People send me stuff. In this case I have received an embargoed paper and press release from Nature from another member of the news media who wanted me to look at it.
The new paper is scheduled to be published in Nature and is embargoed until 10AM PDT Sunday morning, July 20th. That said, Bob Tisdale and I have been examining the paper, which oddly includes co-authors Dr. Stephan Lewandowsky and Dr. Naomi Oreskes and is on the topic of ENSO and “the pause” in global warming. I say oddly because neither Lewandowsky or Oreskes concentrates on physical science, but direct their work towards psychology and science history respectively.
Tisdale found a potentially fatal glaring oversight, which I verified, and as a professional courtesy I have notified two people who are listed as authors on the paper. It has been 24 hours, and I have no response from either. Since it is possible that they have not received these emails, I thought it would be useful to post my emails to them here.
It is also possible they are simply ignoring the email. I just don’t know. As we’ve seen previously in attempts at communication with Dr. Lewandowsky, he often turns valid criticisms into puzzles and taunts, so anything could be happening behind the scenes here if they have read my email. It would seem to me that they’d be monitoring their emails ahead of publication to field questions from the many journalists who have been given this press release, so I find it puzzling there has been no response.
Note: for those that would criticize my action as “breaking the embargo” I have not even named the paper title, its DOI, or used any language from the paper itself. If I were an author, and somebody spotted what could be a fatal blunder that made it past peer review, I’d certainly want to know about it before the paper press release occurs. It is about 24 hours to publication, so they still have time to respond, and hopefully this message on WUWT will make it to them.
Here is what I sent (email addresses have been link disabled to prevent them from being spambot harvested):
===============================================================
From: Anthony
Sent: Friday, July 18, 2014 9:01 AM
To: james.risbey at csiro.au
Subject: Fw: Questions on Risbey et al. (2014)
Hello Dr. Risbey,
At first I had trouble finding your email, which is why I sent it to Ms.Oreskes first. I dare not send it to professor Lewandowsky, since as we have seen by example, all he does is taunt people who have legitimate questions.
Can you answer the question below?
Thank you for your consideration.
Anthony Watts
—–Original Message—–
From: Anthony
Sent: Friday, July 18, 2014 8:48 AM
To: oreskes at fas.harvard.edu
Subject: Questions on Risbey et al. (2014)
Dear Dr. Oreskes,
As a climate journalist running the most viewed blog on climate, I have been graciously provided an advance copy of the press release and paper Risbey et al. (2014) that is being held under embargo until Sunday, July 20th. I am in the process of helping to co-author a rebuttal to Risbey et al. (2014) I think we’ve spotted a major blunder, but I want to check with a team member first.
One of the key points of Risbey et al. is the claim that the selected 4 “best” climate models could simulate the spatial patterns of the warming and cooling trends in sea surface temperatures during the hiatus period.
But reading and re-reading the paper we cannot determine where it actually identifies the models selected as the “best” 4 and “worst” 4 climate models.
Risbey et al. identifies the 18 originals, but not the other 8 that are “best” or “worst”.
Risbey et al. presented histograms of the modeled and observed trends for the 15-year warming period (1984-1998) before the 15-year hiatus period in cell b of their Figure 1. So, obviously, that period was important. Yet Risbey et al. did not present how well or poorly the 4 “best” models simulated the spatial trends in sea surface temperatures for the important period of 1984-1998.
Is there some identification of the “best” and “worst” referenced in the paper that we have overlooked, or is there a reason for this oversight?
Thank you for your consideration.
Anthony Watts
WUWT
============================================================
UPDATE: as of 10:15AM PDT July 20th, the paper has been published online here:
http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate2310.html
Well-estimated global surface warming in climate projections selected for ENSO phase
Abstract
The question of how climate model projections have tracked the actual evolution of global mean surface air temperature is important in establishing the credibility of their projections. Some studies and the IPCC Fifth Assessment Report suggest that the recent 15-year period (1998–2012) provides evidence that models are overestimating current temperature evolution. Such comparisons are not evidence against model trends because they represent only one realization where the decadal natural variability component of the model climate is generally not in phase with observations. 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.
of interest is this:
UPDATE2: rebuttal has been posted
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But if this is science then how can you know your replication of the model ‘experiment’ matches theirs?
Anyway, here are some other climate models. This is like a man with 2 watches showing different times, he’s never sure of the time. Modelling in the dark.
The most accurate climate models are the ones that have huge decadal oscillations and they just happen to be oscillating on the down-side right now meeting the flat hiatus temperatures.
In other words, the accurate global warming models are the ones that project no global warming.
Steven Mosher says:
July 19, 2014 at 12:35 pm
Nope. Steve, you’re wrong there.
[See, this kind of debate is easy. I learnt it at kindergarten.]
The rest of this scientific debate goes like this:
‘Tis
‘Tisn’t
‘Tis
‘Tisn’t
[ad infinitum]
Steve, for an intelligent man you really do cause readers to waste a load of time reading your [kindergarten] remarks (and me a load of time responding to them!).
This is garbage. Anyone can carry out MULTIPLE model runs and point to 4 of the best matchers for say precipitation over a region. This doesn’t tell my anything. Just look at the models the IPCC uses for its global surface temperature projections. You could pick the 4 best performers and publish a paper. Yet the vast majority failed miserably.
Steven Mosher;
I wish that willis were here to tell you to quote my words
I did quote your words. It is right there upthread, go read it again.
does it make sense to average models? probably not. But you get a better answer that way
so until someone devises a test to score models.. that is what you have,
In one breath you say averaging models probably doesn’t make sense and in the next you say you get a better answer. Mosh, you can’t have it both ways.
But there’s really no way to justify averaging of models. What if 10 new models appeared tomorrow showing even higher sensitivity than the current crop? Would you just add them in and say, hey, 28 is better than 18? What if they were all lower? Would that make is better? What if 10 of the 18 current models were discontinued for some reason, all of which were high sensitivity. Would you argue that the remaining 8 should continue to be averaged? Would you then apply an “adjustment” to the average to gloss over the resulting negative discontinuity?
Presuming that the errors in artificial constructs cancel each other out by being averaged together and thus give you a “better” answer is ridiculous.
Steven Mosher says:
July 19, 2014 at 12:38 pm
“..the democracy of the models?” Say what? The models have a vote???
Steven Mosher says:
July 19, 2014 at 12:41 pm
‘Simple fact is that the avergae of models is a better tool than any given one.
deal with it.’
So the average of twelve wrong clocks will tell you the right time, or not as is more likely. The truth is that models only become a ‘better tool’ once they have proved a reasonable power of prediction.
As a smart person once said, ‘all models are wrong, but some can be useful’ or something like that.
Sometime, in our (still dark) future:
“Please stop your attempts to extract the urine. I’m a published climate scientist doncha know.” Sincerely, S Lewandowsky/N Oreskes
Steven Mosher says: “Simple fact is that the avergae of models is a better tool than any given one. deal with it.”
You mean, the avergae of models is a less worse tool than any given one. Dealt with.
The latest effort seems to be to just ignore those that don’t agree with the warmists, ala the BBC excluding opposing views. Expect trumpeting of the big “4 best” around the world for the masses and only the whimper of the internet for the inquisitive.
On a related note. I find it utterly hilarious, to not be a “science denier” you must deny the pause. From reading various blogs, one could assume to stop being a science denier, I need to take random variables from the papers attempting to explain the lack of warming and fuse them together. Clearly only science deniers would fail to do so!! LOL
“Anyway, dont expect a more helpful response than:
“Why should I make the data available to you, when your aim is to try and find something wrong with it…”
BINGO. I’m just a lowly QA Mgr,however that is my job,looking for errors. BUT,if you find something wrong with my work,I want you to tell me it is wrong.
Why are some people so scared to just own up and say I screwed up?
If the four best (forget about the worst) are named, it won’t take a genius PR strategist to parlay that adulation and recognition and morph it into jealousy and strife.
(If there’s one thing I’ve learned this year, it’s you scientists are an creative, intelligent and punishingly contemptuous lot.)
It could only help the science behind modeling if we had more public dissonance between the various modeler camps. I would like to see the models become accurate. One way to do that is to let them compete — iron sharpening iron and all that.
Will it happen? Nah. There’s no money in it save that which spills from the government’s purse. Climate models are sort of like artists in that way. And everyone knows you can’t judge art.
Doesn’t the IPCC go with the central temperature (average) projection or thereabouts? That failed badly, while a couple of the models did come closest to observations. That makes your assertion a bit off the mark. Average can still be wrong, ask the ipcc.
Steven Mosher says: “Simple fact is that the avergae of models is a better tool than any given one. deal with it.”
==============
Please explain how an ‘average’ of unvalidated models is a better ‘tool’ than a simple (unvalidated) guess?
Why are some people so scared to just own up and say I screwed up?
This issue is about politics, domination, and control. It is not about science. Those who want to drive mankind back into a pre-industrial state of being are not going to be forthcoming about their mistakes and errors now are they?
There may be a few honest men and women scientists who have been deluded into thinking that a tiny addition of anthropogenic CO2 into the atmosphere will lead to the destruction of life as we know it — but I really do find that difficult to believe. The evidence is overwhelming that increasing levels of CO2 do not produce warming. The last 17 plus years should be clear enough to any honest person. (and remember that mankind’s portion of the increase in CO2 was tiny) http://hockeyschtick.blogspot.com/2014/07/new-paper-finds-only-375-of-atmospheric.html
However, let us remember what Sinclair Lewis once wrote: “It is difficult to get a man to understand something if his salary depends upon his not understanding it”.
Steven,
In reference to my previous comment. Have the current set of Climate Models been validated, in the scientific sense? As far as I know (and of course my knowledge is limited) they have not. Given that being true, what value would we gain from an average of models we don’t know are a valid representation of reality?
Steven Mosher says:
That does seem to be true. But is it useful?
I argue No.
Models each represent an opinion of the relative significance of the factors that affect the climate. They are all hoped to be reasonable (no-one includes the effect of the morning star entering the House of Sagittarius); they are all hoed to be sciency.
All models make a judgement call as to what is not sciency. They all share the same bias to include only realistic factors. But they all make mistakes (to err is human) and include factors that are almost or entirely insignificant and undervalue the big ones. Not the same mistakes but still mistakes.
Now read Tolstoy’s Anna Karenina: not the lot, just until “All happy families are alike; each unhappy family is unhappy in its own way.” Only one answer is right; we are one planet.
The potential errors are infinite but the right bits are all there in every model. So we average and end up with the Wisdom of Crowds.
But we Do not have the Knowledge of Crowds as we don’t know which bits are rightest from the aggregate.
dccowboy says:
July 19, 2014 at 1:37 pm
Steven,
In reference to my previous comment. Have the current set of Climate Models been validated, in the scientific sense? As far as I know (and of course my knowledge is limited) they have not. Given that being true, what value would we gain from an average of models we don’t know are a valid representation of reality?
Verification and validation testing and publication of the tests and results are something that is not done in academia. At best you see the equivalent of ‘HarryReadMe’ files. This lack of validation extends to the entire realm of climate ‘science’ including NCDC and NASA GISS. Or perhaps someone can point to the suite of validation tests and results that have been published? The models are expensive electronic handwaving as they have not been validation tested, yet the entire world economy is expected to be crippled due to the ‘results’ from these random number generators. Now with ‘the pause’ it is blatantly obvious that the models are junk and do not do what they are claimed to do. Is there any other area of science where continually getting the wrong answer from unvalidated software would obtain funding?
Don’t overlook the conditional language “4 “best” climate models could simulate the spatial patterns.” Why phrase it as “could simulate”? Why not be definite with “simulated”?
Other than that the best model is the one supported by the most grant money. You have to make the customer happy.
“Simple fact is that the avergae of models is a better tool than any given one”
Only if the models are unbiased estimators for the variables of interests. As such, the statistical “expected value” of model error for each such variable would be zero.
Demonstration of unbiased estimation would be key to validating part of methodology of this paper and should be mentioned.
Has anybody demonstrated that the GCM’s are unbiased estimators? Doubtful that anybody has if the model temperature forecasts are “running hot”. As such, the expected value of the model temperature estimates would be equal to their bias.
Further, if the they models are unbiased estimators, it is not clear why the methodology would select and average 4 models. Surely the standard error of 18 unbiased estimates would have the smallest standard error: why not use all 18? The selection of 4 makes no sense.
NONE of existing so called model lives up to needed criteria they are said to be “written”. Had the so called scholars had enough knowledge in how to write a sound systemprogram, had they used at least 43 of the most important factors to be taken into consideration, had they also had elementary knowledge in Mathematic Statistic and Geology, they had been much better off.
Sadly to say they haven’t lived up to their own promises.
I have tried to present Archimedes principle here more than once. Still many people, scholars or strawmen, doesn’t seem to understand the simple fact that land under glaciars which melt rises and that ice melting in water never ever result in rising waterlevel. Well guess it’s time to present proof of that –
During the ice-melting period after the last Ice age the land rised when ice over land had melted. The uplift is strictly according to Archimedes principle To many people haven’t had teachers aducated enough in Geography-; History- and/or Physic subjects. Thus they haven’t learnt these basic knowledge of our Earth history.
While working with my C-essay in History 1993 (written D-essay, so called Master essay later) I hade to know as exact waterlevels for the Baltic Sea as possible and thus I had to know the sealevels in Oceans along coast around the world. My primary exam I had in Computer science (originally graduates trained system programmer -71). I wrote a program using 43 needed factors for analysing sea levels mainly from Stone Age up to 1000 AD.
At first I had to determ the sea level, ie. , the normal waterlevels around the worlds coast. To reach as correct algoritm as possible I compared genuine actual levels with known deposits, sludge and archaelogical reports. The needed 43 necessary factors to be taken into account include straiths, landrise, erosion, grounds, techtonical plates, meandering of pre-historic and historic rivers, biotops (including seed and weeds found in C-14 analysed layer in coast area during excavations), tectonical plates movements, known eruptions from vulcanos etc etc. The amount of needed factors taken into account is significantly more than the 7 to 9 the so called CO2 scientists usually use in their models.The Baltic Sea in older ages
please look at the maps in the bottom of the page. when I had them up in 1993 it was said that they were significant proof of landrise. In today’s CO2-discussion they can be used to disprove the assumption of rising waterlevels when glaciars and ice in water melt.
That’s only one of many other parts of the so called computer models I might present. I haven’t found any of the so called model reaching up to standard needed to show that Theories of Science been used at all.
One could say the same of McIntyre and McKitrick. A person’s title or background is irrelevant. The paper should stand or fall on its own merits or shortcomings.
I Wouldn’t have posted this before the end of the embargo. It just leaves you open to criticism for no real benefit. Either they read your e-mail and take steps to check out any problems you point out, or they don’t. If the don’t, then you’ve got something worth righting about AFTER the embargo is lifted.
Mosher, “average of the models” what an ignorant statement. Why not just take all the models code and compile it all together and run a single result. Yeah that will work. You must not know what a GCM is.