Weather vs. Climate

By Steven Goddard

I recently had the opportunity to attend a meeting of some top weather modelers. Weather models differ from climate models in that they have to work and are verified every hour of every day around the planet. If a weather model is broken, it becomes obvious immediately. By contrast, climate modelers have the advantage that they will be long since retired when their predictions don’t come to pass.

Weather and climate models are at the core very similar, but climate models also consider additional parameters that vary over time, like atmospheric composition. Climate models iterate over very long time periods, and thus compound error. Weather modelers understand that 72 hours is about the limit which they can claim accuracy. Climate modelers on the other hand are happy to run simulations for decades (because they know that they will be retired and no one will remember what they said) and because it provides an excuse to sink money into really cool HPC (High Performance Computing) clusters.

But enough gossip. I learned a few very interesting things at this meeting.

1. Weather modelers consider the realm of climate calculation to be “months to seasons.” Not the 30 year minimum we hear quoted all the time by AGW groupies. That is why NOAA’s “Climate Prediction Center” generates their seasonal forecasts, rather than the National Weather Service.

2. The two most important boundary conditions (inputs) to seasonal forecasts are sea surface temperatures and soil moisture. No one has shown any skill at modeling either of those, so no surprise that The Met Office Seasonal forecasts were consistently wrong.

For example, just a few months ago the odds of La Niña were considered very low. Compare the December forecast with the May version. How quickly things change!

SST modeling capabilities are very limited, and as a result seasonal weather forecasts (climate) are little more than academic exercises.

Oh and by the way, Colorado will be exactly 8.72 degrees warmer in 100 years. But they can’t tell you what the temperature will be next week.

If I don’t understand it, it must be simple.

– Dilbert Principle

In the top picture, which boxer is weather and which one is climate? What do readers think?

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211 thoughts on “Weather vs. Climate

  1. While I consider myself a AGW skeptic, I don’t think the “if they can’t tell you what the temperature will be next week, how can they know what it will be in a 100 years?” arguments do any service to spreading critical thinking over this issue.
    Unless people modelling climate are simply taking weather models and running them with a larger time step, which I very much doubt is the case, the argument is ridiculous. Similar to saying we can’t know the pressure of a gas is, because we can’t even predict with certainty what the trajectory of a given molecule will be…

  2. jcrabb says: Climate defines the outliers of daily weather
    JC not quite sure what that means, however, I have never been someone who is happy to separate climate from weather. To me, climate was always just another word to describe weather but in a very loose, non-descript way. Climate, the word, allowed the formation of another university/government department for creating acedemic, non-productive jobs for school children who never want to grow up and “go out to work” as my dear old mother used to tell me. Although Anthony succinctly describes the difference between weather and climate models in terms of parameters used, the climate parameters he describes also affect weather when then affects the climate. See what I mean?

  3. I think it’s the other way around. Weather is in constant motion, more aggresive, volatile, and packs a punch at short notice. Clearly the heavyweight.
    Climate, however (despite the raving predictions of the AGW lobby) continues to do it’s own sweet thing at its own pace, and really doesn’t need to be that dynamic – long time, small, cyclical effects.

  4. Thank you for mentioning the compounding error issue.
    I try to explain to friends and colleagues about floating point representation and problems arising from that. I dipped into some of the online models and some of the CRU code and it seems to all rely on the standard number handling of the hardware and software platform.
    Anyone who needs to know about it should read Knuth’s “Art of Programming”, he deals with the issue with typical humour-tinged clarity. While you’ve got it out, check out his section on random numbers. I believe (not sure) that most of the models use random numbers to some extent, and yet we never learn about the actual algorithms used in these models.

  5. “Weather models differ from climate models in that they have to work and are verified every hour of every day around the planet. If a weather model is broken, it becomes obvious immediately. By contrast, climate modelers have the advantage that they will be long since retired when their predictions don’t come to pass.”
    This is the one statement that has totally nailed the problem. Weather science is so real, so verifiable and for the most part trustworthy. On the other hand, but in the same field it is incredible that climate modelling is nothing more than junk science. And the reason it is junk science is that what is describe above is the scientist will be long since retired or dead when their predictions don’t come to pass. And this is how science became prophecy.
    But even now, six months after climatgate, Michael Mann worried about his own legacy, is putting out feelers to the public and science at large that tell us his hockey stick models are not to be taken as the basis of climate change. Amazing, simply amazing. Even Michael Mann now sees climate modelling as junk science, even though he is going in a round about manner of telling us. All we have at this moment in science is weather.

  6. Equatorial Pacific is the area where the Earth magnetic fields vertical component GMFz changes its polarity. There is a possibility that the movement of the geomagnetic Equator in relation to the geographic Equator has some influence on the Equatorial currents of the area.
    http://www.vukcevic.talktalk.net/LFC20.htm
    Similar relationship between the GMFz and temperature anomaly has been established in the Arctic ocean.
    http://www.vukcevic.talktalk.net/NFC1.htm

  7. Got interested lately in the whole climate thing and can’t help but wonder if weather (and thus climate) is largely dependant on what the oceans are doing. So instead of studying the atmosphere shouldn’t the oceans be the prime subject of climate study.
    Seeing the cyclical behaviour of the major ocean driven events like El Nino, PDO etc. have the variations in the gravity pull of the moon been studied?
    Seeing the daily tides and the large variations therein you would expect an influence (perhaps large).
    I understand the variations in the moons orbit give some 50% variation from the average gravity pull. Maybe Milankovitch cycles have an influence on the combined gravity pull of the sun and the moon as well.
    In any case the gravity pull changes cyclically, and is maybe worth looking into?

  8. Several years ago now, I was part of a discussion panel with a local TV meteorologist. I was doing computer modeling of astronomical phenomena at the time; he was discussing weather forecasting models, I was talking about the difficulties of complex, long-time-span models.
    The forecaster related the story of how his own mentor, who was a very popular meteorologist on TV, back in probably the late 70’s or early 80’s, resigned his position rather than give a 7-day forecast. He refused to be part of something he felt was a hopeless waste of time.
    The guy on the panel said 3 days is believable, 5 is a stretch, but hey, everybody wants a 7-day outlook, right?
    Jeff

  9. Climate is maybe more like the ring than the fighters who stumble about, inside the boundaries… Actually, seriously, “climate” is more like predicting the probability distribution of the outcomes of 1 million fights, whereas “weather” is predicting the outcome of the next round of a single fight.
    Generally speaking, it would seem that the author does not quite understand the fundamental difference between weather and climate, or how climate models work or what their output and purpose are. So, IMHO, this article falls flat on its face – just like the small boxer seems to be on the verge of doing.

  10. Steven, Your Good!
    It all comes down to what are the rules and what are the boundries that separate the two fighters assuming the arena is the world. What label do you put onto each fighter depends also on what you would like to achieve. Most people would assume climate to be the “big guy” with the power, money and backing of governments and the assumption that they are invincible or supreme in the science. In a short term duration (such as the science now) the energy and power would be a good bet but over a longer span, they tire out and fall apart. Weather will still continue on way past the climate models due to the lack of total understanding ALL the input and not staying “hyper-focused” on one area such as CO2 or strictly temperatures.
    This same situation can be said for AGW and the “Deniers”(enlightened ones? truth finders? hmmmm)

  11. Thank you Steve for summarizing, in a few paragraphs, my personal view of the current state of numerical climate modeling, based on my 20+ years of experience in academic and industrial high-end computational fluid dynamics.
    “Weather and climate models are at the core very similar…”
    This, of course, is correct, but the most important similarity is that the differential equations both groups are solving** are non-linear. There are NO guarantees of having ANY solution, much less the CORRECT solution. Moreover, no where in the climate modeling literature has anyone attempted to show that the climate problem is well-posed and is indeed solvable by numerical means…
    **The exception here is NASA GISS. Nobody knows what equations they’re solving with Model E…

  12. The smaller boxer would be climate, because he, being more fit would be able to outlast his opponent, wearing him out essentially.The larger boxer (weather) might seem to dominate at first, but would eventually succumb to the smaller boxer’s speed, agility, and endurance.
    In the battle between the climate Alarmists vs Skeptics/Climate Realists, the latter would be represented by the small boxer. The Alarmists appear to be exhausted now, lashing out furiously but ineffectually in their last-ditch efforts to survive.
    Man’s effect on climate could be represented by a fly buzzing about climate’s head.

  13. surferdave :
    “I believe (not sure) that most of the models use random numbers to some extent, and yet we never learn about the actual algorithms used in these models..”
    I’m not sure this is the case. For example, CCSM3 has a 226-page technical paper describing the equations in the atmospheric model (CAM3 – the atmospheric component of CCSM3) – http://www.cesm.ucar.edu/models/atm-cam/docs/description/description.pdf
    And more about models at Models, On – And Off – The Catwalk – Part Two and Models, On – and Off – the Catwalk – Part One

  14. well, here’s hoping the moderator can fix my tags in the previous comment and close out the bold tag at the start (wasn’t trying to shout)… thanks moderators!

  15. If you think about it, an accurate climate forecast would be totally dependant on deterministic long range weather forecasts, and that can only be done by predicting changes in the solar signal.

  16. ‘To punch below one’s weight’ is to achieve or perform at a level lower than should be expected based on one’s preparation, attributes, rank, or past accomplishments.  
    The big guy is climate.

  17. Piers Corbyn seems quite good at predicting WEATHER a season or so ahead.
    By which I mean extreme weather rather than ‘it’ll rain a bit today and be sunny tomorrow’.
    His models use solar, geomagnetic and atmospheric parameters and I didn’t see him document anything about oceanic contributions yet. He may do, I may just not pick it up.

  18. Jaime says:
    July 1, 2010 at 2:46 am
    ” … the argument is ridiculous. Similar to saying we can’t know the pressure of a gas is, because we can’t even predict with certainty what the trajectory of a given molecule will be…”

    The gas is not a chaotic system, however the atmosphere, oceans, and landmass is.

  19. This is REALLY easy.
    Weather is anything that can just be brushed under the carpet out of view because it is inconvenient, like predicted mild winters that turn out to be exceptionally cold.
    Climate on the other hand is all the “WussThanWeThort” things that prove conclusively how evil mankind and CO2 really is. Like the summer heatwave in 2003 that killed 30 billion French people or whatever it was claimed to be.
    Simple, really!

  20. Of course, there’s actually no such thing as climate. It’s an abstraction, a statistical fancy, which amuses those who enjoy torturing numbers but provides nothing useful, except a general guide to what conditions one is likely to experience at any given spot on the earth at a particular time. But unlike weather forecasts, which give fairly accurate predictions that help you plan your clothing layers and umbrella choices for a few days ahead, climate study makes too much of averages, which hide the potentially massive swings either side of the ‘norm’. Lay persons know only too well that the exception is the rule, and bear the scars of ruined vacations. This is also why weather forecasters are more sanguine about the future.
    A cynic could conclude that it’s the study of something of such questionable utility that has led so many climate practitioners to forecast catastrophe, otherwise they’d have nothing interesting to say.

  21. If we compare the size of the boxer to the grants climate vs weather receive then the answer is pretty obvious.
    However the guy on the right is a little small for a realistic comparison.

  22. Oh and by the way, Colorado will be exactly 8.72 degrees warmer in 100 years. But they can’t tell you what the temperature will be next week.
    Really, “Steven Goddard,” would you have written a howler like that under your own name?
    Weather is chaotic and unpredictable. Climate is weather averaged out over time. Simple analogy: you can’t predict whether a coin will land heads or tails, but you can predict statistically how thousands or millions of coin tosses will go.
    There are dozens and dozens of good arguments which could be made about the inaccuracy of climate models, how they are misused and how poorly the science is understood. This, however, is not one of those arguments.
    “I award you no points, and may God have mercy on your soul.”

    REPLY:
    What happened to posting as Paul Daniel Ashe? Why go back into the closet, you were doing so well? – Anthony

  23. In the top picture, which boxer is weather and which one is climate? What do readers think?
    I think that “the fight” itself is the climate and both fighters are weather.
    Formal 1-on-1 fights have been going on for thousands of years. The the styles and rules change slightly over time (regional differences: sumo, boxing, eastern martial arts, etc.) but these fights still take place under rules that have remained fairly constant over time (current climate steady state or “equilibrium” if you prefer).
    The disparate sizes of the fighters merely illustrate weather extremes within the fight game (global climate.)

  24. The “weather” just produced a 46F (7.5C) low for July 1 here in western MD. Just a few degrees above a record low for the date. Last yr I had a record-low for the date of 44F in mid-July.
    It’s getting worse than we thought.

  25. ‘Climate modelers on the other hand are happy to run simulations for decades (because they know that they will be retired and no one will remember what they said) and because it provides an excuse to sink money into really cool HPC (High Performance Computing) clusters.’
    The hilarious paradoxical nature of all that is, of course, that people in the future will literally laugh their collective ass’ off and call those philosophical doctor farts utterly mental for trying to predict future climate 50 and 100 years hence with slow ass retarded LPC clusters.
    Think about it, would they not have had to eat their shorts every online day if they’d been on mainframes of PDP-10s in the sixties having tried to predict todays climatic change of an “ice age”. They were stellar back then, helped take people to the moon, so they were seen almost as automagical really, yet today a simple ipod packs more punch in processing power, RAM, storage capacity, programming versatility, et cetera, not even 40 years later.
    And that’s how the climatological nutties will be remembered, whereas the rational skeptical ones probably’ll be remembered as the both feet on the ground stoic’s that stood against the flood of crazies–for an age. :p

  26. Hi Steven,
    Let’s make a bet. I’ll bet you that the average temperature in the United States in July 2100 will be warmer than the average temperature in January 2100. If I’m wrong, I’ll give you $100. If I’m right, you give me $1. (What a deal!)
    Do you accept? If you’d like this bet to be a bit more tangible, we can change the year to 2015, or any other year of your choosing. According to your logic, accepting this deal should be a no-brainer, since you’ve claimed that prediction of climate variables and weather variables are mathematically equivalent.
    Let me know. Thanks!
    Dan

  27. In my efforts to obtain a degree in electrical engineering I took some courses in computational analysis. In some of the last classes on multivariable analysis, one of the topics was on picking the right (independent) variables, and how would one know they are correct, and independent. That was a long time ago, and undoubtedly I have lost a lot of the knowledge.
    But one thing still stands out. That is, over a defined set, one can model, or at least try to model, just about anything that shows some correlation over a defined set. I’m surprised that someone hasn’t modeled AGW (assuming existence) directly to population –human, or chicken, or even mammoth (oops they have in the case of the last).
    Such a model might even appear valid over a defined data set. However, to go from there to declaring that humans, or chickens, or mammoth are responsible for some warming leaves a huge void in science, and obviously isn’t valid.
    I was listening to a CBC science show about 8 or 10 years ago where a “scientist” was running 20 years (or something like that) of data through climate models and declared them valid. Also, claiming validation of C02 link to global warming.
    I immediately thought to myself Bull! Of course the models align, the same data used to develop the models was used to prove the models!!! And yes, I realize someone is getting paid big bucks to constantly refine these. But I still don’t believe everyone is aware (or even honest about) about the correct independent variables.

  28. Anthony, I have two computers, and I just cleared the cache on the one downstairs. My bad, I’ll straighten that out right away.
    And I’m assuming you’re giving “Steven” just as hard a time for being “in the closet” as you do everyone else who writes under a pseudonym. Right?

  29. PDA says:
    July 1, 2010 at 5:33 am
    […]
    “Really, “Steven Goddard,” would you have written a howler like that under your own name?
    Weather is chaotic and unpredictable. Climate is weather averaged out over time. Simple analogy: you can’t predict whether a coin will land heads or tails, but you can predict statistically how thousands or millions of coin tosses will go.”

    Assuming a fair coin, assuming a fair landing surface, assuming a fair coin-flip method…
    ==> Assuming one knows the mechanisms producing the conditions that allowed Otzi the Iceman to cross the alps, then get burried in (I forget how many) meters of ice, then have his remains discovered discovered 5,300 years later when the ice melted, and assuming one can predict within a few years, based on long term averages, when those mechanisms will act…
    … well then I’d say that stochastic climate models are pretty darn good and I’d have to concede your point.
    But I don’t think so.

  30. After a couple of days of high heat in D.C. Climate Progress declared climate change last week. After a heavy rain in Tennessee, they declared the climate was changed. In January 26, 2009 they declared the southwest would have a permanent drought.
    It is warm enough to raise oranges in Manitoba today. Actually both June and July. Shall we turn that into a trend line?

  31. The Met Office has provided annual temperature forecasts and 10 consecutive years have been wrong. 9 of the years they predicted hotter than actual. How are those forecasts working for the warmists?

  32. Steven at the public govt questioning of Phil Jones representatives of the Hadley Centre were questioned. The question was asked how the Climate Models were tested. The woman who seemed to have some authority answered that the same code was used for short term forecasting as for the GCMs. For that reason she claimed they had been thoroughly tested! I wonder how many people would believe such rubbish. From personal experience it is quite difficult to make sure large computer systems to work correctly even when the correct output can be easily calculated. It takes dedicated meticulous testing by a number of testers. In system I worked on ten to twenty people were tasked for this.
    Surferdave your reference to Knuth’s “Art of Programming” was a surprise I thought everyone had forgotten about it. How about we create a fake GCM using RNGs would anyone notice? Then again perhaps it has already been done? Another test is to say if GCMs produce the same results then they must be correct!

  33. stevengoddard replied to Jaime, “Climate models are basically extended weather models. They have to be, they are modeling the same atmospheric and oceanic processes.”
    Your assumption is that climate models model oceanic processes. Many do not, including the GISS Model E.

  34. I work in the area of computer modeling but not with weather or climate. Feedback on the goodness of my models is more or less immediate and has economic consequences. I learned many years ago that models not carefully tested on “out of sample” data (i.e. data not included in building the models) are virtually useless in prediction of future events or conditions. Computer models can be made to fit any set of data yet have no ability to accurately predict for new data. Climate modelers engage in the fantasy that their untested models are somehow valid and the delusion that it would be good for the world to turn its energy economy inside out based upon them. This is the height of folly and arrogance.
    People (including climate modelers apparently) have a naive view that just because a prediction comes out of a computer it must somehow be accurate. Not so. If I relied on untested models I would have been out of business a long time ago. I hope the world wakes up on this computer climate modeling scam before it enacts cap-and-trade. My prediction on that (not computer generated) is that it will destroy our economy and reduce our standard of living to underdeveloped country levels.

  35. PDA says,
    “Weather is chaotic and unpredictable. Climate is weather averaged out over time. Simple analogy: you can’t predict whether a coin will land heads or tails, but you can predict statistically how thousands or millions of coin tosses will go.”
    Heard it before. Same old false analogy, but you’d be surprised how many people bring it up. The obvious fallacy of logic is that we know before we start what the probability of tossing a head or a tail is – it is 0.5. Given this data, it can be proved mathematicaly and empirically that as the number of tosses becomes very high, the ratio of heads to tails approaches their individual probability, namely 0.5. Climate however, is modelling uncertainty right from the off. Nobody knows the feedbacks, or even whether they are net positive or negative. It can be demonstrated that when the probability of an event is uncertain, then the more iterations there are, the further the possible outcomes diverge from the mean.

  36. There’s a rather big difference between weather and then seasonal forecasts, and long range climate projections.
    The former are very sensitive to the initial conditions. Long-range climate, less so.
    Downscaling it a bit: I can’t tell you the exact temperature and precipitation for your hometown in three week’s time. Butterflies and chaos and all that.
    But I can sure tell you that the average temperature in your summertime month will be more than in your wintertime month. For that, the initial conditions don’t much matter; the boundary conditions are felt such that we can pretty much count on the seasons to appear.
    Similarly, if the irradiation from the sun went up by 20% for some reason by 2100, I can sure tell you that on average, it’s going to be warmer here on Earth. I don’t have a chance at telling you if there’ll be an El Nino or a La Nina in Jan 2100, and I don’t have a chance at telling you if it’ll rain on Jan 21, 2100, but you can still be sure that the Earth will be warmer on average due to the active sun.

  37. @Rhys Jaggar says:
    July 1, 2010 at 5:17 am
    “Piers Corbyn seems quite good at predicting WEATHER a season or so ahead.
    By which I mean extreme weather rather than ‘it’ll rain a bit today and be sunny tomorrow’.
    His models use solar, geomagnetic and atmospheric parameters and I didn’t see him document anything about oceanic contributions yet. He may do, I may just not pick it up.”
    Weather Action forecast for the UK, daily rainfall with a lattitude of 0.5 t0 1.0 days in timing, with often very good regional variation in the specification. A very high percentage of the total number of active weather fronts hitting the UK will be forecast at this level of timing accuracy, and forecasting at this level can be acheived at well over a year in advance. Similar levels of success are acheived with tropical cyclone forecasts, in formation periods and locations, tracks and intensity.
    SST`s are considered, as are Lunar modulations of the solar wind and atmospheric circulation patterns.

  38. Dan
    From your comments, it appears that you probably haven’t worked with GCMs. If they were simple statistical models as you imagine, there wouldn’t be need for running them on supercomputers. Your view of a climate model could be run on an abacus. Even simpler, you could make a graph of CO2 vs. temperature and just extrapolate it out to some future CO2 value. That would probably be a fairly accurate model.
    As I stated in the article, a climate model run is essentially the same as a weather model run, only with more iterations, more input parameters and often a coarser spatial and temporal granularity.

  39. I think an analogy between predicting weather and climate would help here – imagine you have a hot, fresh cup of coffee in front of you. You pour in some cold cream, and stir it up with a spoon. Now, tell me, which is easier, predicting the temperature and cream content at a given spot in the coffee cup in 30 seconds, or predicting the ensemble temperature of the coffee in 20 minutes (given you know the room temperature, etc)? Its clear that it is much easier to predict the coffee temperature in 20 minutes.
    Why then, is it so difficult to understand how creating/using a climate model, working on averages and long trends with small changes in each variable is nowhere near the same thing as trying to model the temperature in my backyard 3 days from now at 6h23?

  40. PDA
    I can tell you what the temperature will be like in July 100 years from now. Most likely very similar to the present. Over the last 80 years, summer temperatures in the US have hardly changed at all.

  41. Dan @ July 1, 2010 at 5:56 am

    I’ll bet you that the average temperature in the United States in July 2100 will be warmer than the average temperature in January 2100 …

    You utter, deluded fool. Everybody knows that by 2100, the United States will have been abolished and then reconstituted as a dining club in Sidney Harbour. Therefore, it is a racing certainty that January will be warmer than July .. except in the kitchen, when I predict the air conditioning will break down in July.

  42. Ulric Lyons says:
    July 1, 2010 at 5:03 am
    If you think about it, an accurate climate forecast would be totally dependant on deterministic long range weather forecasts, and that can only be done by predicting changes in the solar signal.
    You are assuming only one variable, which is surely wrong.

  43. @Expat in France
    (finally a topic on WUWT I have some expertise in to comment on, heh)
    “I think it’s the other way around. Weather is in constant motion, more aggresive, volatile, and packs a punch at short notice. Clearly the heavyweight.”
    As a boxer myself my un-peer reviewed “professional” opinion is that the above description much better suits the smaller fighter. That larger fighter is probably only capable of slow haymakers. The smaller boxer will probably take his time, giving the larger fighter a much longer time in the ring that his fighting skills rightly deserve, being carried only through sheer size and momentum (the smaller boxer will want to avoid letting the larger corner him and use his weight against him, though even then the larger fighter’s options are limited). That description of the larger boxer to me accurately represents the nexus of CAGW committed media-political-and activist interests with the smaller boxer representing skilled and sincere scientists and truth-seeking laypeople.
    Someone above said the smaller boxer looked like he’s stumbing, he’s not. He has ducked into position to give a left bodyshot and looks like he is about to follow through with a right cross.

  44. Dan says:
    July 1, 2010 at 5:56 am
    Hi Steven,
    Let’s make a bet. I’ll bet you that the average temperature in the United States in July 2100 will be warmer than the average temperature in January 2100. If I’m wrong, I’ll give you $100. If I’m right, you give me $1. (What a deal!)
    Do you accept? If you’d like this bet to be a bit more tangible, we can change the year to 2015, or any other year of your choosing. According to your logic, accepting this deal should be a no-brainer, since you’ve claimed that prediction of climate variables and weather variables are mathematically equivalent
    These are not climate variables. They are weather variables or seasonal. Apples and oranges. Similar to I bet you will find apples on an apple tree and oranges on an orange tree. You see! not variables.

  45. 1. Weather modelers consider the realm of climate calculation to be “months to seasons.” Not the 30 year minimum we hear quoted all the time by AGW groupies. That is why NOAA’s “Climate Prediction Center” generates their seasonal forecasts, rather than the National Weather Service.
    This isn’t entirely accurate. The seasonal forecasts put out by the CPC use a standard 30 year climatological norm to determine predictive probabilities. They take into account other factors, such as El Nino and soil moisture, but when you look at a seasonal forecast, like this one:
    http://www.cpc.ncep.noaa.gov/products/predictions/long_range/lead01/off01_temp.gif
    “Normal” refers to — at present, in the US — a 1971-2000 climatology. So it isn’t accurate to suggest that 30 years isn’t being used to define “climate” in the CPC’s forecasts.
    I think what you meant to draw attention to, of course, is that they are not predicting climate out for 30 years. The seasonal forecasts just go out 12 months. That’s as far as the “climate” specialists at the CPC are comfortable projecting using current methods and technology. But to be accurate, what they are projecting is how the climate over the next 12 months will compare to a 30 year climate norm.

  46. Matt
    Suppose that a climate model had predicted decreasing sea ice in Antarctica from 1978-2010. The erroneous predicted positive albedo feedback would compound over time, and the model would go further and further off into the weeds. ;^)
    There is no mechanism for climate models to correct themselves, which is why they consistently predict higher than observed temperatures.

  47. Climate is weather averaged over time.
    Any attempt to be more specific is artificial, and in these politically charged times, likely to be agenda biased.
    Climate is a useful concept for weather prediction. For example, I may reliably predict that in July, 2011, in Tucson, Arizona it will be mostly hot, and in Tierra del Fuego, Argentina, mostly cold. The variations in climate (climate change?) are usually sufficiently small that they are measured in fractions of a degree over a period of years and decades. Climate is useful.
    However, when the agenda-driven get hold of it, and like so many Cassandra’s, cry “Doom, doom is nigh….doom deserved because we are eco-evil!”, then climate “science” descends into a quasi-religious farce.

  48. This is the whole global warming scam in one article. Unlike real science, climate “science” pretends that it is a science, because it talks and acts like a science and does all the experiments it can … except it can’t because it takes decades for anything to change with the climate.
    So … what they try to kid us, is that even despite the fact they have never ever done any actual experiments and almost all their predictions have been wrong, that doesn’t matter because they’ve learn from those and … what they’ve learnt is never to let themselves get pinned down by the necessity of real experimental/scientific procedures.
    There is a saying that if you take enough climate “scientists” and allow them to make enough predictions, then sooner or later one of them will predict something that actually happens … which is all they need to prove they were all right all along!

  49. Steven,
    Couple points:
    1) No models are perfect, and scientists using them will readily admit this. It tends to be the scientific-illiterate media that place an extreme amount of trust in climate model results. The fact is that even simulating evolution of an afternoon thunderstorm is extremely difficult. (Look at cloud-resolving models and single-column models for instance)
    2) Models tend to be subjected to rigorous validation. Yes, none are perfect, but there is always one more advanced and accurate than the rest which goes on to beadopted for broad use. If there was a model predicting sea ice decline in Antarctica over the past several decades, and this failed to match the observational record, then any results from this model predicting the next several decades should be regarded with suspicion.
    3) The example you give also illustrates the reason that for the majority of serious model results (be it climate, weather, hurricane, or otherwise), an ensemble average is used to determine the most likely outcome. You seed small perturbations in the initial conditions, then use a few different models, and average the results. This also gives you a nice range of possibilities.
    4) Just something quick I noticed – in your 2 ENSO model forecasts shown above, several models in the December run did a very good job at predicting the SST anomaly in May and beyond.

  50. carrot eater says:
    July 1, 2010 at 6:28 am
    …you can still be sure that the Earth will be warmer on average due to the active sun.
    And by extension, cooler due to an inactive sun. Wow. “carrot eater” is finally beginning to see the light. Who’d a’ thunk.

  51. Matt says: I think an analogy between predicting weather and climate would help here – imagine you have a hot, fresh cup of coffee in front of you. You pour in some cold cream, and stir it up with a spoon. Now, tell me, which is easier, predicting the temperature and cream content at a given spot in the coffee cup in 30 seconds, or predicting the ensemble temperature of the coffee in 20 minutes (given you know the room temperature, etc)? Its clear that it is much easier to predict the coffee temperature in 20 minutes.
    Matt, that is an entirely false analogy. A real analogy would be to predict:
    1a. the flow of water in a river at one spot (in a rapid/turbulent flow) in a day
    1b. compared to the flow in that spot in a years time
    2a. compared to the whole flow of the whole river in a day
    2b. compared to the whole flow in a year
    These comparisons change not only in the spatial extent but also in time. YOU WERE BEING HIGHLY DUBIOUS …. and comparing apples with cars.
    If we take local temperature, and compare it like local current to next day or a year. It doesn’t take a genius to work out that rivers change and whilst the state of flow in the river now is a good indicator of the flow tomorrow at one location, it is really a pretty poor indicator of the flow next year.
    This is because like climate/weather, local water flow has increasing noise levels with longer periods. In contrast to your bogus example, weather & climate (of one place) actually gets more difficult to predict over longer periods.
    And the same is also pretty obvious about bulk flow, just as it is about average global temperature. Today’s flow is a pretty good indicator of the flow tomorrow (even better if you have a weather forecast to hand), but it is a pretty lousy indicator of the flow in a year’s time.
    If however, you were to take “speed” of the water rather than “volume/second”, it all gets a lot worse. Because the whole dynamics of the river continually vary, and a section that may have been rapid one year, may be silted the next. And a silted section may have been scoured by a storm to have become fast flowing.
    Likewise climatic noise follows a 1/f^n type relationship, in that the longer you look at the climate, the more variation there will be.
    In total contrast to your coffee cup bogus humbug example. The truth is that the variation of the climate increases: look it for a decade it is largely than in any one year (on average). Look at it over a century, it will have MORE variation than in any decade. Look at it over a millennium and it will have even more.

  52. “There is no mechanism for climate models to correct themselves, which is why they consistently predict higher than observed temperatures.”
    Ah but there is and that is the ever fallible “seat to keyboard” interface him/herself.

  53. Climate (if you consider rainfall an element of climate) sometimes varies almost as much as weather. Look at this graph of prehistoric lake levels of Devils Lake in North Dakota.
    http://mapservice.swc.state.nd.us/4dlink9/4dcgi/GetContentPhoto/PB-42/640/480
    Devils Lake is a lake in the prairie pothole region of the US that has no outlet and thus gives a picture of how changeable precipitation patterns are in this region. The lake levels are inferred from diatom studies like this http://www.jstor.org/pss/3225026 . If it is true that soil moisture is a key difficulty with creating long term climate models, I have to think that the changeable moisture patterns in the western plains suggest that climate models are robustly intractable.
    I also remember hearing Bill Gray remark on C-SPAN that momentum fields that weather forecasters use are less troublesome than the energy fields that have to be used to create more faithful longer term models. I took this to mean that momentum being a product (mv) is less prone to error compounding than energy (mv^2) which involves a squaring.
    Is it possible that the enterprise of creating statistical climate averages misleads us into thinking something unwarranted? That this notion that we’ve created called climate is really just an average as it seems from the perspective of a lifetime or decades. To me the existence of the Roman Warm Period and the Medieval Warm Period and the Little Ice Age and for that matter the Younger Dryas all suggest that there is no such thing as a stable global climate. In and of itself there is no reason to be surprised or alarmed that we find we are in trend. What would be more surprising would be to find that with a surface as variable and varying as the earth’s that there should be a rock steady average global temperature.

  54. “Weather is chaotic and unpredictable. Climate is weather averaged out over time. Simple analogy: you can’t predict whether a coin will land heads or tails, but you can predict statistically how thousands or millions of coin tosses will go.”
    “There are dozens and dozens of good arguments which could be made about the inaccuracy of climate models, how they are misused and how poorly the science is understood. This, however, is not one of those arguments.”
    “I award you no points, and may God have mercy on your soul.”
    Answer:
    “There is no mechanism for climate models to correct themselves, which is why they consistently predict higher than observed temperatures.”
    For my chime in, comparing coin tosses to climate models is apples and oranges. There is no mechanism for climate models to correct themselves as said by Steve. The coin toss model by virtue of probabality does have self-correction inherrent in its design.
    Although, I might add a caveat here: The problem with climate models is that they are attempting to predict the future. What they should be doing is taking a wide range of input data for their training (say 1800-1950) and see if their model predicts what is known about the climate from 1950-2000. If and only then can you say these models MAY be able to predict the future.
    In the coin toss example, we can model 100 tosses as our training data, and come up with good probabalities for what the next 100 will be simply because we are certain of what certain factors are.
    HOWEVER, I should add another caveat here. Even though we might be say 95% sure that we will get between say 40 and 60 heads out of 100, there is that 5% chance that we are completely wrong. Its not in the realm of impossibility to get 100 heads out of 100. Even knowing the mechanism of a model does not mean you can predict the future to 100% at any time.
    And climate suffers from a very big disadvantage in that even with all the unknowns we have today, there is still the big unknown of “outside events.” I am talking the volcano, Feedback correction loops we don’t know about, mutations in plants that take more CO2 out of the air, asteroids, solar cycles that we have no seen yet…and the list goes on and on.
    Coin toss only suffers from the outside event that the person tossing it may be able to “ham” the results by using a weighted coin… Which is probably the only similarity between coin tosses and climate models, the process of “hamming the result set”.

  55. @ PDA July 1, 2010 at 5:33 am:
    You can’t compare this to coin flips. If we were, then you would be talking about someone claiming to predict a million coin flips to the accuracy of 10 +- 15. Unlikely garbage.

  56. And aside from that, each coin flip is independent. I would not say that each day’s weather is independent, and you certainly cannot say that climate is independent of weather.

  57. Mike,
    Your analogy is flawed in several ways – the glaring one is you’re comparing an open system (the river) to a mostly* closed system (the earth). This is why the coffee cup analogy works – its a closed system in everything except energy.
    Examining your claim that “Likewise climatic noise follows a 1/f^n type relationship, in that the longer you look at the climate, the more variation there will be,” its true in some sense, but given a broad enough timescale, you can make fairly accurate predictions, because the nature of a long time scale tends to smooth out small-scale effects. Take the Vostok ice core data, for example – http://faculty.gg.uwyo.edu/neil/teaching/Geomorph/lect_images/Vostok-ice-core-petit.png Over a large enough time scale, the temperature follows a fairly regular oscillation, which is driven by the well known Milankovich cycles. Given a sufficient understanding of the oscillation of the past, and the Milankovich cycles, it wouldn’t be unreasonable to give a ballpark prediction for several thousand years from now.
    * I say mostly, because the Earth is a closed system in almost all respects except energy, the input/output of which are fairly quantifiable on broad timescales.

  58. vukcevic says:
    July 1, 2010 at 3:21 am
    I am sure, these, in turn, are closely related to the Sun. Someone, from across the twilight zone told you, in another post, that these field forces are too low to make any change, however it is precisely the contrary, as electric/magnetic fields are 39 orders of magnitude more powerful than Fred Flintstone’s gravity powered axe!
    It´s the growing apple tree vs. the apple falling!

  59. I can tell you what the temperature will be like in July 100 years from now. Most likely very similar to the present. Over the last 80 years, summer temperatures in the US have hardly changed at all.
    Now you’re not even trying. Hint: as weather is not the same as climate, so mere extrapolation is not the same as modeling.
    As I stated in the article, a climate model run is essentially the same as a weather model run, only with more iterations, more input parameters and often a coarser spatial and temporal granularity.
    Yes, and a Peterbilt is essentially the same as a bicycle, only with more circular rotational devices, more mechanical motive power and often heated seats. If you can’t haul 160,000 lbs GCW coast to coast with a bicycle, why do you think you can do it with a Peterbilt?

  60. Feedback is by definition iterative. Suppose that a climate model assumed clouds to be a positive feedback, and it turned out they were actually negative. Each successive iteration of the model would produce increasingly inaccurate results.
    The belief system seems to be that two wrongs makes a right.

  61. Even knowing the mechanism of a model does not mean you can predict the future to 100% at any time.
    No one but you is talking about “predict[ing] the future to 100% at any time.” No one but “Steven” is saying that “Colorado will be exactly 8.72 degrees warmer in 100 years.” It’s the reductio ad absurdum where the wheels fall off you guys’ arguments.
    There is no mechanism for climate models to correct themselves, which is why they consistently predict higher than observed temperatures.
    Do they “consistently predict higher than observed temperatures?” Do you have a source for that assertion or is it just an article of faith?
    Others might disagree.

  62. Bruce Cobb,
    If you accept that we can predict that a sun with much lower radiation output would lead to a colder climate, and that a sun with a much higher radiation output would lead to a warmer climate, then you are accepting that it is possible to use physics to make some estimates of how climate may change over the long term in response to changes in the energy flows into and out of the system.

  63. WMO, IPCC, AMS, etc, etc, all define “Climate as average weather”,
    but do not define, in a reasonable scientific manner: WEATHER,
    which means there is no chance to interpret anything from CLIMATE, as discussed
    at: http://www.whatisclimate.com/
    According the AMS-Glossary:
    ___ “The “present weather” table consists of 100 possible conditions”
    ____ with 10 possibilities for “past weather”,
    _____while popularly, weather is thought of in terms of temperature, humidity, precipitation, cloudiness, visibility, and wind.
    Funny that there seems to be big, medium, and small weather, just as it pleases. More serious: WEATHER is used by science in completely unscientific manner, just as layman used it since the Ancient Greeks. That makes a fruitful discussion impossible.

  64. Paul Daniel Ash
    Climate models are backfitted with thousands of empirically derived parameters, so not surprising that they work backwards.
    I tried a stock forecasting program once which generated a fifth order polynomial to backfit past behaviour of stock prices. It was incredibly accurate looking backwards, and demonstrated zero skill looking forward.
    “With four parameters I can fit an elephant, and with five I can make him wiggle his trunk”
    Johnny Von Neumann

  65. PD Ash,
    Wake up. If models could consistently make accurate predictions, there would be no argument about any of this.
    But the plain fact is that climate models fail to accurately predict anything worthwhile, and when on occasion they happen to be right, it’s for the same reason that a broken clock is occasionally right. The climate is inherently unpredictable; the IPCC stated exactly that in AR-1.
    The only thing predictable about climate models is that their perpetrators will continue to suck money out of the public trough and waste it on their toys.

  66. carrot eater: July 1, 2010 at 6:28 am
    ……..Similarly, if the irradiation from the sun went up by 20% for some reason by 2100, I can sure tell you that on average, it’s going to be warmer here on Earth. I don’t have a chance at telling you if there’ll be an El Nino or a La Nina in Jan 2100, and I don’t have a chance at telling you if it’ll rain on Jan 21, 2100, but you can still be sure that the Earth will be warmer on average due to the active sun.

    That’s not necessarily a foregone conclusion. If the Sun suddenly increased its output, there would undoubtedly be a fairly immediate short-term warming response, but that would be accompanied by increased evaporation from the oceans, which would result in greater cloud cover, which would inhibit the inflow of solar energy and counteract the increase in temperature. Similarly, if the Sun’s output were to suddenly drop, there would be short-term cooling, but then the evaporation would decrease, producing fewer clouds, and allowing a higher proportion of the energy from the fainter Sun to penetrate to the ground, thus counteracting the decrease in temperature.
    From the geological record, Earth appears to have “hard walls” at 12°C and 22°C, and the temperature has always been somewhere in that range, through many cataclysmic changes of every kind over hundreds of millions of years. In more recent times (mere millions of years), that ±5°C has been more like ±3°C or less. Nobody knows why either of these things is true, but somehow here we are, with all of the other abundant life on the planet, still in one piece, and every single one of our ancestors has managed to survive (at least long enough to procreate).
    /dr.bill

  67. @stephen richards says:
    July 1, 2010 at 7:09 am
    Ulric Lyons says:
    July 1, 2010 at 5:03 am
    If you think about it, an accurate climate forecast would be totally dependant on deterministic long range weather forecasts, and that can only be done by predicting changes in the solar signal.
    “You are assuming only one variable, which is surely wrong.”
    Not if the Sun is driving all terrestial variables.

  68. The coin toss argument can be seen in a post here at WUWT a couple of months ago if i remember correctly. Noticed some new trolls lately here and JONOVAs site, carrot eater seems to be getting the hang of things. Myself just a laymen, dont understand all the math used but this site and some others are very good about helping you to understand it all. It is nice to see some [very few] do stay around and find just how nutty the alarmist view really is in a lot of ways. side note: Pamela Gray what happened have not seen your post in a while hope all is well?

  69. “Climate modelers on the other hand are happy to run simulations for decades (because they know that they will be retired and no one will remember what they said) and…..”

    Some will have been long dead as well. We had a 10 year tipping point from the UN back in 1989 and in 2010 we have a pasturised tipping point of 2200.
    Doesn’t the Independent ever get tired of reporting utter rubbish.
    20 March 2000 “Snowfalls are now just a thing of the past
    Verified as rubbish

    The Independent – 28 June 2010
    ‘Scientists ‘expect climate tipping point’ by 2200′
    “The global climate is more than likely to slip into an unpredictable state with unknown consequences for human societies if carbon dioxide emissions continue on their present course, a survey of leading climate scientists has found. “

    Unverified rubbish

  70. Ulric Lyons
    I think it is safe to say that all weather variables can ultimately be traced back to the sun. There would be essentially no heat and thus no weather without the sun.

  71. the plain fact is that climate models fail to accurately predict anything worthwhile
    Smokey,
    I know that you tend to be a “belief” rather than “evidence” guy, but that’s not a factual statement. It’s just not.
    Wake up.
    Wake up.
    Wake up.
    http://journals.ametsoc.org/doi/abs/10.1175/1520-0442%281998%29011%3C0109%3AAPSPWA%3E2.0.CO%3B2“>Wake up.
    Models have been shown to be accurate – not perfect, but accurate within reason, and improving – so the “fail to accurately predict” claim is false on its face.
    Again: overreach. It is possible to make meaningful objections and critiques without going overboard into “ITZ ALL A HOKES!!1!” territory.

  72. Coin flipping isn’t a good model to use when thinking about climate. It’s all predicated on a human manufacture known as the fair coin. Where is the fair coin in a climate? You only get even balance in coin flips because someone has troubled themselves to create a uniform, unvarying, even object. As Steven Goddard points out there is too much variance in things like positioning of ocean heat, soil moisture, cloud cover, and snow cover to think there is anything like an even coin with a easily readable heads and tails. The better metaphor than flipping coins for climate modeling would be augury or forecasting based on the reading of entrails.

  73. Steven:
    “If [GCMs] were simple statistical models as you imagine, there wouldn’t be need for running them on supercomputers. Your view of a climate model could be run on an abacus.”
    Are you saying that if you run a weather model out over many years, it won’t capture the seasonal cycle? Of course it does, because we understand very well how solar insolation varies by latitude during the course of a year. To leading order, predictability of the seasonal cycle is not dependent upon the chaotic dynamics that make weather prediction localized in space and time so difficult, but instead is simply dependent upon the predictability of the orientation and position of the Earth relative to the Sun.
    Similarly, when I blow air onto my hand, the dynamics of the individual particles moving out of my mouth are chaotic and thus totally unpredictable beyond some very short time-frame, but predicting the aggregate–that I will feel air hit my hand–is highly predictable.
    In this way, then, the logic of this article is incorrect. If you disagree, please feel free to respond.
    Cheers,
    Dan

  74. dr. bill:
    None of that changes what I said. If the solar output increased by 20%, and all other forcings remained the same, then the climate on earth would on average be warmer.
    What you are describing are various feedbacks. The feedbacks determine how sensitive the climate would be to the imposed change in solar – precisely how much warmer it would be, as the system responds and reacts. Some feedbacks could strengthen the initial warming, some would counteract it. But overall, it’d still be warmer, than had the sun not done that.
    I think some pretty impressive things happen within your limits. The difference between ice age and interglacial is ~ 6 C. I’d say an ice age and an interglacial are fairly different circumstances for the earth to find itself in.

  75. As a follow up to my recent post, I myself do not particularly like our climate models, especially in any context involving regional climate change projections (the scales for which predictability is indeed highly questionable). The models may indeed be very wrong even in prediction of global temperature, perhaps even for reasons given in this article, since the climate sensitivity is dependent upon boundary conditions, which themselves may have limits of predictability due to the internal dynamics of the system. However, this article does not follow that logic, but instead applies the incorrect logic that climate predictability is de facto impossible because weather predictability decreases to zero after only a few days.

  76. Of course, it is not weather vs climate in the real world, for it is all one system of interactions, with the weather/climate system being a chaotic and periodic dynamical system. If it snows in Florida, this is certainly a reflection of both the weather and the climate, for this weather/climate system is the same system, subject to both shorter term and longer term dynamics. Some find it convenient to speak of climate as an average of what the weather does over the longer term, but this is certainly not accurate, as it would miss the longer term dynamics, i.e. such as the Milankovitch cycles or events such as the Maunder Minimum. And certainly weather is more than just a reflection of the climate day by day, for to see it as such would miss the smallest of details that cause the formation of a tornado or thunderstorm for example. It might therefore be more accurate to speak as weather being the shorter term chaotic variations that ride on top of the longer term variations, much as little ripples in the ocean that ride on top of a much larger wave. Both have chaotic dynamic elements, and each is worth studying, but ultimately both are the same ocean.

  77. vukcevic says:
    July 1, 2010 at 10:20 am
    That page of yours hope to see it in science books texts, after the collapse of current paradigm and holy creed along with the disappearance of the funds which artificially support it. No money=No self indulging post normal science.

  78. Paul Daniel Ash says:
    July 1, 2010 at 10:03 am “. . . Yup, and hindcasting would show whether [there was a problem with positive vs. negative feedback]: the model would show different results than what was actually observed. And yet they don’t. Why do you suppose that is?”
    When you mention hindcasting, you hit a hot button with me. There are several reasons why GCMs produce good hindcasts, but a particularly troublesome one is their handling of aerosols. The paucity of comprehensive data on global aerosol conditions through the decades enables modelers to use convenient input parameters on this man-made contribution to climate change. Aerosols can essentially become dummy variables which make hindcasts accurate, and thus GCMs suggest a key role of CO2 in increasing temperatures since the LIA.

  79. Coin flipping isn’t a good model to use when thinking about climate.
    Agreed, which is why I wasn’t using it as “model” for “thinking about climate” but rather to highlight the clear and trivially obvious difference between predicting discrete events (a single coin-flip, next Tuesday’s weather) and statistically modelling a series of such events (10,000 coin flips, long-term climate).
    You get that. I get it. It’s not at all clear that “Steven” gets it.

  80. Paul Daniel Ash
    You linked to Scott Mandias excellent site, which states;
    “Climate models do have their limitations and modelers are constantly improving their models with newer data as the understanding of climate processes improves with research. According to the IPCC (ibid): “Nevertheless, models still show significant errors. Although these are generally greater at smaller scales, important large-scale problems also remain.”
    The IPCC themselves over the years have stated that models are not accurate and should be used with great caution. In hindcasting their own models the Met office say with confidence that temperature variability was very limited until humanity caused emissions to rise and obviously concur with Dr Mann’s view on this.
    However, to come to this conclusion they ignore their own -and other-instrumental records demonstrating very considerable variability which is overlaid by a gently warming trend that commenced in the 1680’s.
    Scott has a very nice article on the Vikings on his web site (read his disclaimer) which comtradicts Dr Mann’s and the Met Office view.
    tonyb

  81. Dan
    People run weather models out to two weeks, but they are pretty useless after 72 hours. I check the accuweather two week forecast almost every day – it changes radically from day to day.

  82. stevengoddard says:
    July 1, 2010 at 10:46 am
    Ulric Lyons
    I think it is safe to say that all weather variables can ultimately be traced back to the sun. There would be essentially no heat and thus no weather without the sun.
    ________________
    The energy from the sun is certainly the major supply of energy on earth, but for example, the Milankovitch cycle is not the sun per se, as the sun is not changing its output significantly, but it is the Earth’s eccentricity, axial tilt, and precession that are changing. So some distant alien astronomer trying to predict the Earth’s longer term climate by studying the small variations of just the total solar irradiance would fail miserably if they didn’t take the Milankovitch cycles into account. So too they would fail if they didn’t undertand the cycles of weathering of rock on earth and the changes in CO2 in the atmosphere that can be altered greatly by these geological cycles. The level of GHG’s directly impacts the climate, so in this case, it once more is not the sun per se, but the energy balance of the planet dictated by how much of that sunlight actually stays in the system.

  83. Climate models are deterministic, not random. They use random numbers for appropriate Monte Carlo issues, like locations of clouds within a grid cell. But that is a far cry from being based on randomness.

  84. carrot eater says:
    July 1, 2010 at 9:52 am
    If you accept that we can predict that a sun with much lower radiation output would lead to a colder climate, and that a sun with a much higher radiation output would lead to a warmer climate, then you are accepting that it is possible to use physics to make some estimates of how climate may change over the long term in response to changes in the energy flows into and out of the system.
    Not really, no. Climate is far more complex than that. At present, we can only study what has happened in the past wrt the sun, and try to make projections based on the history. We know that solar activity is related to, and somehow tied with sunspots, as shown, for example, by the Maunder Minimum. We know too that it has something to do with clouds, but so far, they can’t be modeled (and may never be).
    The “energy budget” concept of Warmists is a nice idea, but it conveniently diminishes some influences (like the sun) and grossly exaggerates the role of C02.

  85. There is a basic flaw in the climate forecast models and the defense of them here.
    We have the coin toss comparison:
    “Weather is chaotic and unpredictable. Climate is weather averaged out over time. Simple analogy: you can’t predict whether a coin will land heads or tails, but you can predict statistically how thousands or millions of coin tosses will go.”
    and the similar but more complex argument:
    Climate is maybe more like the ring than the fighters who stumble about, inside the boundaries… Actually, seriously, “climate” is more like predicting the probability distribution of the outcomes of 1 million fights, whereas “weather” is predicting the outcome of the next round of a single fight.
    Both of these make the same mistake – climate is not a set of “Markov” daily weather models – climate has no Markov properties a cold day affects the following day, heavy rain one day leads to higher soil moisture the next etc. As forecasters know there is a stochastic property in weather that can at times appear to be a Levy Flight although the likely bounds of the dispersion about the expectation are known (the boxing ring) where the boxer will next step may be chaotic and the step after that depends on the previous step. The ring will move to be the likely Levy Flight bounds from each boxer and could be said to represent the climate. After a round lasting a century it is difficult to forecast the position of the ring – the climate – with any accuracy.
    Added to the problem of the non-Markov Levy Flight is the lack of full understanding of the inputs that affect the weather or even knowledge that they exist. It is difficult enough attempting to forecast the behavior of a chaotic system of chaotic systems but when not all the variables are known and the effects of the known variables are uncertain it becomes gifted guesswork at best.

  86. Venter (July 1, 2010 at 7:57 am), thanks for the Pielke link. Though brief, the discussion of “initial value problem” vs “boundary value problem” really puts the issue in perspective.

  87. Climate is not exactly an average over weather, is it a wise average over weather.
    In the case of the flip of a coin, it is easy to do a wise average because the probability is 50/50 for each flip. In the case of climate, the probability to have a temperature under 40F in New-York is not the same all the time. Meteorologists are aware of several cycles wich modulate the temperature: day-night, summer-winter, el nino-la nina. Now how many other cycles are present in the system? If you calibrate a model during a positive phase of one of these cycles, you will automatically predict a positive trend that does not exist.
    I find it very difficult to believe a wise average of climate can be done when the existence or nonexistence of the medieval warm period is not supposed to have any effect on the predictions of the model.

  88. carrot eater: July 1, 2010 at 11:21 am
    Actually, I know perfectly well what I am describing, and it substantially changes what you said. You are making the standard mistake that has led the the entire ‘climate industry’ astray, namely the categorizing of physical processes as being either ‘forcings’ or ‘feedbacks’. The equations don’t neatly divide things up that way, and don’t ‘know’ which is supposed to be which. This is true even in very simple systems that are easy to solve exactly. See here, for example. If you add to that model the possibility of the ‘output hole’ altering itself in opposition to a change in the input rate (which is easy to do – you just have to add a genuine ‘feedback’ term ☺☺), you obtain a steady-state system that can be almost impervious to change. But feel free to rave on.
    /dr.bill

  89. Global warming/climate change has splitted the personalities of many former scientists, who in order to survive in such a competitive environment have surrendered their science replacing it for a creed. This is why some show two or more personalities at the same time, playing the eternal drama of good vs. evil, appearing like Dr.Jekyll and Mr.Hyde.

  90. carrot eater says:
    July 1, 2010 at 11:21 am
    “dr. bill:
    None of that changes what I said. If the solar output increased by 20%, and all other forcings remained the same, then the climate on earth would on average be warmer.
    What you are describing are various feedbacks. The feedbacks determine how sensitive the climate would be to the imposed change in solar – precisely how much warmer it would be, as the system responds and reacts. Some feedbacks could strengthen the initial warming, some would counteract it. But overall, it’d still be warmer, than had the sun not done that.”

    That assumes that the feedbacks are an invariant set. If solar output remains pretty much constant, and yet we have changes of 4, 5, 6C, then something is changing amongst the set of feedback mechanisms.
    “I think some pretty impressive things happen within your limits. The difference between ice age and interglacial is ~ 6 C. I’d say an ice age and an interglacial are fairly different circumstances for the earth to find itself in.”
    So… small differences in CO2 are enough to completely throw the various feedbacks way out of kilter? What rearranges the feedbacks to swing global temperatures back the other way?
    And back to the topic, has anyone developed a model that holds the earth’s temperature within the 12-22C range and reasonably closely models the temperature history over the past 600-800 million years? (Rhetorical of course; not that I’m aware of.)
    The point you were making in response to dr. bill is pretty clear. I’m just trying to point out the the set of the state feedback mechanisms is not constant over time nor are all the feedback mechanisms well understood or even if all feedback mechanisms completely known.

  91. R.Gates
    Both have chaotic dynamic elements
    Chaos’ explanation, or rather, justification, appears where knowledge is lacking.
    Knowledge is not so hard to attain than hard to accept.
    Pitagoras with his simple monochord attained it, how about you?

  92. “If I don’t understand it, it must be a hoax.“
    – Goddard Principle
    😛

  93. “Climate models do have their limitations and modelers are constantly improving their models with newer data as the understanding of climate processes improves with research. According to the IPCC (ibid): “Nevertheless, models still show significant errors. Although these are generally greater at smaller scales, important large-scale problems also remain.”
    I agree with this and haven’t asserted anything to the contrary. I also agree with the sentence preceding the “nevertheless,” which was not quoted: “Model global temperature projections made over the last two decades have also been in overall agreement with subsequent observations over that period.”

  94. “Climate models iterate over very long time periods, and thus compound error. ”
    Non sequitur.
    “Weather modelers consider the realm of climate calculation to be “months to seasons.””
    Whichever arbitrary and unspecified subset of weather modellers you spoke to were gravely mistaken. You can no more measure climate over months or seasons than you can measure continental drift in a minute.

  95. Günther Kirschbaum
    Don’t pollute this thread with garbage. I have never said anything about a hoax and I have an excellent understanding of climate models.
    Take it back to Romm or Tamino’s site where BS is the norm.

  96. “That assumes that the feedbacks are an invariant set. ”
    At this point, time scales matter. There are some feedbacks that operate on the shorter term. There are some feedbacks that operate over the longer term.
    For example, for a sloooooow feedback, there’s the volcano/rock weathering one. Or, similarly, all the carbon dioxide being introduced into the climate system now will eventually end up in rocks somewhere. But just because all the carbon dioxide will eventually go away if you just wait many thousands of years does not mean you can’t predict it will warm in the meantime.
    Just as there might be some feedback, perhaps now unimagined, that would over a long time counteract a huge change in the sun, it doesn’t mean you can’t predict that a huge change in the sun would have a climate impact in the meanwhile.
    To make an extreme example to prove the point: if the sun magically ceased to exist tomorrow, I really don’t care that we can’t predict weather more than a week ahead of time. I know that I’m going to be cold and dead. Actually, if we wait long enough, we’re going the other way with the sun, but you get the point.
    “you obtain a steady-state system that can be almost impervious to change. ”
    You can write whatever you want into your equation, but the actual Earth clearly isn’t impervious to change. There are ice age cycles, after all. There may have been a snowball earth or two. There was the PETM. And so on.

  97. Steven:
    “People run weather models out to two weeks, but they are pretty useless after 72 hours. I check the accuweather two week forecast almost every day – it changes radically from day to day”
    That is correct, but that’s the point: run the model out for a year, and you will see the seasonal cycle. Any given day’s forecast at a particular location (i.e. the weather forecast) will probably be wrong, but I assure you the model will predict that it will be warmer during the month of July at, say, Boston, than in the month of January (i.e. a climate forecast). One quantity may be predictable only out to a few days, but other quantities may be predictable on much longer time scales.
    Do you agree with the above statement? If not, please explain. If you do, then you understand why the logic of this article is flawed.
    Thanks,
    Dan

  98. dr.bill says: July 1, 2010 at 12:28 pm
    “…..But feel free to rave on.”
    If you are real Dr. (someone ?), then for the above choice of words, the real name rather than the ellipsis would be more appropriate, so readers can judge the real command of authority you articulate.

  99. Paul Daniel Ash mentions that some models got something right. Paul Daniel Ash: When your model does not get the cloud distribution right but in the end the temperature fits, does this not give you the feeling that it might be right for the wrong reasons? And has there ever been a climate model that gets cloud distribution over latitudes halfway right? I think it has yet to be invented.

  100. “I have an excellent understanding of climate models. ”
    Not once have you shown that you understand that weather prediction is an initial value problem, and climate is a boundary value problem.

  101. vukcevic: July 1, 2010 at 1:21 pm
    dr.bill says: July 1, 2010 at 12:28 pm
    “…..But feel free to rave on.”
    If you are real Dr. (someone ?), then for the above choice of words, the real name rather than the ellipsis would be more appropriate, so readers can judge the real command of authority you articulate.

    Translate, please?
    /dr.bill

  102. To Anthony Watts:
    Who is this “Steve Goddard” character, who now pretty much dominates your website? Do you support his posting style, which seems very far from genuine scientific scepticism? His biases are manifestly clear in his posts (he can’t seem to ever resist slipping in a snide comment at the end, even if the rest looks pseudo-scientific). Who is he? We deserve to know.

  103. When your model does not get the cloud distribution right but in the end the temperature fits, does this not give you the feeling that it might be right for the wrong reasons? And has there ever been a climate model that gets cloud distribution over latitudes halfway right? I think it has yet to be invented.
    First off, they’re not my models, and secondly yes, as I’ve been saying throughout the thread, there’s lots to criticize in how models are run and in the certainty ranges. And absolutely: parameterization of clouds and aerosols go near the top of that list. “Failing to accurately predict anything worthwhile” doesn’t even make the list.
    Past a certain point, as the goalposts get moved from “wrong” to “right but for the wrong reasons,” one has to wonder if we’re talking about science or belief. And i don’t get into religious arguments, on principle.

  104. Dan
    If all inputs were static, then every year would indeed average out to be the same.
    But the whole point of the climate models is to evaluate the feedback from changes to the environment. Feedback is calculated through iteration, and if the feedback assumptions are incorrect, the model output will become progressively divergent from reality. There is no magic averaging function which will come to the models’ rescue.

  105. Paul Daniel Ash
    I quoted verbatim from Scotts site and did not leave anything out preceding
    ‘ nevertheless’ it must have been Scott himself that truncated that quote-not me.
    Tonyb

  106. carrot eater
    If you have something specific to say technically, I’d like to hear it. But when people start quoting terminology they learned earlier in the day, it is pretty much of a turn off.

  107. When your model does not get the cloud distribution right but in the end the temperature fits, does this not give you the feeling that it might be right for the wrong reasons?
    Maybe it means clouds are not as important as you think.

  108. “weather prediction is an initial value problem, and climate is a boundary value problem” – carrot eater
    Why imagine that things divide so neatly? Isn’t it more likely that both weather prediction and climate prediction are both initial and boundary value problems?

  109. PDA, there is a big difference between random events (coin tosses) and chaotic events (climate). Get back to us when you understand the difference.
    Steve, IMHO the two fighters is a bad analogy. I see no relationship to weather and climate. Climate basically contains weather. A better analogy would be a large team of fighters vs. a single fighter on the team.

  110. Carrot said:
    “use physics to make some estimates of how climate may change over the long term in response to changes in the energy flows into and out of the system.”
    Reasonable, but then your model must expand to consider the factors in changes in the sun, and whether these factors are uncoupled to the thing predicted. Each iteration of modeling that observes external factors to the model must expand to include those factors, or your model is aliased garbage. The wonderful thing about lab-scale experiments is they can be uncoupled from multiple factors and controls can be used, but the earth??? The statement that if you can’t predict the weather you can’t predict “climate” is a completely valid viewpoint: If you don’t understand energy distribution changes over a small time, how can you assume they will react in your predicted manner indefinately? The assumption that a warmer sun leads to a warmer climate may be valid for a small window: How large, how long and how high? What factor that leads to a change in the sun also has a terrestrial effect uncoupled to irradiation? Who the [snip] knows? Who’s bothering to find out?
    Saying: CO2 and solar insolation both went up, and so did temperature, means instantly that prexisting models F(CO2)=delT and F(SI)=delT are both incorrect, and instead you must have F(CO2,SI)=delT or you are wrong, and even then you’re probably still wrong, because you can’t uncouple delT from any other factors. I think the objection at the moment is: F(CO2)=delT is too simple to be any sort of credible science. I agree.
    /general rant (again)
    Also, to have a model you must have a thing which is defined. All these completely ridiculous analogies here, subjective definitions and feel-good probability similies suggest that climate is a simple concept, some summation of some amount of particular types of weather over time which can be predicted to behave a particular way according to limitations established during the experiment. “Skeptics” point out ice ages and warm periods to suggest that what we call “climate” is really a dynamically-limited snapshot of a much larger and varied dataset which encompasses any current delT across all testable regions and that assuming “climate” should fit into that snapshot indefinately into the future is ignorant, and that concluding
    F(CO2)=delT is 1) true 2) dominant 3) indefinite is also ignorant. Where’s the valid argument to this?
    The “Climate” I see described here realistically amounts to no more than the energy distribution of a TINY (couple of miles) shell around one enormous, complex gravity producing electromagnetic body floating in an unbelievably enormous soup of radiation, gravity and magnetic fields. F(CO2)=delT IS retarded. Get over it.
    I saw somebody suggest you could mix cream in a cup of coffee and this was some analogy to climate. What utter trash is that? Splash that coffee on top of a table, put one drop of cream somewhere in the puddle, turn the lights on and off, put in a few fans, hit the table with a hammer a few times, freeze it, thaw it, stir it around with a wire brush once or twice, grow some Sea-Men in it, kill them off, let mold take over, stir the mold around, start clearing some of the mold here and there, drop a giant firecracker in it and then at the very very end of your experiment, add some warm grains of sand to represent cities and take 5 measurements of cream concentration in various locations, then use these five measurements to predict the concentration of cream correctly across the whole puddle after you add one more drop and repeat the above process. Hey, look, coffee analogy that is exceedingly more complex and accurate to reality and still fails miserably to describe external factors comprehensively.
    Climate science as a valid scientific discipline is stunted and aborned by AGW scare tactics and the world is a poorer place for it.

  111. blockquote cite=”Dan says:
    July 1, 2010 at 5:56 am
    Hi Steven,
    Let’s make a bet. I’ll bet you that the average temperature in the United States in July 2100 will be warmer than the average temperature in January 2100. If I’m wrong, I’ll give you $100. If I’m right, you give me $1. (What a deal!)
    Do you accept? If you’d like this bet to be a bit more tangible, we can change the year to 2015, or any other year of your choosing. According to your logic, accepting this deal should be a no-brainer, since you’ve claimed that prediction of climate variables and weather variables are mathematically equivalent.
    Let me know. Thanks!
    Dan
    “>
    I think you’ll find that January colder than July in the northern hemisphere due to Earth’s orbit around the Sun and the axial tilt of the Earth WRT the orbital plane.

  112. A weather forecast is what you are expected to remember.
    On Sunday you are expected to say “It’s raining, but they said on Friday it was going to be sunny”
    A climate forecast is what you are expected to forget.
    On October 31st 2013 you are not expected to say “There is still ice in the Arctic, but they said seven years ago it was going to be Ice Free.”
    The difference is that the weather forcaster will still be working at the same job when their predictions are falsified, whereas the climate forecaster will likely have already died of old age when their predictions are falsified.

  113. Found in: PDA on July 1, 2010 at 5:33 am

    REPLY: What happened to posting as Paul Daniel Ashe? Why go back into the closet, you were doing so well? – Anthony

    By the circumstantial evidence I’d say the word has gone out to take out Steven Goddard. Since “PDA” is known here, time to break out a mask, which turned out to be a lousy one. You recognized him so now the mask is off but he’s going ahead anyway.
    Seems like they’re using the plan they started using at the “Amazing Grace” thread, complain about his credentials, complain about his posting name being fake, and keep working him down until he feels he has to defend himself by declaring where his degrees are from, where he works, maybe they’re hoping he’ll skip to the chase and just give his real name and save them the effort of the tracking down. Then they can stick his name on the list and destroy him professionally.
    Heh, “PDA” linked to a one-entry new blog where he doesn’t even use the name found here, of which the domain has an anonymous registration. And while there is complaining about Steven being “anonymous”… Hey look, it’s carrot eater! Yup, got a real party going on here now. 🙂

  114. Nigel Harris
    The orthodoxy always gets upset when their position of power is threatened by outsiders.
    Team AGW is behaving more and more like the 16th century Catholic Church. Can you imagine the catastrophe which would occur if word got out that the earth is not the centre of the Universe?

  115. The Climate Model Paradox:
    If climate physics is “settled” science why are all climate models not identical? If it is not settled how can a computer projection based on unknown climate physics give remotely usable output?

    Where is Leif when you need him, he thinks computer models cannot be programmed to get the results that you want. If most climate scientists think like him it is likely they are all computer illiterate.
    RE: The silly seasonal argument,
    Saying that the winter months will be colder than the summer months in the northern hemisphere is based on observational data since man recorded such things. No need to model something you can look up in the farmers almanac. Yes of course we now know why based on the orientation of the Earth to the Sun, none of which has anything to do with being able to correctly predict or project the temperature of those months in the future.
    The problem with those who never studies computer science is they think “close-enough” results from a model are accurate, they are not they wrong (right in the sense that the model did exactly what it was supposed to, wrong in that they do not match reality). Why they are wrong (do not match reality) is a guessing game and cannot be determined on a computer. Wrong results (do not match reality) are worthless.
    Virtual reality can be whatever you want it to be and computer climate models are just that, they are the code based on the subjective opinions of the scientists creating them. The real world has no such bias.

  116. andrew adams
    If you vary clouds in radiative transfer models by 5%, you get a huge difference in the resultant surface temperature. Think about the difference in afternoon (or nighttime) temperature on a cloudy day.

  117. RW
    You should get on the phone with NOAA’s “Climate Prediction Center” right away and tell them that based on your understanding of the definition of climate, they have no business doing seasonal forecasts.
    I bet you will get a really positive response.

  118. @R. Gates says:
    July 1, 2010 at 11:51 am
    “The energy from the sun is certainly the major supply of energy on earth, but for example, the Milankovitch cycle is not the sun per se, as the sun is not changing its output significantly, but it is the Earth’s eccentricity, axial tilt, and precession that are changing. So some distant alien astronomer trying to predict the Earth’s longer term climate by studying the small variations of just the total solar irradiance would fail miserably if they didn’t take the Milankovitch cycles into account”
    The energy from the Sun is certainly the only supply of energy on earth. And as temperature change follows the large changes in solar wind velocity (and hence geomag` recordings) and not TSI, then you can regard Milankovich cycles as curious proxy for solar variation. As well as orbital cycles cannot explain the shift from 41kyr to c.100kyr glaciation cycles, and should not produce a `saw tooth` shaped feature on the rapid rise out of deep glaciation.

  119. I feel that Climate pushes Weather around, so I go with the big guy being Climate.
    The Earth isn’t the center of the universe? Things look pretty spread out in all directions to me. What would Dr Hawking say?

  120. @Enneagram says:
    July 1, 2010 at 12:37 pm
    {R.Gates
    Both have chaotic dynamic elements}
    “Chaos’ explanation, or rather, justification, appears where knowledge is lacking.
    Knowledge is not so hard to attain than hard to accept.
    Pitagoras with his simple monochord attained it, how about you?”
    Yes, weather events and temperature deviations can be (and are being) forecast way in advance from predictable changes in the solar signal. Nothing chaotic in terms of `without cause` or `random` that I can note. I understood chaos to mean change, the weather nearly always does that fortunately.

  121. PDA says:
    July 1, 2010 at 5:33 am
    […]
    Weather is chaotic and unpredictable. Climate is weather averaged out over time.

    Common quality of chaotic systems is they tend to be self-similar at any scale. If we Define weather a a phenomena lasting 15 minutes and climate as a phenomena lasting 30 years, weather seems erratic when viewed over a period of a week, like wise climate will seem erratic when viewed over a period of a millenia. Additionally whether a phenomena erratic and unpredictable, or it is chaotic are two separate issues.

  122. Ulric Lyons says: July 1, 2010 at 5:53 pm
    “I understood chaos to mean change”
    I do not think that chaos means change. I think that is in closer to a Brownian motion contribution to a system.
    I understand chaos as an attribute of a system; it is a collection of unrelated or seemingly unrelated events that have a visible effect on the system but no known or predictable underlying cause.
    Given a long enough sample of the externally visible changes in a system that contains a chaotic group of contributors one can project the next few samples. Since the chaotic contributors may be completely unrelated and not share any common cause, their contributions to the system can not be anticipated and therefore the reliability of any projection of the future state of the system beyond the immediate next few samples is as best a guess, the error bars quickly overwhelm the projection.
    Modeling a system that contains a large collection of chaotic contributors is very difficult.

  123. Tom in South Jersey
    Yes, team AGW has convinced themselves that the world depends on their belief system. The same delusions as the fanatics of every generation and every culture.

  124. One other attribute of chaotic systems that some folks seem to misunderstand is that changes can happen fast. There may be long periods of stability and then many fast changes. We see this in both weather and climate at different scales.
    Just like a change in weather often brings changes in a day or less, big changes in climate could lead to ice age conditions in a few decades. That makes predictions of events in 2100 silly at best … dishonest at worst.

  125. @paul jackson says:
    July 1, 2010 at 6:30 pm
    “Given a long enough sample of the externally visible changes in a system that contains a chaotic group of contributors one can project the next few samples….
    Given a long enough sample of the externally visible changes in a system that contains a chaotic group of contributors one can project the next few samples. Since the chaotic contributors may be completely unrelated and not share any common cause, their contributions to the system can not be anticipated and therefore the reliability of any projection of the future state of the system beyond the immediate next few samples is as best a guess,”
    Yes, weather events and temperature deviations can be (and are being) forecast way in advance from predictable changes in the solar signal.
    And from an accuracy currently of 49/52 weeks per year correct for temperature deviations from normals, and with an understanding of temperature/precipitation relationships at different seasons, it is possible to not only do very exacting climatic temperature forecasts, but also the all important hydrology factors, ie. flood/drought cycle mapping.

  126. tonyb:
    it must have been Scott himself that truncated that quote-not me.
    I wasn’t making a specific accusation, just pointing out that there was more context.
    KD Knoebel:
    Since “PDA” is known here, time to break out a mask,
    I’m “known here?” Under a name I’ve never posted with before? Awesome! Sorry I haven’t blogged more, but please feel free to come over and comment.
    I only tweaked “Steven Goddard” about his pseudonymity as a way of responding to Anthony’s hypocrisy about “anonymous cowards.” I made a number of substantive comments too, “KD Knoebel.” Did you read them? Do you have any response, or is attempting character assassination all you’ve got?
    By the way, where’s your blog? Where’s your WHOIS registry, what’s your online record? Or is creepy webstalking only for people you disagree with?
    paul jackson:
    Common quality of chaotic systems is they tend to be self-similar at any scale.
    You are saying “chaotic systems” but you mean “fractals.” It might be cool around here to just redefine scientific concepts on the fly, but that doesn’t mean it makes any sense.
    Andrew30:
    I understand chaos as an attribute of a system; it is a collection of unrelated or seemingly unrelated events that have a visible effect on the system but no known or predictable underlying cause.
    Ditto. You could try reading about chaos, or you could just keep groping around in the dark. Your choice!

  127. Ulric Lyons said:
    “The energy from the Sun is certainly the only supply of energy on earth…”
    _________________
    Quite untrue. There are several more, and so I don’t think you’ve thought this through very well, but let me give you a hint: Think Madame Curie. Here’s another hint: Think of Eyjafjallajokull. So when our spacecraft leave the Earth and travel deep into space where the influence of the sun’s energy is even less, or non-existent, then we rely on the first of these non-solar sources of energy (it being too impractical to take small volcanoes onboard a spacecraft)
    But in general, I don’t deny the major role that the sun plays in the Earth’s climate, but I also am not blind to the other factors. The weathering of rock for example and geological processes such as volcanoes are completely independent of solar output but have major influences on the composition of our atmosphere and in creating the GHG forcing that we enjoy and the subsequent climate, without which, we’d all be, well…nonexistent.

  128. stevengoddard says:
    July 1, 2010 at 7:14 pm
    Tom in South Jersey
    Yes, team AGW has convinced themselves that the world depends on their belief system. The same delusions as the fanatics of every generation and every culture.
    _______________
    Well, I guess I currently am part of this “team AGW” (at least 75% of me), and I am certain that world (both natural and man made) could give a rat’s ass about my belief systems. I look around and see fanatics on both sides of this issue– a fanatic being someone who absolutely will never change their paradigm no matter what facts are presented to them because it is an emotional bond they have with their beliefs, not a rational one. I have no such attachment, and could easily change my beliefs given rational evidence to do so.

  129. @R. Gates says:
    July 1, 2010 at 7:31 pm
    Ulric Lyons said:
    “The energy from the Sun is certainly the only supply of energy on earth…”
    _________________
    Quite untrue. There are several more, and so I don’t think you’ve thought this through very well, but let me give you a hint: Think Madame Curie. Here’s another hint: Think of Eyjafjallajokull.
    __________________________
    So if the Sun were to `switch off`, x billion people huddle round a handfull of active volcanoes and some nuclear reactor cores as planet Earth ice balls?

  130. R. Gates
    All of the heat being generated in the earth is ultimately from radioactive decay, including that coming out of volcanoes. But that is a tiny amount compared to what the earth receives from the sun.

  131. R. Gates, you should listen to Bobbie Burns: “To see oursels as ithers see us!”
    You claim that “no matter what facts are presented to them [skeptics – the only honest kind of scientists] because it is an emotional bond they have with their beliefs, not a rational one. I have no such attachment…”
    Who are you trying to kid? You constantly call yourself a 75% climate alarmist [while heading a 2-car household], and pretend that you have an open mind??
    Please.
    Admit what you are: a CAGW advocate pushing an agenda.
    And for my skeptical part, simply show me where the climate has exceeded its past parameters, and you will have a CAGW convert.
    Word up.

  132. carrot eater says:
    July 1, 2010 at 1:42 pm
    “Not once have you shown that you understand that weather prediction is an initial value problem, and climate is a boundary value problem.”
    This is NOT true! Please have a look at the differential equations being solved. This idea that the solutions do not depend on the initial conditions is simply bogus and demonstrates a fundamental lack of understanding of mathematical physics…
    Also, read this.

  133. Having spent much time examining anomalies on 4,200 months of CET, it became apparent to me that the majority of the coldest winters, were soon followed by above normal temperatures, usually as early as April, and typically July at the latest. It is not very easy to identify many times where a significant number of years in succession have markedly both lower winter, and lower summer temperatures. The two clear examples are a run from the mid 1680`s to the late 1690`s (the worst of Maunder), and a few years around 1815. The observation of a none to clear climatic signiture of the late LIA in CET has also been noted here;
    http://homepage.ntlworld.com/jdrake/Questioning_Climate/_sgg/m2_1.htm
    The majority of the series would appear to consist of short term changes in temperature, showing far larger range in the winter months, and very little evidence for what is conventionally regarded as a climatic tendancy or trend/cycle, more like event clusters, a bunch of warm winters and then a bunch of cooler winters, to simplify.
    This very useful resource shows the same patterns through the earlier parts of the LIA, in terms of hot years right next to very cold years, or cold winters followed by hot summers:
    http://booty.org.uk/booty.weather/climate/histclimat.htm
    It is very clear to me that what is regarded as weather, not only completely dominates climatic structure, but season by season, is what we really need to know about first, due the magnitude of natural variation.

  134. On Canada Day nothing better than an Environment Canada gem:
    “Asked if there may be a hot spell on the horizon, Jones said he couldn’t say other than noting mid-July to mid-August is typically the driest time of the year for Vancouver:
    “Just ignore [the long-term forecast] because there’s nothing we can tell you with any reliability,” he said.”
    Amaaaaazing!

  135. This is what Kerry and Waxman said about GRACE. I’m surprised all the GRACE apologists here didn’t rush to Washington to straighten them out.

    Congressional Democrats, including Sen. John F. Kerry (Mass.) and Rep. Henry A. Waxman (Calif.) said yesterday that the two new papers show that the United States must act quickly to impose mandatory limits on carbon dioxide and other greenhouse gases.
    “Climate change is not just someone else’s concern but a very real threat to the lives and livelihood of people across the globe,” Kerry said.

  136. Paul Daniel Ash says: July 1, 2010 at 7:27 pm
    “You could try reading about chaos, or you could just keep groping around in the dark. Your choice!”
    When was the last time you took money from a automated teller machine?
    Was it empty? Why did you choose that ATM at that time? Why not an hour later or the next day? Why did you not choose one a few blocks down the road? Somehow the machine seldom runs out of cash and yet the bank pays the minimum possible overnight interest of the unsold cash in the machine while spending a minimum amount in filling charges.
    In that model you are the chaos. Unpredictable, yet I knew that you would be there 3 days before you did.
    When was the last time you made a cell phone call? Did you get a signal? Was there space on the tower when you needed it? Did you notice when you were moved to another tower in anticipation of another call or that you were ok with the tower that you were on?
    In that model you are the chaos. Unpredictable, yet I knew that you would be there 3 hours before you did.
    Some models of systems must work with chaotic elements, like you.
    I think I understand how to model a cyclical system with a large contingent of chaotic influences. Do you? Or do you just read about it?

  137. winterkorn July 1, 2010 at 7:51 am:
    However, when the agenda-driven get hold of it, and like so many Cassandras, cry “Doom, doom is nigh….doom deserved because we are eco-evil!”

    At the risk of being accused of pedantry, I’ll point out that Cassandra was blessed with the gift of prophecy, and cursed so that her predictions, though correct, would not be believed. So I certainly hope that the doom-sayers are not Cassandras.
    I wouldn’t be disappointed, though, if the not-believed part were accurate.

  138. dr.bill says: July 1, 2010 at 12:28 pm
    “…..But feel free to rave on.”
    vukcevic: July 1, 2010 at 1:21 pm
    If you are real Dr. (someone ?), then for the above choice of words, the real name rather than the ellipsis would be more appropriate, so readers can judge the real command of authority you articulate.
    dr.bill says: July 1, 2010 at 2:02 pm
    “Translate, please?”
    No need doc. I also use Vuk etc. when frivolous…

  139. CarrotEater declares: “Not once have you shown that you understand that weather prediction is an initial value problem, and climate is a boundary value problem.”
    This primitive authoritarianism is really annoying. I am tired of repetition of this meaningless AGW gobbledygook.
    There is no “climate boundary or initial or whatever problem”, there is only one coupled dynamical system that can be considered as two coupled boundary value problems, oceans and atmosphere, with non-trivial (and non-stationary) boundary conditions and with uncountable set of possible initial states (“values”) of the system. There is only one (and fully deterministic) evolution of these initial states called “weather”, which appears to be quite irregular and chaotic.
    One can apply various spatio-temporal filters over these solutions and call them whatever you wish, “regional climate”, “global seasonal (or yearly) temperature”, whatever suite your needs. However, the science (classical mechanics) of condensed media has come to conclusion that averaged equations of this turbulent motion are not closed, and therefore no new physical abstraction can be identified (that can be called “climate”) and governed by some special physical equations. Therefore, one cannot “calculate climate” without calculating physical weather first.
    This does not mean that the weather must be calculated precisely to reproduce every hurricane or location and time of every tornado in Texas. Since topological properties of phase flow on weather attractor are known to have hyperbolic qualities, the weather seems to be pretty ergodic, and therefore small computational imperfections should keep the [correctly designed] system on the attractor, such that statistically speaking the GCMs should be capable of predicting climate. The keyword here is “correctly designed”, especially with regard to slow-changing boundary conditions and long-distance weak interactions.
    Cheers to audacious climate modelers – Al

  140. Paul Daniel Ash
    The IPCC also say:
    http://www.ipcc.ch/ipccreports/tar/wg1/505.htm
    “In sum, a strategy must recognise what is possible. In climate research and modelling, we should recognise that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible. The most we can expect to achieve is the prediction of the probability distribution of the systems future possible states by the generation of ensembles of model solutions. This reduces climate change to the discernment of significant differences in the statistics of such ensembles. The generation of such model ensembles will require the dedication of greatly increased computer resources and the application of new methods of model diagnosis. Addressing adequately the statistical nature of climate is computationally intensive, but such statistical information is essential.”
    The IPcc and Kevin Trenberth continually cite concerns over computer models of which clouds-amongst other factors-are a particular fly in the ointment.
    That is not to say that such models are not interesting, but merely that the phrase ‘not possible’ should be a hint as to the degree of credence we should place on them
    tonyb

  141. IPCC climate modelling GIGO
    Relative forcing
    Solar irradiance — 0.12 W/ m sq , CO2 —- 1.66 W/ m sq, for CO2 10 x greater
    http://www.ipcc.ch/graphics/syr/fig2-4.jpg
    Models gives results
    http://www.ipcc.ch/graphics/syr/fig2-5.jpg
    Now interesting thing about it is: Observations are always in the middle of the modelled range. Smell of a ‘dead’ rat.
    I suspect: Use observations, work backwards and calculate relative forcing then adjust the range to fit observations.
    I suggest to the Core Writing Team of IPCC i.e. Pachauri, R.K. and Reisinger, A. (Eds.) to take a look at this:
    http://www.vukcevic.talktalk.net/AMOFz.htm
    No forcing, no back calculations and no fiddles here, just what natural system does, like it or not.

  142. Steven:
    “But the whole point of the climate models is to evaluate the feedback from changes to the environment. Feedback is calculated through iteration, and if the feedback assumptions are incorrect, the model output will become progressively divergent from reality. There is no magic averaging function which will come to the models’ rescue.”
    That may be true, but it is not de facto true as you try to claim in this article–and this is my point of contention. Just because some of the dynamics of the system are chaotic does not mean all of the dynamics are. I have no problem with skepticism over the models (I myself am quite weary of them as well; I am an atmospheric scientist), but your particular skepticism is based on the faulty science. And when you purport to be a science blog, you lose credibility.
    Re: your response to carrot eater
    CE: “Not once have you shown that you understand that weather prediction is an initial value problem, and climate is a boundary value problem.”
    SG: “If you have something specific to say technically, I’d like to hear it. But when people start quoting terminology they learned earlier in the day, it is pretty much of a turn off.”
    Do you think that is a reasonable, professional response?
    timheyes:
    “I think you’ll find that January colder than July in the northern hemisphere due to Earth’s orbit around the Sun and the axial tilt of the Earth WRT the orbital plane.”
    Exactly. And the dynamics of the Earth’s orientation relative to the Sun are well-understood and easy to predict long into the future.

  143. Tonyb,
    I’m glad at least someone else here gets that models are used to predict “the probability distribution of the system’s future possible states by the generation of ensembles of model solutions.” The highlighted words are important: using output from a range of different models – rather than relying on just one – to estimate the likely ranges of a host of variables. Very different than a specific forecast.
    The idea that models are thought of as perfect predictors in part comes from the popular press, no doubt, who treat big computers as some sort of time machines. It’s also a useful straw man to some, obviously, as evidenced by this whole nonsense about “100%” and “exactly 8.72 degrees warmer.”

  144. “By contrast, climate modelers have the advantage that they will be long since retired when their predictions don’t come to pass.”
    =====
    Ot long since retired when their predictions do come to pass.

  145. Smokey says:
    July 1, 2010 at 8:29 pm
    R. Gates, you should listen to Bobbie Burns: “To see oursels as ithers see us!”
    You claim that “no matter what facts are presented to them [skeptics – the only honest kind of scientists] because it is an emotional bond they have with their beliefs, not a rational one. I have no such attachment…”
    Who are you trying to kid? You constantly call yourself a 75% climate alarmist [while heading a 2-car household], and pretend that you have an open mind??
    Please.
    Admit what you are: a CAGW advocate pushing an agenda.
    And for my skeptical part, simply show me where the climate has exceeded its past parameters, and you will have a CAGW convert.
    Word up.
    _____________________
    Actually Sparky, you once more really twist my words as I was quite clearly talking about the true believers on both side of the issue, “warmist” and “skeptic” alike. I may be on the side of believing the AGW is likely happening, but I’m hardly an alarmist nor do I put the “C” in front of my AGW beliefs.
    I’m not out to convert anyone, but simply try to present alternative views to plainly wrong or completely cherry-picked data, though it may be hard for some so-called skeptics to imagine that there are those who think that AGW could be happening without being alarmist, wild-eyed radicals. True believers want to see the world in extreme terms, and in fact can ONLY see the world in extreme terms– everyone is a saint or a sinner, whereas in reality most people are neither.

  146. I’ve noticed that most people’s perception this issue is pretty broadly colored by their cultural preconceptions.
    Folks who dislike big business will see reports of potential consequences in the media and discard anything that doesn’t fit as misinformation paid for by Big Oil, calling for changes in the economy and Western lifestyle that suit their ideological preferences.
    Similarly, people who tend to mistrust government and academia see any ambiguous or contradictory study as vindication of beliefs that AGW is mostly or entirely a sham foisted upon the public by cynical scientists and liberal ideologues, for grant money and to further a particular political agenda.
    There are – of course – exceptions to the rule, but I’ve found the correspondence between climate change attitudes and cultural affinities to be very strong in almost every case.

  147. “This idea that the solutions do not depend on the initial conditions is simply bogus and demonstrates a fundamental lack of understanding of mathematical physics…”
    The solution does depend on the initial condition. That’s why you run the model several times at different initial conditions, to get an ensemble of results.
    But given the same boundary conditions (the external forcings), the long term trends are going to be about the same in each case. It’s the short term and decadal wiggles that differ.
    Same as my point with the sun. Crank up the sun by 20%, and I won’t know if it’s El Nino or La Nina in Jan 2100, but I know on average it’s going to warm up over time.

  148. Hi Paul your 7.44
    Is that your web site linked to from your name? Some interesting articles.
    I partially agree with what you write above, but I think that those on the ‘other side’ completely fail to notice that there are some considerable differences between those you would put under the one generic term of ‘sceptic.”
    I wrote the folowing comment to another warmist but think it is very relevant to your observations. Comment from my warmist friend first;
    “My theory would be that nearly all sceptics, and I can’t see any exceptions on this blog, start off being sceptical, usually for political reasons, and any science they later bring into the argument is done to try to bolster their preconceived position.”
    I disagree. Most disbelievers start off agreeing with the party line-that there is AGW-and only after looking at it properly do a proportion then realise all is not what it seems. They have looked at the facts and changed their minds, so how is that bolstering their pre conceived position?
    I think what you have failed to appreciate is that there are two main types of ‘disbelievers’.
    The first are ’sceptics’ who have thought deeply about it, read the papers and changed their original position based on actual facts and observations. With this group you consistently hugely overestimate the political aspect.
    The second group are ‘deniers’ (lower case and non perjorative) who hate the govt, hate authority, believe they should be able to do whatever they want. AGW is just one of many things they automatically disbelieve because they think it is a govt attempt to control them. There is a political element here, but equally very many hate govt of any complexion.
    This last group hate AGW because they believe it is being used as a tool of the govt to intrude in to their life. The latter would go on denying until their last breath- no matter the proof. The former are perfectly rational people and would look at the evidence presented to them, but based on the past performance of some of those involved in promoting AGW-and the exaggerated claims made-would want to delve behind the headlines before accepting anything as factual.
    Your group also has similar schisms. The quote you are trotting out about Al Gore is replicated in numerous green blogs where the green believer has as much made up their mind as the ‘denier’. There was a prime example of that this morning from the latest climate group interviewed on the BBC who said they ‘just know’ that man is wrecking the planet.
    When there are so many question marks about the reliability of data-sea level rise,arctic ice variation through the centuries,global temperatures to 1850, Ocean temperatures,Co2 levels, and so many unknown facets- such as the real effect of the sun, the PDO etc, it is supremely arrogant of anyone to believe that the science is settled.”
    So Paul, I believe that there are two broad movements on my side, one more rational than the other and most of whom probably started off in your camp. Equally there are two broad movements on your side, of which only one is reasonably rational and the other who would believe anyting that fitted into their world view.
    I have come to believe over the years that ‘our’ rational wing is somewhat larger than yours. 🙂
    Best regards
    Tonyb

  149. From: Paul Daniel Ash on July 2, 2010 at 5:38 am

    I’m glad at least someone else here gets that models are used to predict “the probability distribution of the system’s future possible states by the generation of ensembles of model solutions.” The highlighted words are important: using output from a range of different models – rather than relying on just one – to estimate the likely ranges of a host of variables. Very different than a specific forecast.

    Major problem being, that might not be how “ensemble” is used.
    From Zhang’s (and Lindsay’s) “Introduction” section on the “Seasonal Ensemble Forecasts of Arctic Sea Ice” page:

    The model is the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS, Zhang and Rothrock, 2003). The ensemble predictions are constructed by using the NCEP/NCAR atmospheric forcing from the previous 7 years (corresponding to 7 ensemble members) and the PIOMAS retrospectively estimated, with assimilation of satellite ice concentration data, ice and ocean conditions at a given date at which ensemble predictions start. Details about the ensemble prediction procedure may be found in Zhang et al., 2008.

    In the 2008 paper we find:

    The ensemble predictions consist of seven numerical experiments with PIOMAS. Each of these seven individual ensemble members is associated with a unique set of forcing fields that are used to drive the model from 1 October 2007 to 30 September 2008. We use daily forcing fields from the NCEP/NCAR reanalysis such that ensemble member 1 uses the reanalysis forcing over the period 1 October 2000 through 30 September 2001, member 2 over the period 1 October 2001 through September 30, 2002, etc., and member 7 over the period 1 October 2006 through 30 September 2007. To our knowledge this is the first time ensemble prediction methods have been applied to forecasts of Arctic sea ice.

    Same model, different input data. You can see what the output looks like in the 2008 SEARCH Sea Ice Outlook (Full Report tab), Figure 6. From the ensemble came a median map.
    As you quoted, “…by the generation of ensembles of model solutions.” This is what Zhang does. What you interpreted: “The highlighted words are important: using output from a range of different models – rather than relying on just one – to estimate the likely ranges of a host of variables.” Sorry, but only one model could be used for an ensemble forecast. Thus the accuracy of the ensemble forecast is dependent on the accuracy of that single model.

  150. Dan
    I am not talking about chaos. If you have the wrong polarity on a deterministic factor like cloud feedback, the results will increasingly diverge from reality through each iteration.

  151. For example, if your bank gives you -5% interest and you are expecting +5% interest, you may come up with different compounded numbers after a few years. ;^)

  152. TonyB,
    What you describe has been noted over and over here: readers regularly comment that they assumed at first that “global warming” was a problem — until they did a little investigating, and realized that the whole CAGW premise has no empirical, testable evidence supporting it.
    Those who claim that scientific skepticism is ‘political’ suffer from psychological projection. They are hobbled by their political belief system, and they cannot accept that what skeptics are saying is: prove it. Or at least provide real world, verifiable evidence showing that an increase in a minor trace gas controls the planet’s temperature.
    If the financial stakes weren’t so high, the self-serving clowns promoting the CO2=CAGW conjecture would be laughed off stage for being a crowd of pseudo-scientific Elmer Gantry clones.

  153. I think what you have failed to appreciate is that there are two main types of ‘disbelievers’.
    No, I allowed for that. I don’t have any way of knowing how large each group is, but I’m sure that the blind skeptics and blind believers well outweigh their counterparts when it comes to internet postings.
    Or at least provide real world, verifiable evidence showing that an increase in a minor trace gas controls the planet’s temperature.
    Smokey, you keep saying that over and over again, but you never indicate what it could possibly mean. What would this “real world, verifiable evidence” look like? Can we tag individual molecules of CO2 and measure the forcing of that molecule and no other? Obviously not. What, then, would constitute the evidence you claim to be searching for? Give an example, or let go of the talking point: you can’t look for something without any way to recognize when you’ve found it.
    [REPLY – At a guess, I think perhaps he means something that would refute Lindzen’s study on radiative forcing observations. However, you may be correct about the blindness of most on both sides as expressed on the internet. (Not in this forum, of course!) ~ Evan]

  154. Goddard:
    If you have some feedback completely wrong or completely missing, then obviously yes, your projection of where things will be in the distant future will not be in the right ballpark.
    If that’s the basis of the point you’re trying to make, you could have actually written that in the original post.

  155. carrot eater says:
    July 2, 2010 at 8:08 am
    “The solution does depend on the initial condition. ”
    Yes it does! The PDEs demand it :^)
    “That’s why you run the model several times at different initial conditions, to get an ensemble of results.”
    So the climate solutions don’t “forget” their initial conditions like some claim. Excellent! :^)
    “But given the same boundary conditions (the external forcings), the long term trends are going to be about the same in each case. It’s the short term and decadal wiggles that differ.”
    However, the problem is that the boundary conditions depend non-linearly on the evolving solution. And the external “forcings” are not known perfectly. In the end, the “trends” generated by these models are going to be highly dependent on the behavior of the submodels (which are themselves imperfect) and the prescribed forcings. By the way, if everyone uses the same forcings, do you think the trends will be similar?? …hmmmm…
    All of this begs another question – if the short term climate solutions are not accurate, why run them with high resolution grids? For example:
    http://www.hpcwire.com/offthewire/NASA-Center-for-Climate-Simulation-Debuts-Spring-2010-95542709.html
    “With the new augmentations of Discover we probably have a 3 to 4x increase in the amount of work that we can push through the computer in a day,” Webster said. “You can run more simulations at the same resolutions you’ve had, but the thing that really excites us is that we can run much higher resolution simulations.”
    By the way, the multi-million dollar “new augmentations” of the Discover computing facility (referred to above) were paid for by US government “stimulus” money…just in case anyone was wondering who’s getting the climate ca$h…

  156. Paul Daniel Ash said:
    There are – of course – exceptions to the rule, but I’ve found the correspondence between climate change attitudes and cultural affinities to be very strong in almost every case.
    ___________
    I agree, the correspondence is high (for the extremists on both ends, but less so for the larger group moderates in the middle) and runs the full range from social and religious to political and economic.

  157. Thus the accuracy of the ensemble forecast is dependent on the accuracy of that single model.
    Depends on what you mean by “model.” If you run simulations on the same system (e.g. PIOMAS) with different parameters, different forcings, different initial conditions, I wouldn’t call those the same “model.”
    What you seem to be referring to is meta-ensembles: my understanding is that’s been tried and is tricky but promising:
    http://journals.ametsoc.org/doi/pdf/10.1175/BAMS-89-3-303

  158. Paul
    I have always taken the view that there are very many more important things than AGW to worry about, that can be tackled much more cheaply and with greater overall benefits.
    So should we worry about weather-known to knock humanity sideways at times-the climate-surely something more powerful than any of us- or trying to influince things where we can make a difference?
    I think you’ll enjoy this article from Bjorn Lomberg in todays Telegraph. I think this would make an interesting thread here together with the opportnity to vote as to where we should conentrate our resources.
    http://www.telegraph.co.uk/comment/personal-view/3613517/Save-the-world-ignore-global-warming.html
    tonyb

  159. Evan,
    No need to guess on my behalf, I’m here to help. As I’ve repeatedly explained, empirical evidence consists of verifiable facts, such as raw temperature data – you know, the kind of raw data that’s so difficult to get, despite FOI requests, and Steve McIntyre’s non-stop efforts, among others. It is clear that mainstream climatologists do not believe in the scientific method.
    I’m currently reading Montford’s The Hockey Stick Illusion, and it reinforces the fact that there is almost no empirical evidence in climatology. Everything has been “adjusted” [almost always upward] and getting the original raw data is harder than pulling teeth. Montford pulls no punches, labeling this meddling with the original data “scientific misconduct.”
    Also, I have no problem with radiative physics. The problem is again that there is no empirical, testable data showing the extent of any warming due to human CO2 emissions; it is all based on climate models.
    If there existed verifiable, testable data showing the impact of increased CO2 on temperature, then there would not be any argument over the climate sensitivity number. The sensitivity number gets ratcheted downward in every new Assessment Report, and based on the planet’s response to the CO2 being emitted both naturally and by human activity, it’s easy to see that CO2 has very little real world effect once the natural warming from the LIA is taken into account.

  160. Excerpts from: Paul Daniel Ash on July 1, 2010 at 7:27 pm

    I’m “known here?” Under a name I’ve never posted with before?

    Near as I could tell since I wasn’t here when it was posted, Anthony had you pegged as “PDA” right away. Afterwards you went back to the full name. BTW, your “explanation” doesn’t make sense. Purging the cache, actually the “personal data” like the cookies, leaves a blank comment form. Since “Name” is a required field then automatically hitting “Post Comment” while assuming the fields (which includes “Email” and “Website”) were auto-filled should have caused the post to be rejected. After such purging, I know of no mechanism by which “PDA” would have been auto-filled in that field. Therefore for “PDA” to be there, someone typed it in. Most likely, you typed it in.
    If you have an alternate explanation of how “PDA” got in the “Name” field, perhaps some funky weird Windoze auto-fill thing which would seem to indicate you have used “PDA” before, that actually makes sense, or can properly explain how your previous explanation really does make sense, feel free to supply it.
    BTW, from your “explanation”:

    And I’m assuming you’re giving “Steven” just as hard a time for being “in the closet” as you do everyone else who writes under a pseudonym. Right?

    Now that the “Climate Wars” have escalated to (C)AGW proponents drawing up hit lists, note the last part is not in quotes, anonymity is self-protection from reprisals. Indeed, certain “Doubters” not up to doing Resistance work would be well justified in pulling an Anne Frank for a while.
    Another excerpt:

    By the way, where’s your blog? Where’s your WHOIS registry, what’s your online record? Or is creepy webstalking only for people you disagree with?

    My, aren’t you reaching? You have my first initials and last name, I am in central Pennsylvania “near the river” as I have posted before. I am also in relatively close proximity to at least three (C)AGW-friendly universities, sole caretaker of my mother who is in frail health, as I was to both my parents not long ago, and groups of (C)AGW deluded protesters or even a sole “determined” individual showing up on the property could well be enough stress to kill her. After anywhere from a day to a few years from now that will change, then you will find out the rest.

  161. Smokey, regarding data and proof of CO2 effects.
    Does the satellite data of Roy Spencer et al. count? That shows stratospheric cooling and tropospheric warming which cannot be accounted for by any other mechanism than CO2, being on a global scale, and is somewhat in line with what would be expected to be observed.

  162. Jim D,
    Yes, Dr Spencer’s data appears to be empirical evidence. However, you shouldn’t overstep by saying that CO2 is the only possible mechanism. That’s the often used argumentum ad ignorantium fallacy here: because we can’t conceive of any other explanation, then the one we have must be the only possible answer. In fact, there are many possible answers.
    What we lack is empirical evidence showing the impact of a given amount of CO2 that results in a specific increase in global temperature. We don’t even know the true global temperature, because the raw data has been adjusted and re-adjusted so often [the CET is an exception, which does not agree with the IPCC or Michael Mann’s version of reality]. At this point there is too much we don’t know, which results in guesswork. If we knew the true climate sensitivity number, all this would be moot.
    But we are really just guessing at this point, which is why the scientific method is so critical. The alarmist crowd wants us to take their word for it, while the skeptics respond: make your case by using unadjusted empirical evidence. The alarmists’ consternation at having their feet held to the fire of the scientific method is obvious.

  163. From: Paul Daniel Ash on July 2, 2010 at 10:49 am

    Depends on what you mean by “model.” If you run simulations on the same system (e.g. PIOMAS) with different parameters, different forcings, different initial conditions, I wouldn’t call those the same “model.”

    “Model” is a glorified name for a program, with all its subprograms and subroutines etc, which can use some data that is not inputted at the start or during the running (the “tweaking” etc). Your argument boils down to saying since different numbers were used then it’s not the same program.

    What you seem to be referring to is meta-ensembles: my understanding is that’s been tried and is tricky but promising:
    http://journals.ametsoc.org/doi/pdf/10.1175/BAMS-89-3-303

    Tricky but promising, yet acceptable for use by Zhang et al? If the method is good enough to stake a professional reputation on it, then it must be considered acceptable at least by those doing so, don’t you think?
    BTW, what is this talk of the Global Climate Models being run with different initial conditions? The initial conditions would be the previous weather records, or “climate records” if you insist, with the related info like CO2 concentrations and ocean temps. You have to run a model from a starting point, so you input the starting point. How can you have different “initial conditions” of the same starting point? You can have different runtime parameters to generate an ensemble of predictions, but it’s still the same starting point thus the same initial conditions for all runs in the ensemble.

  164. groweg says:
    July 1, 2010 at 6:24 am
    ….My prediction on that (not computer generated) is that it will destroy our economy and reduce our standard of living to underdeveloped country levels.
    _________________________________________________________________________
    One of the things everyone seems to forget is underdeveloped countries have a working society and knowledge base that can support their civilization at a lower level of development. Western civilization do not. We do not have the level of expertise or the social structure to keep our society going when our idiotic governments yank the rug out from under us by limiting CO2.
    Think about it.
    1) The UK is planning to shutting down 30% of its present power capacity by 2030 and replace it with “green energy”
    2) the EU has ban the building of heated family homes in the year 2020.
    3) And a new report, published today, which features input from 13 universities and 12 research bodies…call for an 80% reduction in livestock numbers
    Now add in higher taxes, higher real costs for everything, lower food production because of energy/oil limitations and higher unemployment. Seems to me the politicians have come up with a really really good recipe for anarchy and riots. On the other hand destabilizing a country is the first step in making it vulnerable for take over. I wonder if there is a reason, Maurice Strong, Architect for this madness called CAGW, has moved to China to be an advisor to the Chinese government…..

  165. kadaka asks: “How can you have different “initial conditions” of the same starting point?”
    A model usually has much bigger space of initial conditions than “weather records” can provide. For each “weather record” (usually obtained at ground point) one needs to supply the state of entire atmosphere. For each ground “weather record” there could be a large number of slightly different atmospheric “configurations”. Also, “weather records” have finite (and very lousy) accuracy; therefore small deformations of the same “weather record” within the range of data errors would produce different trajectories in a long run, just as Ed Lorenz has originally discovered in his attractor. However, the space of deformations might not be contiguous, and might have “islands” that belong to different attractors, and climate modelers do not have much of an idea that their initial conditions might provide very different outcomes for the same model. The climateprediction.net is an example.

  166. @Enneagram says:
    July 1, 2010 at 12:29 pm
    “Global warming/climate change has splitted the personalities of many former scientists, who in order to survive in such a competitive environment have surrendered their science replacing it for a creed. This is why some show two or more personalities at the same time, playing the eternal drama of good vs. evil, appearing like Dr.Jekyll and Mr.Hyde.”
    So the Alter-Ego (like the alter in a church) of Global warming/climate change dominates the true self of `just a change in the weather` through its feelings of inadequacy of not being able to understand its own true nature and personality (traumatised ego), and hence what it would do next, while needing to appear to be `in the know`, which then provides the need for a social`mask` of respectability…. Enter the alter-ego, whose nature is typically the complete opposite of the self, and totally unable to to see the true self, while being totally at its mercy. This puts increasing pressure on the alter-ego to expand its reasons for its own existance, and its own claims of self importance, to a point of critical mass, where the whole thing has to essentially super nova, as it has become so detached from reality, and is an unbearable strain on relationships.
    The harder they come, the harder they fall.

  167. How about using the word `climate` in its traditional sense as a regional norm, and then discuss the weather as it happens (or in advance if you are a good forecaster) and just leave it at that.

  168. Enneagram thanks for the note. I will eventually put some units on it, and may write a bit, but at the moment working on something else, just as controversial. Our cat is enneazoe.

  169. Dave F said:
    July 1, 2010 at 9:15 am
    And aside from that, each coin flip is independent. I would not say that each day’s weather is independent, and you certainly cannot say that climate is independent of weather.

    OK, how about tossing a coin where you place the coin on your thumb with the previous result facing upwards, i.e. if the last flip landed heads, start the next flip with heads facing upwards.
    This way the result of each flip is not independent of the previous one since the system is strictly deterministic (governed by deterministic newtonian mechanics -unless you want to try and argue that quantum effects are somehow significant).
    But it doesn’t make any difference. Now you have a system where each outcome depends on the previous outcome, you cannot predict the outcome of any single coin flip, but you can accurately predict the outcome of a large number of flips.
    The logic Steve Goddard used in the article was flawed.

  170. timheyes says:
    July 1, 2010 at 3:32 pm
    “I think you’ll find that January colder than July in the northern hemisphere due to Earth’s orbit around the Sun and the axial tilt of the Earth WRT the orbital plane.”
    So what happened to the orbit and/or axial tilt when, between 1907 and 1949 in The Netherlands; 1947 recorded a January temperature of 17.2 C and July 13 1907 a temp of 13.9? Something is missing? Weather?

  171. @Enneagram says:
    July 3, 2010 at 10:31 am
    vukcevic says:
    July 2, 2010 at 4:04 am
    http://www.vukcevic.talktalk.net/AMOFz.htm
    This graph it is astounding, but now you have to relate it to the Sun, as GMF is modulated by it. I would suggest you a real post to decipher all your graphs for us “commoners”.
    _______________________________________
    Thats Gleissberg, call it 32700 days, and check it against the major synodic periods of J/N 4669d, J/U 5045.5d, J/S 7254d, S/N 13102d, S/U 16571d, E/V 583.9219d, E/Mars 779.9356d, E/Ceres 466.7165d etc, so clearly the Sun doing it.
    We still need to know about the weather though, the short term range is massive in comparison, maybe 10degC in England in January, the Sun is doing that too.

  172. From: bemused on July 3, 2010 at 7:22 pm

    OK, how about tossing a coin where you place the coin on your thumb with the previous result facing upwards, i.e. if the last flip landed heads, start the next flip with heads facing upwards.
    This way the result of each flip is not independent of the previous one since the system is strictly deterministic (governed by deterministic newtonian mechanics -unless you want to try and argue that quantum effects are somehow significant).

    Wrong. For that system to be deterministic you would have to know all initial conditions and all energy transfers that would occur during the flip before the flip took place. To keep it simple, if you can simply crank a set of numbers through the equations and always get the same repeatable result, then a system is deterministic. If you can’t, there is some amount of randomness involved, then the system is stochastic. By invoking a thumb you have invoked a person, thus you would have to know what energies a person would transfer during the launching of the coin, thus you would have to “solve” a person to calculate the result of the flip. Thus the “person” system involved would have to be deterministic. Good luck demonstrating that.
    Besides, a “coin flip” is by definition a random event that has only two possible results, with equal probability assigned to each. It is not normally given the messiness of real world coin flips, where differences in the faces will make one side more probable, nor is the on-edge landing considered. Retaining the previous result as an initial condition during a succession of coin flips does not make each flip not independent, as the initial state of the coin does not matter.
    Thus the logic of your comparison is flawed.

  173. Wrong. For that system to be deterministic you would have to know all initial conditions and all energy transfers that would occur during the flip before the flip took place.
    I assure you that Newtonian mechanics are deterministic. The coin does not magically move itself for no reason. It’s motions are governed entirely by the forces acting upon it.
    To keep it simple, if you can simply crank a set of numbers through the equations and always get the same repeatable result, then a system is deterministic. If you can’t, there is some amount of randomness involved
    Yes, but an important characteristic of chaotic system is that they are deterministic systems which are observationally indistinguishable from indeterministic systems. If you take a simple non-linear set of equations (for example see Lorenz’s equations), then the outcome is deterministic (i.e. it depends on the initial conditions), but minute differences in those initial conditions (below observational error) will get larger with time and make the two solutions so different that they may as well be random. But crucially, in the Lorenz system you can predict the bounds of the attractor (the climate) even though the internal fluctuations of the system within those bounds are, to all intents and purposes, random.
    I don’t want this discussion to degenerate into a metaphysical argument over whether or not humans have free will so, for the sake of argument, why not let a robot arm flip the coin? If the coin is thrown sufficiently high then I am almost certain that the results will not always be repeatable.

  174. If anyone is left reading this thread, here’s one more. I think many people aren’t comfortable with simple analogies (e.g. coin tosses, cups of coffee etc), but maybe some examples using the real atmosphere would be more convincing.
    A small parcel of air is made up of billions of molecules travelling in different directions, colliding on seemingly random paths. You can’t predict the exact path of each individual molecule -in fact, you don’t even know the initial conditions of each molecule. So, given that the individual molecules are completely unpredictable how can you possibly predict the statistics of a large sample of those molecules? Steve’s logic would have you believe that it is impossible. How can I possibly predict that if I increase the pressure (while keeping the volume constant) then the temperature (=average kinetic energy of all those molecules) will go up?
    Meteorologists can make reasonably accurate short range predictions of mean wind speed and also peak gusts. But gusts are caused by small (10s of metres) eddies in the air which (even if you knew the initial conditions of each individual eddy -which you don’t) are completely unpredictable beyond a few seconds in advance. Steve’s logic would have you believe that because you can’t predict the individual eddies you can’t possibly predict the statistics of many of those eddies over a time period (the peak gust).
    A weather forecasting model may be able to accurately predict that in 24 hours there will be convective showers in the North Atlantic behind a cold front. Yet anyone who has tried to make extrapolation nowcasts from radar animations will understand that individual convective showers are unpredictable beyond an hour or two in advance (or slightly more for more organised mesoscale convective systems). Steve’s logic would have you believe that as you can’t predict the individual showers 24 hours in advance, you cannot possibly predict the statistics of many of those showers (e.g. the fact that a number of showers will occur across a defined area and time window).
    Hopefully, these examples show that it is possible to make accurate predictions of certain statistics associated with the atmospheric system despite the fact that the individual events that make up those statistics are themselves unpredictable.
    If the sun disappears in 2015, I predict that Earth will get colder. I don’t have a clue about the individual weather events that will transpire, but the average of all those events will still give an increasingly cold Earth. Climate prediction is not impossible.

  175. Bemused, you are confusing statistics of a relatively short-term events with individual (unique) trajectory of a long evolving object.
    To apply your line of reasoning more coherently, yes, billions of colliding molecules on a billiard with negative curvature gives you a very good ergodic system, such that applying mathematics of big number one can get a clean thermodynamical state of continuous matter (in the limit of thermodynamic equilibrium).
    However, when this system is subject to variable forces or is far from equilibrium under some uniform field, the media becomes unstable, and dynamics of individual parcels becomes unpredictable again, as Navier-Stokes equations demonstrate. Again, you need to resort to statistics (of turbulence, invariant measure of a chaotic attractor) to be able to predict dynamics, but only for a time scale that is characteristic for this eddy motion or whatever.
    Furthemore, to do so you either need a coherent theory of eddy interactions (which you don’t have due to divergence in Reynolds averaging process), or use experiment to establish these probabilities (eddy viscosity, “universal logarithmic profiles”, Obukhov mixing length, etc.) from observations. To get this statistics for a minute-long process, people run various tanks and wind tunnels for months collecting zillions of spatio-temoral data points, all under very well controlled conditions.
    Now, the key point is that when you combine all this stuff into a much bigger system, you have unspecified strange attractor of weather that, according to known facts from nonlinear dynamics, would certainly have long tails of slow-evolving fluctuations. Yes, theoretically one can find invariant measure of this attractor and construct various PDFs out of it, but practically it would require experimental verification. This verification, as usual, should be conducted over time scales that are characteristic for this type of motion.
    Typically, even in studies of well-defined strange attractors people would take time series of thousands of characteristic cycles and billions of data points to characterize the attractor statistically. Since we are talking about climate, so far we have only a fraction of climate trajectory. Even to get a single turn around climate attractor one need to get full data for entire atmosphere (and all boundary conditions as well) for at least 100,000 years. Only then you can have some basis for climate prediction.

  176. Re: bemused on July 4, 2010 at 2:57 pm
    Several times now I’ve tried composing a reply, it continually gets too wordy. The problem, I have come to realize, is you just don’t understand the simplifications normally done when using deterministic Newtonian mechanics to predict real-world behavior. Predictions are what is being discussed, specifically climate models. You yourself have resorted to simplifications, using the far-simpler system of coin flipping to argue for the accuracy of the vastly more complex global climate models, which themselves are already greatly simplified from the real world climate systems. You have essentially agreed that even coin flipping is too complex for accurate predictions, since when faced with having to know exactly what a person will do while flipping the coin beforehand you have resorted to suggesting using a robot arm, a further simplification.
    One may argue that everything is deterministic. True randomness does not exist. In reality, there are too many variables to keep track of. So, one simplifies things down to where predictions can be calculated. In the process you lose precision, a measure of accuracy is lost. Those factors dropped from consideration aggregate into that which is ascribed to chance, to randomness. Yes, in an absolute sense all systems are deterministic. In reality, we settle for “close enough” predictions, normal procedure being the performing of many test runs and invoking statistics to show your method of prediction is indeed close enough.
    Thus so far, you have done a good job showing why the global climate models fail. They are a simplification of the actual climate systems to start with. They are “tuned” to provide (reasonably) accurate hindcasts, but have not been show to provide “close enough” predictions. Due to simplifications, they ascribe many things to randomness thus a stochastic nature is presented of what ideally is a deterministic solution.
    Heck, with the repeated iterations even the rounding off of the numbers can grow into a significant source of inaccuracy.
    Now if there is this much difficulty in applying deterministic Newtonian mechanics to accurately predicting something as relatively simple as coin flipping, how can you think that vastly complex global climate models can accurately predict conditions for decades and even centuries past the starting point?

  177. kadaka:
    “Now if there is this much difficulty in applying deterministic Newtonian mechanics to accurately predicting something as relatively simple as coin flipping, how can you think that vastly complex global climate models can accurately predict conditions for decades and even centuries past the starting point?”
    The point you keep missing is that you can predict that about 50% of coin flips will land on heads. If you run a deterministic prediction for long enough then even if the individual flip outcome sequence is incorrect, the statistics of that system can still be correct.
    Nobody is trying to predict the specific weather conditions at a city for a given day in 100 years time -they are just trying to predict the statistics of those weather conditions when averaged globally and over a decade or so. That is a very different problem.

  178. bemused says:
    July 5, 2010 at 5:16 pm
    …..Nobody is trying to predict the specific weather conditions at a city for a given day in 100 years time -they are just trying to predict the statistics of those weather conditions when averaged globally and over a decade or so. That is a very different problem.
    ______________________________________________________
    Yes and the models get a straight line. Straight lines are not seen very often in nature, curves and cycles are much more common especially with weather and climate.
    North to south throubh the middle of my state
    North – Raleigh NC
    Middle – Fayetteville NC
    South – Lumberton NC
    Atlantic Multidecadal Oscillation Amazing how the temperatures follow the Atlantic ocean oscillation – a 60 year cycle or there about.

  179. kadaka said: “Heck, with the repeated iterations even the rounding off of the numbers can grow into a significant source of inaccuracy.”
    No, this concern is unfounded. The reason is that the weather attractor oscillates within strong bounds, the weather trajectory eventually returns into a very close proximity state space after several iterations. From many known attractors in hydrodynamics, the structure of phase flow on an attractor is a horrible web of homoclinical orbits, but each of this orbit belongs to the same attractor (if it is “structurally stable” one). Therefore, even if the numeric algorithm produces rounding errors and the trajectory jumps to a different orbit of the attractor, it is still on the same attractor. Therefore the system does not go anywhere (it does not “blow up”) and produces (allegedly) the same statistics.
    This is in theory of course. In reality of, say, climateprediction.net, evidence is that their model could suddenly produce “outliers”, which they simply discard. They discard about 40% of runs for this reason. To me it means that their dynamical system of pseudo-weather is unphysical and fundamentally wrong, and the results of forward calculations have little to do with reality.

  180. Al Tekhasski:
    Bemused, you are confusing statistics of a relatively short-term events with individual (unique) trajectory of a long evolving object.
    No, I’m not confused at all. The thing that is trying to be predicted is not the 100,000 year+ range of possible states that the climate system may ever evolve into. People are trying to predict 100 years into the future i.e. in the context of the 100,000 year turnover period you quoted it is still “a relative short term event” (any reference where that figure came from by the way?).
    “you have unspecified strange attractor of weather that, according to known facts from nonlinear dynamics, would certainly have long tails of slow-evolving fluctuations.”
    -I am genuinely interested in this so if you have any good pointers where I can read more on this specific topic (in relation to the atmosphere) then I’d really appreciate it.
    “Even to get a single turn around climate attractor one need to get full data for entire atmosphere (and all boundary conditions as well) for at least 100,000 years. Only then you can have some basis for climate prediction.”
    …and yet, if you give the system an external hammer blow by say, turning off the sun, you can still predict that the climate will get colder. It is not black and white, it is possible to make predictions about certain aspects of the climate with differing amounts of uncertainty.
    With weather forecasting, you could say “my model is not perfect, I can never know all of the initial conditions” so there is no basis for weather prediction. But, weather forecasts of synoptic scale systems are pretty accurate up to 3 days ahead. Lives are saved every year as ships know in advance how to avoid gales. A certain amount of pragmatism is not a bad thing.

  181. Gail Combs:
    “Yes and the models get a straight line. Straight lines are not seen very often in nature, curves and cycles are much more common especially with weather and climate.”
    No, the models don’t produce straight lines -in fact they are very wiggly. People often get confused about this as often the time series shown in publications are smoothed with running means or are the average of an ensemble of different model simulations.

  182. bemused:
    “The thing that is trying to be predicted is not the 100,000 year+ range of possible states that the climate system may ever evolve into. People are trying to predict 100 years into the future i.e. in the context of the 100,000 year turnover period you quoted it is still “a relative short term event” (any reference where that figure came from by the way?).”
    The 100,000 years came form the period of ice ages. I am under an opinion that if the attractor in a climate model does not reproduce this cycle, the entire topology of attractor cannot be trusted, and the 100-years long trajectory should not be trusted either. After all, you would still need a multitude of SAME experimental conditions to validate this model to build an ensemble. If we have only one sequential trajectory but the return map of the overall attractor needs 100,000 years, one cannot conclude that 100-year sequential segments originate from nearly the same state, so no statistics can be derived.
    [ and I probably should use “conflating” instead of “confusing”. Damn English!]
    “I am genuinely interested in this so if you have any good pointers where I can read more on this specific topic (in relation to the atmosphere) then I’d really appreciate it.” [regarding slow tails]
    Unfortunately, I cannot provide any references with regard to applied atmospheric studies; this observation came from highly academic studies of simplified hydrodynamic of Couette-Taylor flow between rotating cylinders of about 30 years ago. The general idea is that if a spatially distributed system has nearly individual localized attractors that are weakly coupled due to sheer physical distance between them, this weak interaction leads to very slow type of “wobblings”, “walkings”, etc. , and weaker interaction simply yields slower motions. I believe today this kind of models are called “lattices”.
    “But, weather forecasts of synoptic scale systems are pretty accurate up to 3 days ahead. Lives are saved every year as ships know in advance how to avoid gales. A certain amount of pragmatism is not a bad thing.”
    I was under impression that they can do 5 or even 7 days… I agree that climate models do not need precise weather “forecast”, but I still think that climate models must reproduce typical weather elements and their individual shapes and dynamics pretty accurately, otherwise statistics of goofy events will result in goofy outcome.

  183. “The 100,000 years came form the period of ice ages. I am under an opinion that if the attractor in a climate model does not reproduce this cycle, the entire topology of attractor cannot be trusted”
    Well, my understanding of the latest thinking (and I stand to be corrected) is that the ice ages occur primarily from external forcing of the system by Milankovitch cycles. i.e. external forcing of the system changes the shape of the attractor. I don’t think they’re caused by internal variability of the system (within a stationary attractor).
    I guess it all depends on how you define the ‘system’ and what you consider to be external to it. If you don’t give a model the external forcing then it won’t reproduce variability on those timescales.
    “I was under impression that they can do 5 or even 7 days”
    Well, yes. These vague statements are all rather meaningless really unless we define exactly what it is we are trying to predict. Small scale features like thunderstorms may be predictable a few hours in advance, synoptic scale features may be predictable up to 3-5 days (or more in favorable conditions), planetary scale waves are often predictable out to 10 days or longer. In the tropics, seasonal forecasts out to 3 months for certain variables have been demonstrated to have skill.
    “but I still think that climate models must reproduce typical weather elements and their individual shapes and dynamics pretty accurately, otherwise statistics of goofy events will result in goofy outcome.”
    Absolutely. But you may be surprised by how well the latest GCMs do reproduce atmospheric modes of variability. High resolution models produce very realistic convective storms and tropical cyclones. Synoptic systems and planetary waves have more or less been nailed for some time. Things like El-Nino Southern Oscillation are pretty well represented these days. The Quasi-Bienniel Oscillation in the stratosphere is beginning to appear in the latest models. Many models struggle to produce a fully fledged Madden-Julian Oscillation in the tropics, but there are promising signs from the latest global weather forecast models. The models are becoming less ‘goofy’ as time goes on. It is worth noting that the models spontaneously produce these modes of variability on their own -they are not programmed to do so.

  184. Bemused, I appreciate your posts. It is well known that ENSO parameters correlate with land temperatures. The cause and effect mechanism is fairly well understood as the hydrological cycle. Thus the theory of land temperatures being significantly affected by oceanic temperature is established.
    The major underlying assumption of AGW models has to do with added heat from increased greenhouse gas concentration effects. Between land and water, only water has the potential to absorb this heat (land is such a poor candidate for this part of the theory that it can be dismissed). The modeled hypothesis is that the stored heat is then released along with natural heat under warm ENSO parameters, thus adding to the increased land and SST temperatures of warm ENSO parameters. It is also modeled that cool ENSO parameters will not be as cool due to these same greenhouse gasses.
    An alternate modeled hypothesis has to do with AGW air temperature changes creating human-induced changes in the natural bimodal atmospheric circulation patterns. This model is less well accepted because air and land do not store heat.
    Also, of great importance, the set of models predicting increased warming assume that CO2-AGW is added heat, not overwhelmed heat.
    But what if the models have underestimated natural ENSO parameters? And what if the models have not accurately modeled all ENSO parameters, including clouds? Is it possible that these weaknesses in the models produce enough measurement error that any CO2 warming would fall within that error band? Is it possible that what we are seeing as a warming trend, is within the error band of natural variability and weak modeling of this variability?

  185. Pamela Gray:
    “But what if the models have underestimated natural ENSO parameters? And what if the models have not accurately modeled all ENSO parameters, including clouds? Is it possible that these weaknesses in the models produce enough measurement error that any CO2 warming would fall within that error band? Is it possible that what we are seeing as a warming trend, is within the error band of natural variability and weak modeling of this variability?”
    I’m not an ENSO expert, so don’t want to comment too deeply on the specifics of it, but in short no, I don’t think the warming trend is within the bounds of natural ENSO variability, or caused by poor modeling of ENSO.
    Look at the GISS observation data here:
    http://data.giss.nasa.gov/gistemp/graphs/Fig.E.lrg.gif
    -you can see how ENSO effects global temperatures (you can match up individual peaks and troughs). However, the warming trend is larger than the ENSO variability.
    Another good read is here:
    ftp://ftp.gfdl.noaa.gov/pub/gav/PAPERS/VW_09_ENSOCCreview.pdf
    -look at figure 3. It shows the ENSO cycle in a model where no CO2 increase is applied (i.e. the control run). It shows the model produces a stable ENSO over 2000 years (showing variability on annual, decadal and centennial timescales, but no drift).

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