agrees with that statement.

    Your citation of a couple of pal reviewed clowns playing with models . . . .
    You’re just utterly lost, aren’t you Smokey. These “pal reviewed clowns” were cited by *Anthony Watts*–who couldn’t even *get the citation right*, and who don’t even agree with his fundamental assertions (or yours) about climate change. I wonder how Anthony Watts and Ross McKitrick feel about you calling *their* source “clowns.” Beautifully done, Smokey. Just beautiful.

    “Evidence” . . . does not mean computer models, or IPCC assessment reports, or pal reviewed papers. Evidence has a very specific, rigorous meaning.

    I have to wonder what Anthony Watts *really* thinks about your posts, Smokey. Nobody said “models” or the “IPCC report” were the evidence. Unprecedented and heretofore otherwise unexplainable late 20th century warming is just one part of the evidence, but that is for a different thread.

    There is no ‘evidence’ showing that anthropogenic CO2 is altering global temperatures, because no such testable, reproducible data exists.

    How could it, Smokey? We can’t gather data from a parallel universe where no anthropogenic CO2 existed. You’re just parroting what untrained so-called “skeptics” are saying. By your logic there is no evidence for evolution–or do you believe that as well?

    If it did, the climate sensitivity number for 2xCO2 would be definitively established, and the question of the quantifiable effect of human emissions on global temperature would be decisively resolved and predictable.

    Utterly naive. The article that Anthony Watts so clumsily mis-cited is written by two statistical forecasters who would *vehemently* disagree with you. It you actually believe that a climate sensitivity figure must be precisely nailed for AGW to be true, then you know nothing substantive of the issue.

    Here, you get both sides of the argument.
    That is, unless you don’t. I know from firsthand experience that AW censors when he is cornered.

    That’s why WUWT has such high traffic numbers.
    Wrong, Smokey. The reason this blog has such high traffic numbers is the same reason psychic hotlines have such high traffic numbers: people like being told what they want to believe, and for a culture and species inimical to the unpleasant truths of climate change and the implication that we have responsibilities in the face of it, that is exactly what Anthony Watts provides.

    You won’t get away with your appeals to authority here.
    Again, Smokey, you’re lost in space. I never appealed to any authorities in this thread. I never used their “models” as evidence. You have–as you have before on this blog–unequivocally missed the point, and spent several hundred words missing it.

    But happy Father’s Day nonetheless, if you are like me, dad.
    (non-sarc)

  133. skip says:

    “Of course you’re not “seeing” censorship, because what I attempted to post was being *censored*.”

    As if. Out of nearly a million reader comments, yours stands pretty much alone in claiming that your posts are being “censored”. Just like you fail to understand the scientific definition of ‘evidence’, you cannot even understand the definition of ‘censorship’. Censorship is the muzzling of free speech by the government.

    You can spend a couple of months searching the WUWT archives, looking for anyone else who claims to be “censored”. Good luck with that. You will find that the very few comments that are snipped – and your comment was no exception, from what I can see – were snipped due to violating site Policy. That does not fit the definition of “censorship”, which refers to government restriction of free speech. That is exactly what your pals at RealClimate do, while they are on the government’s payroll. If you can’t even get a simple definition correct, there is no reason to give the rest of your comments any credibility since you are so far from being up to speed on the topic of computer models.

    For example, you flatly denied ever appealing to authority – while repeatedly citing computer modelers Fildes and Kourentzes. No credibility there. You should read what you wrote before making easily debunked claims like that.

    As for your naive belief that RealClimate does not censor different points of view, I have in fact personally posted more than a dozen well-reasoned, polite and to the point comments over several years at RC, effectively refuting their various climate alarmist claims. Not one of my comments has ever made it out of moderation. They were censored without comment. So I no longer bother commenting at RC, for two reasons: first, RC’s censorship is deliberate, pervasive, unethical, and shows fear of scientific debate. And second, RC is so thinly trafficked that only a handful of RC’s head-nodding Kool Aid drinkers would even see my comments if they were posted. Now, if you would like to debate science here, such as Mann’s mendacious use of cherry-picked, upside down proxies, or discuss Gavin Schmidt’s hiding out from any new debates after being so badly spanked in the debate he lost a few years ago, I will be happy to oblige. And you will not be ‘censored’ here for expressing a different point of view, no matter how wrong it is.

    Many of my comments at RC were made back in the day when they used time/date stamps, providing irrefutable evidence that Gavin and Mann were running RC on taxpayer-funded paid government time. As a U.S. citizen I expect to be afforded my rights under the 1st Amendment when commenting on a government supported blog. Instead, government drones used their official positions to censor my legitimate views. And I am not the only one. Commenters here regularly report that RealClimate has censored their posts, too.

    You do not even understand the difference between censorship and site Policy at WUWT, which accepts no government subsidies, or payments, or “big oil” money. And I know Anthony Watts to be uncommonly honest. He is a straight shooter. So when a newbie commenter with a big chip on his shoulder suddenly appears out of nowhere, and from his very first comment starts sniveling about “censorship” like a spoiled William Connolley, I know which one of them is full of it. And it’s not Anthony Watts.

    Finally, it is clear that I’m responding to someone deficient in Logic 101. Look up “non sequitur”: “It (sic) you actually believe that a climate sensitivity figure must be precisely nailed for AGW to be true, then you know nothing substantive of the issue.”

    Wrong.

    Earth to skip: AGW is a conjecture. An opinion. It is not a hypothesis, and it is certainly not a theory. A hypothesis must be testable. AGW is an untestable, unquantifiable conjecture. AGW may be true. Or not. But it is un-measurable, non-reproducible, and un-testable. It is an opinion, based vaguely on radiative physics.

    The central problem with the CO2=AGW conjecture is that the real world is not responding as predicted. All of the predictions made by the alarmist crowd have come crashing down: there is no ‘tropospheric hot spot’ [the “fingerprint of global warming”]. The Arctic has been routinely ice-free during the Holocene, thus the current cycle is well within past parameters. And the Antarctic, home of 90% of polar ice, has been steadily gaining ice, thus debunking the putative role of “carbon”. Some glaciers are retreating – but some are advancing; I did not realize that CO2 was so selective. Coral bleaching is due to natural cycles; they are recovering even as CO2 continues to rise. Tuvalu and other coral atolls are not sinking as predicted. The sea level rise is decelerating – fast. The planet is greening in lockstep with rising [harmless, beneficial] CO2. And despite the ≈40% rise in CO2, the global temperature has been declining. And there has been no temperature acceleration despite the big rise in CO2. The long-term rise from the LIA is unchanged.

    All the predictions made by the climate alarmist crowd have been falsified. None withstand scrutiny. But the true believers cannot admit they were wrong about every prediction. Their ego gets in the way, with the result that they look ever more foolish as more real world data becomes available. Planet Earth – the ultimate Authority – is falsifying their belief system.

  134. skip says:
    June 17, 2012 at 3:38 am
    The point is that someone who makes an unsubstantiated allegation and then draws a conclusion based on the assumption that the allegation has been substantiated merely because he stated it is indulging in a logical fallacy. –Bill tuttle
    Is this what you are claiming I did? OMG . . ..

    I’m not *claiming* you did — I cited the actual quote. Are you now saying you *didn’t* make an unsupported assumption and then proceed to draw a conclusion based on that assumption?

    You’re referring, Bill, I assume, to your statement that there is no evidence that “CO2-induced climate change exists.”
    Bill, even so called *skeptics* agree that CO2-induced climate change exists. All they dispute is it’s magnitude.

    You’re making another unsupported assumption. Skeptics agree that *climate change* exists, that it’s natural variation causing it, and that changing CO2 levels are the result, not the cause. Skeptics examine the evidence, and all the evidence shows that the supposition that increased CO2 causes an increase temperature is flat-out wrong. Instead of making assertions that CO2-induced global warming exists, show some proof. Point out the mid-tropospheric hot spot — ooops, it’s not there. Point out the increase in the overall altitude of the tropopause due to expansion by warming of the troposphere — ooops, it isn’t happening. Point out the inexorable rise in global temperatures accompanying the observed increase in CO2 levels — ooops, it isn’t happening.

    Bill, you are simply an amazing exemplar of the mindset of the contributors to this blog. You think your arguments are brilliant, when in fact they are boorish.

    Translation: “I have neither the background nor the knowledge to dispute you, so I’ll settle for calling you names and hope you’ll be too angry to think straight.”

    Of *course* I have a response to that, and I would love to go at it with you some time…blah, blah, blah, desperately returning to the point I’ve already been taken down on but am too stuck on to drop…

    Translation: “Again, I got nothin’.”

    You understand the article so poorly that you seem to think the it should provide evidence of CO2-induced climate change, and proudly “nail” me with the point. This, again, stems from relying on blogs like this instead of original sources.

    You keep claiming I’m “missing the key point that Fildes and Kourentzes *agree* with the fundamental science of anthropogenic climate change induced largely by CO2 *and* that there are real risks associated with it” and *you* keep ignoring the point that there *is* no fundamental science involved with AGW — it’s all conjecture and consensus, neither of which have jack to do with science. Show the proof. Prove that CO2 causes warming, and that elevated CO2 levels have been causing the temperatures to rise *continuously* from the onset of the Industrial Age until today.

    Stop with the emotional crap and produce some hard evidence.

    Oh, yeah — happy Father’s Day!

  135. . . . yours stands pretty much alone in claiming that your posts are being “censored”.

    Great argument, Smokey. Have you considered that maybe this is because most people who study climate think this blog is a joke, and the vast majority of this blog’s participants are people such as yourself—who cannot, for example, even grasp the simplest point of a debate thread? (See below)

    Just like you fail to understand the scientific definition of ‘evidence’, you cannot even understand the definition of ‘censorship’. Censorship is the muzzling of free speech by the government.

    No Smokey. It need not be only by the government. Consult a dictionary, please. And in any event, even if the word *was* linguistically inappropriate, this blog still engages in its equivalent: exclusion of threatening ideas.

    your comment was [snipped] due to violating site Policy.

    I have no doubt of that. Unofficial (but preeminent) policy on this blog is that Anthony Watts may never be shown to be in error.

    For example, you flatly denied ever appealing to authority – while repeatedly citing computer modelers Fildes and Kourentzes.

    Oh . . . my . . .God. You still don’t get it, do you, Smokey. I *never* appealed to their “authority”. They were *Anthony Watts’s* source! Do you still not grasp this? I beseech the administrator of this site: Mr. Watts, do you believe Smokey grasps the dispute on this thread? Please answer that simple yes or no question.

    As for your naive belief that RealClimate does not censor . . . .Not one of my comments has ever made it out of moderation.

    Smokey, there is no way to say this nicely. Based on my interactions with you on this forum, and your repeatedly demonstrated inability to follow even the simplest chain of argument, I strongly suspect *that* is the reason your comments were declined: they were not perceived as threatening, there were perceived as valueless. This is *not* to say I think you’re a bad person; for all I know you’re a great guy outside scientific discussions; only that your obvious inability to grasp even the point of this thread discussion suggests the quality of your submissions to RC were rejected for similar reasons.

    And you will not be ‘censored’ here for expressing a different point of view, no matter how wrong it is.

    Except I have. I *dare* Anthony Watts to deny it.

    And I know Anthony Watts to be uncommonly honest. He is a straight shooter.

    Great. Then I challenge you to ask him to be honest about this. He censored me on the Tsunami thread when all I did was ask him a direct question to which he had no good answer and I called him on it. That’s your straight shooter for you, Smokey.

    AGW is an untestable, unquantifiable conjecture. AGW may be true. Or not. But it is un-measurable, non-reproducible, and un-testable. It is an opinion, based vaguely on radiative physics.

    And an opinion which is shared by every major scientific organization in the world—but you know better, don’t you Smokey—even though you *can’t even follow the discussion on this thread.*

    And on you go with the rest of your post—the tired and foolish talking points of those who cling to pseudo-science to deny reality: the missing hot spot, etc. Incredible.

    And of course all this your attempt at a distraction from my key points, which I challenge you to specifically deny:
    1. AW [unsuccessfully!] linked to an article *he had not even read*.
    2. The authors of said article *don’t even agree with his position on climate change.*
    3. The readership of this blog—none of whom had read the article either—accepted AW’s portrayal of the article (as demonstrating that computer models of climate have no value—which is not even exactly what the authors were saying, but that is another point) without question and without investigating the quality and perspective of the source themselves. This says quite a bit about both the administrator and the readership of this blog.

    Direct question, Smokey: With of the above assertions do you dispute?

  136. skip says:

    I dare *anyone* on this site to reprint an example of a thoughtful comment Real Climate censored.

    Poor skip are you new to this game or just naive?

    http://www.populartechnology.net/2009/07/truth-about-realclimateorg.html

    http://cstpr.colorado.edu/prometheus/archives/climate_change/001180a_little_testy_at_re.html

    http://www.nationalcenter.org/Z031507=realclimate_climate_censorship.html

    http://climateaudit.org/2005/10/29/is-gavin-schmidt-honest/

    Gavin, your statement: “throw it out completely, it still makes no difference” is not correct. The following longer version of his statement that you made recently is also not correct:
    “The removal of the Gaspe series, or indeed of all the Bristlecone pine trees as well, has a minimal effect ( ~0.05 deg C) on the reconstruction as long as you include consistent numbers of PCs as described in the Dummies Guide. This is most clearly seen in the upcoming W&A paper in Climatic Change where they specifically go into these details (sorry I can’t post the figure).

    A whole website was set up just because of the censorship at RealClimate,

    http://rcrejects.wordpress.com/

  137. Skip, I don’t think there’s another poster here who’s continually proven himself so devoid of intellectual honesty, logical consistency, or just plain civility as you are. Your continued presence is proof that you’re not being censored.

  138. skip says:
    June 17, 2012 at 11:34 am
    And on you go with the rest of your post—the tired and foolish talking points of those who cling to pseudo-science to deny reality: the missing hot spot, etc. Incredible.

    You do realize, of course, that you just called one of the major tenets of your religion “pseudo-science.”

    On second thought, no, you probably don’t realize it…

  139. Bill Tuttle says:
    June 15, 2012 at 11:33 am

    ‘The paper *does* say that plotting random numbers — “using the last period’s value in each location as the forecast for the next period’s value in that location” — resulted in a more accurate forecast than those produced by the models.’

    Such a process is called a martingale.

    PS to all: Stop bothering with Skippy. He is just a typical thoughtless drone, his comments provide no value added and do not merit the attention.

  140. Bart says:
    June 17, 2012 at 2:14 pm
    Bill Tuttle, June 15, 2012 at 11:33 am: ‘The paper *does* say that plotting random numbers — “using the last period’s value in each location as the forecast for the next period’s value in that location” — resulted in a more accurate forecast than those produced by the models.’

    Such a process is called a martingale.

    Phil’s going to have a fit — “an unbiased random walk is an example of a martingale”…

  141. I would love to comment further on the . . . . “contributions” . . . made so far on this thread. But I want to hear everyone who has commented so far to tell me why they think *Anthony Watts* has remained silent to this point.

    It’s just a simple question! Please–enlighten me!

  142. skip says:
    June 17, 2012 at 10:35 pm
    I would love to comment further on the . . . . “contributions” . . . made so far on this thread. But I want to hear everyone who has commented so far to tell me why they think *Anthony Watts* has remained silent to this point.

    Doing that would require me to make an unsupported assumption.

  143. skip says: June 17, 2012 at 3:38 am

    Based on an undeniable history of censorship: If you ask AW a question for which the only truthful answer is an embarrassment and any non-embarrassing answer is a lie, you’re post is toast. It’s a fact.

    That, skip, is both an unsupported assertion and a bare-faced lie. Asserting that something is a “fact” does not make it so. Comments get snipped here for violation of site policy. Period. Any assertion to the contrary is simply mendacity. If you were snipped on a previous thread, it was not simply for asking a question.

    He didn’t read it. … He links based on what he *thinks* an article says. If he really knew that the authors of this article do not agree with him on the larger questions of climate change, he would *not* have brought attention to the article….

    Another unsupported assertion. You *know* Anthony will only reference articles that support his “position”, hmmmm? And you *know* this how? It obviously is not because you’ve carefully analyzed the content of all the articles and books that have been referenced here because you would have quickly seen that Anthony often links to articles that do not support his “position”. His “position” is to provide the references and let others make their own informed choice. He does not need to read every article he links to, and when he was given the name of the article, he linked to it. In my last comment I said : “Let’s put this in perspective: Anthony posted an article published in the popular press by Dr. Ross McKitrick, who is not exactly a fool, by the way, and then posted a link to the article that McKitrick was discussing but failed to link to in his own article. You replied:

    That is not what happened. The not-exactly-a-fool Ross McKitrick *also* had the journal title wrong… McKitrick himself had just quote mined the part of the original research article he liked and Watts simply replicated McKitrick’s double error. … but I am certainly criticizing anyone who would invest any credibility in either of these men.

    Sorry, but that is exactly what happened. You accuse McKitrick of “quote mining”, but in fact, the conclusions of the study were actually as he reported. The fact that the authors also made their ritual obeisance to the current orthodoxy does not change that, nor does it do much to obscure the fact that these so-called science-based models don’t work. If they are based on accepted science, then why don’t they work? Critical thinking does not seem to be your strong suit “skip”.

    A question. Are you suggesting that your status as a professor of criminal justice is a qualification to comment on this blog? Another question: do you think we should base our opinions of climate on what experts say? Finally, if you don’t know what my qualifications are, then how do you know they are inferior relative to other posters?

    Well, if I were a professor of criminal justice I would probably be very ill-qualified to comment on this blog, but as it happens, I’m not. You’d know that if you bothered to check. I teach sociology and anthropology and I am very interested in the interaction of social systems and environment. I teach that stuff. I also teach deviance and criminology and have an ongoing interest in the way elites deviantize and criminalize behavior to further their own agendas and dominance. So, yes, I think I am qualified to comment on this blog. Opinions of experts? There is a term you need to learn: “cultural cognition”.

    Oh, and I never said that I didn’t know what your qualifications were, I simply said, “whatever they may be”. As it happens, Timmy, I know exactly what your qualifications are. You’re not as bright as you think you are.

  144. Note to Skippy: Never, ever, ever poke a salt-water crocodile on the nose and never, ever, ever say “And as for you, Professor Phelan”…

    The results in either instance will not be to your liking.

  145. [Note: Here are a few more of skip’s personal attacks and insults on Anthony Watts and the readership of WUWT]:

    “Anthony Watts’s rank blunder is …an embarrassment to Mr. Watts and everyone who reads this blog. …so intellectually lazy…another humiliating example of why the mainstream scientific community rejects Anthony Watts and his ilk… The blunt and ugly truth is that they think Anthony Watts is the scientific equivalent of a court jester, and his acolytes, such as yourselves, are easy marks for his nonsense… And your collective unwillingness to acknowledge Mr Watts’s – and your own — blunders is yet further confirmation of it.”

    [The rest were snipped, with a fair warning to ‘skip': any more of the same will get your entire post deleted. Stick to the science and you will have no problem, your comments will be posted no matter what your scientific point of view. And note also that Anthony had nothing to do with this particular comment moderation. ~db stealey, mod.]

  146. Robert E. Phelan,

    The Fquit CAGW Alarmist Theorem:
    There is a CAGW alarmist such that if he is wrong then all of them are wrong.

    Application:
    If we find him we can all go home . As luck would have it, I reckon skippy the prancing chancer here is the one we’re looking for. 

    Incidentally, “[Directed at ‘skip‘:] You’re not as bright as you think you are.” [REP]

    Yes, it certainly looks that way. I understand there are various IQ scales, but taking one with a mean of 100 and a standard deviation of, say, 15, what do you reckon he is capable of scoring? A rough upper bound will do. Do you think it might be positive?

  147. skip says:
    June 17, 2012 at 10:35 pm

    I would love to comment further on the . . . . “contributions” . . . made so far on this thread. But I want to hear everyone who has commented so far to tell me why they think *Anthony Watts* has remained silent to this point.

    It’s just a simple question! Please–enlighten me!

    =========================================
    I defer to Mark Twain on this, to a quote attributed to him

    “Never argue with a fool, onlookers may not be able to tell the difference.”

    Since this thread has devolved into “all about Skip”, and Skip has started to make routine policy violations with many of his comments, making this a waste of everyone’s time, I’m closing comments. Thanks to the moderation staff.

    “Skip” is welcome to be as upset as he wishes.

Comments are closed.