People send me stuff. This one reminds me of a famous wrong way:
Hi Anthony
Today we had some rumour in the Dutch media due to a paper by a couple of econometricians which projected dramatic warming. Ross McKitrick discovered they had used a wrong dataset; We blogged about here: http://climategate.nl/2010/03/09/four-degrees-warming-in-2050-oops-you-used-the-wrong-dataset/It would be nice if you could post it on WUWT as well,cheersMarcel CrokScience writer
This morning, there was lot of noise in the Dutch media (unfortunately in Dutch only) about new research that was claiming a dramatic warming of 4 degrees in 2050. The news report quoted Dutch econometricians from the University of Tilburg. They had done a statistical analysis of temperature data and the influence of CO2 and solar radiation and concluded that aerosols masked much more of the warming of greenhouse gases than previously thought. This also means there is more warming in the pipeline for the future if the trend of global brightening, that has been detected by researcher Martin Wild of ETH in Zürich, will continue in the coming decades. They also draw policy conclusions from their research stating that in order to avoid more than 2 degree warming more drastic measures are to be taken. This news was copied by many Dutch news outlets.
Detection
Although at first I could not figure out if there was a paper behind the news article and whether or not it has been accepted for publication (I still don’t know), I finally determined it had to be this paper: http://center.uvt.nl/staff/magnus/wip04.pdf
I decided to pass the paper on to Ross McKitrick, who, as many of the readers know, published two interesting papers (here and here) on the influence of different economic parameters on the pattern of warming at the surface. Within hours McKitrick came back with an interesting finding which makes any detailed discussion on the paper let’s say… irrelevant.
Remember, their study is an attribution study depending on long term trends in temperature measurements. For their study they use a rather obscure CRU dataset: CRU TS 2.1. You can find its documentation below. The webpage reads:
The CRU TS 2.1 data-set comprises 1224 monthly grids of observed climate, for the period 1901-2002, and covering the global land surface at 0.5 degree resolution. There are nine climate variables available: daily mean, minimum and maximum temperature, diurnal temperature range, precipitation, wet day frequency, frost day frequency, vapour pressure and cloud cover.
Read the documentation
There is also a peer-reviewed paper behind CRU TS 2.1: Mitchell and Jones, International Journal of Climatology, 2005, so that’s OK. However, if the authors had just cared to go through this webpage in some detail, they would have found a link to this page:
It says:
Q1. Is it legitimate to use CRU TS 2.0 to ‘detect anthropogenic climate change’ (IPCC language)?
A1. No.
CRU TS 2.0 is specifically NOT designed for climate change detection or attribution in the classic IPCC sense. The classic IPCC detection issue deals with the distinctly anthropogenic climate changes we are already experiencing. Therefore it is necessary, for IPCC detection to work, to remove all influences of urban development or land use change on the station data.
In contrast, the primary purpose for which CRU TS 2.0 has been constructed is to permit environmental modellers to incorporate into their models as accurate a representation as possible of month-to-month climate variations, as experienced in the recent past. Therefore influences from urban development or land use change remain an integral part of the data-set. We emphasise that we use all available climate data.
If you want to examine the detection of anthropogenic climate change, we recommend that you use the Jones temperature data-set. This is on a coarser (5 degree) grid, but it is optimised for the reliable detection of anthropogenic trends. For precipitation trends, use the Hulme data-set (5 degree grid or 2.5 x 3.75 grid). There are few alternatives to Hulme in the first half of the 20th century; later, to include the oceans use the Xie and Arkin data-set; for the last 25 years you could also use the GPCC data-set.
Yikes. This dataset is not to be used for the type of study performed by these econometricians. Never. Period. Don’t use it. Lies, damned lies, statistics and very sloppy science.
Its not “very sloppy science”. Economists and their ilk ARE NOT SCIENTISTS!!!!
But how can it be possible to model such a chaotic system as climate? Isn’t climate the ultimate chaotic system? Is it possible to model chaotic systems?
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No .
“Chaotic system” and “model” are antinomic . Chaotic systems , despite the fact that they are strictly deterministic (most people think they are random what they definitely are not) , cannot be predicted beyond a finite rather short horizon . It is even their defining property .
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Weather is chaotic therefore can’t be predicted and will never be predicted regardless the power of the computers beyond a horizon of a few days .
It is , per definition , also impossible to simulate them numerically beyond the horizon .
These are well known and mathematically proven properties of chaotic systems .
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Now there exists a class of chaotic systems that have a property of ergodicity .
While they can’t be predicted like every other chaotic system , there exists a unique PDF (probability density function) that gives the distribution of the dynamical states in the phase space in the infinite time limit .
Such systems have a kind of statistical “predictability” over very long times .
Ergodic systems are mostly found only in temporal chaos (e.g systems with no spatial autocorrelation) as opposed to spatio-temporal chaos like clouds and fluid flows .
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Now climate is a spatio-temporal chaotic system at all time scales and spatio temporal systems are generally NON ergodic .
Non ergodic systems can’t be predicted with any reasonable accuracy even statistically over long times .
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So yes you are absolutely right : the Earth’s ocean-atmosphere-cryosphere dynamical system may be viewed as an example of an “ultimate” chaotic system .
Being Dutch I also read the article in the press. The most amazing thing about it is that the modellers should immediately have rejected their results on the basis of the most basic sanity check. The results simply do not make any sense in view of actual climate stability and cycles observed. Economics is not a science and no meaningfull understanding of anything has been gathered since Adam Smith, it is based on rather dodgy ceteris-paribus reasoning, economists generally adhering to one school or another, sticking to their right, irrespective of observations to the contrary. This is much like climatology – we know the theory is right- its just the bloody climate that messes up all the time. Still a real pain that my tax payer money is wasted on this kind of propaganda.
Have a look at figure 2 in the paper: the highest temperature happens in 1990; 1998 is 2nd, 1999 3rd, and 1994 4th. That’s not the usual order.
Alexander Vissers (01:31:41) :
“Economics is not a science and no meaningfull understanding of anything has been gathered since Adam Smith,..”
David Ricardo – comparative advantage? Frederic Bastiat – candlemaker’s petition?
Maybe it’s time for a real science of the climate to emerge. It should be called “climatonomy”.
After all, we have astrology versus the real thing: astronomy.
Looking back, there was a big clue in the name “climatology”.
“Pamela Gray (18:25:06) :
Ah. This would be a gray paper then? We know how that turns out. AGW researchers still email nasty stuff to each other about contrarians and get papers published on the net or their comments quoted in magazines, in shades of gray, as if they haven’t been noticing the 700 lbs gorilla in the room.”
Your gorilla appears to have been on a diet, since all the anecdotal gorillas that I have read about in the past were 800lbs or above.
Homogenising the data does not account for your discrepancy and sadly I must conclude that you are displaying all the signs of negative feedback syndrome. Please re-weigh your gorilla and express the result as an anomoly.
No gorillas have been hurt in this posting.
Wren (22:53:26) :
As the authors of the paper say:
“What matters is whether small deviations from our assumptions will cause large or small changes in our conclusions.”
What matters is that they used a dataset specifically labeled “Do not use for climate change detection because you’ll get skewed results” and used it for — *sigh* — climate change detection.
Their assumptions are based on skewed results, and their conclusions are based on those assumptions.
It’s like me taking a topical medication for a skin rash — say, hydrocortisone cream — labeled “Not for internal use” and eating it, then concluding that, as a topical medication, it’s useless, because it didn’t improve the rash, and adding that the only thing that could affect my conclusion would be whether or not I chewed the medication before I swallowed it.
roger (03:12:46) :
Your gorilla appears to have been on a diet, since all the anecdotal gorillas that I have read about in the past were 800lbs or above.
Homogenising the data does not account for your discrepancy and sadly I must conclude that you are displaying all the signs of negative feedback syndrome. Please re-weigh your gorilla and express the result as an anomoly.
The 800-pound gorilla may itself be anomalous, based on Primary Source information acquired by multi-decadal association with users of the phrase “900-pound gorilla,” or NHPG, generally as the subject of the inquiry “When a NHPG walks into the room, where does he* sit?”
*raw observation of sexual dimorphism in gorillas adjusted by a factor of 1.5 to clarify that the interlocutor can only be speaking of a male.
Arn Riewe (16:33:02) :
I certainly know of economists, but can someone please tell me what an econometrician is?
These are close cousins to the elite economic PHDs and MBAs who convinced the world that Liar (NINJA) mortgage loans were safe to package and leverage at up to 60 to one.
‘Econometricians’ don’t have a Guild Master yet, all the practioners today are novice apprentices. Wait 200 years and you’ll see some ‘real’ stuff.
The study was actually lead by a good econometrician (Magnus, from UvT).
The data issues are indeed problematic, and it is quite awkward that they failed to notice this problem.
There is however, in my humble opinion, another potential problem with the study. They find an autoregressive term close to 1 (namely 0.91). Given that most authors conclude that temperature series are integrated of the first order, this should raise a red flag (i.e. the series contains a unit root, which, loosely put, implies that teh AR term is equal to 1, making regular inference invalid).
They do not even mention unit roots in their paper.
I do have to repeat that Magnus is a respected scientist, so all of this is highly awkward. However, I also have to add that I was a bit dismayed with how the paper started out:
“The Earth is getting warmer and much or all of this process is generally believed to be caused by humans. It is possible that humanity is about to face the most serious catastrophe since the Bubonic Plague in the fourteenth century killed 35 million people in Asia and half the population of Western Europe. Death from the plague was horrible, but swift. In The Decameron, Giovanni Boccaccio writes that victims often ‘ate lunch with their friends and dinner with their ancestors’. Global warming is not as swift, but its consequences could be no less horrible. There is much uncertainty about global warming. The purpose of this paper is to investigate the statistical evidence, using econometric panel data techniques.”
…. doesn’t sound as ‘impartial’ as an econometrician / statistician ought to be.
P.S. For those wondering: econometrics is the discipline of hypothesis testing using non-experimental data/observations. The issues it deals with are e.g. sample selectivity, unit roots in time series, clustered volatility, etc etc etc, and other non-experimental issues complicating (or even invalidating) statistical inference.
It was first developed by Gauss in the form of Ordinary Least Squares, for the purpose of calculating the parameters of planetary orbits. Calculating a linear ‘trend’ is in fact the most simple form of ‘econometrics’.
The field has grown exponentially since Jan Tinbergen (first Nobel laureate, economics, together with another econometrician Ragnar Frisch) basically set it in motion.
The term itself is quite misleading, because this is general ‘metrics’ we are talking about, rather than ‘statistics applying solely to economics’.
There was a post here on WUWT a few weeks ago, on a study by Beenstock and Reingewertz (two econometricians), who also apply (in their case different) statistical / econometric methods to evaluate the AGWH.
They however reject any long term relationship between CO2 and temperatures (and they take extreme care to ensure that the unit root issue I outlined above is dealt with).
It will always be the same , this is the wealthy supporting the mighty or the other way around , if you keep them dumb we shall keep them poor . Is this the name of the agw-game ?
“They had done a statistical analysis of temperature data and the influence of CO2 and solar radiation and concluded that aerosols masked much more of the warming of greenhouse gases than previously thought.”
That is the real fault of this study. Using the wrong data set is one thing, but we should not recognize it as good science if they use the ‘right’ data set. The sentence above reveals this paper to be a classic case of building assumptions upon assumptions and then stating conclusions as if they were facts.
What is the influence of solar radiation and CO2? The IPCC assumption is that the change in solar is very small and diminishing slightly. They only look at total irradiance and give no heed to a possible cosmic ray influence. The CO2 effect is assumed to be very large with strong positive feedbacks. They state that there are no other significant influences on global temperature during the time studied, according to the IPCC, for they go to great effort to ignore all of the internal variations in climate, mainly derived from ocean cycles.
Given these extremely bad assumptions, it is impossible to explain the mid 20th Century cooling! (It is easy to explain if you recognize the obvious influence of ocean cycles.) So they had to make something up.
The mid 20th century was not a good time for clean air in the industrialized western nations. Europe and the US had a lot of smoggy cities. In the 1970s and 1980s things started to improve in the west, but things started to get worse around Asia. Today we have the infamous brown cloud of aerosols originating in India and China and impacting a good part of the Northern Hemisphere.
How does the climate impact of the aerosols of today compare to the impact of the mid 20th Century? NO ONE KNOWS! There is still a debate as to whether these aerosols produce a net warming or cooling effect. Furthermore, we have no data on the 20th century pollution. It was not measured in any meaningful way. There were no satellites tracking the smog or monitoring its effects. Today the smog is concentrated in a different part of the globe, but is it really much different than 60 years ago? Again, no one knows.
Also, it is very damning to note that the mid-20th Century Southern Hemisphere cooled in lock step with the Northern Hemisphere. There was no smog in the south, so aerosols can not be used to explain the cooling there. The most likely answer is that the earth cooled 60 years ago because of the cool phase of the Pacific Decadal oscillation and that aerosols had little, it anything, to do with it.
But what do you do if you ignore the ocean cycles and potential cosmic ray effects, assume CO2 is the primary driver of climate, and all other impacts were minor? You get a theory that is completely at odds with the available data, UNLESS you can throw in a ‘Deus ex machina’ wild card! Aerosols, my friend. Just give them any trait you want to make your models work. You need cooling…they give you cooling (just don’t look at the Southern Hemisphere. Nothing to see there!). Give them any value you need, because nobody really knows what they do. And, as a special bonus, you can force the made up numbers to give a ‘its worse than we thought’ conclusion.
It is not science. It is insanity!
Doh!
Econometrics it’s stochastical !!!☺
While dutchs living in europe worry about year 2050′ s climate and plant windmills instead of tulips, their businessmen, practical people, have taken all their businesses to asia. Keep on dreaming babes! if you wake up you’ll find yourselves with nothing to eat.
fred wisse (06:20:08) :
It will always be the same , this is the wealthy supporting the mighty or the other way around , if you keep them dumb we shall keep them poor . Is this the name of the agw-game ?
REPLY:
Of course it is. CAGW is about funding a nondemocratic world government. The wealthy and powerful are not happy with democracies or national borders that interfere with trade. You will note the progressive shift to nondemocratic leadership in the last thirty years. A classic example is this from the United States FDA website:
International Harmonization: http://www.cfsan.fda.gov/~comm/int-laws.html
“The harmonization of laws, regulations and standards between and among trading partners requires intense, complex, time-consuming negotiations by CFSAN officials. Harmonization must simultaneously facilitate international trade and promote mutual understanding, while protecting national interests and establish a basis to resolve food issues on sound scientific evidence in an objective atmosphere. Failure to reach a consistent, harmonized set of laws, regulations and standards within the freetrade agreements and the World Trade Organization Agreements can result in considerable economic repercussions.
Participation in:
Codex Alimentarius
Cosmetics International Activities
International Organizations and Standard-Setting Bodies
International Office of Epizootics
International Plant Protection Convention
World Health Organization
Food and Agricultural Organization
Joint FAO/WHO Expert Committee on Food Additives (JECFA)
Joint Meeting on Pesticide Residues
Joint FAO/WHO Expert Committee on Microbiological Risk Assessments
Pan American Health Organization
Organization for Economic Cooperation and Development “
The FDA is now taking its orders, not from the people of the USA but from the United Nations and the World Trade Organization. For Europe the EU does similar things.
Unfortunately any reference to the move away from democracy towards governing by the wealth is called a “Conspiracy Theory”
kadaka,
Random femur breaks – OMG that might just be the most disturbing thing I’ve ever read. If climatologists would put equivalent warning labels on their research as drug companies do, I’m pretty sure we wouldn’t be in this mess… but the Hansens and Schmidts of the world quite clearly aim to give the impression that everything is accounted for in errors bars, confidence intervals, flux, etc – and that they more or less have it all figured out. Statistics is no replacement for empirical understanding – we might be able to get away with it for drugs, but for trillion dollar investments that will negatively impact the lives of every man, woman and child on the planet (k, maybe everyone other than Gore amirite ; ) we should set the bar at least equivalent to drug manufacturing, if not much… much higher.
Juraj,
They appear to have taken a crap data set, surmised somehow that the shading/cooling effect of particulates was under estimated (meaning the CO2 effect already is, are you ready… everybody now… worse than we thought, and probably extrapolated a uniquely steep trend for CO2 and worst case scenario for particulates (i.e. we’ll clean up all those coal plants in the next 40 years but not shut any down). Note – this is all stuff already built into the IPCC projections… these guys just took it to (more) ridiculous orders of magnitude.
Sjoerd,
Wow… that’s not raw data then (as someone here was speculating), that’s something else all together. I wonder if this is an attempt at a temp record minus ENSO and irradiance (i.e. natural variability removed)? I could see how a climate modeler would find such a product useful. At the same time I could also see the need to put a big fat warning label on it because the idea of completely removing natural variability from the temp record is purely academic.
Loved this bit in the “A1” response:
[…] the Jones temperature data-set […] is optimised for the reliable detection of anthropogenic trends.
That’s a corker.
Gail Combs (06:53:51) :You are pointing to a real issue. Global Government it is already working, it didn’ t need any Copenhagen agreement on climate change. We are done unless taking a diverse type of action against those activities which daily affect individual lives, as the famous AH1N1 vaccine for a phantom illness called pig’s flu and made out from the year 2000′ s avian flu virus and which is provoking pregnant women deaths.
This is it! The “econometrics” of the leftist global revolution.
I was under the impression that aerosols were on the decline…
http://www.nu.nl is not real media. They don’t make their own news.
Leif Svalgaard (16:57:42) :
This is on a coarser (5 degree) grid, but it is optimised for the reliable detection of anthropogenic trends.
If so, no wonder they find some.
Eureka! My thoughts exactly.
@ur momisugly NickB. (07:04:48) :
The report was on ABC (US, not Aus.). Just now I Googled a new article from them. First four paragraphs:
I agree, it is disturbing. To summarize, as I have heard things, hormone replacement is not that good, calcium supplements don’t work (beyond minimum metabolic requirements that you can get with diet), and now the bone building drugs are not working all that great.
What does work is weight-bearing exercise, which convinces your body of the need for strong bones. With bone and muscle mass, even brains and cardio-pulmonary fitness, “use it or lose it” is the rule, and the body likes to fight back against attempts to tell it otherwise.