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Jim Hunt at 22:23 PM on 23 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Barry - Over the years a variety of different algorithms (not just bootstrap) have been applied to data from a variety of different satellites. By way of example see:
https://climatedataguide.ucar.edu/climate-data/sea-ice-concentration-data-overview-comparison-table-and-graphs
I don't recall a similar debate over an Arctic sea ice "step change", but changes have certainly happened from time to time. See for example "old" DMI versus "new" DMI extent. -
Ashton at 22:22 PM on 23 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
It was in the piece from Tamino for which I gave the URL in 7 above. It is http://tinyurl.com/qxt7jts. I checked the abstract at Cryosphere (http://www.the-cryosphere.net/8/1289/2014/tc-8-1289-2014.html) and agree with you. As the paper critiqued by Tamino was a pre-release obviously the final words were thought not appropriate. Also I note that the words "raise the possibility that this expansion may be a spurious artifact of an error in the satellite observations" are modified to read "much of this expansion". I should have but didn't, check the final version and apologise for that. However the conclusion from Tamino is that the "increase in Antarctic sea ice cover is robust"
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Rob Painting at 21:46 PM on 23 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Ashton - where does your quoted text come from? The last part of the sentence, after the comma, doesn't appear in the abstract.
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CBDunkerson at 21:35 PM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ wrote: "The authors took an ensemble of 38 models, and selected a narrow subset (~4) for analysis, excluding the other models."
Russ, you do get that people are objecting because this is straight up false, right? You keep plowing ahead as if you've got great points, and you would... if the basic foundations of your arguments weren't fictional.
You might as well be arguing that 'the Risbey paper is bad because it advocates killing puppies'. I understand your outrage at the heinous things you imagine them to have done... but given that these offenses exist in your own mind, its an exercise in self-delusion which is painful to watch. Either the Risbey paper picked ~4 climate models out of 38 or it didn't. Until you can connect with reality enough to see the truth on that point (and various others) you are arguing from a set of 'facts' different from the rest of us, and thus naturally reaching different conclusions.
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Ashton at 20:04 PM on 23 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Rob Painting @8 The authors wrote this in their Abstract:
“The results of this analysis raise the possibility that this expansion may be a spurious artifact of an error in the satellite observations, and that the actual Antarctic sea ice cover may not be expanding at all".
Agreed they don't say categorically Antarctic sea ice hasn't expanded but they certainly intimate it may well not have done.
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Charlie A at 20:02 PM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
The second area of confusion is related to what is the expected performance of the models not in phase with actual real-world Enso.
While the 15 years period 1998-2012has had more La Nina years than El Nino, the ratio hasn't been spectacularly, abnormally lopsided compared to past history. See NOAA ONI table. So, if the random Enso phases of the model runsis the cause of mismatch in GMST trends between models and observations over the last 15 years, then quite a few model runs should have 15 year trends that lie above observations. Correct?
To put it another way, if the only model problem is phasing of Enso, and the current 15 year GMST trends are below all model runs (or perhaps only below 97.5% of all model runs). then I would expect that either 1) that La Nina in the real world over the last 15 years is at or above the 97 percentile point, or 2) that the distribution of Enso in the entire CMIP5 ensemble of model runs is overwhelmingly biased towards El Nino.
#1 is not true. I have not inspected the model oututs, but I doubt that #2 is true.
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Charlie A at 19:49 PM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
I'll list a few of the key points this blog post made, and then explain more clearly my concern. Please tell me if you disagree with any of these statements made in the blog post
1. " ...because over the long-term, temperature influences from El Niño and La Niña events cancel each other out. However, when we examine how climate model projections have performed over the past 15 years or so, those natural cycles make a big difference."
2. "They looked at each 15-year period since the 1950s, and compared how accurately each model simulation had represented El Niño and La Niña conditions during those 15 years, using the trends in what's known as the Niño3.4 index."
3. "Each individual climate model run has a random representation of these natural ocean cycles, so for every 15-year period, some of those simulations will have accurately represented the actual El Niño conditions just by chance."
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Everything sounds fine to me up to this point. For each 15 year period, the authors of the paper select that subset of model runs where trends in the Enso 3.4 region best match observations. If they pick the models where enso 3.4 trend best matches observations, I would expect a good match in that area, as shown in fig 5 cell a. However, the authors make a more general claim. They claim the selected "climate models have provided good estimates of 15-year trends, including for recent periods and for Pacific spatial trend patterns."
Surely, the authors and the people posting here at SkS mean some other Pacific spatial trend pattern other other than the Enso 3.4 trend for which those specific models were selected.
Correct?
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Jim Hunt at 19:32 PM on 23 July 2014Is global warming causing extreme weather via jet stream waves?
@Edward - My apologies for my belated response, but given the UK context you may also wish to take a look at another paper by James Screen, which I discuss on my own blog:
Does the Arctic Sea Ice Influence Weather in the South West?
@Ashton - I arrive here fresh from the Arctic Sea Ice Blog, where one of my comments precedes your own! I note you have yet to reply to Neven's comment in response to the question you posed over there. Are you now content that the "remark" you highlight above is not in fact "extraordinary" at all?
@scaddenp - Neven's link doesn't actually cover "all" observations of the Arctic. Particularly if you're interested in Arctic sea ice thickness and/or volume you may wish to also take a look at this collection of my own devising: -
Rob Painting at 18:58 PM on 23 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Ashton - The paper indicates that the magnitude of the increase may be exaggerated, not that Antarctic sea ice hasn't increased.
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Ashton at 17:26 PM on 23 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
John Hartz Looking at the figure in the article you have mentioned the step change is about 200,000 sqare kilometers. Tamino at Open MInd has critiqued the paper to which you refer and concludes that the increase in Antarctic sea ice is statistically significant (http://tinyurl.com/qxt7jts)
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scaddenp at 14:40 PM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Charlie A, actually thinking about this more, would it be fair to characterize your position as believing that models are hopelessly wrong (despite the results of this paper) for reasons that have nothing to do with ENSO and that positive ENSO conditions will still result in observed temperatures running below ensemble mean?
If I have got this wrong, then can please state more clearly what your position is, especially in light of this paper?
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Tom Dayton at 11:44 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ, scaddenp has provided yet another way of phrasing the purpose of the study. It was entirely possible that the model runs best at matching the ENSO index stubbornly would have been nearly as poor at projecting global surface temperature as were the model runs worst at matching the ENSO index. The conclusion would have been that failure to project ENSO timing was not really a major reason for the models' poor projections in 15-year timescales.
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Rob Honeycutt at 11:00 AM on 23 July 2014Deep Decarbonization Pathways Project (DDPP) Presents Interim Report to UN Secretary-General Ban Ki-Moon
Larry, and the trick there is just getting it started in the first place, even at a low level. As I mentioned some number of comments back, I don't think it will take much of a tax to have a fairly significant effect. Then, once it's in place and people see the benefits, it becomes far easier to raise the per ton rate.
The biggest challenge is merely the fact that the FF industry knows they are the ultimate losers in this game. There is no scenario where they come out okay, AFAIK. That means they're going to continue to fight this as long as they can.
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Larry E at 10:37 AM on 23 July 2014Deep Decarbonization Pathways Project (DDPP) Presents Interim Report to UN Secretary-General Ban Ki-Moon
Rob, I'm sure it's the best bet. The trick is to make it stiff enough to get the job done.
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barry1487 at 10:37 AM on 23 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
I wonder if the supposed step-change applies to Arctic sea ice data also.
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scaddenp at 09:46 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Charlie A
"This sounds dangerously close "it's the sun" Most Used Climate Myth (upper left sidebar)"
This sounds more like you have completely misunderstood. Would that be deliberate? "its the sun" tries to explain observed warming by changes in the sun. Tom's argument is explaining why models (which have to guess actual forcing) get it wrong if the actual forcing is different. Happens both ways.
The subject of this thread is a paper looking at why observed is low compared to ensemble mean. That they are low is acknowledged in opening of the paper. Does the data support the hypothesis that this is due to state of ENSO? They contend yes and present data to support that.
This has important implications. If the paper is correct, then trends will rapidly increase when ENSO moves positive. Agreed? Or perhaps Charlie you think ENSO is going to stay negative forever?
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Rob Honeycutt at 09:37 AM on 23 July 2014Deep Decarbonization Pathways Project (DDPP) Presents Interim Report to UN Secretary-General Ban Ki-Moon
Larry... Honestly, the one and only way any movement is going to happen is to get a carbon tax implemented. That is the only politically viable solution.
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Larry E at 08:21 AM on 23 July 2014Deep Decarbonization Pathways Project (DDPP) Presents Interim Report to UN Secretary-General Ban Ki-Moon
GHGeous, we are certainly in agreement then on a central point: "I hope I have made it clear ... that IMO we face a much more severe emissions threat than the experts have (to my knowledge) identified ..."
And that, too, is what Anderson is saying (even if his explanation for why his conclusion differs from those of other experts doesn't resonate with you).
Your "Pareto Secret Corollary" seems to be a different fish than Pareto's principle (which is merely a rough first guess, even if apparently accurate in some instances). My belief is that changing the consumption patterns (directly or indirectly) of your 5% of the global population (or Anderson's 1%) is an insufficient incremental target, given the amount of climate change to date, the growing impacts, and that climate scientists are regularly surprised that things are worse than they expected. 5% is only 350 million people, or less than 1/3 of the 1.2 billion population of OECD countries where unsustainable consumption and emissions are ubiquitous. As well, affluent individuals in the developing world are part of the problem as well.
We are down to the move of the last moment, in my view, and focusing on just 5% of us leaves off the hook far too much of the world population that needs to be part of the solution. I believe we need deep change in the very short term, across the affluent section of the world population. Time is scant for addressing the 5%, then the next 5-10%, etc.
How to instill deep, short-term change? That is the dilemma. We should call ourselves Homo lemmingiens, since we seeingly can't break the bonds of our hardwired behaviour despite a recognizable existential crisis. I see society's inabiltiy to consider sacrificing leisure air travel (in degree if not totality) as one strong indicator of this.
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Charlie A at 06:44 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
@Tom Curtis #19 "...the models only use historical Total Solar Irradiance (TSI) up to 2008, and then repeat solar cycle 23 (April 1996 to June 2008) thereafter. ......This will lead to their warming trends being overestimated by some small amount. "
This sounds dangerously close "it's the sun" Most Used Climate Myth (upper left sidebar).
Figure 2 of this paper show the "small amount" by which forecasted trends have diverged from reality in the sort period of true forecast vs. hindcast. Look closely at the trends from recent observations vs the models. Note it is nearly outside the 2.5 percentile line.
Moderator Response:[PS] This is starting to drift well away from discussing the paper that is the subject of this thread. For general discussions of modelling skill, please put any responses in the "Models are unreliable" thread
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Charlie A at 06:33 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
@Russ R #1 "..hich parts of planet would you say that the models "accurately predicted"?" and
Russ R #26: " I'd like to know which spatial trend pattern estimates from their selected models were even "good"? "
Obviously, the 4 selected model runs are good in the Enso 3.4 area. The area for which they were selected as being good. Texas sharpshooting at its best.
These are the same models that will be the source for downscaling runs to create the regional predictions that are so popular in the adaptation community, so the poor performance of regional trends outside of the Enso 3.4 area gives and indication of the usefulness of such downscaling.
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scaddenp at 06:24 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ, this is verging on sloganeering and repetition. You have had it explained to you but at this stage it looks like willful failure to understand.
If you think they what they did was a cherry-pick, will you please explain to us what you think is the appropriate way to test their hypotheses (not yours) in a way that could use the full data set? I would perhaps suggest to the moderators that Russ's posts be deleted if wont either answer the question or withdraw the accusation.
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Tom Dayton at 05:05 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ: An obviously decent metric of how well the models projected the Pacific spatial trend patterns is the difference in match to observations, of the model runs that worst matched the ENSO index versus the runs that best matched. You can see that in HotWhopper's post by scrolling down to the images that contain the Risbey et al. Figure 5 images.
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Rob Honeycutt at 04:50 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ... The whole concept was Lew's idea. Did he perform the modeling tests? Probably not. That was left for the researchers who had specific skills in that area.
Read again, Russ: "...natural variability (represented by El Niño/Southern Oscillation) largely in phase with observations..."
Again, your expectation of what models do is absurd. The authors were trying to get the best in-phase runs for a specific region in the eastern Pacific. That's all they're doing. They looked at the 35 runs and selected the ones that were largely in phase with observed ENSO cycles.
How hard is this to comprehend? Really?
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John Hartz at 04:06 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
In her Carbon Brief blog post, Slow surface warming since 1998 is “not exceptional”, say scientists, Roz Pidcock discusses the findings of Well-estimated global surface warming in climate projections selected for ENSO phase, Risbey et al in conjunction with the findings of a second paper, Changes in global net radiative imbalance 1985-2012, Richard P. Allan et al.
Pidcock's post nicely supplements Dana's OP.
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Russ R. at 04:04 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Rob Honeycutt,
"I believe you are grossly underestimating the expertise of the researchers and reviewers involved in this paper"
Really? What exactly is Lewandowsky's "expertise" in climate modeling? Is "zero" a gross underestimate?
"You're making an absurd insinuation that a small subset of model runs is going to predict exact regional temperature anomalies."
That's funny... the authors themselves wrote: "We present a more appropriate test of models where only those models with natural variability (represented by El Niño/Southern Oscillation) largely in phase with observations are selected from multi-model ensembles for comparison with observations. These tests show that climate models have provided good estimates of 15-year trends, including for recent periods and for Pacific spatial trend patterns."
Nobody's asking for "exact" anything. I'd like to know which spatial trend pattern estimates from their selected models were even "good"? A correct average doesn't mean much if every underlying region is wrong.
If you spend a night at the roulette table, and you get every single bet wrong, can you still claim to possess predictive skill because the average value of your picks was close to the table's average result?
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keithpickering at 03:29 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Dana,
Thanks for this, which shows again that successful ENSO prediction may be the missing key to short-term climate modelling.
In that regard, allow me to draw your attention to a series of remarkable posts at ContextEarth, where our intrepid blogger has managed to successfully retrodict ENSO for multiple centuries into the past with surprising fidelity. The trick is to use Matheiu functions (which are similar to trig functions in the elliptical co-ordinate system) rather than sine waves. This models the sloshing of water in the Pacific basin, and is tied to at least one lunar cycle.
Rules prohibit me from posting links, but Google should find it. C.E. remains anonymous for now, but he or she is apparently aiming for publication. So keep your eyes open.
Keith
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keithpickering at 03:02 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ,
It appears to me that you have read everything not behind a paywall, and then didn't understand what you read.
The authors selected CMIP5 models on their ability to replicate the Nino3.4 index. That index is based on the sea surface temperature between 170W and 120W, 5N and 5S. Data shows cooling in that region during 1998-2012, and the 5 best models also show cooling in that region during the same period. Panel b of figure 5, which you omitted because WUWT omitted it (and because apparently you can't be bothered to spend $5 to read the article you criticize) shows that the 5 worst models show warming in that region during the same period.
When the stated aim of the paper is to determine whether there is really something wrong with GCMs or not, comparing a "best" subset to a "worst" subset is not only appropriate, it is often enlightening.
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Tom Dayton at 02:20 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ, your "cherry picking" complaint is groundless. The researchers' goal was to identify a source of model inaccuracy at a 15 year timescale. The researchers did not conclude that those particular models are better than other models at projecting global temperature. As Rob pointed out, the researchers selected only particular runs. The models used for those runs did not accurately predict ENSO events in other runs, nor will those models accurately predict ENSO events in future runs. The researchers did not claim that climate models are better than previously thought. They "merely" identified a still-unsurmounted barrier to models projecting well at short timescales.
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greenhousegaseous at 02:19 AM on 23 July 2014Deep Decarbonization Pathways Project (DDPP) Presents Interim Report to UN Secretary-General Ban Ki-Moon
LarryE, the DDPP is an attempt to move the discussion closer to the plan and implementation debate, so I commented in this thread.
I hope I have made it clear in my wordy comments above that IMO we face a much more severe emissions threat than the experts have (to my knowledge) identified, and that we need to focus our mitigatory planning and action steps on the 5% who are the source of about 95% of the emissions: the Pareto Secret Corollary, better known in my office as the old 95/5 Rule.
And I hope it is clear that IMO we need to have a functioning economy that, far from being paralyzed by our radical decarbonizing program, is restructured and energized by it.
As for Prof Anderson, I find discussions about the 2% or 4% ceiling or any carbon budget to be diversionary, divisive, and unlikely to help. These discussions are not about the science, but first, the economics of coping with the conclusions of the science, then second, about the politics of implementation.
I have addressed Prof Anderson’s presentation, but not in detail. I have no interest in critiqueing his presentation, since I reached a similar conclusion to Anderson’s central idea about two dozen years ago: a very small percentage of the human population has placed all of us in serious jeopardy - - and are unlikely to do anything to rectify their consumption behavior.
I cannot comment on Anderson’s target of eliminating emissions radically, since he has offered no plan to analyze. Targets are easy to run up the pole, and easy to snipe at; I have no time for either.
It may grab our attention to talk about cutting emissions in the gluttonous countries by 10% a year, but that is meaningless without explaining how, or, more to the point, how to instantly build the necessary political consensus to do so in the face of every established power-elite on the planet.
Rather than find technical (economic and engineering in my case)fault with others’ analysis or proposals, I have been working since the Gore fiasco on finding a more effective way to communicate with a much wider audience than the scientists have managed to reach.
Only quite recently has technology made it possible to reach an audience of millions very fast, *assuming the messaging is effective.* And ours, to be blunt, has not been. My guess is that, so far, all of us on the realistic side of history are reaching perhaps 3 million, half of whom are in countries that will essentially play no part in dealing with the problems.
We must engage and mobilize at least 3 *hundred* million voters and near-future voters to have any chance of survival.
Hence, my concern is not promoting my own hypothesis about the energy-addicted Ape, but in getting the bigger message to all of those folks, in words and numbers and graphics the ordinary voters in the industrial democracies can “get” - - meaning in small doses and across all messaging platforms. Oh, and with a bit of humor, same as John Cook is doing here, now.
So, Larry E, with all due respect, readers here may judge for themselves if I have addressed the entire problem, beginning later this year with the initial free educational tool, and then the initial volume on the carbon “problem”. As of now, there will be 5 or 6 follow-on volumes, each focusing on a tight family of topics and issues, and all timed to synch in with the UN meetings re: the Kyoto Protocol replacement treaty.
I think you may find if you care to that, ultimately, I will in fact address all aspects of “the problem”, in time. Including all those billions of humans Prof Anderson blithely excludes from his discussion. :-)
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Rob Honeycutt at 01:47 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ... I believe you are grossly underestimating the expertise of the researchers and reviewers involved in this paper, while over inflating your (and Tisdale's) capacity to comprehend the methods being used.
First off, these were model runs rather than different models. And the paper explains exactly why they were selecting specific runs. They were choosing runs that were phased with the ENSO cycles. That doesn't make it cherry picking (the suggestion being an act of grasping for straws on your part). They selected those model runs as a new and unique way of testing the models.
In case you don't understand, and as I've stated before, climate modelers do not expect for their models to phase with ENSO because it's not possible. Over time the ENSO phases all balance out, so what matters is the results over longer periods of time.
Risbey et al were merely saying, "What if we select the in-phase runs and use that to test the predicability of the models." They could have turned up something far more interesting in their results, like identifying some aspect of the models that had been previously overlooked. But, what they found was the models actually do a pretty good job.
Your complaints about fig 5 (a) and (b) (c) are completely meaningless. It's more grasping at straws. Somehow those two figures don't look enough alike to satisfy you (and Tisdale). Well then quantify it. Roll up your sleeves and do some real science. If you think that somehow that difference is something significant that was missed by all six of the authors and the list of expert reviewers, then you have a big job ahead of you explaining, in detail, with real numbers, what the difference actually are and why they are meaningful.
As for your "original question," it's not even rational. You're making an absurd insinuation that a small subset of model runs is going to predict exact regional temperature anomalies. Your question is a straw man in and of itself.
The pompacity of your position borders on the ridiculous.
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Leland Palmer at 01:25 AM on 23 July 2014Toward Improved Discussions of Methane & Climate
I do hope that Skeptical Science will revisit this issue. Flood basalt erruptions and release of methane from the methane hydrates seems to be intimately connected, according to the carbon isotope excursions that coincide with a long list of extinction events. This list of flood basalt erruptions, many with coincident carbon isotope excursions corresponding to trillions of tons of methane hydrate dissociation, is from the authors' reply to a more recent article Rapid climate change more deadly in Earth's past than asteroid impacts, study shows. Note that ma= millions of years ago.
Yes we see a pattern of such events. Here's a list grabbed from a couple of papers - note that the dating of some of the events is better than others. The coincidence of LIP and Mass Extinction/Climate event is strongest where the latest high-precision dating has been applied (Permian, Triassic, Mid-Cambrian).
LIP event /extinction or climate event:
Columba River 17ma (Mid Miocene Climate Optimum)
Yemen/Afar 31ma (none?)
North Atlantic 62/56ma ?PETM/Hyperthermals?
Deccan Traps 66ma (Cretaceous extinction precursor)
Sierra Leone 70ma (?)
Caribbean 90ma (Cenomanian/Turonian Anoxic Event);
Madagascar 90Ma (ditto)
Hess Rise 100ma (?)
SE Africa/Maud/Georgia 100ma (?)
Kerguelen 120ma (?Aptian)
Ontong Java 122ma (Aptian Anoxic Event);
High Arctic LIP 130ma
Parana-Etendeka 132ma
Shatsky Rise 145ma
Karoo-Ferrar-Dronning Maud Land 183ma (Toarcian OAE)
Central Atlantic 201 (Triassic Mass Extinction)
Angayucham 210ma (?)
Siberian Traps 252ma (Permian Mass Extinction)
Emeishan traps 260ma (end Guadaloupian extinction)
Tarim 280ma (none?)
Skagerrak- Barguzin–Vitim - Carboniferous Rainforest Collapse (Moscovian and Kasimovian stages);
Viluy - End Tournasian;
Pripyat–Dniepr–Donets - End Famennian–end Frasnian;
Kola/Kontogero - End Frasnian;
Altay–Sayan - End Silurian (?);
Ogcheon S Korea - End Ordovician?;
Central Asian intraplate magmatism - End Late Cambrian;
Kalkarindji - End Early Cambrian;
Volyn - End Ediacaran; -
Russ R. at 01:12 AM on 23 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Let me make a couple of my points "crystal clear".
- Cherry picking. The authors took an ensemble of 38 models, and selected a narrow subset (~4) for analysis, excluding the other models. Anytime someone wilfully excludes data, it ought to immediate raise a yellow flag. What selection criteria did they use for inclusion? Ex-post Nino 3.4 index data, which is itself positively correlated with the surface temperature data and predictions they're evaluating. I'd call that retrospective or hindsight selection bias (a.k.a. cherry picking). That's a red flag. Worse than that, instead of just picking the best four models and running them over the entire time span, they used a different selection of models for every single 15 year period. They've advanced the art of cherry-picking to a whole new level.
- Predictive Skill. Leaving aside the first issue, Figure 5 accidently shoots a gaping hole in the authors' conclusion. They claim that the "4 best" models (i.e. those which were selected as being "in-phase" with ENSO over the 15 year period from 1998-2012) accurately predicted warming. Which is true on average but they make an even bolder claim in the abstract... that "climate models have provided good estimates of 15-year trends, including for recent periods and for Pacific spatial trend patterns." . CMIP5 models have spatial resolution of 1-2 degrees, and Figure 5 shows the SST spatial trends of the "best", "in-phase" models predictions against observation. And in virtually every region, Pacific included, the trend predictions are not just wrong in magnitude... they're totally backwards. Clearly this was not what the authors intended to show in Figure 5... they meant to show the difference between the "best" and "worst" models as the basis for their selection, but since they presented predictions and observations, comparing their "best" models to reality is a perfectly legitimate comparison (In fact, what would be the point of comparing the "worst" models to reality?).
So, back to my original question... in what region of the world did these best 4 "in-phase" models show any predictive skill over the 1998-2012 time period that the authors presented?
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John Hartz at 00:48 AM on 23 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Hold the press!
"New research suggests that Antarctic sea ice may not be expanding as fast as previously thought. A team of scientists say much of the increase measured for Southern Hemisphere sea ice could be due to a processing error in the satellite data. The findings are published today in The Cryosphere, a journal of the European Geosciences Union (EGU)."
Read more at: http://phys.org/news/2014-07-antarctic-sea-ice-expansion-overestimated.html#jCp
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edward hurst at 20:56 PM on 22 July 2014Is global warming causing extreme weather via jet stream waves?
Thank you all for your useful comments.
Regards,
Edward Hurst
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Leto at 18:48 PM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
This is the study I had in mind here.
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Larry E at 17:50 PM on 22 July 2014Deep Decarbonization Pathways Project (DDPP) Presents Interim Report to UN Secretary-General Ban Ki-Moon
GHGeous, it seems plain that you don't care to address the magnitude of the problem (ergo the magnitude of the necessary remedy) or what the man acutally said.
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Tom Curtis at 14:15 PM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Charlie A @17, there are a number of reasons for differences between the models projections and the observed values. One such reason, for example, is the fact that the models only use historical Total Solar Irradiance (TSI) up to 2008, and then repeat solar cycle 23 (April 1996 to June 2008) thereafter. As the start of cycle 23 had a higher TSI than the start of cycle 24, and as the TSI rose faster at the start of cylce 23 than in cycle 24, this means CMIP5 models overestimate TSI for the last part of the trend period. This will lead to their warming trends being overestimated by some small amount. Similar problems apply to volcanic forcings, and anthropogenic forcings.
These are not issues addressed by Risbey et al. They are confounding factors in the study. The proper way to address that is to show the SST trends in the models with the same ENSO phase and those with the opposite ENSO phase. Both will include the confounding factors. Consequently the effect of the difference in the ENSO phase will be found in the difference in trends between the two. It is that difference that needs to be compared to observed trends to see if they have the same spatial pattern.
By not including the middle panel, Russ (and Tisdale) prevent us from making that comparison. They have included two pieces of relevant information, but deliberately excluded the third piece which is germaine to the analysis. That is cherry picking. (They also make detailed comparison of the panels they included difficult be alternating them in a GIF so that they cannot be compared at the same time - something I consider to be a bad practise).
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barry1487 at 13:58 PM on 22 July 2014Climate data from air, land, sea and ice in 2013 reflect trends of a warming planet
Hi Ken,
Antarctic sea ice has been receiving more interest as a relatively flat trend has grown to a (statistically significant) rising trend for ice cover. NSIDC has been featuring it more of late in their sea ce page. Eg -
Antarctica’s positive trend in sea ice extent (halfway down the page)
Global sea ice for the full period (1979 - 2014) has declined. The Arctic has lost a lot more than the Antarctic has gained.
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greenhousegaseous at 13:49 PM on 22 July 2014Deep Decarbonization Pathways Project (DDPP) Presents Interim Report to UN Secretary-General Ban Ki-Moon
@Larry E:
So far as Prof Anderson’s “differences with the analysis of others”:
1. ...is a straw man sort of difference. I have zero confidence in the many “official” rates, and choose to waste no time on them. We will see much higher emissions, period. I am therefore concerned with when and where these might peak. All I am prepared to say now is that it will be far too late. Excuse me: in UN-speak, “I am 95% certain it will too late to prevent much worse feedbacks and hence, disaster.”
2. “Realistic Emissions Rates” is a matter of dispute, so why bother disputing it? See above.
3. The argument is “We cannot develop/deploy alternative energy sources fast enough to prevent us exceeding the 2 degrees C carbon budget. Therefore we must cut by 10% per year etc.” I know of no one (outside the bureaucracies) who is spending any time on strategies to keep us under 2 degrees C. That discussion has been superceded by inaction. As will be the 4 degree level by, oh, say 2025. My judgment, of course, unprovable. As to why Prof Anderson thinks he is “different”, you will need to ask him.
4. Even Dr Pacala is now admitting the wedges concept is dead, at least as far as 2 degrees C is concerned.
I confess to a bias here: I am writing about the carbon budget mainly to dispense with it as a pointless distraction from action. The issue is not staying under budget, but how to enforce *any* agreement, and how to implement the carbon taxation regime Rob and I see as necessary.
‘Nuff said for now.
You would be mighty prescient if you *were* “familiar with my work”, Larry E, seeing as the first volume in the projected series of all-platform ebooks will not be published until late this year. :-)
Suffice to say that I am no scientist, just the messenger, and my “work” is not “science”, rather a hopefully accessible quantitative assessment of the coming crisis, and a bridge for “normal” folks back here and the other science sites to the great people who have taught me so much these past 5 years.
Please feel free to contact me if you wish more info, although it beats me why you would:
gg screen name at yahoo dot etc.
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scaddenp at 13:11 PM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Charlie A - read more carefully. Russ accused Risbey of cherry-picking but the second line of paper explains why that interval was chosen. No other interval makes sense to the purpose of the exploration.
A and B are similar in that they have more red than observed, but the spatial pattern in ENSO area is what is being discussed and best has cold east just like observed and completely different to B. Jumping to conclusions without reading the paper is pointless.
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Charlie A at 12:36 PM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
@15 Tom Curtis says "Further, I note your exclusion of the middle panel of the figure showing regional trends. As a comparison is being made between the performance of two groups of models, excluding the data for one group of models suggests cherry picking."
The middle panel that Russ R omitted was the one showing regional trends of the worst models. Cherry picking would be selecting the worst models to compare against observations. The correct, scientific procedure is to pick the best 4 of 18 models to compare against observations.
I do find it interesting though, that there is a better match between panels A and B (the best and the worst models) than there is between A and C (best models and observations).
I note that other posters have accused Russ R of cherrypicking by selecting the 1998 to 2012 period. That period was chosen by Risbey et al.
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ranyl at 12:10 PM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
The paper is demonstrating that models that by chace had a cooling La Nina trend for the last 15 years similiar to what just happened, tend to be at the low end of the range of model predictions just where observations are, meaning that observations are in keeping with a continued high rate of global warming and that during the next El Nino predominent period the earth's temperature should catch up again. Also imply that when a EL Nino trend occurs rate temperature rise accelerates and when La Nina occurs it decelerates.
The rate of temperature change in the observations graph is interesting though?
Seems the NH hemisphere has increased its rate of temperature increases quite a lot whilst the southern ocean rate seems to have slowed down.
Can see the LA Nina cooling off Americas.
Not sure why the of rest of Southern Ocean is cooling, in marked contrast to the NH, presuming something to do with ocean currents or the winds or both?
Any thoughts?
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Tom Curtis at 11:53 AM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ R @6:
1) The 15 year trends mentioned in the abstract are for the GMST as I have already mentioned, and as is stated in the OP, and illustrated in the OP with figures from the paper. Your failure to acknowledge this point makes your comments look like a calculated excercise in distraction.
2) Without reading the paper (which is behind a paywall), I cannot say which Pacific spatial trend patterns they are drawing attention to. However, I can see that the spatial trend patern in the eastern and central, tropical and southern Pacific are a reasonable match. Further, I note your exclusion of the middle panel of the figure showing regional trends. As a comparison is being made between the performance of two groups of models, excluding the data for one group of models suggests cherry picking.
3) I note from the abstract that comparison was made between models that were merely in phase with observed ENSO changes. That is, if they went from El Nino to neutral or La Nina; or from neutral to La Nina over the period, they counted. That was a very weak hurdle, and one which will clearly not match the observed, very sizable ENSO trend - and hence effect on GMST, or regional Pacific trend patterns. Indeed, the strong ENSO trend observed is far more likely to overwhelm the overall GW trend, resulting in negative rather than weakly positive trends. Given this, the contrast in trend strength between two model sets is likely crucial to understanding the claims made regarding Pacific spatial trend patterns.
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scaddenp at 11:35 AM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Well fig 4 (c,d) from the paper is also reproduced above and I think it is likewise telling, but it doesnt tell you about spatial patterns especially in ENSO affected regions. (ie without Fig 5, you couldn't be sure the results in fig 4 were for the stated reasons). (a and b from Fig 4 show essentially the same information but are compared to GISS instead of C&W). Apologies for tone Russ, I didnt realise you didnt have access to the whole paper.
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Rob Honeycutt at 11:25 AM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ... Previously you stated that, "All I would like to know is where might I find some of these 'good estimates' of 'spatial trend patterns' because they're certainly absent in the Pacific over the 15 years the authors presented."
Perhaps, if you're not getting the answers you want from the abstract and illustrations, you might see if you can track down the full paper.
I would suggest that you (and Tisdale) are reading something into Fig 5 that is not of consequence for the purposes of the study. No one is expecting the models to create a perfect match image. What they were looking for were models that were in phase with the ENSO cycle.
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Larry E at 11:22 AM on 22 July 2014Deep Decarbonization Pathways Project (DDPP) Presents Interim Report to UN Secretary-General Ban Ki-Moon
Rob and greenhousegaseous, I am interested in your takes on Prof. Anderson's reasons that his (and colleagues) analysis is different than those of others, as summarized in point 1-4 in comment #40, above.
Greenhousegaseous, I am unfamiliar with your work. Can you provide a few links?
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Russ R. at 11:18 AM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Rob Honeycutt,
I've read everything made available outside the paywall.
Does that mean I'm not allowed to ask questions?
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scaddenp at 11:10 AM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Rob, it looks to me like someone (Tisdale?) has jumped on the paper, misrepresented one figure to feed the meme "models are not reliable" and Russ has fixated on that. It remains to be seen whether Russ is only looking for confirmation bias or is going to read the paper for understanding instead.
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scaddenp at 11:07 AM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
As per text, I see the cool east Pacific pattern of the observed in the inphase models whereas out-of-phase has the warming over this region. The text is about the ENSO-affected areas, so that is where I look.
Let's get a couple of things crystal clear. Models have no skill at decadal level prediction and dont claim to. Part of this is because especially ENSO (but also other modes of internal variability) is not predictable and not a single model run will have reproduced the actual ocean modes observed. Since ENSO is the perhaps the biggest contributor to internal variability in surface temperature, you would expect model runs that were in-phase to be better predictors than out-of-phase. This is more than adequately demonstrated in the paper, especially when taken as a whole.
In terms of model reliability, internal variability averages to climate of long enough period (30 years) and so model ensemble mean should be a reliable indicator of climate.
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Rob Honeycutt at 10:55 AM on 22 July 2014Climate models accurately predicted global warming when reflecting natural ocean cycles
Russ... Have you read the paper yet?
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