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Comments 41701 to 41750:

41701. franklefkin at 00:01 AM on 8 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Tom Curtis, Climate Change 2007: Working Group I: The Physical Science Basis ContentsSPMProjections of Projections of Future Changes in Climate < A major advance of this assessment of climate change projections compared with the TAR is the large number of simulations available from a broader range of models. Taken together with additional information from observations, these provide a quantitative basis for estimating likelihoods for many aspects of future climate change. Model simulations cover a range of possible futures including idealised emission or concentration assumptions. These include SRES[14] illustrative marker scenarios for the 2000 to 2100 period and model experiments with greenhouse gases and aerosol concentrations held constant after year 2000 or 2100. For the next two decades, a warming of about 0.2°C per decade is projected for a range of SRES emission scenarios. Even if the concentrations of all greenhouse gases and aerosols had been kept constant at year 2000 levels, a further warming of about 0.1°C per decade would be expected. {10.3, 10.7} Since IPCC’s first report in 1990, assessed projections have suggested global average temperature increases between about 0.15°C and 0.3°C per decade for 1990 to 2005. This can now be compared with observed values of about 0.2°C per decade, strengthening confidence in near-term projections. {1.2, 3.2} Model experiments show that even if all radiative forcing agents were held constant at year 2000 levels, a further warming trend would occur in the next two decades at a rate of about 0.1°C per decade, due mainly to the slow response of the oceans. About twice as much warming (0.2°C per decade) would be expected if emissions are within the range of the SRES scenarios. Best-estimate projections from models indicate that decadal average warming over each inhabited continent by 2030 is insensitive to the choice among SRES scenarios and is very likely to be at least twice as large as the corresponding model-estimated natural variability during the 20th century. {9.4, 10.3, 10.5, 11.2–11.7, Figure TS.29} http://www.ipcc.ch/publications_and_data/ar4/wg1/en/spmsspm-projections-of.html

       In the above, taken from AR4, the predictions clearly state warming will be between 0.15 and 0.30 c/decade. In fact, they state that if ghg (and aerosols) were to remain at 2000 levels - with no increases, warming would proceed at 0.1 C/decade.

        

        

       Moderator Response:

       [JH] The readibility of your posts would be greatly enhanced if you were to avoid composing lengthy paragraphs such as the first one above. If you group your thoughts into shorter paragraphs, readers will be better able to understand what your points are.

41702. One Planet Only Forever at 00:00 AM on 8 October 2013
       A rough guide to the components of Earth's Climate System
       

       The El Nino that led to the 2010 temperature should not just be called a strong El Nino, an event in the same category as the one that led to the 1998 temperature.

       The ENSO values from NOAA should be referred to for the El Nino and La Nina relative magnitudes.

       http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml

       It is clear that the 2009/10 event was shorter than the 1997/98 event and had a significantly lower "peak" temperature value. The resulting higher global average surface temperature from a less significant event is more significant than if the thought is that the El Ninos are “comparable”.

       Of course, the duration and “peak” value are not the only factors affecting how much heat is transferred from the Pacific surface into the lower atmosphere but they are major factors in how much “warmer” the global average surface temperature is.

       On a related point, it may be helpful to track the rolling averages for every new month of data, like Dr. Roy Spencer has done for the satellite data results. There is no need to wait for the “end of a year” to identify what the trend is. And during an El Nino event the peak result can spread over 2 years rather than more significantly increasing one year.

       Of course, I would recommend the average meant to represent an annual average be a true 12 month average not the “13 month average” used by Dr. Roy. He may have chosen this to be able to declare the month in the middle as the “middle of the average” but that is a little lazy.. Every 12 month set of temperatures represents the same data as 12 months ending in December or January. 13 month averages do not as accurately represent an “annual average”.

41703. KR at 23:51 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Tom Curtis - Very clear reply to SAM, thank you. 

       Cynicus - As Tom Curtis pointed out, McIntyre is only using the HadCRUT4 data, which is notably missing polar areas with higher temperature trends. A comparison between global model trends and not-global observations is inaccurate unless the model data is masked to the same extent - and I see no sign that McIntyre has done so. 

       McIntyre has not shown the real distributions over the model runs, de-emphasized natural variability, compared masked observations with unmasked models, on and on and on. He has not made his case. Far from his claims - Observations continue to validate the models. 

41704. Tom Curtis at 23:04 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Franklefkin @85, thankyou for your inquiry.  Following it up I discovered that I had mistakenly used trends from 1975 rather than the trends from 1990.  Here is the graph reproduced with the correct trends:

        

       From 1990, the minimum trend is 0.08 C per decade.  That is literally the minimum trend from any member of the ensemble over that period.  There are 6 (out of 54) ensemble members with a lower trend than HadCRUT4, and 8 with a lower trend than GISS.  I cannot comment on your quote from AR4 unless you actually cite it.

41705. Tom Curtis at 22:45 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Cynicus @84a, how has he fudged it?  Let me count the ways:

       1)  To start with, only 42 models were used to explore the RCP 4.5 scenario.  With 13 named models in the box plot, that leaves 29 singletons.  In turn that means that there are only 80 model runs by those 13 models, or an average of 6.15 model runs each.  If your thinking it's a bit of a statistical stretch doing a box plot on just six data points, you are right.  It is worse than that, for while some models such as the CSIRO Mk3 have all of 10 runs, others such as the CESM-CAM5 have only 3 runs.  The CESM-CAM5 still gets its own little box plot, with median, 25th and 75th percentiles, and the 90% range whiskers all of its own, and all of just three runs.  That is a bit of a joke statistically.  In fact, even the CSIRO Mk 3, with its box plot and whiskers based of 8 runs, plus two outliers (I'm cracking up here) is essentially meaningless statistically.  McIntyre had too few samples to make any statistically meaningful claims about individual models, and he knew it.  More importantly, the restricted range of the 90% range reflects only the very few samples rather than being a real indication of the variability to be expected from the model.

       That means the only meaningful statistic in the entire figure is the box plot coloured gold on the right, ie, the full ensemble.

       2)  McIntyre compares with only HadCRUT4.  HadCRUT4 excludes some of the fastest warming regions in the world.  Most notably the Arctic, but also large sections of north Africa, the middle east and areas north of India.  Curiously those later areas are where most of the 19 nations that set new national temperaturerecords in 2010 are located.  Therefore we know that HadCRUT4 understates the actual trend in GMST, although we don't know exactly be how much.  (GISS, in constrast, may either overstate or understate it.)  Therefore, absent the use of a HadCRUT4 mask (almost impossible to set up on the KNMI explorer), we know the HadCRUT4 record understates the trend in that period.  A reasonable estimate of how much it understates it by is 0.1 C/decade.

       3)  As can be seen in the graph @69 above, using a 1979 start point introduces a significant negative trend to observed temperatures due to ENSO fluctuation.  This is exagerated in the HadCRUT4 record because it includes most areas affected by ENSO, but excludes many areas that are not.  Absent this effect, the observed record would be about 0.1 C higher.

       If we ignore the nonsense about doing box plots for models with just three samples, the comparison is interesting.  There is nothing wrong with making such comparisons, provided you are aware, and make your readers aware, of potentially misleading aspects of the comparison (as in points (2) and (3) above).  Further, even using GISTEMP, or an ENSO adjusted GISTEMP, it is likely the observed trend would still have fallen between the 75th and 90th percentile of model trends.  The CMIP5 models do run hot relative to observations.  Just not as hot, perhaps, as is suggested by the comparisons with HadCRUT4 (unless it is ENSO adjusted, and the models have a HadCRUT4 mask applied). 

41706. Tom Dayton at 22:32 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       JasonB's comment and Tom Curtis's top image and the paragraph immediately underneath it, I think should be part of the new post that mammal_E is working on, about prediction intervals versus confidence intervals (I hope).

41707. CBDunkerson at 22:22 PM on 7 October 2013
       Global Warming’s Missing Heat: Look Back In Anger (and considerable disbelief)…
       

       I've been thinking about where, other than the deep oceans, we might have missed measuring some of the 'missing heat' lately and wondering if transformation of energy might be a factor. For example, more energy hitting the planet's surface means more surface heating... which means more/stronger thermal updrafts... which presumably means stronger winds. Similarly we might see changes in the rate of ocean currents. Wouldn't the energy required to move these masses of air and water at greater speeds ultimately be coming from the 'global warming' energy imbalance? Basically this is the transformation of light into heat and heat into kinetic energy. If so, has any research been done on how wind and ocean circulation have changed and how much energy would be required to drive these changes?

       I haven't seen these factors listed in previous 'energy budget' analyses so they either somehow aren't applicable, are too minor to have a significant impact, have been included but generally not mentioned, or have been left out. Could some of the 'missing heat' be missing because it is no longer 'heat' at all, but rather has been transformed into motion?

41708. franklefkin at 22:09 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       Tom Curtis @79,The trend graphs tell a concise story. What value did you use for the Min trend line? Was it 0.10 C/Decade? In another thread "IPCC models did better than you think", I posted that in AR4, the IPCC actually quote the min to be 0.15 C/Decade. If you were to use this trend line, it would be obvious that the min and actual were very close. This would tell a very different story than the graph you have shown.
41709. chriskoz at 21:28 PM on 7 October 2013
       2013 SkS Weekly News Roundup #40B
       

       Thanks JasonB, your explanation is very helpful.

41710. cynicus at 20:48 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       In an earlier post McIntyre als showed a box-plot from 1979-2013 that suggest that the trend in the AR5 models run significantly 'hotter' than the observed temperature trend (HADCRUT4) over the same period.

       
       The box-plot:

       

       I notice this boxplot don't include the uncertainty in the HADCRUT4 trend, which included (using the SkS trendcalculator) shows that the uncertainties overlap (0.158 ±0.044 °C/decade (2σ)), thus may in fact be the same trend afterall. Is there more to critique? Thanks.

41711. JasonB at 18:25 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       SAM @ 39,

       Furthermore, what does the spaghetti add to the information? It doesn’t appear to add much, but it certainly clutters up the chart, making it nearly impossible to see the actual temperature plot. The simple banded range of model projections in the draft image make it easier read the chart.

       The point of the spaghetti rather than the simple banded model is to compare like-with-like — individual climate model realisations with the actual temperature record, which is also an individual climate realisation. "Skeptics" love to compare an actual temperature record with the ensemble mean — which, as predicted by the Central Limit Theorem, is a lot less noisy and fails to show important but unpredictable short-term effects like ENSO because of differences in timing from one realisation to the next — and then use the difference between them to claim that the models do not do a good job, ignoring the true spread of the model realisations and even adjusting the baseline.

       If the models truly did not do a good job, then the actual temperature record would still stand out when plotted with the individual model runs, as Tom did @ 79. If it went outside the banded range, it would also go outside the spaghetti, since the former is merely an indication of the spread of the latter.

       If a "Skeptic" cannot pick out the actual temperature record from one of those spaghetti charts, then how can they claim the models are not doing a good job?

       The magnitude of the apparent random variations of the individual realisations is also valuable to illustrate, because it shows that climate models also have wild swings and plateaux when you carefully cherry-pick a high point for the starting point of a trend calculation.

       As for the OP:

       Suppose the draft version of Figure 1.4 had used 1992 as the starting point rather than 1990. I can guarantee that all those "skeptics" who are so confused about baselining now would instead be instant experts on the subject and endlessly pointing out how the IPCC had tried to mislead readers by using an inappropriate baseline that exaggerated the temperature record compared to the projections.

41712. Tom Curtis at 17:43 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Klapper @80, the rationale is that the topic of the post is the treatment of the comparison between CMIP3 and observations in AR5.  Specifically, the difference in treatment of figure 1.4  between the 2nd order draft and the final draft.  I am happy to discuss the CMIP 5 results, but this is probably not the correct thread to do so. 

41713. Rob Painting at 17:38 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Tom @ 79 - that's quite brilliant. I hadn't thought of expressing it in that way, but the image you provided gets the point across very clearly. Nice work!

41714. Klapper at 16:41 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @Tom Curtis #79:

       What is your rationale for continuing to use the CMIP3 data instead of the more recent CMIP5 as the model reference?

41715. Tom Curtis at 16:12 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       SAM @77, I believe what you were trying to produce was an honest comparison between observations and the CMIP 3 (AR4) model ensemble.  Is that right?

       

       Is that not fair?  Can't you pick out the observations from the model runs?  Isn't that rather the point!  If you cannot easilly pick out the observations from the model runs, then the model runs have predicted the observations within the limits possible for stochastic processes (such as short term climate variations).

       Of course, despite Rob Honeycutt's sage advice, you may be more interested in short term trends.  Nothing in science dictates what you are interested in, regardless how futile for advancing knowledge.  Of course, if you are interested in trends, compare with trends:

       

       Doing otherwise is an apples and oranges comparison.  The only justification I can think of for doing so is a deliberate intent to mislead.

       You will now find a number of CMIP3 - observation comparisons produced by me above.  All are done with based on sound methods of comparison; and none show a significant divergence between models and observations.  It is only by doing illegitimate comparisons - by poor baselining, by comparing individual observations to trends, etc - that you can create the impression that something is radically wrong with the models.  The effort various deniers are expending on justifying such illegitimate comparisons is, IMO, a fair mark of how little regard we should have of their opinion.

41716. One Planet Only Forever at 15:06 PM on 7 October 2013
       A rough guide to the components of Earth's Climate System
       

       The list of Latent Heat items should include the Heat of Fusion to melt ice.

       It takes 334,000 J to melt 1.0 kg of ice with no temperature increase occurring.

       If snow and ice volumes fluctuate about a steady or unchanging normal amount of total frozen water then the Heat of Fusion simply goes into ice to melt it and comes out of water as it freezes with no net imbalance. However, if the volume of frozen water is trending down there is a capture of energy into the water without any increase in temperature. If energy is coming in and is creating a net melting of ice, when the rate of loss of ice reduces the energy that was going into creating less frozen water would show up as increased heat content of other parts of the system which would experience rising temperatures.

       Also, it may help to add a section that describes the way the Earth's energy will rebalance. There are many factors that can affect how rapidly the global average surface temperature increases (including a net melting of ice), but the expectation is that excess CO2 and other GHG's will eventually rebalance in a state that will have a higher global average surface temperature.

       Of course the global average surface temperatures should be measured and tracked as the average of 30 years or longer, since there are many factors that could significantly affect the global average surface temperature for a short period of time. Most of those effects are reasonably averaged into a 30 year period. The 30 year averages of global surface temperature based on the NASA/GISS data set are currently increasing at about 0.17 degrees C per decade, in spite of the lack of any annual average temperatures since 1998 significantly exceeding the 1998 value. And though it is not really important, every new month of global average temperature is warmer than the month 30 years before. That is still likely to be the case when 2028 rolls around (it will be warmer than 1998), but it would be absurd for anyone to suggest we would have to wait until then to “prove anything”. The stronger claim to make is that until an El Nino event as strong as the 1997/98 event occurs nothing can be claimed about a “lack of comparative warming of global average surface temperatures (unless a significant volcanic eruption occurs at that same time of course)”

41717. Rob Honeycutt at 13:47 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       StealthAircraftSoftwareModeler...   There's a big problem with the Excel graph you've created.  You're only looking at the trend.  Modelers know they can't project short term (10-15 year) surface temperature changes.  

       I keep stating this over and over, but I'll say it again.  Climate modeling is a boundary conditions experiment.  You're treating like an initial conditions experiment.

       Stealth, what you've done with your chart is to completely remove the boundaries established by the modeling.  Thus, you've removed the most relevant aspect of the climate models.

       Modeling is not about the mean.  It's not about the trend (except >30 years).  It's about the boundaries that are established by the range of model runs.

41718. JasonB at 13:47 PM on 7 October 2013
       2013 SkS Weekly News Roundup #40B
       

       chriskoz #1,

       The Australian system is actually not that complicated.

       For the House of Representatives, voters number candidates in order of preference. If no candidate receives 50% of the vote, then the least popular candidate is eliminated and their next preferences are distributed as if they were first preferences — effectively asking "What would the outcome be if this candidate didn't run?" This process repeats until a candidate has 50%. That candidate may well have started out with a low first preference percentage, but the fact that they won in the end means that more than half preferred that candidate to the alternative.

       The Senate is complicated by the fact that there is more than one position being filled and a "quota" of votes is required to be elected. (The House of Representatives method can be seen as a special case where there is only one position and therefore the quota is 50% + 1 vote.)

       The Senate vote count proceeds in the same way as above when unpopular candidates are eliminated, but the wrinkle is that when a candidate has reached the quota and been elected, their voters' subsequent preferences are also reallocated in proportion to the "surplus" that the successful candidate had (so the second preferences of a really popular candidate will be worth more than the second preferences of a candidate that only just got over the line.)

       In the case in question, the PUP candidate was elected because he had a quota and the Green's candidate did not. The fact that the PUP candidate received preference flows from similarly-minded organisations who are likely to be voted for by similarly-minded voters means that if you asked all of those voters who they would have preferred out of PUP and the Greens, they would probably pick PUP.

       The "gaming of the Senate vote" that people are complaining about is related to the short-hand Senate voting system introduced by the Hawke government in the 80s. Traditionally you would have to number every candidate in order, just like you do with the House of Reps candidates. However, because there are so many more candidates in the Senate, Hawke introduced the "above the line" voting option, where you could simply put a "1" in the box above the line that belonged to the party you supported, and your ballot paper would be treated as if you had filled it out according to the template that the party had registered. (I normally vote below the line even though it takes a lot longer.)

       In this particular election, there were quite a few surprising preference flows registered by the various minor parties, which might have meant that those voting for those parties might not have agreed with the order of the other parties had they bothered to look it up before the election.

       In this case, however, the final Senate seat was a battle between the Greens and Labor anyway, so the outcome wouldn't make a difference to the Carbon Tax. PUP leapfrogged both to win the fifth seat thanks to some late flows from the Libs, Nationals, and Liberal Democrats, which have similar ideologies to PUP, so it seems the system worked in this case even if the outcome is undesirable.

       It seems that Tony Abbott is going to get his way when the new Senators take their positions next year. It's also very unlikely that he would back down on his plan to "Axe the Tax" given the opportunity. The best we can hope for, it seems, is a major groundswell in support for doing something about climate change that paints the Libs as Luddites that caused us to miss an opportunity because their heads were firmly buried in the sand and unable to accept reality and forces climate change back onto the agenda at the next election. It's possible that having the country take a step back from having "solved" the problem will focus people's attention on it again. In addition, the fact that he's likely to get his way next year might mean it takes some of the heat out of the issue until then and avoids any attempt he might have otherwise made to get rid of it in the meantime. Until then, we'll just be getting on with the business of living with a carbon pricing scheme that is doing its job and not causing the end of the world, making most people wonder what all the fuss was about and hopefully making it easier to bring back in the future.

41719. StealthAircraftSoftwareModeler at 13:16 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Moderator [DB] @ 39: I read the OP again and it doesn’t address my question @39 at all. The discussion in the OP is about the baseline is the location of zero on the Y axis scale. I want to know why the IPCC zoomed out so far and covered the actual temperature with messy spaghetti lines. So, I have gone off and gathered raw data from original sources and plotted it. This is my first time trying to post an image -- hopefully it works.

       I have downloaded HADCRUT4 (baselined 1961 to 1990) and plotted the data in Excel. I have also plotted a center weighted 5 year moving average. I then have digitized the original IPCC AR3 and AR4 model projections from the IPCC’s website and plotted those in the chart. Note that both the AR3 and AR4 projection are aligned to the year they were projected – 1980 for AR3 and 1990 for AR4 – and at the location of the 5 year moving average for those years. This aligns the trend projections of AR3 and AR4 to the center of the HADCRUT data for their respective years. While the chart speaks for itself, it is clear that the actual temperatures generally run a little cooler than model projections. In 2005 the actual temperatures have clearly departed from model projections.

       

       Moderator Response:

       [DB] Please constrain image widths to 450.

       As this thread concerns the AR5 projections, please take your course of inquiry to this discussion of the TAR and the AR4 IPCC projections.

41720. Klapper at 12:04 PM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @Tom Curtis #72:

       You pre-empted my next post somewhat since I was going to agree the 1990-1992 to 2006/now trends didn't prove much other than the models overcool during major volcanic episodes and we should instead focus on McIntyre's 1979 to 2013 model vs observations analysis. Since you've basically done the analysis from 1975 showing the same thing as McIntyre we can skip the argument of whether the models run too hot or not.

       Now we can discuss the significance of the models running too hot. I think the models run too hot since they have tuned their feedbacks to radiative forcing during only the warm phase of ocean cycles. (-snip-).

       (-snip-).

       I'll leave the discussion of Figure 1.4, the politics and personalities of global warming to others (for today anyway).

       Moderator Response:

       [DB] Sloganeering snipped.

41721. John Hartz at 11:31 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @Tom Curtis #73:

       Not exactly. I'm trying to draw attention to the fact that manmade climate change is real and is happening now. 

       Unless we have a time machine, we'll never know how well the models perform their primary task, i.e., long-range forecasts say to the year 2100.

       In the meantime, we're wasting valuable time by arguing over minutiae.

41722. Tom Curtis at 11:30 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Further to the discussion above, here are the observed trends from 1990 to current relative to the CMIP 3 (AR4) trends from 1990-2015:

       

       On the left hand side, the number of models in each 0.025 C/decade bin is shown, with values shown being the upper limit of each bin.  It should be noted that observed trends are also assigned to a bin.The trend of the GISS record is 0.152 C/decade, resulting in it being assigned to the 0.15-0.175 bin.  It is not shown as having a 0.17 C per decade trend as might be assumed from casual inspection of the graph.  In a similar manner, the HadCRUT4 and NOAA records are shown in a bin, rather than having trends as low as might be assumed from a casual inspection.

       On the right hand side, the 54 member ensemble mean, maximum, minimum and mean plus or minus two standard deviations with are shown with the actual observed trends.  Observed trends place by hand, so are only approximately accurate.

       The key point for this discussion is that the 2nd order draft version of Fig 1.4 shows the observed data falling below the AR4 envelope, suggesting visually that the trend would fall below the minimum value in the ensemble (green line), whereas in fact they lie well above that value.  That is shown much better in the final draft version of 1.4.

       Obfusticate as much as they like, the deniers cannot alter the fact that the 2nd order draft version of figure 1.4 was a misleading graphic for comparing models and data for AR4, due primarilly to poor baselining.  The final draft version corrects the baseline issues and is far superior.

41723. Tom Curtis at 10:36 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       John Hartz @71, are you trying to draw attention to the fact that the models are underestimating some effects of global warming; and that assessing the validity of the models base on just one number (GMST) rather than on their total output is rather facile?  If so, I agree with you.  Personally I think there is little doubt that the CMIP5 models perform worse than the CMIP3 models with regard to GMST.  It does not follow that the models are worse.  To make that assessment we must consider the whole range of model data.

41724. Tom Curtis at 10:32 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Klapper @70, yes.  The models currently run hotter than observations.  Specifically, taking the trend since 1975, the observations run 16.5% (HadCRUT4, GISS) to 21.5% (NOAA) cool compared to CMIP3, and 27.6% (HadCRUT4, GISS) to 31.9% (NOAA) cool compared to CMIP5.  Alternatively expressed, the observations run 0.64 (HadCRUT4, GISS) to 0.84 (NOAA) standard deviations cool compared to CMIP3, and 1.29 (HadCRUT4, GISS) to 1.49 (NOAA) standard deviations cool compared to CMIP5.

       Do you think these facts falsify the models?  Even though observations are running within 2 Standard Deviations of the ensemble means?

       Alternatively, do you think that if temperatures run 15% cooler than AR4 projections for BAU, that is sufficient lee way to not have to do anything about global warming (the effective current policy setting in most of the world).  That the difference between 3.65 C and 4 C at the end of the century makes all the difference in the world?

       Or more to the point (ie, the actual topic under discussion), do you think the final draft version of figure 1.4 inaccurately represents the relationship of these trends?  Or do you think it is more accurate to show the 1990-2015 trend with observations lying below the model envelope (as shown by Fig 1.4 in the 2nd order draft), even though with the same baseline the observations (and trends) lie well within the two sigma envelope for AR4 (as the final draft shows)? 

41725. Jim Eager at 10:25 AM on 7 October 2013
       2013 SkS Weekly Digest #40
       

       First, the difference between what the models predicted and observed temperatures is not "huge", as observed global mean temperature has been well within the projected range of the model ensembles. Try reading the approriate post: skepticalscience.com/curry-mcintyre-resist-ipcc-model-accuracy.html

       
       Second, that observed global mean temperature has been in the lower portion of the projected range of the model ensembles has been due to natural variability, e.g. 1) a string of neutral or relatively strong la nina years and the total absence of a strong el nino year, and 2) an unusually deep and long solar minimum and unusually weak solar max.

41726. John Hartz at 10:23 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @Klapper #70:

       Is that why the Arctic sea ice is disappearing? Is that why alpine glaciers are melting? Is that why the Greenland ice sheet is loosing mass?

41727. Klapper at 10:03 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @ John Hartz #66:

       Yes, I do have a point to make: the models run too hot.

       Moderator Response:

       [DB] As others have already pointed out to you, the actual evidence is to the contrary.  Thus, you merely express your opinion.  Please characterize it as such in the future.  Or else moderation for sloganeering will ensue.

41728. Tom Curtis at 09:37 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       As a follow on from my post @68, below is the inverted, lagged Southern Oscillation Index (SOI):

       

       For the purposes of the discussion in 68, the important thing is that the El Pinatubo erruption coincided with an El Nino event that was almost as strong as, but more sustained than, that in 1997/98.  The prior, El Chichon erruption also coincided with a strong El Nino event (in fact the strongest on record based on the SOI).  These ENSO events may explain part of the weak response to those volcanoes in the observational record relative to the models.

       In respect to the 1992-2006 trend, it is particularly important to note the relative strength of the 1992-95 El Nino event to the conditions in 2006, which exhibit weakly positive SOI conditions (ie, neutral to a mild La Nina).  Thus, to the extent that the 1992-95 ENSO event is not consistent across all models, we would expect modelled trends over that interval to be significantly greater than observed trends.  On that basis, the CMIP3 ensemble mean shows too little trend over that period, even though it gets the prediction almost perfect.  CMIP5, with a greater apparent divergence is more likely to better model the ENSO neutral (because not consistently timed across all ensemble members) conditions.

       Of course, there is a possibility that the ENSO conditions were induced by the volcanoes; and that this behaviour shows up in the models.  Therefore this analysis should be treated with caution. 

41729. Tom Curtis at 09:10 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Michael Sweet & Albatross, the mean trend for the CMIP5 81 member ensemble from July 1992-June 2007 is 0.413 C per decade (as calculated by me, today from data downloaded from KNMI.  The observed trends lie within 1.1 (HadCRUT4, NOAA) or 0.91 (GISS) standard deviations of that value, but below that value in each case.  In contrast, for the 54 member ensemble of CMIP3 (AR4), the mean trend is 0.297 C per decade over that period, with observations falling within 0.1 standard deviations (HadCRUT4 and NOAA below the ensemble mean, GISS above it).

       This is largely irrelevant to the discussion.  Tamino compared a trend resulting from variability that is modelled to one that is not.  Therefore we expect the former divergence to also show up in the computer models, while the later does not.  It does not alter the fact that we have two significantly different trends from the long term trend as a result of short term variability in the climate system.  It would be inappropriate to use the 1992-2006 interval to suggest warming is much greater than we expect from the long term ensemble mean trend (ie, the one that is actually projected into the future).  Likewise it would be inapproprate to use the later to suggest it will be much less.

       Nor is it particularly illuminating to compare the 1992-2006 observed trend to the modelled trend for that period.  It does illustrate that the computer models over predict global cooling due to volcanoes, but that was something already well known.  To take that fact and try and finesse it into a claim that the models are wrong long term trends is dubious at best.  If, however, Klapper does want to make that argument, he ought to do so explicitly rather than taking short term trends impacted by that known flaw and pretend that they demonstrate some other flaw by the expedient of not mentioning the impact of the known flaw.

41730. Albatross at 09:08 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Klapper,

       You admit then that your posts are essentially off topic, especially those referring to McIntyre's blog posts.  Let us focus on the actual post above.

       1) Do you agree that Curry's claims quoted above were incorrect for the reasons stated?

       2) Do you agree that the initial problem with the draft figure 1.4 for AR5 has now been corrected? 

       3) Do you agree that McIntyre's and Mckitrick's accusations of foul play regarding figure 1.4 are incorrect?

       We'll take it from there.  Right now I have to be somewhere for the evening with friends and family.

41731. John Hartz at 08:56 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Klapper:

       Do you have a point make, or do you just enjoy engaging in a never-ending discourse with people like Rob Honeycutt, Michael Sweet, and others?

41732. Klapper at 08:42 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @ michael sweet #62:

       "...numbers that are wildly different from those posted on scientific blog posts"

       The numbers I've posted are correct. If they are not then will someone here please tell me what the correct ones are. If the CMIP5 model ensemble warming trend between 1990 and 2013 is not 0.29C per decade then what is it?

41733. Klapper at 08:28 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @Albatross #60:

       "...But that rate is for CMIP3 not CMIP5..."

       I checked my work on the CMIP5 SAT warming from 1990 to mid 2013 for the model ensemble for the RPC45 scenario and the rate is 0.29C/decade. The data I downloaded the first pass were the "One run per model tas rpc45". I also checked the "all runs per model tas rpc45" but the number is the same  at 0.29C/decade. Of course 2013 is not done yet and I wanted to compare apples to apples so my comment references the mid year since both CMIP5 and HadCRUT4 are available monthly.
       

       I think CMIP3 is for 4AR not TAR as you suggest. My point in #36 was to check the most recent data (5AR) against what Tamino had done for FAR, SAR and TAR. As for your comment on "...Then one should be using a common baseline.." that is not applicable to the comparison of linear regression trends which only compare the rate of change not the absolute averages.

       Both you and Rob Honeycutt have confused my references to McIntyre's work as something to do with his recent post on the 1990 baseline issue. My references to McIntyre relate to his earlier "2 minutes to midnight" post and the analysis comparing CMIP5 model experiments to the observational trend. If you think there is something wrong with his comparison of 1979 to 2013 trends, models to observations, then what is it?
       

       
       

41734. Rob Honeycutt at 07:35 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Klapper said... "It seems a reasonable approach to comparing the models to observations to me."

       That's because you're looking for a specific conclusion.  Confirmation bias.

41735. michael sweet at 07:28 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Klapper,

       Looking back through this thread I see that you have provided not a single citation or reference, not even to a blog post.  You provide only your unsupported assertions with numbers that are wildly different from those posted on scientific blog posts.  It is impossible for me to continue an argument with you since you refuse to support your data.

       Moderator: I am sorry for the strong language, I was tired of Klapper's unsupported claims.  I will not use such langusge in the future.

       Moderator Response:

       [JH] Thank you.

41736. Albatross at 07:17 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Just a point of clarification.  Of course, my reference to the baseline is with respect to McIntyre's and McKitrick's confusion about the draft figure 1.4 in AR5.

       Hey that reminds me, since you are such a fan of Steve and Ross, maybe you could ask them who leaked the draft report, and if they do who that person was.  Thanks.

41737. Albatross at 07:11 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Klapper @36,

       Following your posts is like playing a game of find the pea under the thimble. Talk about obfuscation ;)

       You agree though that the observations lie within the envelope of possible model outcomes.  Good.  So I'm not sure why you wish to keep arguing moot points.

       That said, there is obviously something wrong with your calculated trend in your post.  The maximum rate of warming for TAR for 1990-2012 comes in at near 0.29C/decade.  But that rate is for CMIP3 not CMIP5.  Anyhow, your rate is clearly way too high.  If one's calculation is an outlier it is time to consider that your result is the one that is most likely in error.  You also say you have calculated the rate through 2013, a little odd given that the year is not done yet ;)

       Regardless, you and McIntyre are not evaluating the model output correctly.  First, and foremost you should be only comparing those gridpoints at which one has both observations and model output. Then one should be using a common baseline; a term and concept that McIntyre does not appear to understand except when attack scientists Marcott et al., ironically the choice of baseline period was then central to his whole uncertainty argument ;)  Also, ideally you evaluate the models when they have been driven using the best estimates of the observed forcings.

       Last, but not least, the ensemble mean model estimate can be misleading and is not necessarily the best metric to use for evaluating the models.

       Oh well, at least while Steve McIntyre is very busy trying to figure out what a baseline is (allegedly) he is not attacking, smearing and stalking climate scientists :) Small blessings.

41738. Klapper at 06:34 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @ Rob Honeycutt #57:

       My references to the trends calculated by McIntyre are from his "2 Minutes to Midnight" post, not the one on Figure 1.4. He calculates the SAT warming trend for multiple runs of different CMIP5 models and then all 109 runs and compares them against the actual warming trend in a "box and whiskers" plot. It seems a reasonable approach to comparing the models to observations to me.

41739. Klapper at 06:30 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @ Rob Painting #55:

       We are not comparing observation trends vs. model trends since 2000 are we? The data since 2000 are only relevent to longer trends starting in 1979 or 1990 if they represent a longer term secular trend in the impact of aerosols. We know from the Solomon et al 2011 paper the impact might be -0.1W/m2. That's not significant for the longer term trends that McIntyre compared where the CO2 forcing was 8 times that magnitude.

       If you can make a point there is a long term trend in the background of the impact of aerosols, that the models don't capture, then put if forward. If the background aerosols in the '80s were no different than the last decade, then the net impact on an observations trend spanning the last 30 years is probably nil.

41740. Rob Honeycutt at 05:30 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Klapper...  The difference here is that McIntyre/Tisdale are doing a lot of hand waving and Tamino is actually testing the claims with analysis.  

       The point is quite clear that 1990 is an anomolous warm year in the trend.  Anyone honestly interpreting the data would look at that simple explanation and conclude that it would be better to use a longer term baseline.

       It's just fascinating to me how people like McIntyre and Tisdale will scream at the top of their blogger lungs about tiny nuances in climate science they find objectionable, but they completely ignore when someone shows them missing such simple points.

41741. Klapper at 04:44 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @ michael sweet #54

       None of the graphs in the OP are peer-reviewed. Tamino is cited in this blog and comments and none of that analysis is peer-reviewed. The CMIP5 data methods/review are in fact not peer-reviewed although they form the basis for much comment and many graphs in the AR5 IPCC report.

       The surface warming rate of 0.43C/decade from 1992 to 2006 is correct for the CMIP5 ensemble of experiments from different models for the RCP4.5 scenario. These data are freely available at the KNMI data explorer website. I'll withdraw the number if you can tell me the correct one.

41742. Rob Painting at 04:30 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Klapper - you misunderstand, this is not a matter of belief, that is simply what the evidence is - stratospheric aerosols blocked more sunlight from reaching the Earth in recent times. Neely et al (2013) show that since the year 2000 these sunlight-blocking sulfate particles have offset some 25% of the effect of the extra greenhouse gases. In their study abstract they write:

       "Observations suggest that the optical depth of the stratospheric aerosol layer between 20 and 30 km has increased 4–10% per year since 2000, which is significant for Earth's climate. Contributions to this increase both from moderate volcanic eruptions and from enhanced coal burning in Asia have been suggested. Current observations are insufficient to attribute the contribution of the different sources. Here we use a global climate model coupled to an aerosol microphysical model to partition the contribution of each. We employ model runs that include the increases in anthropogenic sulfur dioxide (SO2) over Asia and the moderate volcanic explosive injections of SO2 observed from 2000 to 2010. Comparison of the model results to observations reveals that moderate volcanic eruptions, rather than anthropogenic influences, are the primary source of the observed increases in stratospheric aerosol."

       Rather than rely on some climate science contrarian blogger, as you do, do you have any peer-reviewed literature to support your claims? As you know anyone can write anything they like on the internet, but we here at SkS rely upon the work of actual experts in the field of climate science whose ideas and research is subject to the scrutiny of other experts. That would be the peer reviewed literature.    

41743. shoyemore at 04:02 AM on 7 October 2013
       2013 SkS Weekly News Roundup #40B
       

       Incidentally, the report of the Irish Met Office (Met Eireann)  Ireland in a Warmer World can be found here:

       Ireland in a Warmer World

41744. shoyemore at 03:56 AM on 7 October 2013
       2013 SkS Weekly News Roundup #40B
       

       chriskoz #1

       Commiserations ... in the Proportional Representation system (auch as we have in Ireland), voters express preferences in descending order. If no candidate (for 1 seat, say) gets more than 50% first preferences, then the candidate with the lowest number of first preferences is eliminated, and his/ her 2nd preferences is divided among the others. And so on, until there is only one candidate left with a clear margin of victory.

       It is a bit more complicated with n seats per constituency - a "quota" is calculated by the Total Valid Poll divided by (n+1), and votes are counted and candidates eliminated until there are n candidates left standing. PR is much beloved by math anoraks because of its complexity - the purpose is supposed to ensure that the total number of seats held by a party is proportional to the number of votes it received. A first-past-the-post system can skew results.

       It is popular in continental Europe, where it ensures small parties at least some representation. At its best it opens the political system to minority views, at its worst it leads to factionalism and paralysis.

       For example, the German PR system ensured the Greens would sit in parliament while the anti-renewable energy Free Democrats would not. Here in Ireland we had a small group of Greens in government up to 2011 thanks to PR - but they all lost their seats (due to the country's fiscal crisis, for which they were not to blame - just caught in the crossifre). However, at least some should  re-gain seats at the next election.

       Sometimes PR can work for you, sometimes against. Best roll with the punches.

41745. michael sweet at 01:53 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Tamino got a high warming when he cherry picked the start date.  Deniers currently pick the strongest El Nino of the 20th century as their start date, obviously as much a cherry pick as Tamino's.  It is up to you to provide data to support your cherry pick.

       Please provide a citation to your bullshit number of 0.43C/decade.  Your claim of 30 years of errors that I previously cited is also bullshit.  Provide a peer reviewed reference to this wild claim or withdraw it.  Provide a link to McIntyres peer reviewed analysis.  The OP shows using  peer reviewed data that the IPCC has been accurate, you must provide links that support your wild claims in the face of this peer reviewed data.

       When you make claims that are directly contradicted by the peer reviewed data in the OP and you provide no citations you are comparing your unsupported opinion against peer reviewed data.  That has no place in a scientific discussion.  Although the denier blogs encourage unsupported argumentation, this is a scientific blog.  You must provide links to peer reviewed data or you are dealing in bullshit.  If you link to a non-peer reviewed blog it will carry no weight in a scientific argument.

       Moderator Response:

       [JlH] Please cease and desist from using the word, "bullshit" in future posts. It is inflamatory and uncivil to do so.

       This is warning #2. 

41746. MA Rodger at 00:23 AM on 7 October 2013
       Residence Time and Prof Essenhigh
       

       Leto @21.

       That's a lot of question you present in 21 ranging from the basic to the quite technical. I will not address most of it.

       CO2 is being absorbed by the oceans and the biosphere. For a long time that was but an inference based on ocean & atmosphere measurement & data for fossil fuel use. The biosphere absorption was not measured and assumed to be the sole missing CO2 sink. However, I hear the biosphere can now be assessed (estimated) as a sink.

       These two sinks were always predicted although it took some time to fully understand why oceans didn't absorb much more CO2 than they actually did. The oceans can now be modeled with some confidence as a CO2 sink (See the Archer link @15 or AR4 for instance.) The net effect of the biosphere is not something that can be predicted so easily. Plants will absorb more CO2 at higher levels up to a point but such absorption depends on the type of plant involved and relies on climate providing the environment to maintain such growth. This reliance on climate extends to carbon within soils which can also become a significant source/sink with changes in rainfall or temperature (eg the permafrost melting). Thus predicting future biosphere absorption is only for the brave.

       The amount of our emission that are presently absorbed is about 43% if changing land use is accounted for. This value waggles about with ENSO but has remained reasonably constant over the last half century. The value is simply the result of the rate of increase of our emissions. So far there is no obvious indication of changes in absorption in oceans or  biosphere. Although saying that, the last 18 months has seen inceases in atmospheric CO2 higher than I would have expected during ENSO-neutral periods. Is it a marker of things to come? We will have to wait and see.

41747. Klapper at 00:06 AM on 7 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       @ michael sweet #50

       I'm not sure which Tamino graph you are referring to but the second Tamino graph does not compare observations to the models, which is the point of discussion here. The second Tamino graph compares one observation trend vs a second observation trend.

       Taminos choice of a random trend starting in 1992 and going to 2006 (the red trend line) is a very poor one if you want to demonstrate the validity of the model predictions against the observations. His intent was to show a "hot" trend in the observations, hence he started the trend in the Pinatubo global temperature slump.

       So he got a very warm 15 year trend in the GISS dataset, 0.29C/decade to be exact. However the SAT trend in the latest model experiments, the CMIP5 ensemble, is even warmer, substantially so at 0.43C/decade over the same period. I think the reason for the extreme warming trend in the models 1992 to 2006 is mostly that they overcool in the episodes of major vulcanism, and in this particular interval, starting as it does in one, the temperatures at the start of the model run are too low accentuating the warming rate.

       As for your claim that my numbers are "bullshit", be specific as to which of them are wrong. McIntyres choice of a trend period 1979 to 2013 to compare model trends vs observations should be above reproach since the period is 34 years, above the defined 30 year length needed to capture the climate signal. My analysis of the 1990 to 2013 period using CMIP5 (5AR) was just to compare to the above FAR, SAR, TAR graph of 1990 to now.

41748. Klapper at 23:20 PM on 6 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Rob Painting @#50

       McIntyre analyzed trends in the models from 1979 to 2013, a period over which the theoretcial forcing from increasing CO2 is about 0.8Wm2. If you believe stratospheric aerosols have played a role in suppressing warming in the observations, then ask yourself: What is the secular trend in aerosols over that period? (if any). Looking at Solomon et al 2011's Mauna Loa charts there is no secular trend in background transmission values from the late 70's to now. If there is no secular trend in background stratospheric aerosols over the analysis comparison period, then that can't be the reason for the difference between models and observations, no matter how strong the effect of aerosols.

       The other point is that the observations are less responsive than the models to stratospheric aerosols if we compare the response of the observations to El Chichon and Pinatubo to the models, global SAT-wise. So not only is there no secular trend in background stratospheric aerosols, but they don't seem to have any more leverage over SAT in the real world than the model world.

41749. Leto at 22:28 PM on 6 October 2013
       Residence Time and Prof Essenhigh
       

       Could someone please explain what is known about the dependence of the fluxes upon the amount of CO2 in each compartment of the system? That is, which fluxes are proportional to the concentration of CO2, which fluxes have a rate-limiting bottle-neck that is indifferent to the concentration, which have a combination of these (saturable kinetics), and so on? How would the magnitudes of the fluxes change, for instance, if atmospheric CO2 was 200 ppm (or 600 ppm) instead of 400 ppm?

       The mass-balance argument suggests that nature has obligingly absorbed some of our excess CO2, with natural processes acting as a net sink, but is this something that could have been predicted from first principles, or is it simply an observation after the fact? To me, it suggests that sink fluxes are more active when there is more CO2 around, which is what I would have expected intuitively, but what does the evidence suggest?

       Note that I'm not talking about potential positive feedbacks from permafrost melting, and so on, just the main fluxes at work now.

       Thanks in advance for any clarification.

41750. michael sweet at 21:51 PM on 6 October 2013
       Why Curry, McIntyre, and Co. are Still Wrong about IPCC Climate Model Accuracy
       

       Klapper:

       In post 45 you say:

       "I don't think a negative forcing of 0.1W/m2 over 4 or so years at the end of an analysis period is enough to explain the large errors in the model trends over the last 20 to 30 years compared to observations."

       The Tamino graph in the opening post shows that in 2007 the models were statistically much too low.  Did you complain then that the models should be raised to compensate for their low errors?  Scientists at the time said that it was probably due to natural variation.  More data has shown this to be the most likely explaination.  What is your response to the extreme warming from 1992-2006???  Your claim of 20-30 years is bullshit and should be withdrawn.  Over the past 20-30 years the models have been accurate.  Read the opening post so that you stop making such wild, demonstratably inaccurate claims.

       Moderator Response:

       [JH] Please cease and desist from using the word, "bullshit" in future posts. It is inflamatory and uncivil to do so. 

       This is warning #1.

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