This QOTW is from MIT’s Dr. Richard Lindzen, from his response to critics on the WUWT post: Lindzen on negative climate feedbacks
…it has become standard in climate science that data in contradiction to alarmism is inevitably ‘corrected’ to bring it closer to alarming models. None of us would argue that this data is perfect, and the corrections are often plausible. What is implausible is that the ‘corrections’ should always bring the data closer to models.
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My choice also from Dr. Richard Lindzen:
“What ever the reason for the differences between tree ring or non tree ring temperature proxies,
it becomes evident, that choosing tree rings or not is the same as choosing a MWP or not. “
Was watching the Masters this weekend (golf) and noticed how all the trees are green in Georgia right now. Well I live in Ohio, all are trees are bare right now.
According to the alarmist if Ohio goes up 2 degree’s we will not be able to farm anymore, too many crop failures. Can people in Georgia grow food? It sure looks like it’s more than 2 degree’s warmer than Ohio.
You’d think that “errors” would be sorta kinda random, over the long haul, with the information being distilled from large amounts of data.
It seems odd to this non-scientist (except in a philosophical sense) that the “corrections are always in the same directions.
Furthermore, it seems to me that the need for corrections seems only to arise when the catechism is threatened.
The
correctionscorruptions will continue unabated,
unabashed.
How about “…when dealing with small temperature changes in a turbulent system, there is little appropriateness to dogmatism…”
http://www.ecoworld.com/features/2006/10/07/global-warming-facts/
How many grant-chasing climatologists and commentators are actually “climatautologists”, drawing the same convenient conclusions from contradictory ata?
Today’s misinformation wars might be creating an industry for future historians (and just imagine what is being destroyed in anticipation of the future audits).
I looked into the technical details of data homogenization awhile back. I was horrified to see the methodology employed and the impact on signals in raw time series.
It is only implausible if you don’t think that models are any good.
Personally, if the models, theory, and the majority of the available data sets say X, and one individual data set says Y, well, then, it doesn’t surprise me when it turns out that Y is wrong. The big examples I can think of are satellite based tropospheric cooling trends not agreeing with models or surface trends, ocean cooling in 2003 not agreeing with models or sea level rise measurements, etc.
Having said that, there are actually plenty of times that models have been corrected and changed. Models are continually being upgraded as our understanding of the underlying processes improve and our computational capacity increases. I can throw out a number of such things that have changed in the past few years: possible underprediction of Arctic ice retreat rates (despite the so-called recovery everyone here seems to talk about, ice levels are still under the ice levels expected a decade ago), possible underprediction of Greenland + Antarctic mass balance loss (a decade ago it was assumed that the mass balance loss would be zero over the century, whereas observations show continuing mass loss in both ice masses), overprediction of possible thermohaline circulation collapse (a decade ago it was a big worry – not so much anymore), all sorts of corrections on aerosol modeling, etc.
Lindzen seems a little bitter, possibly because he hung his hat on a bunch of faulty datasets and flawed theories. Now he seems to see conspiracy everywhere.
Another good one from Richard Lindzen
“Future generations will wonder in bemused amazement that the early 21st century’s developed world went into hysterical panic over a globally averaged temperature increase of a few tenths of a degree,and, on the basis of gross exaggerations of highly uncertain computer projections combined into implausible chains of inference, proceeded to contemplate a roll-back of the industrial age”
I was expecting book burning, not data remodeling.
Global Climate Rapid Alteration Program runs on richly remodeled data. The thing would ping on the real deal.
Here’s to you, Dr. Lindzen.
OT
Big change of pace for the Sydney Morning Herald
One of Australia’s foremost Earth scientists, Professor Ian Plimer, comes down hard on Climate modelling and alarmists.
http://www.smh.com.au/opinion/beware-the-climate-of-conformity-20090412-a3ya.html
Marcus:
“
LindzenMarcus seems a little bitter, possibly because he hung his hat on a bunch of faulty datasets and flawed theories.”There. Fixed it for you.
Here’s Prof. Freeman Dyson on the climate models:
I think I’d prefer to listen to Professors Lindzen and Dyson, rather than people who sit in their air conditioned buildings, tweaking their models and believing the garbage* that comes out.
[*The link scores the accuracy of GCMs. In a score of 1-8-2, for instance, the first number means the model got correct results, and the second number shows when the model was wrong. The third number means undetermined.]
Not just Richard Lindzen and Freeman Dyson but also Antonio Zichichi, who has said this :
“…models used by the Intergovernmental Panel on Climate Change (IPCC) are incoherent and invalid from a scientific point of view”
Who is Antonio Zichichi? President of the World Federation of Scientists, President of the Enrico Fermi Centre, discovery of Nuclear Antimatter.
about him :
http://www.ccsem.infn.it/em/zichichi/short_bio.html
“What is implausible is that the ‘corrections’ should always bring the data closer to models.”
That is only “implausible” if the models are assumed to a priori be incorrect.
If the models are, in fact, in the process of being proven correct then the data should trend towards supporting the models, and the corrections to bad data should be more in line with models than against them. This is exactly the behavior that would be expected if the models are right.
I don’t recall the exact quote. But there’s an old quip. To the effect. Allow me to adjust 1 or 2 variables. I can prove just about anything. Allow me to adjust one more. I can prove pigs fly.
Michael (12:47:10) : with your OT. Plimer also gave this speech 8 months ago :
(p.s., no offense charles moderator;) )
I imagine some day in the future, when after many years of deep study, a computer´s model is provided with all the real and actual data needed, the computer´s screen when providing the most waited for answer will read like this:
It’s the sun stupid!
Global Climate Rapid Alteration Program
G-CRAP…good one!
Lamont:
I’m re-posting this link just for you: click.
As you can see, the GCMs are almost always wrong.
Lamont (13:11:12) :
“What is implausible is that the ‘corrections’ should always bring the data closer to models.”
That is only “implausible” if the models are assumed to a priori be incorrect.
……
Not really.
It’s also implausible if your life’s experience tells you that you’re never totally right about everything.
If there were just one question under consideration, i.e. is it getting warmer? then what you say is true, but, in fact, there’s a host of corrections from SST to animal migration and never a one contradicts the orthodoxy.
That’s fishy.
Models can be shown to be correct only when the models work or accurately predict the future. Examples of the first crterion are the atom bomb and airplanes. Examples of the second are eclipses and tide tables. Climate models might be mathematically elegant but have not been shown to “work” nor to be predictive.
All these examples of substantiall corredt models required centuries of trial and errot (cf music of the spheres and Copenicus). Climate models are in their infancy and computers do not help.
Paul Vaughan (12:17:57) :
Today’s misinformation wars might be creating an industry for future historians (and just imagine what is being destroyed in anticipation of the future audits).
——————-
…. audits and depositions, whistleblowers and incriminating e-mails.
I just hope those clowns have not destroyed ALL the raw data. Future generations (or this one even) will need the real data to interpret correctly.
TYPOS: substantially correct
My apologies.
M.
One can only hope that there will be times when scientists can laugh at the agenda driven “science” of today.
It’s not yet, in the middle of it, so easy to laugh out loud, although it’s easy to see anyone laugh at this on distance.
Lamont, for any model eventually proven true, it is implausible that before it is proven true allcorrections in contrary data should bring the data closer to the models. This is pretty close to obvious, if you think about it. Science, and contrary data, are messier than that.
Which is why your post has to make the claim stronger in order to make it look false. The claim you take issue with in your post is quite different and stronger, namely the claim that it is implausible that most corrections should bring the data closer to the models (your “corrections to bad data should be more in line with models than against them”). That claim is indeed false. But not Lindzen’s weaker claim.
Lamont (13:11:12) :
This is exactly the behavior that would be expected if the models are right.
This is patently not true. It is only the behavior that would be expected if the data errors were a result of a systemic fault and not random. Whether the models are “right” or not is an irrespective point concerning data errors themselves.
That the models are not right sort of refutes that theory as well.
Mark