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Comments 73951 to 74000:

73951. 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)
73952. 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.
73953. 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!
73954. 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...

73955. 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?
73956. 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?
73957. 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.
73958. 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.
73959. 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.
73960. 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
73961. 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.
73962. 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. :)
73963. 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?
73964. 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.
73965. 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?
73966. 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.
73967. 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.
73968. 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.
73969. 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.
73970. 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.

73971. 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.
73972. 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.
73973. 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?
73974. 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.

73975. 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.
73976. 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.
73977. 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
73978. 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.
73979. 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.
73980. John Hartz at 00:29 AM on 25 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Has Lucia left the building?
73981. 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.
73982. 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.
73983. 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.
73984. 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."
73985. 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)
73986. 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.
73987. 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.
73988. 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.
73989. Charlie A at 23:33 PM on 24 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       Please clarify whether the total energy in the graphs of figure 2 are observed total energy or the total energy as simulated by a model. My understanding is that what is shown is the correlation between two outputs of the model and that none of the data in Figure 2 is measured, observed data. Correct?
73990. Bob Lacatena at 23:27 PM on 24 September 2011
       Galactic cosmic rays: Backing the wrong horse
       12, Paul D, The first sentence says the rebuttal features his own words, not contradicts. Here are those specific words:

       "At the moment, it actually says nothing about a possible cosmic-ray effect on clouds and climate, but it's a very important first step" -- Dr. Kirkby

73991. mlyle at 23:15 PM on 24 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       Actually, average depth of the oceans is 3.8 km, not 4.3. Otherwise, a good post. In terms of the short term climate sensitivity, yes, putting heat into the ocean slows down warming but in turn means that the eventual cooling will not be fast.
       Moderator Response: [John Hartz] Source please.
73992. Alexandre at 23:09 PM on 24 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Charlie A at 12:29 PM on 24 September, 2011 What's the difference between the trends in your graph, and the trend in Dana's graph?
73993. Dikran Marsupial at 23:01 PM on 24 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Jonathon "reasonably accurate" is not a "strong conclusion" and hence is supportable by the evidence. To my eyes "reasonably accurate" means "as accurate as there is reason to suggest it should be". As I have said before, even if the model is perfect, there is no reason to expect anything more than for the observations to lie within the spread of the model runs. If the observations (considering their uncertainty) lie within the bulk of the model runs, rather than right out in the tails, then "reasonably accurate" would be an excellent summary. In order to work out whether the models are accurate, you first need an estimate of the variance that can be caused by internal climate variability. We can't get a good estimate of that as we have only one realisation of the observed climate. So the best estimate we have of climate variability is given by the spread of the model runs. If you have a better estimate, lets hear it, the models mean cannot be expected to be any closer to the observations that that.
73994. chris at 22:53 PM on 24 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       John Hartz asked: John Hartz (at 06:42 AM on 24 September, 2011) asked:

       @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?"

       The last section is very problematic to me, and seems to contain logical incompatibilities. In the space of a few sentences it states (concerning IPCC AR4 projections), that "it's difficult to evaluate the accuracy of its projections" and that the projections are "reasonably accurate thus far"..... ....and that it will take another decade before we know what the projections will say about climate sensitivity, but that their "reasonable accuracy thus far" indicates that this will provide evidence that climate sensitivity is near 3 oC. This seems a semantic and logical mess. I don't see how one can say at the same time that it's difficult to evaluate the accuracy of projections, and that they're reasonably accurate! Nor can we say at the same time that we consider that the accuracy of the projections so far (which is supposed to be difficult to evaluate) will indicate that climate sensitivity is around 3 oC, and that we won't know what the projections will say about climate sensitivity for another decade. I don't think I'm being overly obtuse (if I am I'm sure you'll say so!). I would have thought that the justifiable conclusions are that the AR4 simulations are not inconsistent with the surface temperature progression since 2000, and that they are not inconsistent with the broad consensus of evidence that the climate sensitivity is near 3 oC (plus/minus a bit). However so far comparison of the AR4 models with the surface temperature progression of the last decade doesn't really tell us anything very much at all about climate sensitivity at all. One the other hand if one were to consider the comparison of climate model projections since the late 1980's, for example, with the subsequent temperature progression, then those models and the empirical data would give us confidence that our understanding of atmospheric and ocean physics and climate sensitivity are quite well supported. Overall I have a few concerns about the perception and use of model data in an out-of-science context. In my experience models are very useful for systematising large amounts of independent physical understanding into a useable predictor (through parameterization), for testing the reliability of our parameterizations through comparison of model output with empirical data, for suggesting possible interpretations and experiments (not quite so useful in the case of climate models) and providing a focus for independent study (for example, by identifying arenas where models and empirical observations are seemingly incompatible; good examples are model success with respect to MSU tropospheric temperatures; tropospheric water vapour uncertainty). There's no question that climate models are important for projecting multi-decadal consequences of specific emission scenarios. However we should be very careful in considering the value of decadal model-empirical comparisons, when it's very well understood that we don't have any expectation that models will necessarily do a good job of this (at least with respect to tropospheric or surface temperature progression).
73995. Jonathon at 22:45 PM on 24 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Michael, I agree that the data set is too short for strong conclusions. It appears that there are two beefs with Dana's conclusion that the AR4 models are reasonably accurate. First, that the time frame is too short to draw an accurate conclusion. Second, that the trend for the observational temperatures does not reflect the most recent data. Either way, the statement that the AR4 projections are reasonably accurate is not supported (nor falsified) by the recent temperatures.
73996. grypo at 21:59 PM on 24 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       Paulk The next line abstract for JoC paper is important

       This is consistent with the fact that CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of short-wave and long-wave cloud forcings.

       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.
73997. chris at 21:53 PM on 24 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       Dikran/John I also live in the UK. I agree that one might not perceive much in the way of temperature change in relation to our notoriously variable summers (the one just past being pretty pathetic warmth/sunshine-wise, 'though we did have a fantastic summer in March-April!). However the earlier onset of Spring is quite noticable on a personal level, and I believe that what I perceive to be an increase in extreme rainfall events is a reflection of real changes in rainfall (increased during Autumn and Winter) that are consistent with expected global changes in precipitation regimes in a warming world. Likewise at a personal level I am aware of the problems in Scotlands skiing industry over the last 25 years with Glencoe shutting down, Glenshee being put up for sale and Cairngorm being taken into public ownership and skier days plummeting in the last 20 years ('though again 2008-2009/10 were very good years snow-wise in Scotland!), and am concerned about global warming related effects on the ecology of some unique habitats e.g. the Cairngorms, etc. Obviously some of these problems are exacerbated by non-climatic factors (continued paving/cementing over of urban centres reducing soil absorption of rainwater; tendency for skiers to head for more glamerous locales). But global-warming related impacts are already occurring and will undeniably bite deeper. Whether that's going to have much of an impact on our unreliable summers is a moot point!
73998. John Russell at 21:44 PM on 24 September 2011
       Review of Rough Winds: Extreme Weather and Climate Change by James Powell
       @Dikran Here in the SW of the UK, we've not had a good summer for the last four years. Instead we've had a lot of rain and it's been very difficult to find a slot for bringing in the hay. Because I grow trees on a large scale, the state of the ground is very high on my radar and it's been on the whole much wetter that it was a few years ago. I accept that in some areas of the UK, say the SE, that's not been the case and certainly a farming colleague in East Anglia has been moaning about drought. As far as the winters go, since the cold spells of my childhood in the 50s and 60s, as you know, winters have on the whole been very mild. Until 2 years ago most people under, say, 40 had not experienced snow drifts that come up to your waist. Most snowfalls in the south of the country seemed to melt within a day or so. The last two winters however have shown us how cold it can get and have caught many people out as they didn't consider it normal (ask your plumber!). You'll be aware that denialist writers like Delingpole and Booker have been making hay with this in the popular press, and will probably do so again this winter. Note that overall I'm talking about perception rather than the facts. I'm well aware that, considered annually, our average temperatures have been slowly rising: but that's not what people notice -- they don't experience weather through a thermometer. In this situation convincing some people that global warming is real, based on their experiences, can be difficult in the UK -- that's why the concept of climate change, with its redistribution of weather patterns, is the idea to push in the UK. I'm sure a shift towards higher temperatures (as illustrated by the temperature 'shift' bell curve) is probably a lot easier to sell in the US and Oz.
73999. michael sweet at 21:37 PM on 24 September 2011
       Lessons from Past Climate Predictions: IPCC AR4 (update)
       There are several posters on this thread who are making nit-picks about how data has been presented. The lead post clearly states that the data set is too short for strong conclusions. These posters are making arcane arguments that there is some problem with the graphs in the post. Can they please post a proper graph that shows the conclusions are not correct? So far the "corrected" graphs argee with the lead post's conclusions. If the changes do not affect the conclusions, why bother? If you think that you are proving doubt by questioning the baseline of a short term graph you are wrong (0.05C!! who cares). Read a book about analyizing data with a lot of noise. There is always more than one way of properly presenting data of this type. If the conclusion is not affected by the change, it is not important. Please post data that shows the conclusion is not correct.
74000. Dave123 at 20:58 PM on 24 September 2011
       Ocean Heat Content And The Importance Of The Deep Ocean
       Rob, [indirect ad-hominem deleted] I've been trying to build in my mind a geography of climate change thought, wondering about the boarderlands of denial vs legitimate skeptcism. The business with both Lucia and Dr. Pielke Sr. sounding 'lukewarmist' was a bit of a trigger. So I see a distinction in this mental geography betweeen the statements- "We have a climate sensitivity of 3 C nearterm and this results in the rapid ice loss at the poles and greenland" and "We have a X w/m2 energy excess that will result in a Y degree GMS temperature rise and a Z rate of ice melting". I know this isn't the topic of this thread...I'm not even sure there is a thread for this...but I'm starting to wonder about the use of GMST as a singular objective function for GCMs and whether Dana is going in the right direction with his historical series on that account. I do not buy into Dr. Pielke's (apparent) view that GC models are not useful if they don't forecast nearterm regional climate change accurately, but at the same time I think ice melt, extent, precipitation, and GMST with appropriate weightings as an objective function might be more useful.
       Moderator Response: [Dikran Marsupial] Please restrict the criticism to the argument, not the source, even if the ciriticm is indirect.

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