The Birth of CGR Science

Guest Post by Willis Eschenbach

I was reading a study published in November 2011 in Science mag, paywalled of course. It’s called “The Pace of Shifting Climate in Marine and Terrestrial Ecosystems”, by Burrows et al. (abstract here,  hereinafter B2011). However, I believe that the Supplementary Online Information (SOI) may not be paywalled, and it is here.

The study has 19 authors, clear proof of the hypothesis that the quality of the science is inversely proportional to the square of the named authors. They study has plenty of flash, something akin to what the song calls “28 color glossy photos with circles and arrows and a paragraph on the back of each one”, like the following:

Figure 1 from B2011.  ORIGINAL CAPTION: (A) Trends in land (Climate Research Unit data set CRU TS3.1) and ocean (Hadley Centre data set Had1SST 1.1) temperatures for 1960–2009, with latitude medians (red, land; blue, ocean).

It’s interesting how they don’t waste any time. In the very first sentence of the study, they beg the conclusion of the paper. Surely that must break the existing land speed record. The paper opens by saying:

Climate warming is a global threat to biodiversity (1). 

I’d have thought that science was about seeing if a warming of a degree or two in a century might be a global threat to biodiversity, and if so, exactly which bio might get less diverse.

I would have expected them to establish that through scientific studies of the plants and animals of our astounding planet. Observations. Facts. Analyses of biodiversity in areas that have warmed. But of course, since they state it as an established fact in the very first sentence, all the observations and evidence and analyses must surely have been laid out in reference (1).

So I looked in the list of references to identify reference (1), expecting to find a hard-hitting scientific analyses with observations and facts that showed conclusively that plants and animals around the globe hate warming and that it damages them and saps their vital bodily fluids.

It was neither encouraging, nor entirely unexpected, to find that reference (1) is entitled “Global Biodiversity Scenarios for the Year 2100”.

Again the paper is paywalled, must be a better way to do science, abstract here. The abstract says:

ABSTRACT

Scenarios of changes in biodiversity for the year 2100 can now be developed based on scenarios of changes in atmospheric carbon dioxide, climate, vegetation, and land use and the known sensitivity of biodiversity to these changes. This study identified a ranking of the importance of drivers of change, a ranking of the biomes with respect to expected changes, and the major sources of uncertainties.

There you have it, folks. They didn’t bother looking at the real world at all. Instead, they had their computer models generate some “scenarios of change” for what the world might look like in 2100. These model results represent the current situation as projected forwards a century by carefully following, in the most scientificalistic and mathematically rigorous manner, the prejudices and preconceptions of the programmers who wrote the model.

But they didn’t just release the model forecasts. That wouldn’t be science, and more to the point, it entails the risk that people might say “wait a minute … what does a glorified adding machine know about what’s gonna happen in a century, anyway?” Can’t have that.

So first, they intensively studied the results in the most intensive and studious manner. They pored over them, they weighed and measured them, they pieced them and plotted them and mapped them, they took their main conclusion and “washed it in permanganate with carbolated soap” as the poet has it, they pondered the eigenvectors, they normalized the results and standardized them and area-adjusted them and de-normalized them again. That is the kind of mystical alchemy that transmutes plain old fallible computer model results into infallible golden Science.

And what did they find? To no one’s surprise, they found conclusive proof that the programmers’ prejudices and preconceptions were 100% correct, that plants and animals despise warming, and they do all they can to avoid warm places. They showed beyond doubt that even the slightest warming over a century is intolerable to wildlife, that there are only costs and no benefits from gradual warming, and … wait, say what?

In other words, the B2011 study is models all the way down. No one has shown that a few degrees of warming over a century is a “global threat to biodiversity”, that is a very poorly supported hypothesis, not a fact. If the feared warming does occur, the majority of the warming is projected to be at night, in the winter, in the extratropics. Call me crazy, but I don’t foresee huge effects on biodiversity if midnights in Siberia in December are minus 37° rather than minus 40° … sure, every change brings changes, and if it warms there will be some, but I don’t see any evidence supporting a “global threat to biodiversity”.

In any case, I started out by looking at their results of the first study, B2011, but I got totally sidetractored by their error bars on their results shown in Figure 1. (That’s like being sidetracked but with a lot more pull.)  They used a tiny, 1° x 1° grid size, and given the scarcity of temperature observations in many parts of the world, I wondered how they dealt with the uneven spacing of the ground stations. At that size, many of the grids wouldn’t have a single temperature station. So I looked to see how they handled the error estimate for the temperature trend in a 1° x 1° gridcell that contained no temperature stations at all. Interesting philosophical question, don’t you think? What are the error bars on your results when you have zero data?

I was amazed by their error procedure, which is what led me to write this post. Here’s what the B2011 SOI says about error estimates for their work:

We do not reflect uncertainty for our estimates or attempt statistical tests because all of our input data include some degree of model-based interpolation. Here we seek only to describe broad regional patterns; more detailed modeling will be required to reflect inherent uncertainty in specific smaller-scale predictions.

So … using model based interpolation somehow buys you a climate indulgence releasing you from needing to display your error estimates? If you use model results as input data, you can just blow off “statistical tests”? This “post-normal science” is sure easier than the regular kind.

It was not enough that their first sentence, the underlying rock on which their paper is founded, the alleged “danger” their whole paper is built around, exists only in the spectral midnight world of computer models wherein any fantasy can be given a realistic looking appearance and heft and ostensible substance.

Indeed, I might suggest that we are witnessing the birth of a new paradigm. The movie industry has been revolutionized by CGI, or “computer-generated imagery”. This includes imagery so realistic it is hard to distinguish from images of the actual world. Here’s an example:

Figure 2. Computer generated fractal image of an imaginary high mountain meadow. Image Source.

CGI has saved the movie industry millions of dollars. Instead of requiring expensive sets or filming on location, they can film anywhere that is comfortable, and fill in the rest with CGI.

We may be seeing the dawn of the same revolution in science, using what can only be described as CGR, or “computer-generated reality”. I mean, the actual reality seems to specialize in things like bad weather and poisonous snakes and muddy streams filled with leeches, and it refuses to arrange itself so that I can measure it easily. Plus it’s hard to sneak up on the little critters to find out what they’re actually doing, somehow they always seem to hear my footsteps. But consider the CGR mice and rabbits and small animals that live in the lovely high CGR meadows shown in Figure 2. When the temperature rises there in the high meadow, it’s easy for me to determine how far the shrews and rock coneys that live in the meadow will have to move. Using CGR a man can do serious, rigorous, and most importantly,  fundable scientific study without all the messy parts involving slipping on rocks and wet boots and sleeping on the ground and mosquitoes and sweating. Particularly the sweating part, I suspect that many of those CGR guys only sweat when there’s emotional involvement. Personally, I think they are way ahead of their time, they’re already 100% into CGR, because studying actual reality is soooo twentieth century. Instead, they are studying the effects of CG climate on CG foxes preying on CG voles, in the computer-generated reality of the high mountain meadow shown above … to my dismay, CGR seems to be the wave of the future of climate science.

But it’s not bad enough that they have forsaken studying real ecosystems for investigating cyberworlds. In addition, they are asserting a special exemption from normal scientific practices, specifically because they have built their study, not on the rock of solid scientific investigation of the real world, but on the shifting sand of conclusions based on their CGR world. It reminds me of the guy who kills his parents, and then wants special treatment because he’s an orphan … you can’t choose to study CGR, and then claim that the fact that you are not studying actual reality somehow exempts you from the normal requirements of science.

Finally, they’ve modeled the global temperature on a 1° x 1° grid, but they say they need “more detailed modeling”. Now, that’s a curious claim in itself, but it also brings up an interesting question, viz:

They say they can’t give error estimates or uncertainty bounds on their current work because they are using modeled results as input data … and their proposed cure for this is “more detailed modeling” to “reflect inherent uncertainty”?

I’d rave about this, but it’s a peaceful morning and the sun is shining. And besides, in response to the urging of my friends, not to mention the imprecations of my detractors, I’ve given up my wicked ways. I’m a reformed cowboy, but it’s a work in progress, and it looks like I have to reform some more, no news there. So let me simply say that this is an example of post-normal, post-reality climate “science” and peer-review at its worst. Why does using a model somehow make you exempt from the normal scientific requirement to make error estimates and conduct statistical tests?

Sadly, this is all too typical of what passes for climate science these days, models all the way down. Far too much of climate science is merely the study of CGR, and special exemptions apply …

My regards, as always, to everyone.

w.

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Mardler

Regrettably, the MSM and 99% of the public will accept this twaddle completely.
Another goal for the warmistas, another loss for us.

steveta_uk

Don’t be shy, Willis, what did you really think?

catweazle666

>>“Global Biodiversity Scenarios for the Year 2100″<<
When I was a lad this stuff used to be called science fiction.

The trouble as always is…why have thousands and thousands not bothered to tell Science this kind of rubbish is unacceptable?
I tell you why…because even the staunchest warmist knows in the deep of his/her heart that “climate change research” is either done with the lowest of standards, or not done at all.
Science like Nature has to fill a quota of climate change pages, if only to support commitments by their parent companies. Therefore expect for.years now the sloppiest of the sloppiest research to see the light of the day.
Climate research will come of age only when climate change papers will be held to a higher standard.

More statistical data fabrication from climate scientists, at least this time they had the guts to clearly admit it in their paper thus showing that their paper isn’t worth using it for toilet paper, can’t wipe **** off with more **** after all.

Robert M

Edit needed, Para 2
Sentence 2
They study has plenty of flash… Should be The study

I think it will be interesting to watch as “warmists/alarmists” point to this study as “proof” of CAGW, or similar.

Frank K.

Again, I ask, why is this kind of press release from yet-another-scary-climate-paper any surprise???
There is SO much ca$h in climate “science” right now, and science professors and government researchers would be derelict if they they didn’t go for the money, particularly when your performance metric as a scientist is based on how much money you bring to your institution.
I do agree that these abstracts hilariously almost write themselves. You could probably come up with an automatic abstract generator for any project like this:
Title: THE RELATIONSHIP BETWEEN [your research topic] AND DANGEROUS CLIMATE CHANGE
Authors: [Your name + 10 of your friends (need not be scientists)]
Keywords: Danger, climate, disruption, hot, warming, chaos, help!, yikes!
Funding: NSF, DOE, and the Taxpayers
It is well-known that dangerous climate change is unequivocal, and that the threat to humans, animals, and plants is obvious. In our study, we show how [your research topic] is related to dangerous climate change. A description of our computer modeling techniques for [your research topic] is presented in this paper. We show that our modeling studies verify our conclusions robustly, and that dramatic reductions in CO2 emissions are required to stave off disaster.

My sentiments exactly. Get off your arses, you lazy bums, and go look at the real world before postulating mere prejudiced guesswork as a reflection of reality, and motivator of public policy.

J B Williamson

Loved the nod to “Alice’s Restaurant Massacree”. One of my favourite pieces of ‘music’. I still have the LP somewhere.

Another brilliant post which should be included in a published anthology of Willis’s writings on here.

George E. Smith;

Well I wouldn’t call a 1 deg x 1 deg grid cell tiny by any stretch of imagination.
One minute of arc on the earth surface is approximately one nautical mile (1852 metres), so a one degree square cell, is about 60 x 60 nautical miles or about 111 x 111 km.
Such a grid cell size, would swallow virtually all ot the SanFrancisco Bay Peninsula area from around San Francisco, down to San Jose. Well any quick look at daily weather maps for this area would show that full temperature cycles in many spatial directions, occur over that space every day, some of them over distances of no more than five miles, and often of ten degree magnitude.
In short, even a one degree cell doesn’t properly follow the Temperature of this region, in compliance with the Nyquist theorem of sampled data systems. So in this area, the aliassing noise would render even the average Temperature indeterminate. And the two Temperatures per 24 hours time sampling would also fail the Nyquist criterion.
Yet Hansen would believe that the Temperature “recorded” here is a perfectly valid number for some place 1200 km away down the Baja Peninsula, in the Sea of Cortez; or off to the east way beyond the Sierra Nevada.
Now of course if you leave a thermometer some place around here and read it now and then and average those results, you will eventually reduce the spread of observed values; you just have no assurance, that your number truly reflects the average Temperature for this region.
And yes, I know they just look at “anomalies”; but those are simply variations from some also quite unknown base value. You can’t fool Nyquist with statistics. The average value of invalid wrong data remains invalid, and wrong.

Rob Dawg

Back testing?

OT.
Dr Leif Svalgaard’s presentation at the STEL, Nagoya, 16 January, 2012
A comprehensive review the some known and some new ideas.
http://www.leif.org/research/The%20long-term%20variation%20of%20solar%20activity.pdf

D Caldwell

One has to admire their advocacy strategy. One more worthless study thrown upon the enormous stack of “peer reviewed” articles consistent with the climate alarmist agenda. They have been very productive in that regard.
It’s not so much about good science as it is about having the sheer weight of the “scientific literature” in support of their position.
They’re not stupid.

Correction:
A comprehensive review of some known and some new ideas.

Robert S

Nature climate change is filled with rubbish papers and studies also; eg – “Severe tissue damage in Atlantic cod larvae under increasing ocean acidification” Jan 2012 vol 2 No1.

John Garrett

“The study has 19 authors, clear proof of the hypothesis that the quality of the science is inversely proportional to the square of the named authors.”
I humbly propose that this hypothesis be hereafter referred to as The Eschenbach Hypothesis. Bravo, w! Well done !

tty

The most ironic thing is that for three hundred years naturalists have braved mud, mosquitoes and those leech-filled streams to explore real biodiversity. And what have they found? That one factor is vastly more important than any other: the warmer the climate is, the greater is the biodiversity.

Brilliant Willis! You have postulated another corollary to Parkinson’s Law:
“The study has 19 authors, clear proof of the hypothesis that the quality of the science is inversely proportional to the square of the named authors.”

Anton Eagle

Hey Willis!
Good to have you back. While you were gone, someone borrowed your online access and kind of went off a little bit. 😉
Anyway, things seem to be back on track now. Great article.
Cheers

RockyRoad

So taking the inverse position from this multi-author paper, biodiversity is enhanced when marine organisms are frozen in the ice? I’m trying to envision how reproduction takes place under said circumstances–without success, I might add.

Garethman

Interesting stuff Willis. While in some ways models are like computer generated graphics, or even the Matrix where the world can be made to seem in any way you want it to, it’s also important to realise that the results of first hand observation are often more subjective than most of us would credit. I suppose we are all familiar with how two sets of politicians will look at the same data, and get differing results, or even closer to home how temperature graphs can be interpreted to show differing trends. However, at least we know in such cases the data is reasonable solid,and it is our own subjective interpretation that varies the results. Unlike an extreme reliance on dodgy models which probably undermines good science more than any other factor I can think of.

Mac the Knife

This should be sold in the B grade Science Fiction section… but they need a ‘catchier’ title. “The Pace of Shifting Climate in Marine and Terrestrial Ecosystems” just doesn’t cut it!

Hoser

It would seem this paper is a setup for future publications. The dire predictions and scary quotations can be cited as peer reviewed. It will be up to the reader to go back and read the paper, find the caveats, and then discount the entire thing. However, does anybody expect grant reviewers to do that? Certainly, other members of the Team never would.

djl

>>They say they can’t give error estimates or uncertainty bounds on their current work<<
because the uncertanty is larger than their results. Plus how can you predict land use patterns for the rest of the century and have any expectation they will be anywhere close to what happens?

Mark Hladik

Paragraph 10 ( if I counted right ), second sentence:
“pored” = poured ?
Mark H.

Legatus

Why does using a model somehow make you exempt from the normal scientific requirement to make error estimates and conduct statistical tests?

This one is easy, because they are using models, not reality. Since they are not using reality, then we know exactly what the error is, 100%, exactly. I mean, think about it, exactly how are you going to make error estimates of measurements that don’t exist, or conduct statistical tests on data that they have not gathered? Their error bars are zero and their data is perfect because they created it that way. Their computer generated gin joint (appropriate Star Trek holoprojector reference, it makes seemingly real landscapes and puts you in them) is the perfect, platonic ideal, not just the world as we know it, but the world as they know it should be.
The “logic” goes like this:
I created and entire, imaginary world, operating the way only I know it must (see, I have a white lab coat, and you don’t).
That makes me “The Creator”.
I am therefore God.
You are not.
To accuse me of error or statistical missteps is to question God.
Heretic!
Note about the white lab coat, this is merely to certify that they are of the priestly caste of scientists, wearing one merely certifies that “I know more than you do” and “you are not qualified to judge me”. It does not, in any way, mean that they actually go into any labs, that would involve actual experiments with messy real life stuff, and we don’t want that!
BTW, you have not given up your wicked ways, no one is fooled for a minute. Your a heretic, and you can’t get more wicked than that!
Note also, unlike what some people said, I don’t care if you are obnoxious, say something I don’t like, or otherwise seriously butthurt me (exactly how does ones words on a furum like this one actually hurt anyone?), all I care is, is the science helping us understand actual reality, or at least leading us closer to it than we were before? If you are, I will read it, no matter how it butthurts me, and the other guys and his unreality, well, I don’t care how nice and luvy-duvy he is, if it ain’t reality I don’t care.

Scott Covert

Error bars, we don’t need no stinking error bars…
We’re saving the planet! /sarc

Robert S

Another rubbish item from Nature climate change:
“Rapid growth in CO2 emissions after the 2008 – 2009 global financial crisis.” Jan 2012 vol 2 No1.
…and another from Jan 2012 – ” Islands, resettlement and adaptation.” Concerning resettlement of people living on islands in anticipation of climate impacts ……
….and another – “An energy revolution.” Meeting agreed targets for the decarbonization of Europe’s energy sector…. by the blue sky greenies.

Septic Matthew

must be a better way to do science,
You could join AAAS and help to defray the costs of publication. Also, authors will frequently send you a copy of a paper if you request it.
It’s a modeling result, like Columbus’ prediction that he could get to India by sailing around the world. It will take longer to test, and there may be surprises along the way, but it’s not unscientific.

Nick Shaw

“28 color glossy photos with circles and arrows and a paragraph on the back of each one”
Thanks Willis! I imagine that provoked a lot more than my one belly laugh!
My only hope is the perps in this case have to do more than just pick up the garbage!
After you posted the first line of the study, I knew it wasn’t worth reading if it had more than two more lines and they would be, “Warming promotes bio-diversity, as does CO2. Cooling, not so much.”
That’s it. That’s all that needs to be said about that, Forest. 😉

John F. Hultquist

“28 color glossy photos with circles and arrows and a paragraph on the back of each one”,
And do recall that the judge in the case was blind. Seems fitting!
As this song relates to the “draft” – young folks may not understand it. Also, the length of the song is exactly the same as the missing minutes on Nixon’s white-house-tape. Arlo did an update wherein he explained this coincidence.

Urederra

It is not the first time I see this kind of papers where they take the output from one computer model and they feed into another computer model, and then they discuss how bad the output of the second model is.
If you cannot tell the difference between computer output and empirical data then you do not have the right to be called a scientist.

Bruce Friesen

Let’s hope for a “case of American blind justice, and there wasn’t nothing he could do about it” – that no one will look at all the glossy colour photographs, or, at least, not be distracted by them!

Owen in GA

So if I write some computer code to show a set outcome then run the code and it gives me the predicted outcome, that only proves that I am a good programmer, it doesn’t say a thing about the real world. I propose this team be given a Nobel Prize in Computer Programing and perhaps a Hugo Award for creative science fiction in creating new fantasy worlds.

Owen in GA

I sometimes feel that most climate scientists are frustrated Hugo nominees.

Stephen Skinner

Another good read. The problem of looking at proxies of the outside world as if they are the real world is all pervasive.
I would like to add this excerpt from Flight International regarding Automation and accidents.
‘Robert Scott, of Scott Consulting, described one facet of this modern problem (automation). The system he said, is increasingly producing pilots incapable of dealing with the unexpected.
The intellectual and physical skills once required of the pilot have largely been replaced by an emphasis on ‘soft skills’ and automation management. The pilot who once cynically challenged sources of information now readily accepts information from a variety of sources, many computer generated without question”.
And this regarding sat navs:
Lorry gets stuck after following sat-nav directions
http://www.bbc.co.uk/news/uk-15395200
A lorry driver, following a directions from his satellite navigation system, caused the 24-hour closure of Bruton high street in Somerset after his vehicle became wedged in a narrow street.
After several attempts to release the lorry it was eventually freed, damaging a 300-year-old house in the process.
Obviously questioning or being skeptical is just unfashionable, whereas it used to a core skill, at least to pilots.

Gary

Surely a nominee for the Hugo Award
http://www.thehugoawards.org/

UK dissenter

“So let me simply say that this is an example of post-normal, post-reality climate “science” and peer-review at its worst… Sadly, this is all too typical of what passes for climate science these days, models all the way down.”
Willis – another blinder of a review. I love your term Computer Generated Reality (CGR). It’s infected many sciences, but it at its worst in so-called climate science.
And your comment that it’s “models all the way down” is a lovely riff on Pratchett’s “Small Gods” infinite regress. That the world sits on the back of a large turtle, and below this one, “it’s turtles all the way down”. As you astutely point out, for climate ‘scientists’ it’s models all the down. Desperately sad, but desperately true.
Congratulations on spotting, and beautifully filleting another load of computer-generated tripe.

Theo Goodwin

Brilliant and hilarious essay, Willis. Full of many wonderful zingers. My favorite the following zinger paragraph:
“But it’s not bad enough that they have forsaken studying real ecosystems for investigating cyberworlds. In addition, they are asserting a special exemption from normal scientific practices, specifically because they have built their study, not on the rock of solid scientific investigation of the real world, but on the shifting sand of conclusions based on their CGR world. It reminds me of the guy who kills his parents, and then wants special treatment because he’s an orphan … you can’t choose to study CGR, and then claim that the fact that you are not studying actual reality somehow exempts you from the normal requirements of science.”
Given the revelations (to some) that Willis produced, does anyone really want to defend this use of models in science? Defend it as science, I mean. Does anyone want to defend the body of scientists for not slamming the kind of “work” that Willis describes? Will Al Gore defend it? Will an editor from Science magazine defend it? I would really like a debate on this. Any takers? Trolls need not apply.

Roger Knights

Mark Hladik says:
January 20, 2012 at 11:38 am
Paragraph 10 ( if I counted right ), second sentence:
“pored” = poured ?

pore n. 1 to gaze at or study with steady continued attention and application. 2 to meditate or study patiently and persistently.

Stephen Skinner

Quote from Nikola Tesla:
“Today’s scientists have substituted mathematics for experiments, and they wander off through equation after equation, and eventually build a structure which has no relation to reality.”

Dr Burns

They should have also modelled a farmer using a greenhouse and pumping CO2 in, to warm and nourish his plants so as to kill them, as is commonly done.

Theo Goodwin

Septic Matthew says:
January 20, 2012 at 11:49 am
“It’s a modeling result, like Columbus’ prediction that he could get to India by sailing around the world.”
Would you care to explicate the word ‘prediction’ as you used it above and show that it meets the standards of scientific method?

ShrNfr

What we need is “blind justice”, the judge with the “seeing eye dog”….

TANSTAAFL

“When I was a lad this stuff used to be called science fiction.”
Science fiction writers use actual science.

CGR or “computer-generated reality”, also know as the Holo deck in Star Treck http://en.wikipedia.org/wiki/Holodeck I wish they could find a way to transport the gophers and moles from my property to their CGR.

Interstellar Bill

The Cabal’s peer-reviewed avalanche is nearing full climax,
their sewage flooding the intellectual landscape
in preparation for the next round of IPCC lies.
Expect papers this bad or worse to be spewing forth daily.
The first principle of Post-Normal Science is from Goebbels
Tell the Lie over and over and over and over, never ceasing,
ever louder, ever shriller, for decades to come.

Theo Goodwin

Owen in GA says:
January 20, 2012 at 12:05 pm
“So if I write some computer code to show a set outcome then run the code and it gives me the predicted outcome, that only proves that I am a good programmer, it doesn’t say a thing about the real world.”
Very well said. The entire internet could benefit from commenters who understand computer programming. Willis’ CGR is a rather good analogy for the latitude that computer programmers have for rigging their results. If scientists are to use computer models for what they call “prediction,” then they have a duty to explicate fully and clearly how their modeling results can be constrained by empirical research in the real world. Science publishers, so-called, such as “Science” should place the same requirements on all articles. Funding agencies, such as NSF, should do the same. Otherwise, all we get is the pie-in-the-sky that Willis reveals.