Cites and Signs of the times

Guest Post by Willis Eschenbach

I’ve been involved in climate science for a while now, this is not my first rodeo. And I’ve read so many pseudo-scientific studies that I’m starting to develop a list of signs that indicate when all is not well with a particular piece of work.

One sign is whether, how, and when they cite the IPCC “Bible”, their “IPCC Fourth Assessment Report”. The previous report was called the “T. A. R.” for “Third Assessment Report”, but the most recent one is called “AR4” rather than the “F. A. R. “, presumably to avoid using the “F-word”. This report is thousands upon thousands of pages of … of … of a complex mix of poorly documented “facts”, carefully selected computer model runs, good science, blatantly political screeds from Greenpeace and the World Wildlife fund, excellent science, laughable errors, heavily redacted observations, poor science, “data” which turns out to be computer model output, claims based on unarchived data, things that are indeed known and correctly described, shabby science, alarmist fantasies, things they claim are known that aren’t known or are incorrectly described, post-normal science, overstated precision, and understated uncertainty. That covers most of the AR4, at least.

Since many of the opinions expressed therein are vague waffle-mouthed mush, loaded with “could” and “may” and “the chance of” and “we might see by 2050”, you can find either support or falsification within its pages for almost any position you might take.

I have an “IPCC fail-scale” that runs from 1 to 30. The higher the number, the more likely it is that the paper will be quoted in the next IPCC report, and thus the less likely it is that the paper contains any actual science.

Image Source

I’d seen some high-scoring papers, but a team of unknowns has carried off the prize, and very decisively, with a perfect score of 30 out of 30. So how does my “IPCC Fail-Scale” work, and how did the newcomers walk off with the gold?

First, there are three categories, “how”, “whether”, and “when”. They are each rated from zero to ten. The most important of these is how they cite the IPCC report in the text. If they cite it as something like “IPCC Fourth Assessment Report: Climate Change 2007 (AR4), Volume I, pages 37-39 and p. 40, Footnote [3]”, they get no points at all. That’s far too scientific and too specific. You could quickly use that citation to see if it supports their claims, without blindly searching and guessing at what they are citing. No points at all for that.

If they cite it as “IPCC Fourth Assessment Report: Climate Change 2007 (AR4), Volume I” I award them five points for leaving out the page and paragraph numbers. They get only two points if they just omit the paragraph. And they get eight points if they leave out the volume. Leaving out a URL so their version can’t be found gets a bonus point.  But to get the full ten points, they have to disguise the report in the document. They can’t seem to be building their castles on air. So how did the winning paper list the IPCC Fourth Assessment Report in their study?

They list it in the text as “Solomon 2007”. That’s absolutely brilliant. I had to award the full ten points just for style. Plus they stuck the landing, because Susan Solomon is indeed listed as the chief culprit in the IPCC documents, and dang, I do like the way they got around advertising that they haven’t done their homework. 10 full points.

Next, where do they cite it? Newcomers to the field sometimes cite it way at the end of their study (0 to 5 points) or in the middle somewhere (six to nine points). But if you have real nerve, you throw it in as your very first reference. That’s what got them the so-called “brownie point”, the extra score named after the color of their nose, the final point that improves their chances of  being in the Fifth Assessment Report. Once again, 10 out of 10 points to the winner, “Solomon 2007” is the first reference out of the box.

Finally, do they cite the IPCC at all? Of course, the authors not citing the IPCC Report greatly improves the odds that the author has actually read, understood, and classified the IPCC document as a secondary source, so no points if they don’t cite it, 10 points if they cite it. One points per occurrence for citing it indirectly through one of their citations, to a maximum of 8. And of course, the winner has ten points in this category as well.

And what is this paragon of scientific studies, this ninja reference-master of analyses, this brazen grab by the newcomers for the crown?

Quite appropriately, it is a study which shows that when the Arctic is warmer, we should expect Northern winters to be colder.

Lately there have been a string of bitterly cold winters … who would have guessed? Well, as the authors of the study point out, none of the climate models guessed it, that’s for sure.

The study is “Arctic warming, increasing snow cover and widespread boreal winter cooling“,  by Judah L Cohen, Jason C Furtado, Mathew A Barlow, Vladimir A Alexeev and Jessica E Cherry. This study proves once again that in the topsy-turvy world of climate science, all things are explainable by the AGW hypothesis … but only in hindsight.

It’s also a curious study in that the authors, who are clearly AGW supporters, are baldly stating that the climate models are wrong, and trying to explain why they are wrong … man, if I say the models are wrong, I get my hand slapped by the AGW folks, but these authors can say it no problem. It does put them into a difficult position, though, explaining why their vaunted models got it wrong.

Finally, if they are correct that a warmer Arctic has cooler winters, then for the average Arctic temperature to be rising, it would have to be much, much warmer in the summers. I haven’t seen any data supporting that, but I could have missed it. In fact, thinking about cooling winters, one of the longest underlying claims was that CO2 warming was going to lead to warming winters in the extra-tropics and polar regions … what happened to that claim?

CONCLUSIONS in no particular order

• I have no idea if what they are claiming, about snow and cold being the result of warming, is correct or not. They say:

Understanding this counterintuitive response to radiative warming of the climate system has the potential for improving climate predictions at seasonal and longer timescales.

And they may be right in their explanation. My point was not whether they are correct. I just do love how every time the models are shown to be wrong, it has the “possibility of improving climate predictions”. It’s never “hmmm … maybe there’s a fundamental problem with the models.” It’s always the Panglossian “all is for the best in the best of all possible worlds.” From their perspective, this never ever means that the models were wrong up until now. Instead, it just makes them righter in the future. They’ve been making them righter and even righterer for so long that any day now we should reach righterest, and in all that time, the models have never been wrong. In fact, we are advised to trust them because they are claimed to do so well …

• Mrs. Henninger, my high school science teacher, had very clear rules about references. The essence of it was the logical scientific requirement that the reader be able to unambiguously identify exactly what you were referencing. For example, I couldn’t list “The Encyclopedia Britannica, Volume ‘Nox to Pat'” as a reference in a paper I submitted to her. I’d have gotten the paper back with a huge red slash through that reference, and deservedly so.

Now imagine if I’d cited my source as just “The Encyclopedia Britannica”? A citation to “The Encyclopedia Britannica” is worse than no citation, because it is misleading. It lends a scientifically deceptive mask of actual scholarship to a totally unsupported claim. And as a result …

Citing the IPCC TAR in its entirety, without complete volume, page, and if necessary paragraph numbers, is an infallible mark of advocacy disguised as science. It means that the authors have drunk the koolaid, and that the reviewers are asleep at the switch.

• Mrs. Henninger also would not let us cite secondary sources as being authoritative. If we wanted a rock to build on, it had to, must be, was required to refer to the original source. Secondary sources like citing Wikipedia were anathema to her. The Encyclopedia Britannica was OK, but barely, because the articles in the Britannica are signed by the expert who wrote each article. She would not accept Jones’s comments on Smith’s work except in the context of discussing Smith’s work itself.

But the IPCC is very upfront about not doing a single scrap of science themselves. They are just giving us their gloss on the science, a gloss from a single highly-slanted point of view that assumes what they are supposed to be setting out to establish.

As a result, the IPCC Reports are a secondary source. In other words, if there is something in the IPCC report that you are relying on, you need to specify the underlying original source. The IPCC’s comments on the original source are worthless, they are not the science you are looking for.

• If the global climate models were as good as their proprietors claim, if the models were based on physical principles as the programmers insist … how come they all missed it? How come every one of them, without exception, got the wrong answer about cold wintertimes?

• And finally, given that the models are unanimously wrong on the decadal scale, why would anyone place credence in the unanimity of their predictions of the upcoming Thermageddon™ a century from now? Seriously, folks, I’ve written dozens of computer models, from the simple to the very complex. They are all just solid, fast-calculating embodiments of my beliefs, ideas, assumptions, errors, and prejudices. Any claim that my models make is nothing more than my beliefs and errors made solid and tangible. And my belief gains no extra credibility simply because I have encoded it plus the typical number of errors into a computer program.

If my beliefs are right, then my model will be accurate. But all too often, my models, just like everyones’ models, end up being dominated by my errors and my prejudices. Computer climate models are no different. The programmers didn’t believe that arctic warming would cause cooler winters, so guess what? The models agree, they say that arctic warming will cause warmer winters. Fancy that. Now that the modelers think it will happen, guess what future models will do.

Now think about their century-long predictions, and how they can only reflect the programmers beliefs, prejudices, and errors … here is the part that many people don’t seem to understand about models:

The climate models cannot show whether our beliefs are correct or not, because they are just the embodiment of our beliefs. So the fact that their output agrees with our beliefs means nothing. People keep conflating computer model output and evidence. The only thing it is evidence of is the knowledge, assumptions, and theoretical mistakes of the programmers. It is not evidence about the world, it is only evidence of the programmers’ state of mind. And if the programmers don’t believe in cooling winters accompanying Arctic warming, the models will show warmer winters. As a result, the computer models all agreeing that the winters will be warmer is not evidence about the real world. No matter how many of the models agree, no matter how much the modelers congratulate each other on the agreement between their models, it’s still not evidence.

My best to all,

w.

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February 2, 2012 1:22 pm

Jan Kjetil Andersen says:
February 1, 2012 at 11:10 pm

AR4 do say that we know for certain that the global temperature has increased substantially in the last century, and that the level of GHG has also increased, but they do not claim that we know for certain that human activity is a cause of the temperature increase. AR4 says that it is very likely that human activity is a cause for the temperature increase, but this is not certainty. I think this comes as a surprise to many.

You have to look at how the terms are derived and applied. In IPCC-speak, “very likely” means either expert consensus (their own) or >95% statistical reliability Neither one is worth spit. Yet having so pronounced, both “likely” (90%) and “very likely” are then taken as givens and the sand-castle-in-the-air building proceeds apace.

Alan Watt
February 2, 2012 1:51 pm

Ged says:
February 2, 2012 at 11:52 am

Watt,
How is Willis being mean or unreasonable? He isn’t being a jerk, nor unkind! Just saying he isn’t going to dance to their tunes, or bow to their preconceived notions of… whatever it is they are trying to make him do, I have no idea what they are hoping to accomplish, do you?

I think it is a bit of a stretch to go from my rather mild query:

What happened to the kinder, gentler Willis?

to the conclusion that I believe Willis is being mean, unreasonable, a jerk or unkind.
What prompted my comment was the recollection (quite possibly in error), that on WUWT within the past several months (I realize with Willis this encompasses a lot of posts) Willis stated he was turning over a new leaf and trying to be less abrasive (probably not the exact wording). In that context, the exchanges between Willis and Conrad seemed to suggest a certain weakening of said resolve.
If I am mis-remembering and Willis never expressed any intent tone down a bit, then my apologies to all — carry on as it were. Although I find it hard to believe I have Willis confused with anyone else who posts here regularly.
I now return you to your regularly scheduled free-for-all …

February 2, 2012 2:49 pm

A lot of this meta-discussion discussion reminds me of a great term/phrase invented by Gestalt Therapist George Bach in “The Intimate Enemy”, when discussing argumentation styles. It labels telling someone what THEY think, feel, or believe “Mind-fucking”. It’s intended to, and very effectively does, stimulate irrational rage reactions. It necessarily implies contempt, the most corrosive of interpersonal attitudes.
If you MUST do it, prefacing it with “I think/suspect/surmise/guess” can somewhat mitigate the loudly implicit and very arrogant insult. But better to resist the temptation altogether.

timg56
February 2, 2012 3:09 pm

Willis,
I don’t think you are a jerk. But then I also know that it is not the best idea to push the wrong button with you, particularly when your cranky side is acting up. I’m fine with others doing so, as the results are pretty entertaining.
BTW – as usual, I agree with you on both the failure to accurately use reference material and on the idea that models are little more than an output of what the modeler put into it, which is not the same as an accurate reflection of anything real.

February 2, 2012 3:25 pm

The question arises, could any amount of aerodynamic modeling have predicted that a fan can in fact blow a sail forward? Once the experiment has been done it’s easy to explain why it happens: the backward component of the wind force bouncing off the sail exceeds the difference between the force on the fan and the force on the sail. So much depends on how close the fan is to the sail. Any aerodynamic engineers out there? See if you can model at what distance between the fan and the sail the boat will not move forward. –AGF

tokyoboy
February 2, 2012 4:44 pm

I wonder if Ms. Laframboise has regarded references to FAR, SAR and TAR as “peer-reviewed” ones or “grey” ones during her team auditing of the AR4 citation.

February 2, 2012 7:13 pm

interesting to view the frequency of comments on this post, i.e. the time comments were published – maybe something to be gained by that analysis – ‘hot’ topics? are those warmists at it again ?
it seems to me that this discussion was highjacked by the Conrad Clark criticism, (a debating ploy?) which takes from discussion of more important matters. i.e. the rebuttal of warmist propaganda. possibly some censorship protocols might be appropriate here.
re ‘academic integrity’ – ‘oxymoronic’ jumps to mind. most of my experience tells me that yes/no pass/fail views are formulated in the first second of sighting. there might be a 10% chance of revision, and a 10% bias towards disposition. yes, ‘blind’ assessments help to avoid this, and multiple choice questions. it’s obviously harder at the more complex end of the intellectual spectrum.
slightly off topic, but I’m interested in the ‘groupthink’ here – maybe via a key word count. does anyone here have a snappy little program that can do that ? even better, put the findings into a summary ?

David A. Evans
February 2, 2012 7:30 pm

Alan Watt says:
February 2, 2012 at 11:23 am

“What happened to the kinder, gentler Willis?”

Where’ve you been?
Willis. You are so right and it isn’t just computer models, it goes right across our life experience.
Everything is dictated by our beliefs, ideas, assumptions, errors, and prejudices.
The model may be validated most of the time or even ALL of the times we’ve tried it.
Still doesn’t mean it’s right.
On the other hand, once it’s wrong, we’ve made a mistake somewhere”
DaveE.

observa
February 2, 2012 9:16 pm

Here’s a sample of what Oz’s once proud Commonwealth Scientific and Industrial Research Organisation has been reduced to ‘exploring’-
http://dancass.com/static/files/assets/08eed16e/Report__Exploring_community_acceptance_of_rural_wind_farms_in_Australia_a_snapshot_CSIRO2012.pdf
Well if the dumb ignorant slobs out there have gone off the Global Warming, Climate Change, Climate Disruption mantra and carbon taxing then it’s much safer to stick to exploring whether they have any violent objections to windmills. Nope! Whew that’s a relief! Quick, print it and get out the press release before they change their minds.
Welcome to our new Climatology Spruikers and Inventive Research Organisation folks!

February 2, 2012 10:20 pm

Willis don’t ever change. Does that mean I agree with you all the time HELL NO. 😉 but I have learned a great deal from you about many things and I for one will continue to read every one of your posts when I see then on my daily travels on the web. Thank you sir and keep it up.

Jan Kjetil Andersen
February 2, 2012 11:22 pm

Brian says ” In IPCC-speak, “very likely” means either expert consensus (their own) or >95% statistical reliability Neither one is worth spit.”.
Well, the global warming debate is very polarized. It seems like almost everyone who have taken a standpoint think that their opponents are either idiots or having a hidden agenda.
I think it is very interesting that IPCC say that it’s not certain, but a 95% chance that human activity plays a role in the observed temperature increases.
This makes room for a serious debate on whether the 5% chance is actually happening.

Anders Valland
February 3, 2012 2:55 am

Willis, you spend a lot of time on us telling us you don’t care… You don’t know me, I don’t know you. I will not stoop to the level of trying to tell you who you are.
I never said I thought you were too harsh on Conrad. I never said I believe you should shy away from people who start their argument with “WTF!”. What I tried to tell you is that your behaviour detracts from your points. When you stoop to the level of that commenter you make a mistake. Stooping lower makes it worse. You know that. Yeah, yeah, I know you don’t care. I have a teenager, I know how that works.
Now, I care about what is on the pages of WUWT because I tend to use it to show people some very good arguments and posts. There is even more gold in the comment section. But not this time. I’ll step out of this thread and leave you to it.

February 3, 2012 9:14 am

Reblogged this on riversmoon416.

Louise
February 3, 2012 10:56 am

Good grief Willis, I’ll say it again:
Willis, when you say “The blog statistics show I am far and away the most popular guest author on the site. ” the phrase ‘car crash TV’ comes to mind.

Louise
February 3, 2012 11:02 am

[SNIP: Louise, put all your zingers in one post and be done with it. You’re trying to provoke a fight. -REP]

Louise
February 3, 2012 11:34 am

I tried to explain exactly why Willis’ posts are so popular and REP decided to SNIP me.
Willis – your posts aren’t popular “because I write clear, interesting, detailed posts about climate science that explore hidden corners of the climate and our responses to them.” but because it is human nature to stop and watch a street fight (or car crash TV).
Most of your fans (of which I am one as I contribute to the numbers who read your posts more than any other guest poster) are tuning in for the vitriol, not the science. Everyone enjoys a bun fight from the safety of their own laptop.

conrad clark
February 3, 2012 1:08 pm

w. says:
“Sadly, you are quite correct about iterative models.”
Wow – something that I can reply constructively to. Your statements about models being nothing more that codified preconception and bias may be true, but, in my opinion, only at the margin.
In the early 1970s while working for a 3-letter security agency, I was asked to justify a major computerized-learning (as it was called at the time) project, using the Army Signal School’s very large FORTRAN iterative model, with lots of inputs and computations, no comments, and obfuscated code (partially the by-product of FORTRAN itself). After days of reverse engineering I found the essential algorithm to be the statement EFFTV=EFFTV*1.08 !!! That is, that the effectiveness of computerized-learning was 8% greater than the alternative! Tracing back EFFTV showed that the only input used in its calculation was the computed effectiveness of the measured non-computerized class.
So that particular “model” went beyond codifying preconception and bias to actually serving only to hide the explicit preconception. Bad as that was, the Signal School at least provided test data (real class measurements) and source code, which none of the AGW crooks are willing to do.
I don’t think that understanding the power and limitations of models is peripheral to any discussion of AGW, climate change, or whatever alarmists call it today. Models are the alarmist’s only argument. After we get a look at their real data and code, I believe they will have no basis for avoiding prosecution for fraud.
Conrad

conrad clark
February 3, 2012 4:54 pm

w.
Your comment to Anders missed his attempt to engage me (which I also missed in the haze of heated discussion (heated discussion is always better with beer and a dart board, not in discussion threads)).
Anders Valland says:
February 2, 2012 at 2:49 am:
“… I would like to know what you think when you say that the Machine Learning class has any relevance to this – do you feel neural networks and self-learning models should be used for modelling climate? Do you think that is feasible, given the complexity of the issue?”
I really don’t have any idea what could be used to model climate with predictions and falsifiability. However, the newer statistical, self-learning and even neural networks could be very useful (using back modeling) in determining which observations seem to be useful over climate time scales, which are echos, and which don’t even have back predictive capability. That’s different from:
1. Using the model to adjust the data (CRU et. al.).
2. Using the models to predict the immediate future as a basis for expensive policy (CRU and various statist criminals).
3. Adjusting the model as more data comes in. Not always evil, but all too often results in overfitting (in the technical model sense) and introduction of experimenter bias.
The data rules. It should be relatively easy to conduct data experiments as above, with little experimenter bias (see http://www.sciencenews.org/view/generic/id/337088, in which the results startled the drug researchers, and even me (note there may in fact be truth or untruth in their model, but it really doesn’t seem to be correctly described as a network analysis)). When I say “relatively easy”, that means we have the computation and storage technology, that doesn’t mean easy or inexpensive. The climate data is a mess, even where it hasn’t been intentionally corrupted.
Conrad

Anders Valland
February 4, 2012 9:14 am

Conrad,
thank you for your reply. My own programming skills are very basic, but we do use models such as you describe in our research. I work with people who makes it possible for us to do analysis using such techniques, I don’t need to know how to make them in order to use them. But I need to know how to set up the algorithms and how to sort out all of the traps that follows what Willis describes. I agree with you that climate data is a mess, and that there is quite a bit of work to do before you can get down to working with whatever part of it that is good.

Gary Hladik
February 4, 2012 1:33 pm

Louise says (February 3, 2012 at 11:34 am): “Willis – your posts aren’t popular ‘because I write clear, interesting, detailed posts about climate science that explore hidden corners of the climate and our responses to them.’ but because it is human nature to stop and watch a street fight (or car crash TV).”
Personally, Willis had me at “Steel Greenhouse”:
http://wattsupwiththat.com/2009/11/17/the-steel-greenhouse/
I read all his articles and most of the comment threads for the information therein, and sigh in amused frustration at the distracting bickering.
Let’s do an experiment. From here on, let’s all stick to the science in WE’s comment threads, ignore any perceived impoliteness in his replies, curb our inner snark, and see if his popularity at WUWT plummets. If it works, we can extend the passion-free zone to the rest of WUWT and drive its popularity as low as a snake’s belly. Or even lower, down to Realclimate’s level.
Oops.
OK, we’ll start after this comment!