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Comments 74101 to 74150:

  1. Lessons from Past Climate Predictions: IPCC AR4 (update)
    radar @53 - the UAH trend isn't zero over the past decade. Moreover, it's odd that you're willing to acknowledge the short-term cooling effects of volcanic aerosols, but don't seem to recognize the cooling effects of anthropogenic aerosol effects over the past decade.
  2. Ocean Heat Content And The Importance Of The Deep Ocean
    Adelady#3, Here's something on the question; don't know if its what you are referring to. Global (magma and lava) production rates are estimated at 3km^3 per year for mid-ocean ridge systems and 1km^3 per year for continental volcanic systems. For global impact, (mid-ocean ridge (MOR) ~80,000km long; average water depth of 2,500m) there’s enough energy in the volume of lava produced by MOR annually to raise the temperature of 8,000 km^3 of seawater by just over 0.5°C – that’s a drop in the ocean (1.3 billion cubic kilometres). New unit: 8000 / 1.3 billion = a drop in the ocean; perhaps this is a quantum of insignificance?
  3. Lessons from Past Climate Predictions: IPCC AR4 (update)
    I don't disagree that 10 years does not a model falsify, but it's not too short to raise an eyebrow. [snip] I reiterate, the point of the post is to say that the models are 'reasonably accurate'. Look at Lucia's graphs above and realize that plenty of folks understandably disagree.
    If you want to raise an eyebrow and impute falsification, one first needs to demonstrate that certain assumed model inputs have actually behaved as was assumed at the time of modelling. As others have noted, solar output has been much lower than was expected at the time of modelling for AR4. Such a result does not falsify the models. Unless, of course, one revisits the models and repeats them with the inclusion of the real-world parameters obtained subsequent to the original runnings, and gets a result that then invalidates the predictions. If there is work that shows this, I'd be most interested to see it.
  4. Lessons from Past Climate Predictions: IPCC AR4 (update)
    radar#53: Do you accept charlie's graph here? If so, how do you not agree that model is 'reasonably accurate'? I don't know what field you are in, but it doesn't get much better a fit over a short period than that.
  5. Ocean Heat Content And The Importance Of The Deep Ocean
    Dave123. Depends what you call short term. I'd wait to see what the next couple of El Ninos do in terms of heat release/ reorganisation before thinking along these lines. And the previously unpredicted speed of loss of Arctic ice might be an indicator of where some of that heat is going. BodHod. I know I saw something only a few days ago on this - and didn't save it. Presumably someone more careful than I am did save it. We just have to hope they show up soon. (Though considering how trivial the CO2 emissions are from all volcanoes compared to ghg emissions, it's pretty well a given that the heating contribution will be similarly tiny.)
  6. Lessons from Past Climate Predictions: IPCC AR4 (update)
    radar "... the point of the post is to say that the models are 'reasonably accurate'." The 'models' - plural - are demonstrably 'reasonably accurate'. The only IPCC model on which we need to withhold judgment for the time being is the most recent one. Judging on past performance, i.e. demonstrated accord with reality, most people are willing to say we'll wait for the decade or so needed before calling yay or nay on this one. (Perhaps if the previous ones had been wildly off the mark, a lot of people might say, "Uh oh. Looks like we're doing it again." But that didn't happen so there's no need to venture down a similar path.)
  7. Lessons from Past Climate Predictions: IPCC AR4 (update)
    I appreciate the feedback. What is the point of this post, if not to 'bust the myth' that the models are forecasting more temperature rise than is being observed and to state that they are 'reasonably accurate' ? I don't disagree that 10 years does not a model falsify, but it's not too short to raise an eyebrow. UAH and RSS may have problems, but we are looking at trends. How many 10 year periods of dead flat temperatures have the models shown that did not immediately follow a volcanic eruption? One might think that this would peak the curiosity of a website named "Skepticalscience". NYJ "The IPCC AR4 was only published a few years ago, and thus it's difficult to evaluate the accuracy of its projections at this point." As Dana said the models supposedly started in 2000 regardless of the publishing date of AR4 so not only a "few years", 10 in this post, 11.58 in reality. I reiterate, the point of the post is to say that the models are 'reasonably accurate'. Look at Lucia's graphs above and realize that plenty of folks understandably disagree.
  8. Lessons from Past Climate Predictions: IPCC AR4 (update)
    #49 Dana says "Charlie, thanks for your (totally subjective) opinion on what's "proper". It looks strikingly similar to Figure 3. " Ummm. I don't know why you call it "totally subjective". The model means are referenced to a 1980-1999 baseline (see the caption you posted in Figure 2, which I assume is a true copy of the IPCC figure). Doesn't it make sense to use the same baseline for both the observations and the model projection? Do you consider using the same baseline to be "totally subjective"?
  9. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Willis - the IPCC does use HadCRUT data [Albatross acknowledged the error in comment #44]. I don't think it really matters what observational data set the IPCC chose. We're not examining their observational data, we're examining their model projections.
  10. Ocean Heat Content And The Importance Of The Deep Ocean
    When considering deep ocean warming, do studies/models consider the effects of submarine volcanoes? Do we know enough about the effects of submarine volcanoes to draw meaningful conclusions about how they affect deep ocean temperature?
  11. Willis Eschenbach at 11:01 AM on 24 September 2011
    Lessons from Past Climate Predictions: IPCC AR4 (update)
    Craig Allen at 15:12 PM on 23 September, 2011 Craig claims that the reason for not doing a sensitivity test is that the IPCC used GISS data, viz:
    Lucia, The post is about the IPCC AR4 projections (as described in chapter 10.3 or the AR4 report) and their accuracy. Figure 2 is the second figure in that report. It presents GISS data up to the year 2000 and model projections from there until 2100. Had the IPCC plot used one of the other instrumental records or a different cut-off between the observational and modelled data then it would make sense for Dana to have used those. But that isn’t the case.
    Albatross agrees that the IPCC used GISS data, viz: Albatross at 15:50 PM on 23 September, 2011
    Hello Lucia,
    ..."a) Included other observational data sets like HadCrut and NOAA. (If s/he thinks they are inferior GISTemp, s/he should say why he thinks so.)"
    What Craig said @12. I think that you know as well as we do that each of the datasets has its limitations. What do you think is the best GAT analysis and why? Dana was simply being true to the original graphic that was shown.
    I find this line of argument curious. Sensitivity analyses don't depend on what the original graph does. It is an attempt to find out if the original graph is correct. In any case, I just followed the link to Chapter 10.3 of the AR4 report. I don't find Figure 2 there, as claimed above. It is located in the SPM ... but there, it says nothing about using GISS data. Nor is this helped by Figure 1, which says nothing about the data source either, only that it is based on Stott 2006b. But Stott 2006b doesn't use GISS either, it uses HadCRUT2 data ... so I fear I can't find a scrap of backup for the claim that the IPCC used GISS for either Figure 1 or Figure 2. Cite? I'm not saying they didn't use GISS, I just can't find any evidence they did use GISS ... and generally, they use HadCRUT. w.
  12. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Charlie, thanks for your (totally subjective) opinion on what's "proper". It looks strikingly similar to Figure 3.
  13. Lessons from Past Climate Predictions: IPCC AR4 (update)
    @Charlie A #46 I completely agree with Dana that for the trend-conclusion the value of the baseline is "diddly squat". It seems you ran into the same problems as I did, trying to reconstruct the Figure 3 graph. When everything is baselined to 1981-1999 you get the your graph, using some average around 2000 you get the graph from this post. When I use all the model data you can download from the IPCC site, I get the same graphs. I tried the opposite of what you did and baselined the IPCC average data or an average of all model data to 1951-1980, this results in a graph where the IPCC A2 model data are a bit lower than in your graph, e.g. the 2005 Giss value will be just a bit lower than the A2-model value. I am still figuring out why. Of course, muoncounter is right and the whole discussion is about some small insignificant value, but it will only take a little time and I will encounter an image on a Dutch denier site with a graph using a certain baseline with real T-data and where they try to convince every Dutchman that the IPCC models are completely wrong and therefore all CO2 related theories can be added to the household garbage. I want to have my answer prepared when that happens. An image like a good explanatory graph is hard to set aside. For example, the famous hockey stick graph immediately tells you what is happening, even when you didn't finish high school. In my opinion that's why there is so much resistance from the deniers regarding this hockey stick graph.
  14. SkS Responses to Pielke Sr. Questions
    @ alan_marshall #190: Excellent post. I sincerely hpoe that people will still drop by this comment thread and read it. Would you be interested in transforming it into an article for guest-posting on SkS?
  15. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Charlie A#46: "the proper apple-to-apple comparison" Nice job. It looks like the projections are less than 0.05 deg from the actual. Given the short time period represented, that's hardly a significant difference.
  16. SkS Responses to Pielke Sr. Questions
    Spin Doctor? In his second question to Sks, Dr Pielke offered two different framings of the climate change debate offered by Mike Hulme. Neither of these framings necessarily reflects Hulme’s own position. He is providing them as examples. Hulme has prepared climate scenarios and reports for the UK Government (including the UKCIP98 and UKCIP02 scenarios), the European Commission, UNEP, UNDP, WWF-International and the IPCC. He therefore knows a lot about communicating climate change science and about accommodating genuine differences of opinion between scientists. He is also aware how the message can be slanted by anyone, with or without the relevant expertise, who has a particular agenda. It will be instructive for those reading this thread to hear Mike Hulme’s own explanation of what “framing” is all about. The material which follows borrows much the profile of Hulme at ABC Carbon. Hulme defines framing as, “The deliberate way of structuring complex issues which lend greater importance to certain considerations and solutions over others”. He offers a sample of six different ways of framing climate change: 1) A market failure In this view, business emits carbon dioxide to the atmosphere for free, but there are ultimately costs associated with that waste disposal. So to ensure the market is operating efficiently, carbon dioxide emissions should be priced. 2) A technological hazard Like asbestos or nuclear waste, carbon dioxide emissions are a potentially toxic side effect of our modern technologies. This view advocates improved energy technologies to allow us to continue our modern life, but without the hazardous side-effects. 3) A global injustice Climate change when viewed through this framework is seen as a problem where the West dominates and controls the global agenda, leaving the developing world out of the picture. A solution to climate change for this world view would involve what Aubrey Meyer describes as ‘contraction and convergence’, or an equal sharing of the carbon dioxide budget between all countries, regardless of their wealth. 4) Overconsumption If our environmental impact is a function of our consumption, our population, and the technologies we use, then solving climate change through this framework would involve finding a path to a prosperous but non-growing economy, or improving contraception. 5) Mostly natural If climate change is mostly natural, then the solution in this framework is to spend money on adaptation to the new environment. 6) A planetary tipping point And finally, if climate change is viewed as leading to a planetary tipping point at which life on Earth becomes untenable, then no holds must be barred, and solutions would include massive geoengineering projects. According to Hulme, our pre-existing values, beliefs, upbringing and maybe even genes cause us to frame climate change in a certain manner. Even before the scientists have whipped out the first graph, people are already disposed to interpret the data in a particular way. In my earlier post (The Games People Play @ 43), I was perhaps a little unfair to Dr Pielke in suggesting his questions on framing were an attempt at entrapment. What I am convinced though, as Hulme so eloquently demonstrates, is that “framing” can be as much about spin as communication. The climate skeptics who have testified before the US Congress appear to be masters of spin. The purpose of spin is sometimes to give emphasis to an aspect of an issue that one believes is important, but all too often its purpose is to confuse and obfuscate. We see this endlessly in what passes for political debate in Australia. Rightly or wrongly, I get the impression that Dr Pielke is more comfortable playing with words that discussing the real implications of numbers. In Australia, there is confusion among the general public, fanned by conservative politicians and radio commentators, over man’s contribution to the CO2 in the atmosphere. Words can confuse, but accurate numbers don’t lie. For example, since the dawn of the industrial revolution, CO2 has increased from 278 to 393 ppm, numbers I expect Pielke would accept. Such numbers can’t easily be spun, and given that climate sensitivity, including short-term feedbacks, is around 3 degrees C, the implications for our future are frightening.
  17. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Dana1981 at #43 says "it's true, baselines can be manipulated for dishonest purposes, but that's not something we would permit on this site, of course. " As shown in the caption to your figure 2, the baseline for the AR4 projections is 1980-1999. You choose to compare the projections to the GISS global temperate time series. The proper thing to do is to use 1980-1999 as the baseline for both GISS and AR4 projections. It is trivial to adjust the GISS to that baseline. This is the plot of the annual data, properly baselined. When using the proper apple-to-apple comparison (and using the GISS temp series preferred by Dana) the only years where the observation exceeds the projection are 2002, 2003, and 2006. Note the difference between this and Figure 3 of this post.
  18. Ocean Heat Content And The Importance Of The Deep Ocean
    Isn't increased heat movement into deeper ocean layers an arrow pointing towards lower short term climate sensitivity?
  19. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    John R#13: "climate shift diagram is a little simplistic" Of course it is; this is a book for a general audience. But this story is entirely consistent with what some are calling 'rolling 13s' - a pair of normal dice gives 2-12; we're seeing that nature has new and different dice. Here's a cogent summary statement from Michael Tobis' analysis of the Texas drought report by John N-G: Climate characterizes the statistics of weather and the statistical bounds of weather. If we start seeing weather patterns change, that can indicate a change in climate. The question is all about how likely it is that this weather would occur if the statistical parameters of the climate were held fixed as it has been since instrumental records began, say. If weather like this is sufficiently unlikely under our previous understanding of regional climate, it may be (a piece of) evidence that the climate is itself experiencing a dislocation. There are new normals; get used to them.
  20. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Hi again Lucia, One more thing. I noticed that you neglected to answer my question: "What do you think is the best GAT analysis and why?" Just to be clear in case it was not already clear from the context, I was specifically referring to the surface temperature record. Thoughts? Thanks.
  21. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    The climate shift diagram is a little simplistic, as it shows globally-averaged temperatures. In the case of the UK, for instance, global warming is tending to change air patterns so that we've been experiencing record cold spells in the winter. This is because the change in climate, certainly over the last few years, has been tending to push Arctic air further south than historically has been the norm. I only mention this because anyone reading the book might think that increases in extreme weather will always tend to be at the warmer end of the scale and -- if they are so minded -- therefore claim that an increase in extreme cold events experienced locally proves climate change to be a hoax. So there's a danger in over simplification. We need to be careful what predictions we make.
  22. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Hello Lucia, Re my comment that "Dana was simply being true to the original graphic that was shown. You are correct. Thanks for pointing that out. The caption does indeed state that they were using HadCRUT3. But that was my mistake, not Dana's. You see, it is quite easy to admit error :) As for your lengthy defence (and obfuscation) of your other demonstrably wrong assertions, it is very unfortunate that you are not willing to concede that you erred. A double standard is evident on your part when it comes to admitting error. You demand it of others, and even go so far as to insinuate intent to mislead, but when it comes to you admitting error the hand waving starts. So be it then. Fortunately, reasonable and sensible people will see right though that. Have a lovely weekend.
  23. Galactic cosmic rays: Backing the wrong horse
    Dave123#10: "rate of formation of droplets of a given size becomes the rate limiting step, NOT the rate of nucleation..." Kirkby's language is qualified on this point: Time-resolved molecular measurements reveal that nucleation proceeds by a base-stabilization mechanism involving the stepwise accretion of ammonia molecules. Ions increase the nucleation rate by an additional factor of between two and more than ten at ground-level galactic-cosmic-ray intensities, provided that the nucleation rate lies below the limiting ion-pair production rate. --emphasis added This point was buried deep within the Nature News press release: Lockwood says that the small particles may not grow fast enough or large enough to be important in comparison with other cloud-forming processes in the atmosphere. The press release ranks as a low point in science journalism, complete with this factually incorrect description: ... bombard the chamber with protons from the same accelerator that feeds the Large Hadron Collider, the world's most powerful particle smasher. As the synthetic cosmic rays stream in, the group carefully samples the artificial atmosphere to see what effect the rays are having. CLOUD uses pions, not protons; small detail to some, but then again, this is science and we're supposed to get small details right. But all of that is entirely ignored by the pro-GCR crowd because the headlines give them what they want.
  24. Lessons from Past Climate Predictions: IPCC AR4 (update)
    John H @35 - no, I believe the conclusions remain valid and don't require any change. I think michael sweet @37 and adelady @40 did a good job illustrating why. NewYorkJ @39 also provides a very revealing quote from lucia's relevant to the discussion here. Jos - it's true, baselines can be manipulated for dishonest purposes, but that's not something we would permit on this site, of course. Thanks for the Dutch translation :-)
  25. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Another serendipity moment. CSIRO has just released results showing that wind speeds across Australia have increased by 14%. Media release And for the Antarctic, this item is on deep ocean heating but there's a lot of Antarctic info in the second half of the article.
  26. Galactic cosmic rays: Backing the wrong horse
    Coming from a chemistry perspective, I find certain concepts missing from the discussion (not yours muoncounter). There is a simplification we use called "the rate limiting step". In multi-step reactions, the slowest reaction governs the rate of the ensemble. Thus a chemist naturally asks what the rate limiting step in a droplet nucleation process is. It may not be the initial nucleus formation. Depending on conditions a droplet may form only to rapidly evaporate again, and only if a critical size is reached will the droplet be stable under the conditions. Thus the rate of formation of droplets of a given size becomes the rate limiting step, NOT the rate of nucleation by contact with aerosol particle or ionization by cosmic rays. The degree of supersaturation is important here. The next consideration is auto-catalysis. Given droplets, they can split, regrow and split again. This process can dominate ab initio droplet formation (and in crystallization processes usually does). Thus only a very low threshold rate of droplet formation is required and other process dominate after that. This kind of process could make cosmic ray triggers irrelevent. I haven't seen any summaries of cosmic ray nucleation discussing these kinds of issues, and it could be there. Is it?
  27. Lessons from Past Climate Predictions: IPCC AR4 (update)
    @dana1981 #34 I completely agree with your conclusions and this comparison which I liked very much. It's just that I wanted to reproduce your Figure 3, which took me a couple of hours to figure out the numbers. Reading your answer, my guess was approximately correct about your baseline. The baselines are not important, that's true of course, but when I visit a deniers site I regularly encounter graphs where they moved baselines just to trick people. An example is Bob Tisdale with his ocean heat content regression line as described in: http://tamino.wordpress.com/2011/05/09/favorite-denier-tricks-or-how-to-hide-the-incline/ I construct and reconstruct graphs just to learn about the relations that exists in data, besides that a strong visual image, like a explanatory graph, is a very powerful tool. Thanks for your time and regards, Jos. PS, I had to look up the meaning of "diddly squat", in Dutch this means "helemaal niks".
  28. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Radar, There are reasons to believe that both HadCRUT and UAH have issues giving enough reason for exclusion. Regarding HadCRUT I have discussed the reasons above. Regarding UAH they are discussed over at Tamino's and it isn't even measuring the same thing as the models would be predicting really and the datasets from the TLT have a strong dependency on El Nino and Volcanism... Also you shouldn't compute trends on monthly data (See RomanM's blog for this). It results in a stepwise trend change from month to month. (maybe stepwise isn't the right word). Finally Dana didn't cherry pick, based upon advice given on the options and on work he's seen he selected the dataset he felt was the most accurate at this time. Perhaps he should have been explicit about his reasoning but ultimately I could not call this a cherry-pick.
  29. Lessons from Past Climate Predictions: IPCC AR4 (update)
    radar, "What does this tell us" ...it's difficult to evaluate the accuracy of its projections at this point. We will have to wait another decade or so to determine whether the models in the AR4 projected the ensuing global warming as accurately as those in the FAR, SAR, and TAR." is the conclusion of the post. That's a very long way from "saying they are accurate". It does say that the IPCC has a good track record from earlier projections. But it does not claim that the latest projections are accurate. Yet. A decade of further observations are required for that (or its opposite).
  30. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Dana accurately says "The IPCC AR4 was only published a few years ago, and thus it's difficult to evaluate the accuracy of its projections at this point." That didn't stop Lucia. In 2008, she stated: "The current status of the falsification of the IPCC AR4 projection of 2 C/century is: Falsified." Now I don't know of she's changed her argument since then, but it's this sort of silly stuff that reduced my time spent reading her blog since then. Related to this, model mean doesn't really tell us much at the decadal level, as trends in individual model runs ("real-world" scenarios) vary wildly at that level. RC had a post on this topic some time back, showing trend distribution of 8-year and 20-year trends of model runs. On a different note, I don't quite understand why trends in temperature data products like HadCrut are compared to modeled trends of the global average as if they are a 100% apples to apples comparisons, expected to match very closely over the long run. As has been mentioned here, HadCrut neglects the Arctic. So if projections were accurate and precise, wouldn't HadCrut be expected to diverge on the cool side, with the divergence becoming larger over time?
  31. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Per Dana “Evaluating all the data is by definition not cherrypicking.” Agreed, so use multiple data sets and up to date data. Decadal Trends: 2000-Current GISS: +.121 HadCrut +.0024 UAH +.143 RSS +.004 Most Recent 10 years (to 2011.58) GISS +.0022 HadCrut -.0075 UAH +.0036 RSS -.006 Sorry I don’t have NCDC on my computer…) Models highlighted in AR4 are not performing well. The data set is too short to say ‘the models are falsified’, but to write a post saying they are accurate is gilding the lily in the extreme.
  32. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Lucia, You have made a very long post. What is your point? You seem to be raising questions about Dana's motivation for the way he graphed the data. When I look at the various graphs presented it is clear to me that not enough time has passed to make any kind of conclusion. Dana pointed this out in the post. You are splitting hairs about a graph of data that is not definative in any case. When the other data sets were added the conclusion is the same, why do you continue to complain? Minor baseline shifts do not matter to the conclusion. Dana claims the data is consistent with the IPCC conclusions, but it is a little low, the changes you recommend would lead to the same conclusion. Do you have a graph that shows that conclusion is not true? If you cannot challenge the conclusion why are you going on and on? Dana did not even point out that the solar radience is at its lowest point in 50 years which affects the data significantly. I have seen you make similar posts on other sites. Please stop whinging and add to the conversation.
  33. Lessons from Past Climate Predictions: IPCC AR4 (update)
    @All commentors: At this juncture in the comment thread, do you have any reason to believe that the conclusions stated in the final paragraph of Dana's article are incorrect? If so, why?
  34. Lessons from Past Climate Predictions: IPCC AR4 (update)
    @dana1981: At this juncture in the comment thread, do you have any reason to revise the conclusions stated in the final paragraph of your aticle?
  35. Lessons from Past Climate Predictions: IPCC AR4 (update)
    JosHag @31 - the point of this exercise was to compare the model projections to the data. The model projections began in 2000, so I adjusted the baselines accordingly. I looked at the 5-year running average for the model projections and GISTEMP, and offset the models such that they matched in 2000. I'm interested in trends, in which case as Zeke noted, baselines mean diddly squat. Charlie A - of course the post-slope adjustments made the models match the data. That was the entire point of the adjustments - to see what slope (sensitivity) would make the models match the data. I haven't done that here because as I noted in the post, there's insufficient data for a meaningful comparison. However, there has obviously been more time elapsed since the SAR, so it was a useful exercise.
  36. Galactic cosmic rays: Backing the wrong horse
    silence(7): Good point.
  37. Galactic cosmic rays: Backing the wrong horse
    silence#7: "the smaller more recent variations would have no discernible impact." Agreed. However, the basis of the GCR experiment rests on proxies for increased GCR flux during past cold events (see any of Kirkby's papers, especially Fig 2 in Cosmic rays and climate 2008). The popularizers and non-science media fixate on this unsupported mechanism with such insightful remarks as, 'Its the sun, stupid'.
  38. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Perhaps Dana used the same baseline adjustment technique he used for the FAR model comparison: "All I did was offset the SAR projection in 1990 to match the GISTEMP 5-year running average value in 1990 (approximately 0.25°C)." Lessons from Past Climate Predictions: IPCC SAR In other words, he matched the start of projections with the 5 year running average in the start year. In that comparison, he also adjusted the slope or scale factor of the projections. Not surprisingly, with after-the-fact adjustments of both slope and offset, the projections were a good match for observations.
  39. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Hi Albatross-- I've commented here before. I just don't visit often and comment here less.
    Dana was simply being true to the original graphic that was shown.
    It seems to me that being true to the original graphic would require Dana to use HadCrut. The original graphic containing data in this post appears to be the one Dana calls "figure 1" and corresponds to figure 9.4 in the AR4-wg1. The caption reads for figure 9.4 in the AR 4 reads:
    "as observed (black, Hadley Centre/Climatic Research Unit gridded surface temperature data set (HadCRUT3); Brohan et al., 2006)"
    Dana's choice of GISTemp represents a switch to a different data set.
    I hope to see you acknowledge your own mistakes (we all make them, no shame in that) and correct your blog post too (if needed) so as to keep you readers informed.
    Assuming your meant to suggest that the observations in Dana's figure 1 are from GISTemp, I hope to see you acknowledge your mistake. :) I conceded that the 2010 in it's entirely was not El Nino. Few years are all one thing or another. But the data in the figure are annual averages and the global surface temperature in 2010 was dominated by El Nino. This is particularly so because the temperatures lag the MEI. You may think it's a mistake to call it an El Nino year, but I consider 2010 an El Nino year and I consider choices of what to include in figures meaningful. I also consider the surface temperature for 2011 dominated by La Nina and I will continue to think so even if El Nino were to unexpectedly turn up at this point or even if it had turned up in August.. On your response to (c): None of those represents reason Dana can't write "was published in 2007' or "was published four years ago" rather than "was published recently". You think it's enough to have readers scan back? I don't. You think it's a nit-pick? I think Dana is using tendentious language and construction. So, there you go. Kevin C
    I'll write two responses on this. In this first one I'm going to disagree with Lucia and Carrick on the problems of polar temperatures in the ITRs.
    I haven't suggested GISTemp is biased. I said that Dana chose the data set with the highest trend; this choice happens to better support this claim than choosing other trends. That's all I've claimed. In my original comment, I didn't point out that his choice of GISTemp results in an inconsistency in that his figure 1 and figure 3 use different observational data sets, but I have pointed that out at my blog. But since Albatross seems to be under the impression the choice of GIStemp results in consistency, I provide the caption for the IPCC figure showing they used HadCrut, not GISTemp. By the way- your pink figure with the observations is similar to the ones I plot when the final of NOAA, HadCRut and GISTemp post. I don't have any objection to someone showing all three observational data sets, or arguing that one is better than the others. But I do consider omitting a set cherry picking. For some reason I don't recall, I did 25 month smoothing a while back. (I think i've varied-- but right now for a quick look, the script has 25 months coded in:) The choice of 25 months means the peak lags the El Nino/La Nina cycle, so the averages were recently coming down from local maxima since monthly temperatures were lower than they were 25 months ago.
    As Zeke was one of the discoverers of Dana's initial error, it cannot be supposed he is trying to distort the data.
    Zeke coblogs at my blog; I agree he is not trying to distor the data. I'll have to ask Zeke if he discovered this before or after I published my blog post. :) I usually avoid speaking for Zeke as he is perfectly capable of speaking for himself. But I would like to point out that Zeke's figure doesn't appear to be either an endorsement nor a criticism of Dana's graph. When Zeke posted the graphic my blog, Bill noticed that Dana appears to shifted the baseline so that it doesn't match the one chosen by the. The IPCC projections are all "relative to a baseline of 1980-1999", but Dana appears to have picked a different one. Zeke then wrote
    Bill Illis, I was trying to recreate his graph. In this case both have a 1990-2010 baseline period. It appears that Dana did graph the correct data, but incorrectly calculated the slope of the last decade. That said, comparing trends is much more useful, is its rather hard to eyeball correlation in noisy data.
    There is further discussion of this. This is Zeke.
    Carrick, I think you have the legend backwards in your graph. This discussion does raise the interesting question of how to objectively determine the best baseline for use in comparison. Obviously for visual comparison purposes you would want to use a pre-validation period baseline, but I’m not sure how to choose between one (say 1950-1980) or another (1970-2000). For trends of course, it doesn’t matter.
    Note that Dana does not use a pre-validation baseline. There are two things that need to be considered Dana's decision to pick a different baseline than that specified by the IPCC: 1) It's just choice Dana, not the IPCC made. 2) Dana did not disclose his rebaselining of the model and observations. 3) Using a baseline of 1990-2010 forces the means for the model and observations to match during that period. Models would have to be very, very bad for the differences to be apparent with this choice. Given this, it's not too surprising that the models seem to agree with data. Agreeing on average has been enforced by subtracting the difference in the means. Dana's choice to not use a "pre-validation baseline" tends to force better agreement between projections and observations; this is why it should not be used. On your response to (c): None of those represents reason Dana can't write "was published in 2007' or "was published four years ago" rather than "was published recently". You think it's enough to have readers scan back? I don't. You think it's a nit-pick? I think Dana is using tendentious language. So, there you go. Kevin C
    I'll write two responses on this. In this first one I'm going to disagree with Lucia and Carrick on the problems of polar temperatures in the ITRs.
    I haven't suggested GISTemp is biased. I said that Dana chose the data set with the highest trend; this choice happens to better suppor this claim than choosing other trends. In my original comment, I didn't point out that his choice of GISTemp results in an inconsistency in that his figure 1 and figure 3 use different observational data sets. But since Albatross seems to be under the impression the choice of GIStemp results in consistency, I provide the caption for the IPCC figure showing they used HadCrut, not GISTemp. By the way- your pink figure with the observations is similar to the ones I plot when the final of NOAA, HadCRut and GISTemp post. I don't have any objection to someone showing all three observational data sets, or arguing that one is better than the others. But I do consider omitting a set cherry picking. For some reason I don't recall, I did 25 month smoothing a while back. (I think i've varied-- but right now for a quick look, the script has 25 months coded in:) The choice of 25 months means the peak lags the El Nino/La Nina cycle, so the averages were recently coming down from local maxima since monthly temperatures were lower than they were 25 months ago.
    As Zeke was one of the discoverers of Dana's initial error, it cannot be supposed he is trying to distort the data.
    Zeke coblogs at my blog; I agree he is not trying to distor the data. I'll have to ask Zeke if he discovered this before or after I published my blog post. :) When Zeke posted the graphic my blog, Bill noticed that Dana appears to shifted the baseline so that it doesn't match the one chosen by the. The IPCC projections are all "relative to a baseline of 1980-1999", but Dana appears to have picked a different one. Zeke then wrote
    Bill Illis, I was trying to recreate his graph. In this case both have a 1990-2010 baseline period. It appears that Dana did graph the correct data, but incorrectly calculated the slope of the last decade. That said, comparing trends is much more useful, is its rather hard to eyeball correlation in noisy data.
    There is further discussion of this. This is Zeke.
    Carrick, I think you have the legend backwards in your graph. This discussion does raise the interesting question of how to objectively determine the best baseline for use in comparison. Obviously for visual comparison purposes you would want to use a pre-validation period baseline, but I’m not sure how to choose between one (say 1950-1980) or another (1970-2000). For trends of course, it doesn’t matter.
    There are two things that need to be considered Dana's decision to pick a different baseline than that specified by the IPCC: 1) It's just choice Dana, not the IPCC made. 2) Dana did not disclose his rebaselining of the model and observations. 3) Using a baseline of 1990-2010 forces the means for the model and observations to match during that period. Models would have to be very, very bad for the differences to be apparent with this choice. Given this, it's not too surprising that the models seem to agree with data. Agreeing on average has been enforced by subtracting the difference in the means.
    Moderator Response: [Dikran Marsupial] Fixed a couple of blockquote tags, I hope this is what was wanted!
  40. Lessons from Past Climate Predictions: IPCC AR4 (update)
    I'm still figuring out the baseline used in Figure 3 of this post, see my reaction #19. I can create the last graph in reaction #23, the baseline there is 1990-2010. I can also create the RealClimate graph where the GISS data are downward adjusted with the Giss-T-average of 1980 - 1990 being 0.244. It seems to me the graph in Figure 3 is constructed with some sort of a difference in the averages of the IPCC and Giss data around 2000 and used that difference to adjust the IPCC data. Is that correct? When I adjust the IPCC data to the Giss baseline of 1951 - 1980, using an offset of -0.309, the model data are clearly above the Giss-T. Is there something with the model data which explains these differences? It's probably me, but I still don't get that.
  41. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Jonathan - the "Absolutely yes" in my reply was to "is the climate really different". I found your "nothing more than a temperature change" the odd part of that paragraph. A temperature change is a climate change, affecting weather, plant life, sea level, etc. My apologies if that was unclear. Did you follow the Antarctica link I provided? Did you see Fig. 2, where an entire group of studies show a high rate of mass loss, a factor more than 5x higher than the study you point to? I believe that the weight of evidence (so to speak) points in the direction of significant Antarctic mass loss, although you have found a (single) study that disagrees.
  42. Galactic cosmic rays: Backing the wrong horse
    No. I'm suggesting that there wasn't a big climate change as a result of the Laschamp excursion, which had a much bigger change in cosmic ray impacts on the Earth's atmosphere than the recent variations we have seen. This would imply that the smaller more recent variations would have no discernible impact.
  43. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Robert #27 - well said. That's exactly why I didn't use HadCRUT - we know it's biased low, so why use it? Of course we know certain parties want to use it precisely because we know it's biased low.
  44. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    KR, First off, Antarctic ice is not decreasing at a considerable rate. In fact, the change in mass does not exceed the measurement uncertainties. http://www.springerlink.com/content/9k58637p80534284/ I find your last paragraph somewhat confusing. First, you agree with me (absolutely yes), then you say that I am astoundingly wrong. All this, while you seem to agree with my position about what constitutes a climate change. [inflamatory deleted]
    Moderator Response: [Dikran Marsupial] Please keep the discussion civil.
  45. Galactic cosmic rays: Backing the wrong horse
    silence#2: "Laschamp excursion" Per Guillou 2004, the global decrease in magnetic field at 40kya was "revealed in polar ice as an abrupt change in the rate of cosmogenic nuclide flux." No one is questioning modulation of GCR flux by the interplanetary magnetic field and geomagnetic field. But did whatever internal mechanism that caused the Laschamp also affect temperatures? That makes GCR flux a symptom, not an agent of climate change. A geomagnetic excursions hasn't happened any time lately: These events, which typically last a few thousand to a few tens of thousands of years, often involve declines in field strength to between 0-20% of normal. Are you suggesting recent climate change is due to a new Laschamp-type event? Are we in the midst of one? Where's your evidence of that?
  46. Lessons from Past Climate Predictions: IPCC AR4 (update)
    @Noesis #24 Would you be interested in joining the SkS author team to work on this?
  47. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Man, I wonder if those more beligerant commenters have the same standards of criticism when they read something at WUWT.
  48. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Jonathan - For your reference, a Strawman Argument is a logical fallacy where one argues against a distorted, exaggerated or misrepresented version of someones position, rather than their actual position. As a logical fallacy, it proves exactly nothing. Antarctic ice is not stable at all - while sea ice has increased a bit, land ice is decreasing at a considerable rate. Your statement is flatly wrong. "...if climate change does not refer to a wholesale conversion, then it is nothing more than a temperature change. Is the climate really different if spring arrives a week (or two) earlier, more rain and less snow falls, and temperatures are higher?" Absolutely yes. Even a slight temperature change can change rainfall patterns, melt polar ice, alter the crops that can be grown in a particular region, shift pests into areas that never had them before, and lead to multiple species extinction as habitats go away. I find that last paragraph of yours rather astoundingly wrong.
  49. Galactic cosmic rays: Backing the wrong horse
    DOlivaw#1: You're correct, of course. Better to say that the sum total of years of cosmic ray activity isn't connected to climate.
  50. Lessons from Past Climate Predictions: IPCC AR4
    @Muoncounter #22, I created a new temperature trend chart with thicker lines. Updated graph link Y axis is start year. X Axis is length of data in years fit. This is all monthly GISTEMP data, but one can get similar results for HADCRUT or UAH data sets. I got all of my data from wood for trees. Years with a disproportionate influence on temperature trend show up as a diagonal down and/or horizontal line. Pinatubo for instance, shows up as a cool diagonal (trends ending on it are cooler) and a warm horizontal (trends starting from it are warmer).

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