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Comments 74151 to 74200:

74151. chris at 08:50 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       tblakeslee, need to be careful in taking Shaviv's analysis at face value, due, amongst other things, to his selection of data sets. For example much of his analysis is based on a set of tide guage records of Douglas (1997), which shows a marked cyclic variation of local sea level that matches the solar cycle. However, this doesn't match the globally averaged sea level variation, especially the satellite-derived record which doesn’t show a marked variation with the solar cycle; e.g. see this paper and Figure 3 - can't find a downloadable version right now: Church JA, White NJ, Aarup T, et al. (2008) Understanding global sea levels: past, present and future Sustainability Sci. 3, 9-22. It’s proposed that the tide guage measures, many of which are close to continental margins, have solar forcings magnified by more rapid warming/cooling in shallow waters, and that this amplifies the amplitudes of responses to forcings by a factor of 2-3 relative to the globally averaged response. So Shaviv’s use of this data to determine a radiative forcing from sea level response may well be erroneous (greatly overestimated) by that sort of factor. Whatever the origin of the discrepancy between tide guage measures and satellite measures with respect to amplitudes of response to solar cycles, I suspect that Shaviv’s analysis will be found to be a rather marked overestimation of the solar cycle response and his required “amplification”. There are some other problems with the paper that we could discuss. Notice that Shaviv himself points out problems with his analysis; e.g.: “Note that the relatively low correlation coefficient between the OHC and solar signals may seem somewhat suspicious” (page 10) This is a serious problem (i.e. that the OHC content variation doesn't really correlate with the solar cycle). Note also that Shaviv neglects to account for the effect of volcanic eruptions, which is important for assessing solar cycle effect on OHC, since for two of the 5 cycles (or 6; it’s not clear from Shaviv’s paper) analyzed, the volcanic forcing happens to be in phase with the solar cycle. This will produce a spurious “amplification” of any apparent solar effects that is not, in fact, related to solar effects. This has been pointed out by Lean and Rind in their recent analysis of attributions to 20th century warming (see section 4 on page 4 of their paper).
74152. tblakeslee at 08:45 AM on 25 September 2011
       Galactic cosmic rays: Backing the wrong horse
       There are many conditions that must come together to produce cloud formation. Cosmic rays can't create a cloud unless temperature and moisture conditions are right. If the air isn't supersaturated you are right and that is why cosmic rays are not sufficient for formation of clouds. This is why some attempts to connect Forbush events with cloud formation have failed. Here is an experiment that found a robust (R=-0.93) connection by working backwards and starting with abrupt cloud changes and then looking at the cosmic ray changes: http://www.atmos-chem-phys.org/10/10941/2010/acp-10-10941-2010.pdf The CERN experiment was much more abstract but this is a real world experiment using nature itself. The CERN experiment is really a confirmation and refinement of results already obtained in 2005 by Svensmark in his SKY experiment: http://www.space.dtu.dk/English/Research/Research_divisions/Sun_Climate/Experiments_SC/SKY.aspx lowclouds%20and%20gcr).pdf
74153. Norman at 08:45 AM on 25 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       Sphaerica @24 In post #7 you state "We can certainly say the climate is changing. The number of extreme events and the extremity of those events has certainly increased." In post #24 you state "A proper verbal interpretation of the graph would say "the overall trend for the period prior to the impact of anthropogenic climate change is downward, but there is not yet enough data to determine if the 'climate change tail' will be definitively upward -- i.e. yet another hockey stick." My position on this topic is that there is not enough data to make a declaration of certainty on the topic. I think earlier data on severe weather events was not as fully reported as today. I do not think there is adequate accounting of severe weather events to take a strong position that the number and intenstiy of severe weather events has certainly increased. I am not stating it has not. I am making the case that there is not enough good reliable data to make any claim of certainty on this issue at this time and we may not know for many more years. Your contention is that if we wait to see if it is getting worse, it might just be too late. I just wish on these threads that more mechanisms would be developed to demonstrate how global warming will create more severe weather. If someone could demonstrate how global warming will create more blocking patterns, or hurricanes, or tornadoes or floods I would maybe share the certainty you have that things are getting worse weatherwise.
74154. Tom Curtis at 08:45 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       There has been some discussion of an apparent contradiction in Dana's summary. I say "apparent" because there is no actual contradiction in Dana's conclusion. Accuracy is not bivalent like truth. Something is either true, or it is not - but things can be more or less accurate. Indeed, Dana clearly states that the AR4 results meet one (vague) standard of accuracy, they are "reasonab[ly] accura[te]", but it is impossible to tell as yet whether they meet another, more stringent standard of accuracy. Because different levels of accuracy are being considered, there is no contradiction. To illustrate the point, we can compare the AR4 projections to predictions analyzed earlier in this series, in this case the one by Don Easterbrook in 2008: The image was formed by overlaying Zeke's version of Dana's fig 3 graph above with figure 3 from Dana's discussion of Easterbrook's prediction (link above). The heavy Red line is a running mean of Gistemp, the heavy blue and green lines two of Easterbrook's three projections (the third declining even faster. Even the best of Easterbrook's projections (heavy green line) performs poorly. From the start it rapidly declines away from the observed temperature series. Briefly in 2008 (the year of the prediction) it is closer to the observations than is the A2 multimodel mean, but then falls away further as temperatures rise so that in the end it is further away from the observations than the A2 projections ever are. Given that 2008 was a strong La Nina year and in the middle of a very deep solar minimum, we would expect it to be below, not above and projected trend. But regardless of that subtlety, Easterbrook's projection performs far worse than the AR4 A2 projection. It is not reasonably accurate, although it may not yet be falsified. However, despite the fact that the conclusion contains no contradiction, I would suggest rewording it, or appending a clarifying update to the bottom of the post. As it stands it is an invitation to misunderstanding by those (apparently including Lucia) who think "accuracy" is an all or nothing property. It is also an invitation to the creative misunderstanding some deniers attempt to foster.
74155. Eric (skeptic) at 08:35 AM on 25 September 2011
       Pielke Sr. Agrees with SkS on Reducing Carbon Emissions
       He closes with "In terms of how to do this with respect to carbon emissions, I completely agree with my son’s perspective as he presents in The Climate Fix" Has anyone read this? I just ordered a copy ($10.40 from the Amazon bargain bin).
       Moderator Response: Clarification: The statement quoted was made by Dr. Roger Pilke Sr. The book was written by his son, Dr. Roger Pilke Jr.
74156. Norman at 08:34 AM on 25 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       I do have a question about the graph in the article titled "Future Climate Shift". I do not know if it is a correct assumption (logic can be perfect but if the assumption is not correct, perfect logic will not lead to the correct answer). The author of the graph is making the assumption that heat waves are a random fluctuation of weather patterns (in order to get a bell curve you need random sampling). The problem with this is that heat waves, monsoon rains and other weather phenomena are not random noise in the variables of heat, humidity, etc. They are not like waves in the ocean. They are organized patterns that persist over time. The current Texas heat wave and drought is caused by a High pressure ridge aloft (similar to what happened in Russia last year). A warmer world does not necessarily lead to more extreme heat wave events. The only way Global warming would create more heat waves (as implied by the graph) would be if the increase in heat content of the atmposphere would cause more blocking highs. I have not seen this demonstrated yet on this thread or the others where this topic has been brought up. If one would conclusively prove that a warmer earth would develop more blocking highs (which cause heat waves and droughts) then I would consider this a valid argument. Showing a bell curve and forming this conclusion is not based upon the mechanisms that are responsible for heat waves and droughts. They are not random events that respond to bell curve descriptions.
74157. adelady at 08:13 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       Paul Magnus, there's a couple of nice maps of thermohaline circulation on wiki. If you read the item they also refer to the meridional overturning circulation.
74158. Norman at 08:13 AM on 25 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       muoncounter @21 "That is starting to scare people, including the same John NG, who doesn't see it ending any time soon:" I would suggest John NG look at the annual temperature graphs of Texas that were provided by Jeffrey Lindner in the link I posted at #15. If you look at the annual temp graph then people must have been really scared from 1920 to 1940. Your graph is only of summer temps, the overall annual temps in 2007 and 2010 were below the normal temp line.
74159. tblakeslee at 07:23 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       Here is an excellent article on using the Oceans as a Calorimeter to Quantify the Solar Radiative Forcing: http://www.sciencebits.com/files/articles/CalorimeterFinal.pdf Using the 11 year solar sunspot cycles, he finds that the total radiative forcing associated with solar cycles variations is about 5 to 7 times larger than would result from only total solar irradiance variations. This is apparantly due to cloud formation changes resulting from the solar cycle.
74160. Paul D at 06:25 AM on 25 September 2011
       Galactic cosmic rays: Backing the wrong horse
       I know what Kirkby said, I'm not sure the sentence above is clear enough though, or maybe I am reading it incorrectly: "Despite an excellent rebuttal here on SkS featuring Jasper Kirkby's own words to the contrary (PAUSE) the popular press is still pushing the preliminary CERN CLOUD results..." One could read the 'contrary' being applied to the first part of the sentence rather than the second part. I think you need another comma after 'own words'. The 'to the contrary' is a break in the flow of the sentence. Alternatives are to use dashes or parentheses depending on grammar style. eg. "Despite an excellent rebuttal here on SkS featuring Jasper Kirkby's own words, to the contrary, the popular press is still pushing the preliminary CERN CLOUD results..." or: "Despite an excellent rebuttal here on SkS featuring Jasper Kirkby's own words - to the contrary - the popular press is still pushing the preliminary CERN CLOUD results..."
74161. Paul Magnus at 06:13 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       Perhaps ocean heat exchange is on a cycle of some sorts. Is it possible to filter this out in data such as ocean sediments? The exchange cycle will probably be affected by GW if we start seeing say more and stronger el nino/la nina cycles. I think things may be more chaotic. The melting of the Arctic sea ice will surely affect the ocean heat exchange dynamics due to a few things like currents and local climate. Wind speed over water in the southern hemisphere is getting significantly higher and may also have a big impact on heat exchange. What exactly is the mechanism of how the heat is transfered from the atmosphere to the ocean surface waters? Re-Radiation, convection or conduction? What effect do storms and wind speed have on this?
74162. Dikran Marsupial at 05:39 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       I should just add, that even with Lucia's variance pooling method (which I agree with in principle even if there may be difficulties in the details), that estimate of internal climate variability is only valid if you accept that GCMs are basically a valid way to model the climate (as the estimate is based on the behaviour of the models rather than the actual climate, so if you don't think the models are representative of the climate then the variability of the model runs can't logically be representative of the variability of the climate either). So those skeptics that don't accept models as being valid need some other way to estimate internal climate variability in order to determine what would be a "reasonably accurate" projection. Best of luck with that!
74163. Dikran Marsupial at 05:20 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       lucia I was talking of an ensemble of perfect models, in which case the spread of (an infinite number of) model runs is exactly a characterisation of the plausible variation due to internal climate variability. Whenever discussing tests or model-data comparison it is always a useful boundary case to consider what you can expect from a perfect model. Of course if you have imperfect models (as all models are in practice) then the spread of the ensemble will also include a component relecting the uncertainty in the model itself. However, the overall spread of the model runs in a multi-model ensemble is still a characterisation of how close we should expect the observations to lie to the multi-model mean, given all known uncertainties. Thus if the observations lie within the spread of the models, then the ensemble is "reasonably accurate" as it would be unreasonable to expect any more than that. Having a hetrogenous ensemble does make things a bit more awkward, I think I am broadly in agreement with Lucia about estimating the effect of climate variability by averaging the variances from the runs for each model type. I am also in agreement about what the observations lying within the spread means, it is essentially a test of the consistency of the models. No big complement if they are consistent, quite a severe criticisism if they are not. Having said which, as GEP Box said "all models are wrong, but some are useful". It is not unreasonable for the model to fail tests of consistency with respect to one metric, but still be a useful predictor of another. I should add that there may be subtleties in pooling the variances due to the act we are talking about time-series, which is more Tamino's field than mine (I'm also a Bayesian and so I don't really agree with hypothesis testing or confidence intervals anyway ;o)
74164. lucia at 04:58 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       

       John Hartz at 00:29 AM on 25 September, 2011 Has Lucia left the building?

       I don't know how our times stamps line up, but there has been plenty of discussion at my blog. I tend to comment lightly on Friday nights, most of Saturday and Sunday. Moreover, I've tried to foster the habit of not responding to unimportant things if I miss the page turn on blog comments. I do, however see something worth commenting on this page. I disagree with this:

       To know whether the ensemble mean is "reasonably accurate" you need an estimate of the plausible effects of climate variability on the observations. Currently the spread of the models is the best estimate of this available.

       I agree that you need an estimate of the plausible effects of climate variability on the observations. However, I disagree with the notion that the spread of all runs in all models in an ensemble is the best estimate of climate variability. I don't even think it's the best model based estimate of the contribution of climate variability to the spread in trends. Or, maybe it's better to say that based on my guess of what DM probably means by "the spread of models", I think the information from the spread in model runs is often used in a way that can tend to over-estimate the contribution of natural variability on trends. First, to engage this, admit I'm guessing what DM means by "the spread of models". I suspect he means that to estimate climate variability we just find all the trends in a multi-model ensemble, create a histogram and that spread tells us the contribution of climate variability to the spread of the trends. (If this is not what he means, it may turn out we agree on how to get a model based estimate.) I don't consider this sort of histogram of all runs in all models to produce the best estimate of the spread in variability due to actual, honest too goodness climate variability. The reason is that in addition to the spread due to natural variability in each model, this distribution includes the spread due to the mean response of each model. That is: if each model predicts a different trend on average, this broadens the spread of runs results beyond what one expects from "weather". So, for example, in the graph below, the color or the trace is specific to a particular model. You can see that run trends tend to cluster around the mean trend for individual models: (Note, a long time period was selected to illustrate the point I am attempting to make; this choice of times does result in particularly clustering of trends about the mean for individual models.) In my opinion, if you wanted a model based estimate of the contribution of climate variability to spread in trends on earth for any time period, it would be unwise to simply take all those trends, make a histogram and suggest that the full spread was due to something like 'weather' or "variability in initial conditions" or, possibly "climate variability". At least part of the spread in trends in the graph above is due to the difference in mean trends in different models. That's why we can see clustering of similarly colored lines for individual runs from the matched models. If someone wanted to do a model based test of the likely spread, I would suggest that examining the variance of runs in each model gives an estimate of the variance due to 'natural variability' based on that model. (So, in the 'blue' model above, you could get an estimate of natural variability by taking the spread over the trends corresponding to the individual 'blue' traces). We have multiple models (say N=22). If we have some confidence in each model, then the average of the variance over the N models gives an ensemble estimate of the variability in trends based on the ensemble. Using a distribution with a standard deviation equal to the square root of this average variance is likely a better estimate of the spread of natural variability. (Note btw that you want to do this by variances for a number of reasons. But lest someone suspect I'm advocating averaging the variances instead of standard deviations because it results in a smaller estimate of variability, that is not so. If modelA gets a variance of 0 and modelB gets a variance of 4. Averaging variances results in an average of (0+4)/2 =2; the standard deviation is 1.4. In contrast, if we average the s.d. we get (0+2)/2=1. There are other reasons to average variances instead of s.d. though. ) The method I describe for getting a model based estimate of the spread results in a somewhat smaller spread than one based on the spread of runs taken from an ensemble of models whose mean differs. Needless to say, since it gives tighter uncertainty intervals on trends, we will detect in accurate models more often than using the larger spread. But I think this method is more justifiable because the difference in the mean trends is not a measure of natural variability. Having said that: I think checking whether the trend falls inside the spread of runs tells us one thing: Does the trend fall inside the spread of runs in the ensemble. That's worth knowing, but I don't happen to think the spread of runs in the ensemble is the best model based estimate of the spread of trends that we expect based on natural variability. I also don't think the full spread of all runs-- including contributions from difference in the means-- should be represented as an estimate of uncertainty in natural variability around the climate trend. Of course, I'm not sure that by "the spread of the models" DM mean the spread of all runs in all models. It may turn out he means exactly what I meant, and in which case, we agree.
74165. muoncounter at 04:40 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       DM#82: Don't feel bad; an interesting list of arguments from over-extending an analogy appears here. I like this one: "The solar system reminds me of an atom, with planets orbiting the sun like electrons orbiting the nucleus. We know that electrons can jump from orbit to orbit; so we must look to ancient records for sightings of planets jumping from orbit to orbit also." Alert Doug Cotton!
74166. muoncounter at 04:36 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Jonathon#80: "the statement is completely devoid of meaning. " To be clear, we are discussing the statement you made: "Without sufficient data, any model, hypothesis, or prediction can be "reasonably accurate". Side question: If a statement has no meaning why make it? In this case, the only reason that there is 'insufficient data' is because of an artificial restriction to a short time period. A more important question to ask might be: Is there any reason in data obtained between the 3rd and 4th assessment reports to invalidate the model that increasing GHGs are influencing climate change? How would you answer that question? Here's one possible answer: None of the criticisms leveled at Dana's graphs (nor charlies, for that matter) suggest that there is any such reason. All else is nit-picking -- and while I understand there is a place for that activity, it does not alter the basic conclusion. "that is not an excuse to do nothing, as you claim." On the contrary, there are many who make exactly that claim under the guise of 'the science is not settled.' Guvna Perry is just one high profile example. Note to DB: a colleague of mine has a 100 sided die; makes grading very easy.
       Moderator Response:

       [Dikran Marsupial] Well I use a Mersenne twister for that, it fills in the marksheet as well! ;oP

       [DB] I found the D100 liked to roll off the table, thus destroying the class curve and my "critical hit" chances at the same time...

74167. Dikran Marsupial at 04:23 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Jonathan Just to verify something. Are you trying to say that the observations should lie within some number of standard errors of the mean (SEM) from the ensemble mean, and that as the size of the ensemble grows the SEM will decrease?
74168. Dikran Marsupial at 04:21 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Jonathon Sadly we can only roll the die once as we only have one planet Earth. It seems you have not grasped the analogy. The single roll of the die represents the value of the trend we observe on earth, note I haven't specified the period over which this trend is calculated, becuase it is irrelevant. If you compute the trend over a longer period then the uncertainty of the observed trend will decrease, but the spread of the distribution of modelled trends will decrease along with it. Why is it that whenever I offer an analogy, the person I am trying to explain something to always proceeds to over-extend the analogy in a way that doesn't relate to reality?
74169. Charlie A at 04:12 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Moderator DB, inline comment #70 "One thinks that the skeptical thing to do would be to first understand the other approach (which you say you do) and either agree that there is no meaningful difference in results (which you do) or show why the other approach is invalid (which you don't)." I agree there is not difference in trends. I did not say, and I do not agree, that there is no meaningful difference in results. If I wished to compare the mean projected temperature for 2000-2010 with observations, my graph and calculations would give a proper comparison. The Figure 3 graph by Dana1981 would give an erroneous result. Do you (and Dana) understand that statement? Do you agree or disagree? If I were to rebaseline the 2000-2010 model mean time series to match the GISS 2000-2010 mean, then the projected temperature for 2000-2010 would perfectly match the observed data, not matter what the projection was originally. Dana uses only a portion of the observed data (up through 2005, if I understand correctly) to adjust the mean of the projection, but philosophically it has the same problem as matching over the entire period for which we are comparing projections vs observation. If DB and Dana1981 don't see any problems using the hindsight of observations performed after the start date of the projections to make post hoc adjustment of the projections, then there is nothing further I can say.
74170. Jonathon at 04:04 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Muon, If it only takes one data point, then that qualifies as sufficient. Yes, the statement is completely devoid of meaning. Based on the observations, reasonably inaccurate would also qualify. However, that is not an excuse to do nothing, as you claim. Dikran, if you continue to roll the dice enough, the uncertainty will decrease until you achieve a mean of 3.5 with an uncertainty such that 5 will fall outside your error. With enough data, we can can get a temperature trend that will determine the whether the model falls within or outside of error bars.
74171. dana1981 at 03:52 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       NYJ - yeah, there have been other cooling effects this decade too. I'll update the post to clarify that later.
74172. John Hartz at 03:38 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       Suggested reading “Hottest Decade on Record Would Have Been Even Hotter But for Deep Oceans — Accelerated Warming May Be On Its Way” by Joe Romm, Climate Progress, Sep 23, 2011. To access this informative article, click here
74173. NewYorkJ at 02:46 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Nitpicking a bit: Dana: "This data falls well within the model uncertainty range (shown in Figure 2, but not Figure 3), but the observed trend over the past decade is a bit lower than projected. This is likely mainly due to the increase in human aerosol emissions, which was not expected in the IPCC SRES" Couldn't the extended solar minimum, leveling off of methane concentration, and/or potentially a negative trend in ENSO (not sure if this applies with the starting date) have had some effect? "A bit lower than projected" and the text that follows implies that there must be a likely explanation for it identified. In fact, the trend is extraordinarily close to the mean model projection, perhaps within measurement margin of error. Starting later reduces the trend quite a bit, but from the RC post we can see that there are many individual model runs over 8-year periods, and in a small percentage of cases, 20-year periods, that run flat or negative. So we're back to short time periods don't tell us much. There's also an impression perpetuated among denial realms that observations are expected to match closely with the mean model projection over a 10-year period or less, which is bogus.
74174. Dikran Marsupial at 02:27 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Johnathon Perhaps an example from a more basic domain will help. Say we roll a six-sided unbiased die, and we get a value of five. This is our observation. To make our model ensemble, we get a get 100 six sided die, and roll them once each and get a mean value of 3.5 with a standard deviation of 1.7. So is our ensemble mean of 3.5 a "reasonably accurate" estimate of the observed value of 5. I'd say yes, because the observation is a random variable, that is only predictable within the limits of its internal variability. In this case, we can accurately estimate this variability by the variability in the ensemble runs (because in this case our models are exactly correct). Model uncertainty is another matter. Say we didn't know what kind of dice we had (c.f. uncertainty regarding climate physics). In this case, we might make an ensmble of D6s, D4s, D8s and D20s etc (ask your local D&D player). In this case we will have an even larger standard deviation, because of the model uncertainty in addition to the inherent uncertianty of the problem. In climate modelling, that is why we have multi-model ensembles.
       Moderator Response: [DB] Not to mention the D10s, D12s and D32s some of us used. :)
74175. muoncounter at 02:16 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Jonathon#72: "Without sufficient data, any model, hypothesis, or prediction can be "reasonably accurate."" Really? It only takes one data point to falsify some hypotheses. You seem to be objecting here to the ambiguity in the phase "reasonably accurate." Yet you now introduce the equally ambiguous qualifier 'sufficient'. So we now have a statement virtually devoid of practical meaning, as we will only have the necessary data to certify a prediction as 'accurate' after the fact. That is the perfect excuse to do nothing -- or as we used to say in the oil business, 'I never lost any money on a well I didn't drill.' Has this level of scrutiny been equally applied to predictions made on both sides of the climate change argument? Or do we have a data point for a hypothesis about the motivations for these objections?
74176. Dikran Marsupial at 02:06 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Jonathon wrote: "To claim as Dikran suggests that this model is "as accurate as there is reason to suggest it should be," is more of a statement about the uncertainty of the model rather than its accuracy." No, you are completely missing the point. The ensemble mean is an estimate of only the forced component of climate change. The observed trend is a combination of the forced change and the unforced change (i.e. a realisation of the effects of internal climate variability). Thus to directly compare the ensemble mean and the observations, is comparing apples with pears. To know whether the ensemble mean is "reasonably accurate" you need an estimate of the plausible effects of climate variability on the observations. Currently the spread of the models is the best estimate of this available. Thus it is not a statement about the uncertainty of the models, but of the uncertainty in estimaing the forced component of the trend in the observations, which is what you need in order to be comparing like-with-like when comparing the observations with the model ensemble. As I said "reasonably accurate" is a good summary, if you understand that the ensemble mean is only an estimate of the forced component of the trend. Saying that the models appear "reasonably accurate" is in no way "validation" of the models, and I don't think anyone is claiming that it is.
74177. Alexandre at 02:01 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Charlie A at 01:06 AM on 25 September, 2011 I don't see the importance of each decade's trend as you seem to see. As noted by others, in such short periods there's a lot of noise, and starting and ending points make a big difference in your results. Are you saying that this decade's trend is less steep than projected, so warming scenarios are exaggerated?
74178. Charlie A at 01:54 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       @#14 Adelady -- I recognize that the SkS author made comments regarding observations. I just wanted to verify that Figure 2 is a model vs. model comparison before I go off looking to see if there is any observational data related to that. I am also looking for observational data to support or contradict the SkS summary point of "The surface layers, even down to 700 metres, are not robust indicators of total OHC." It seems that many studies have shown that the majority of variations in OHC are indeed in the upper 700 meters, and so therefore there is good correlation (although not perfect) between the 0-700m OHC and total OHC. Does anybody have any links for articles discussing the correlation between total OHC and 0-700m OHC? Or alternatively, perhaps Rob Painter can cite the source for his statement that 0-700m OHC is not a robust indicator of total OHC.
       Moderator Response: [grypo] If I'm understanding your question, IPCC Ch 5.2.2.2 discusses this in the paragraph starting:

       There is a contribution to the global heat content integral from depths greater than 700 m as documented by Levitus et al. (2000; 2005a). However, due to the lack of data with increasing depth the data must be composited using five-year running pentads in order to have enough data for a meaningful analysis in the deep ocean...

       The link for Levitus

       While 0-700 m has the most robust data, I do not believe there is anything physically important about that depth. Rob likely has more up to date information.
74179. dana1981 at 01:53 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Charlie A - there is no "bogus data" in the graph. You disagree on the choice of baseline - that's fine, you're entitled to your opinion (and that's all it is, your opinion), but don't start claiming that the data is bogus. In another comment, lucia posted a graph with a very different baseline which frankly I think is rather deceptive. But I didn't comment on it, because baselines don't really matter in this case. She's entitled to her presentation, I'm entitled to mine, and you're entitled to yours. You really need to accept that and move on. Or feel free to continue arguing about it with Zeke and lucia on their site, since they seem to disagree with you as well.
74180. Jonathon at 01:41 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Dana, Without sufficient data, any model, hypothesis, or prediction can be "reasonably accurate." In such a situation, the statement is essential meaningless. Based on the AR4 trend of 0.2C/decade, then the model would predict warming from 1/1/2000 to date of ~0.25C. The GISS observations yield 0.14C increase; HadCRU yields -0.04C. The simple conclusion is that not one of these trends is significantly different from each other. Since 2000, the monthly temperature range is 0.7C To claim as Dikran suggests that this model is "as accurate as there is reason to suggest it should be," is more of a statement about the uncertainty of the model rather than its accuracy. The model no more validates a climate sensitivity of 3 any more than it validates a sensitivity of 5 or 0. This whole exercise appears to be a vain effort to prove (falsify) something that is unprovable to date. At some point in the future, we will be able to ascertain the validity of this model.
74181. Dean at 01:27 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       Rob #7 "because his simple model soaks up heat very quickly he claims climate sensitivity is low" But isn't this mixing up the concepts? If the ocean soaks up more heat it doesn't change the climate sensitivity, just delays the time to the equilibrium. Equivalently, a slower temperature rise might not mean lower climate sensitivity. The heat stored in the ocean might not be visible at the surface for a couple of hundred years but the TOA imbalance is still the same.
74182. wingding at 01:25 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       i could have phrased that question better... What I mean is, is this energy into the deep ocean effectively "lost" (ie it won't come back up in the next 100 years)? Or does the opposite happen (energy from deep ocean comes up) which if it did would cause OHC in the top 700m to rise very quickly during such a period (the greenhouse gas forcing plus the upwelling from the deep ocean)? I guess this might be covered in the next part. Thanks for the article!
       Response:

       [DB] One can surmise that the mechanisms that transfer heat between the upper, mid and deep oceans have always been existent rather than a new development.  In that regard, the extra energy is not being "lost" per se but more than is "normal" is being transferred to the deeps at this juncture.

       Trenberth warns that it is when this mode shifts that we may experience decadal periods when this sequestered "heat" comes roaring back out of the deeps, making the recent period of "cooling" (aka, the hottest decade in the instrumental record) seem very cold indeed.

74183. PaulK at 01:25 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       #62 Grypo, "The models inability to model the cooling effects will mean the models will overestimate warming. If they didn't, it would be more worrisome for the modellers." Well, I agree with your statement, but it introduces a bizarre argument in a conversation about validation. What weight should we attribute to a model that is missing a substantial known forcing, and which gives rise to a warming bias of untested magnitude? If the model is only partly formed, then the obvious solution is to drop the model from the CMIP suite until it is ready to be validated.
74184. muoncounter at 01:23 AM on 25 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       Eric#26: Thank you. I meant to link to the full report. A similar figure is at the end of the Gulledge presentation.
74185. wingding at 01:19 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       What if this bleed of energy to the lower ocean keeps up though? (not permanently - I mean it just keeps happening). Wouldn't that raise the response time to a doubling of CO2 meaning that potentially it takes a lot longer for 2C warming to be realized?
74186. Charlie A at 01:10 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       #55muoncounter "Do you accept charlie's graph here?" Note that the realclimate graph at the end of comment #18 shows the GISS rebaselined to 1980-1981. The model data in that graph is for A1B scenario, but the GISS data does match up with my figure from comment #46. I see all sorts of justifications and excuses for showing bogus data. Showing the correct data does not affect the rather vague conclusions of this article, so I don't understand why there is so much reluctance to correct the figure. again.
       Response:

       [DB] "I see all sorts of justifications and excuses for showing bogus data."

       So if someone has an alternative approach to something than one you favor then the other approach is "bogus"?

       One thinks that the skeptical thing to do would be to first understand the other approach (which you say you do) and either agree that there is no meaningful difference in results (which you do) or show why the other approach is invalid (which you don't).

       Suggestion: since you agree that it doesn't matter, perhaps it would be best to drop this line of discussion as your persistence in this reflects poorly on you.

74187. Charlie A at 01:06 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       @66 Alexandre --- my comments in both this article and the previous one have been with the sole focus of trying to understand what is being presented in Figure 3. I have not made any statements about model validation or trends, other than questioning whether Dana1981's assertion that the AR4 A2 model mean trend from 2000-2010 is 0.12C/decade. I did not even comment upon his related assertion that the A2 model mean from 2010 to 2020 is 0.28C/decade. Obviously offsets do not affect trends. The IPCC could have forecast global surface temperature anomaly of 55C going to 55.2C by 2010 and the trend would not be inconsistent with observations. While a projection of 55C might seem ridiculous, it is an anomaly not a temperature and the trend, as others have pointed out, would be correct. The AR4 projections, however, contain more information that just trends. The projections are anomalies, with a specific baseline of 1980-1999 (See caption of Figure 2 in the article). This allows us to determine not only the error in the projected trend, but to also estimate the rms error of the projection. The RMS difference between GISS and AR4 A2 projection anomalies, using a common baseline of 1980-1999 is 0.09C -- or about 1/2 of the expected difference over a decade. The rms difference between GISS data as plotted, and the AR4 A2 annual series using the link of the article is 0.21C. I cannot directly calculate the rms difference between the two time series as plotted in Dana's Figure 3, because I still cannot figure out how that figure was generated. It appears that the GISS data, after being passed through some sort of spline filter, is plotted using the standard 1951-1980 baseline, but it is unclear how the AR4 A2 projections have been modified. They appear to have been moved upward about 0.2C. This is what would happen if, after the fact, the difference between the projections and the observed data is used to adjusted the projections to minimized the rms difference.
74188. dana1981 at 01:03 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Maybe I'm being obtuse, but I don't see the contradiction in the conclusion. So far, the models and data are in reasonable agreement [falling within the spread of model runs, and not too far off from the average]. At the same time, it's not enough data to say anything meaningful.
74189. Eric (skeptic) at 00:47 AM on 25 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       #25, muoncounter, I agree with your assessment that the shift of the distribution is an oversimplification. My argument has always been that the shape of the distribution is a function of climate change and local weather. For example we could see large changes in the shape and position of the distribution of precip and temp in Alaska but not much in San Diego (perhaps only a small shift). Your link however doesn't seem to contain to the graphic you show. In fact, the full report http://goo.gl/KLpwL shows the shifted distribution in fig 6.4
74190. muoncounter at 00:43 AM on 25 September 2011
       Galactic cosmic rays: Backing the wrong horse
       Paul D: The headline of the press release stated: "Cloud formation may be linked to cosmic rays." OK, they may be, but that is not what Kirkby actually says. Writers ranging from Nigel Calder to the Forbes 'science' blogger picked this up and turned it into 'Hooray! Its proven that cosmic rays cause climate change!' in spite of the Kirkby quote. One has to suspect (and in Calder's case, it is a certainty rather than a suspicion) that is what they wanted to hear. Worse still, they started throwing around the sham argument that 'there's a conspiracy to keep Kirkby quiet' or some such twaddle. But I suppose there are some who still believe the moon is made of cheese.
74191. Dave123 at 00:33 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       Thanks for your thoughts, Adelady. I totally agree that what happens TOA is the prime factor. But my musing is about the geography of thought on the subject. The reason I strongly approved of SkS side of the attempt at a conversation with Dr. Pielke Sr. was that he argued for a single value indicating global warming, whereas the consensus position of the contributors on the SkS was that multiple indicators were important. To make more of the example I started- Suppose for some reason the GCMs are not doing a good job with ice melting. For whatever reason they park the heat the lower atmosphere, and thus over-predict both climate sensitivity and the future temperature record. But the ice keeps on melting and sea levels rise and so forth. If we get too stuck on GCMs and the accuracy of GMT scenarios, we are guided away from action because we can't incorporate the sea level rise properly into the picture. At the end it IS the effects that motivate for change. Given the impressive ability of the denialsphere to change topics, shift goal posts, invent ad hoc goals and so forth, I'm wrestling with how to communicate around that...hence also the concern for the boarderlands of skepticsm and denial.
74192. John Hartz at 00:29 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Has Lucia left the building?
74193. adelady at 00:20 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       charlie, check the summing up "Current observations of the 700 metre surface layer have shown little warming, or even cooling, in the last 8 years; but the surface layer down to 1500 metres has shown significant warming, which seems to support the modeling." So figure 2 does represent model runs and the text below talks about the various features of those models. But the features they remark on are about how well the models match observations.
74194. muoncounter at 00:18 AM on 25 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       Another relevant graphic is Fig 2.4 in 'Degrees of Risk.' This suggests that rather than the simple linear shift to the right of the symmetric probability curve shown in Fig 1 above, we may see a flattening and broadening of the probability spectrum, shapes better represented by Poisson distributions: Along the horizontal axis, plot a 'severity' index; the vertical is probability of occurrence. The m=0.5 curve might represent historic conditions; m=1 or 2 or 4 might be where we are heading. By flattening the distribution, extreme events start showing up under the long tail to the right. That doesn't mean that everyone sees the same extremes; it simply means there are more possibilities. The metaphor of 'rolling 13s' is a very good one.
74195. adelady at 00:12 AM on 25 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       Dave123 "... at the same time I think ice melt, extent, precipitation, and GMST with appropriate weightings as an objective function might be more useful. " Maybe so. But we have to go with a)what we've got b) the most straightforward link to the physics possible. For a), we have to acknowledge that meteorologists, geographers, governments and other observers of 50 years ago weren't aware that a later generation might be interested in long-term data-sets of items that were of only peripheral interest to them at the time. So temperature is really the only consistent record we have for most of the globe. For b), the big issue now and for a long time yet to come, what's happening at TOA. The physics tells us that heat that does (or doesn't) escape to space from there is the major determinant for total heat content of the atmosphere and the ocean. We might as well face that fact. The heat might show up in winds and weather locally or it might go into melting glaciers and icecaps we've never seen. (Apart from the hardy souls who venture into remote, inhospitable realms, that is.) The items you mention are good evidence for the effects of warming, but temperature is the central issue.
74196. Bob Lacatena at 00:08 AM on 25 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       15, Norman, It is very important to note that the current warming trend only covers the last three bars (out of sixteen) in that 1850-2000 bar graph, and of those, only that last 1 or 2 demonstrate enough warming to tease out a climate change impact. As such, I find the reference of no value whatsoever. A proper verbal interpretation of the graph would say "the overall trend for the period prior to the impact of anthropogenic climate change is downward, but there is not yet enough data to determine if the 'climate change tail' will be definitively upward -- i.e. yet another hockey stick."
74197. Dikran Marsupial at 23:53 PM on 24 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       John Russell that is pretty much why "climate change" is a more accurate term than "global warming". Physics sas the globe will warm on average as a result of increasing atmospheric CO2, but that doesn't mean it will warm uniformly everywhere, or that there won't be anywhere tht cools rather than warms. The thing to do is point them toward the regional projections for Europe in the IPCC reports, which suggests that the U.K. is somewhere where it is unlikely to see that much warming. I can't remember what it says about extremes or precipitation off-hand. I'd also point out that internal variability (i.e. weather) is increasingly dominant over short timescales and on small spatial scales, so weather over a decade or two in the U.K. (which is tiny) says virtually nothing about climate, changing or not. It's good we are in basic agreement though, it would be nice if there were more of that generally! ;o)
74198. adelady at 23:52 PM on 24 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       chris, the first thing that people need is to change the reference from 'global warming' to climate ... 'change' or 'disruption' or, for the unlucky ones in some places at the wrong times, 'crisis'. I know that it is global warming, but as soon as people start thinking about themselves or their own location, they drop the 'global' without even noticing. As for Britain's last 2 winters. Those cold winters, below 71-2000 average for temperature, were both accompanied by above average hours of sunlight and below average rainfall. No idea if those things are significant. As for your 'unreliable summers', I remember reading a gardening magazine a few years ago talking about growing some plant or other which grew a lot better with England's consistent rainfall than Oz's long, dry, hot periods. They referred to England's "terrible weather but wonderful climate" for gardeners.
74199. muoncounter at 23:51 PM on 24 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       Norman#15: "an interesting link to Texas climate. " This graphic produced by Texas' state climatologist, John Nielsen-Gammon is very relevant here: It's easy to say that the big red dot (2011's hot and dry weather) is exceptionally odd. But note the years 2006, 2007, 2008, 2009, 2010 and 2011 are all above the curve, with 2004 and 2005 on it. That is starting to scare people, including the same John NG, who doesn't see it ending any time soon: ... we have heightened drought susceptibility during this period, and, according to some studies, the effect of La Niña is likely to be amplified. So this coming year looks very likely to be another dry one, and consequently it is very likely that next summer will have water shortages and drought problems even more severe than this summer. That's what I take the concept of a 'new normal' to signify: Higher probabilities of 'extreme,' 'severe,' 'more intense,' 'never been like this,' etc. But I find it unreasonable to believe that everyone, everywhere will be seeing the same warmer, drier summers at the same time: I'd love to know where that idea got started. My suspicions are that oversimpliers gave the suggestion and deniersphere picked it up with ignorance like this. I apologize to John R and any others who took exception to my brusque turn of phrase, but if a certain governor gets his party's nomination next year, ya'll will be hearin' a lot more of that.
74200. John Russell at 23:44 PM on 24 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       Chris, I agree with everything you say. And I don't really disagree with anything Dikran says -- or muoncounter for that matter. The problem I was addressing -- based on the subject of the post -- is in explaining climate change to people in the UK who do not perceive themselves to be experiencing extreme weather: and what they are experiencing seems not to be connected with 'warming'. Now, if they were in Texas, it might be more obvious.

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