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All IPCC definitions taken from Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I, Glossary, pp. 941-954. Cambridge University Press.

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Comments 74251 to 74300:

  1. 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".
  2. 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.
  3. 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).
  4. 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?
  5. 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.
  6. 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.
  7. 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?
  8. 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?
  9. 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.
  10. Galactic cosmic rays: Backing the wrong horse
    silence(7): Good point.
  11. 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'.
  12. 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.
  13. 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!
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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?
  20. Lessons from Past Climate Predictions: IPCC AR4 (update)
    @Noesis #24 Would you be interested in joining the SkS author team to work on this?
  21. 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.
  22. 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.
  23. 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.
  24. 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).
  25. Galactic cosmic rays: Backing the wrong horse
    Brother, I have to work on my typing/prepost editing.
  26. Galactic cosmic rays: Backing the wrong horse
    It would actually be really neat if this GCR idea turned out to be true. Is it likely ,too? No. But that is exactly what would make it so cool! The things is, the odds of GCRs leading to a reassessment of AGW is even more unlikely than the odds of GCRs being important to climate. The physics of GHG is pretty clear, and we're doing a fine job of prediction without GCRs. If GCRs are playing a role, understanding that role is likely to put the effect of GHG on climate into even more relief by reducing the background "random" noise a bit more. That gets buried in this terrible framing of climate science as GHG vs everything else. It's a complete distortion of the real scientific debate. This is not an alternative hypothesis counter to AGW, it is an additional hypothesis that could move the science forward.
  27. Galactic cosmic rays: Backing the wrong horse
    I'd love to hear more about the Laschamp excursion, and the non-impact that had on the climate.
  28. Lessons from Past Climate Predictions: IPCC AR4 (update)
    I tried posting this at Lucias but it didn't work so since it is related I will bring it up here: Re: Lucia #81953 "While saying it, Dana could still admit that that particular choice for observational data set gives the largest observed trend and happens to support the narrative s/he is conveying to his/her reading audience." "Dana might want to include the observational data set that happens to be the IPCC’s choice in their figure. I’m pretty sure that’s not GIStemp. It’s HadCrut." They may have chosen to use HadCrut but will they in 10 years? My guess is no. It has been demonstrated by others (including JeffID) that Hadleys method will ALWAYS underestimate the trend. We all know that so why is there even a debate on this subject? ECMWF has already also concluded that Hadley has undersampled the warmth, particularly in the Arctic. This is also something we know. I'm getting tired of people saying "the IPCC did it so we can too" despite the huge differences in knowledge we have on these issues. We can't just plug our ears and pretend like Hadley isn't undersampling the warmth. Maybe some people would like to. I can tell you straight up for a region I've submitted a paper on Hadley's method wouldn't even work going back past 1950 despite using a Least Squares method allowing the reconstruction back into the 1880s. This is called an evolution of science and we now know that if you want to use less available station data. Use Hadley. Real "Skeptics" want to evaluate as much data as possible... And for those people who comment on GISS polar interpolations I hope you have the same reservations about UAH which does a similar process? Where is the arms up in the air over that? Can you pick which one is usually always undersampling Arctic warmth from this: It is a no brainer... Let us have a look at the residuals versus all methods... oh wait, it appears Hadley is underestimating the warmth greater through time and it is statistically significant... i.e. undersampling the trend.
  29. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Sphaerica, For some reason, you seem to like strawmen. I do not know what implications they have. As I mentioned earlier, it may be more a matter of semantics, but your observation list is not examples of a changing climate, but simply, a temperature increase (by the way, Antarctic ice mass is relatively stable). Finially, 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?
  30. Galactic cosmic rays: Backing the wrong horse
    Interesting if now confusing and complex. Just one nitpick, wouldn't it be more correct to say: "Thus one of the strongest known GLEs, producing much more ionization than the typical GCR, had no direct connection to WEATHER." A sudden increase in ionization, no matter how strong, would only affect the weather for a short amount of time so in the context of those experiments it's seems to me that it's not right to talk about climate.
  31. SkS Responses to Pielke Sr. Questions
    mea culpa...my followup to VTG @75 was also not helpful. Though technically correct and useful context, background chatter has an influence on the tone of the debate and distracts from the clear flow of ideas. It had the effect of amplifying the general group tone of frustration... Dana @ 160. Just to be clear, you are right of course that Pielke touched on much of what the webpage conclusions say - but I would say in a rambling diffuse way, albeit sometimes punctuated by moments of clarity. My thought was that the webpage conclusions provide the skeleton of his position in clear and concise terms. The comments offer some color and detail that fills in the gaps in those conclusions in a bit.
  32. Lessons from Past Climate Predictions: IPCC AR4
    That's pretty good Zeke. My only concern is the choice of baselines - my thought being that since the IPCC model projections begin in 2000, for the best comparison (if you're trying to evaluate the model accuracy), that's when the models and data should match up. My approach was to take the 5-year running average for both models and data, and adjust the baseline such that they match in 2000.
  33. Lessons from Past Climate Predictions: IPCC AR4
    Here is what I would consider the ideal version of Dana's Figure 3: It uses all three major surface temp series as well as the 1980-1999 baseline generally used by the IPCC for instrumental record/model comparisons.
  34. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Excellent explanations by Tom Curtis in #23. I don't have much to add, except on the point of choosing 2000 as the starting point. The explanation is quite straightforward - that's the year the IPCC projections begin, as you can see for yourself by examining the data file linked in the post and here. People need to bear in mind that SkS is not RealClimate or the Blackboard or any other site. Lucia for example has a very specific target audience, which is different from the SkS target audience, which is as broad as we can make it. Yes, I could have done a more detailed analysis including error bars and such, but this post is intended for a general audience, which might be turned off by too much statistical detail. On SkS we have a wide variety of posts and technical levels, in keeping with our basic, intermediate, and advanced myth rebuttal levels. This post (in fact most of the 'Lessons' series) is intended for the basic and intermediate level audience, who may be interested to know approximately how well models project temperature changes. Pete - yes, there's also JMI. I don't know the details about that data set though.
  35. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    6, Jonathon,
    I am not sure we can say that the climate has changed.
    Yes, and no. We cannot say the climate has changed yet. That's the whole point. If we wait that long, it's game over. But it is in the process of changing and we know that on our current course it will change. We can certainly say the climate is changing. The number of extreme events and the extremity of those events has certainly increased. Other observations, such as the loss of ice mass in Greenland and Antarctica, the retreat of glaciers, earlier springs, and many others all emphatically demonstrate that the climate is in fact changing. Your premise that it has not changed yet is a strawman. Similarly, your later implication that climate change be defined as the wholesale conversion of entire ecosystems ("Temperate regions are still temperate, semi-arid are still semi-arid, polar, etc.") is another strawman. If you think that such dramatic and unassailable changes are the only things that will affect the future of mankind, you are in for a shock.
  36. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Isn't there also a Japanese global temperature data set? If so, it may be an interesting topic for another post.
  37. Lessons from Past Climate Predictions: IPCC AR4 (update)
    I would like to make a suggestion to the operators/moderators about the format of SkS. I read some of the posts on the blogs lambasting SkS over the updated article issue, and I can't help but agree with some of the points they raise. I think it might be in SkS's best interest to keep a "Wiki-like" history link at the top of the articles so that people can go back and see previous versions with a short explanation of why they were updated. I think it's perfectly reasonable to update articles as new evidence emerges and actually a good thing, but I also understand that people who are not inclined to be favorable to anyone who agrees with the mainstream consensus will use the updated article talking point to try and discredit the site. A history section for each of the "permanent" pages would mute complaints of sneaky updating, and allow you to keep old comments around for future reference, simply move the old version of the article with comments intact into the history section and allow the new updated article to start over with a blank comment section. I'm under no illusions that this will be easy or fast to implement, but it's a suggestion on how you might improve the site to make it more resilient to criticisms that you are "covering up" errors. I've been reading this site for a while now, and think it's a very useful reference and hope my suggestion can help make it even better.
    Moderator Response: Thank you. This is a good idea.
  38. CERN - Saying Nothing About Cosmic Ray Effects on Climate
    tblakeslee, The 62 co-authors didn't make a "brave decision". They participated in a study and rightfully have their contributions acknowledged as co-authors. That's how science stuff works. There is nothing whatsoever that is controversial about the most recent study from the CERN CLOUD study, nor is there anything very controversial about Svensmark's original observation that cosmic-ray-sourced electrons can influence the aersol particulation of sulphuric acid in a chamber with controlled humidity levels. What was controversial is the assertion that variations in cosmic ray flux have a significant effect on climate mediated through cloud formation. Whether this hypothesis has any merit in the real world, we know that it has negligible relevance for the very marked warming since the middle of the 20h century.
  39. CERN - Saying Nothing About Cosmic Ray Effects on Climate
    sorry about the repost. I was trying to refresh. Do you really believe that Kirkby got in trouble back in 1998 for telling the press,"The theory will probably be able to account for somewhere between a half and the whole of the increase in the Earth's temperature that we have seen in the last century," After more than a decade of battles to get the CLOUD experiment done, he is much wiser now. You are right that CERN papers often have a long list of authors. People want to share the credit for significant experiments. The 62 co-authors of this paper made a brave decision to lend their name to the work even though it was very controversial because it replicated and extended the results of Svensmark's SKY experiment which was soundly rejected by the establishment. You are also right that there is new work on the sun showing that Alfven waves account for the high temperature of the corona. Alfven tried unsuccessfully to sell this idea starting in 1942. In spite of his Nobel prize, he was often forced to publish his work in obscure journals. Most astrophysics textbooks still virtually ignore his work, which is essential for understanding the magnetic fields that keep us safe from cosmic rays and affect cloud formation over the oceans.
  40. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    Well said CB. The Current Texas drought is ocurring during a La Nina. Previous La Ninas have not resulted in drought, however, the worst droughts have all occurred during La Ninas. Therefore, I would agree with your statement about this weather event being more likely, but not caused by La Nina. Similary, La Nina enhances Atlantic hurricanes, but SST, the jet stream, wind shear and other weather systems all combined to influence Irene. Individual weather events are the result of several factors acting together. While the temperature of the planet has changed over the past 150 years, I am not sure we can say that the climate has changed. This may be more an issue of semantics, but the majority of the world has only experienced minor temperature and precipitation changes. Temperate regions are still temperate, semi-arid are still semi-arid, polar, etc. I firmly believe that there is a big difference between an increased likelihood of certain weather events, and global climate change.
  41. SkS Responses to Pielke Sr. Questions
    @Actually thoughtful #186: I generally concur with your assessment. I specifically agree that a comment thread is not the ideal venue for a discussion of matters of science. For better or for worse, it was the only venue available in this particular instance. As I have previously stated, I made some rookie mistakes as the primary moderator of this thread and regret not having deleted the first five comments. Having said that, I was disappointed in Dr. Pielke's abrupt departure. The dialogue between Dr. Pielke and Albtross is typical of what occurs between scientists in the peer review process.
  42. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Carrick @16: 1) Given three data sets, a, b, and c, which have not been falsified as indices of Global Mean Surface temperature, congruence of the multi-model mean with any of the three means the multi-model mean has not been falsified as a projection of future evolution of the multi-model mean. As the lack of falsification is all that Dana claimed, no issue arises from his choice of just one index, Gistemp, to compare the multi-model mean with. 2) In fact there is good reason to believe that two of the indices understate trends in GMST, in that they do not include data from a region known to be warming faster than the mean for the rest of the globe. In contrast, while there are unresolved issues relating to Gistemp, it is not clear that those issues have resulted in any significant inaccuracy. Indeed, comparison of Gistemp north of 80 degrees North with the DMI reanalysis over the same region shows Gistemp is more likely to have understated than overstated the trend in that region: Your claim that gistemp's method of extrapolation is untested is simply false. What is more, I would suggest this is not a case of your having knowledge from peer reviewed literature of a lack of testing; but rather of you having simply made the claim up because you did not know the contrary and the claim was convenient. 3) Dana uses the average of the model runs because weather is chaotic, so that no individual run can be considered a prediction. The model mean, however, can be considered a projection of the "typical" weather state, something which can be projected. In contrast, the mean of the temperature indices does not represent a "typical" weather state. Rather it represents one possibly accurate measure of one particular evolution of the weather over time. There is no reason to believe that mean is a more accurate measure than Gistemp, and indeed given considerations under point 2 above, it is likely to be less accurate than gistemp. However, because the model mean is a statistical prediction, what it predicts is not the global temperature at any give time. Rather it predicts that the global temperature will lie within its error bars 95% of the time, and that the long term trend will closely match the long term trend of the multi-model mean. To that extent, while your criticism is entirely invalid, that of Kevin C @18 is not. A correct presentation would be similar to that by Real Climate (moderator inline comment @18). That Dana chose a less technically correct comparison for purposes of simplicity is unexceptional, however, in that it leads to no misunderstanding. 4) Dana did not choose 2000 as the start year. The IPCC chose 2000 as the start year of model projections both in its graphic (see figure 2 in the main post) and in the data. Given that Dana was commenting the IPCC's projections, he was constrained to use the same start date for those projections as the IPCC's projections. You are in fact criticizing Dana here for not misrepresenting the IPCC projections. There could not be a clearer example of somebody determined to criticize without regard for the merits of the case than you have provided by this example. However, your suggestion of using Tamino's ENSO corrected temperature index has merit: The trend of the temperature indices once corrected for ENSO, VEI, and solar variation? 0.17 degrees C per decade, against which the 0.18 degrees C per decade AR4 projection is not bad at all. (Note, Tamino only reports the trend over the entire 1975-2010 interval. By eye, the 2000-2010 trend does not differ significantly, but you are welcome work it out more accurately.) 5) Dana did use consistent baselines. This can be seen by comparing his figure 3 with Zeke's version of Dana's original figure (or indeed the RC graph inline @18): As Zeke was one of the discoverers of Dana's initial error, it cannot be supposed he is trying to distort the data.
    Moderator Response: fixed comment per user request
  43. SkS Responses to Pielke Sr. Questions
    Well, now the dust has settled a little I’d just like to add my thanks to the mods and also to agree with those suggesting a slightly different way of engaging with Dr Pielke in the future. I’d also like to acknowledge my #75, even if within the comments policy, was unhelpful – borne not just of frustration on this thread but also an earlier encounter linked up the thread. Notwithstanding that, finally I’d like to thank Dr Pielke for his time here and hope he comes back again. I learned from both of his forays to this site.
  44. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Yes Tom, In another 10 years or so, if the projection matches observations, then it will add another piece.
  45. Lessons from Past Climate Predictions: IPCC AR4
    dana1981
    Wow I didn't even have to wait until morning. Lucia sure is quick on the draw.
    dana is being personally singled out for attention by the 'lukewarmers'. It is their modus operandi.
  46. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Jonathon @20, Dana states that the AR4 projections "will add another piece" (my emphasis) to the puzzle of climate sensitivity, and goes on to indicate that it will take another 10 years of data to do so.
  47. Lessons from Past Climate Predictions: IPCC AR4 (update)
    With regards to which observational data aset should be used, that would rely on which set was used in order to determine the projections. Therefore, whichever temperatures were used in Figure 2, should be used in Figure 3. As mentioned by Dana, the temperature observations will fall within the uncertainy range in the projections, although the uncertainty range in not clearly stated. It appears that the quoted observed trend of 0.15C/decade is from 1/1/2000 through the end of 2010; GISS data to the present yields a trend of 0.12C/decade. It appears that this is still within the uncertainty range, but on the low side, which Dana clearly states. Dana does fine stating, "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." However, claiming that this adds another piece to the puzzle of climate sensitivity, is a bit premature. No conclusion can be drawn yet as to the accuracy of the projection.
  48. Lessons from Past Climate Predictions: IPCC AR4 (update)
    Informative post, thanks. I tried to reproduce the Figure 3, but maybe I'm using a wrong offset in constructing the graph. Using the GISS data from and de IPCC data as referenced here, I get an average for the IPCC data (20C3M values) of -0.309 °C for the period 1951 - 1980. This period is the baseline of the GISS data. Correcting the IPCC data with this offset I get a graph where the A2 scenario is higher than the one shown in Figure 3. For instance the value for the A2 scenario for 2000 is 0.256, using my offset I get 0.565. Eyeballing the value in figure 3 for A2 in 2000, it is about 0.45. Could somebody please explain my error and what the offset should be ?
  49. Review of Rough Winds: Extreme Weather and Climate Change by James Powell
    The whole question 'what caused weather event XYZ' is inherently flawed. You'll frequently hear 'skeptics' claim things like, 'no it was not global warming, it was El Nino'... seemingly unaware that this claim is just as clearly false as blaming global warming alone would be. If the ENSO cycle were "responsible" for the recent Texas drought/wildfires, Mississippi flooding, hurricane Irene, massive tornadoes, et cetera (as many 'skeptics' confidently proclaim) then we would see these events during every ENSO cycle. We do not, because weather is never 'caused' by just one thing. The very concept of the 'butterfly effect' demonstrates this... it argues that in a chaotic system (like Earth's weather) small changes (like a butterfly displacing air by flapping its wings once) can cause large deviations (like a hurricane which would not otherwise have occurred). The aspect of the concept which many people seem to miss is that there are ALOT of butterflies in the world. Along with billions of other things which influence the weather. If a different butterfly on another continent gets hit by a car that could prevent the butterfly-hurricane from forming. Ditto a cloud drifting between the sun and an area of blacktop and thus preventing a thermal updraft from forming. Et cetera. ENSO, like global warming, just makes certain kinds of weather more likely. It does not 'cause' them entirely on its own any more than global warming does because all weather events are caused by the collective action of billions of factors. That being said, global warming has changed the climate of the entire planet. Some butterflies which would not be alive had AGW not taken place are... others have died because of AGW. Evaporation, clouds, precipitation, albedo, and dozens of other factors have changed the world over. Thus, it could be reasonably said that ALL weather we see now is due to global warming. It is all an aspect of the current climate, which has been changed by AGW. Thus, I can guarantee that if the past 150 years or so of global warming had not taken place Hurricane Irene would not have happened exactly the way it did. It could have been nice and sunny... or there could have been an even worse storm, but that exact weather event would not have taken place. Far too many of the 'butterflies' which contributed to the way it played out were changed by AGW. So really, as the article above also notes, the only meaningful metric of the 'effect' of global warming (or ENSO) on the weather is a change in frequency of various types of events.
  50. Antarctica is gaining ice
    DB I see that the responses to the comments in question have been updated and the whole thing makes perfect sense now. Tone trolling should rightly be ignored, but IMO Bishop Hill did have a point, although they vastly overstated the significance of it. That Sks is coming under fire presumably means you're doing a good job, so keep it up!

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