Bishop Hill Keenan's response to the BEST paper
Oct 21, 2011 Climate: Statistics Climate: Surface The Economist asked me to comment on four research papers from the Berkeley Earth Surface Temperature (BEST) project. The four papers were as follows.
- Decadal variations in the global atmospheric land temperatures
- Influence of urban heating on the global temperature land average using rural sites identified from MODIS classifications
- Berkeley Earth temperature averaging process
- Earth atmospheric land surface temperature and station quality
Below is some of the correspondence that we had. (Note: my comments were written under time pressure, and are unpolished.)
From: D.J. Keenan
To: Richard Muller [BEST Scientific Director]; Charlotte Wickham [BEST Statistical Scientist]
Cc: James Astill; Elizabeth Muller
Sent: 17 October 2011, 17:16
Subject: BEST papers
Attach: Roe_FeedbacksRev_08.pdf; Cowpertwait & Metcalfe, 2009, sect 2-6-3.pdf; EmailtoDKeenan12Aug2011.pdf
Charlotte and Richard,
James Astill, Energy & Environment Editor of The Economist, asked Liz Muller if it would be okay to show me your BEST papers, and Liz agreed. Thus far, I have looked at two of the papers.
- Decadal Variations in the Global Atmospheric Land Temperatures
- Influence of Urban Heating on the Global Temperature Land Average Using Rural Sites Identified from MODIS Classifications
Following are some comments on those.
In the first paper, various series are compared and analyzed. The series, however, have sometimes been smoothed via a moving average. Smoothed time series cannot be used in most statistical analyses. For some comments on this, which require only a little statistical background, see these blog posts by Matt Briggs (who is a statistician):
Do not smooth times series, you hockey puck!
Do NOT smooth time series before computing forecast skill
Here is a quote from those (formatting in original).
Unless the data is measured with error, you never, ever, for no reason, under no threat, SMOOTH the series! And if for some bizarre reason you do smooth it, you absolutely on pain of death do NOT use the smoothed series as input for other analyses! If the data is measured with error, you might attempt to model it (which means smooth it) in an attempt to estimate the measurement error, but even in these rare cases you have to have an outside (the learned word is “exogenous”) estimate of that error, that is, one not based on your current data.
If, in a moment of insanity, you do smooth time series data and you do use it as input to other analyses, you dramatically increase the probability of fooling yourself! This is because smoothing induces spurious signals—signals that look real to other analytical methods.
This problem seems to invalidate much of the statistical analysis in your paper.
There is another, larger, problem with your papers. In statistical analyses, an inference is not drawn directly from data. Rather, a statistical model is fit to the data, and inferences are drawn from the model. We sometimes see statements such as “the data are significantly increasing”, but this is loose phrasing. Strictly, data cannot be significantly increasing, only the trend in a statistical model can be.
A statistical model should be plausible on both statistical and scientific grounds. Statistical grounds typically involve comparing the model with other plausible models or comparing the observed values with the corresponding values that are predicted from the model. Discussion of scientific grounds is largely omitted from texts in statistics (because the texts are instructing in statistics), but it is nonetheless crucial that a model be scientifically plausible. If statistical and scientific grounds for a model are not given in an analysis and are not clear from the context, then inferences drawn from the model should be regarded as unfounded.
The statistical model adopted in most analyses of climatic time series is a straight line (usually trending upward) with noise (i.e. residuals) that are AR(1). AR(1) is short for “first-order autoregressive”, which means, roughly, that this year (only) has a direct effect on next year; for example, if this year is extremely cold, then next year will have a tendency to be cooler than average.
That model—a straight line with AR(1) noise—is the model adopted by the IPCC (see AR4: §I.3.A). It is also the model that was adopted by the U.S. Climate Change Science Program (which reports to Congress) in its analysis of “Statistical Issues Regarding Trends”. Etc. An AR(1)-based model has additionally been adopted for several climatic time series other than global surface temperatures. For instance, it has been adopted for the Pacific Decadal Oscillation, studied in your work: see the review paper by Roe [2008], attached.
Although an AR(1)-based model has been widely adopted, it nonetheless has serious problems. The problems are actually so basic that they are discussed in some recent introductory (undergraduate) texts on time series—for example, in Time Series Analysis and Its Applications (third edition, 2011) by R.H. Shumway & D.S. Stoffer (see Example 2.5; set exercises 3.33 and 5.3 elaborate).
In Australia, the government commissioned the Garnaut Review to report on climate change. The Garnaut Review asked specialists in the analysis of time series to analyze the global temperature series. The report from those specialists considered and, like Shumway & Stoffer, effectively rejected the AR(1)-based statistical model. Statistical analysis shows that the model is too simplistic to cope with the complexity in the series of global temperatures.
Additionally, some leading climatologists have strongly argued on scientific grounds that the AR(1)-based model is unrealistic and too simplistic [Foster et al., GRL, 2008].
To summarize, most research on global warming relies on a statistical model that should not be used. This invalidates much of the analysis done on global warming. I published an op-ed piece in the Wall Street Journal to explain these issues, in plain English, this year.
The largest center for global-warming research in the UK is the Hadley Centre. The Hadley Centre employs a statistician, Doug McNeall. After my op-ed piece appeared, Doug McNeall and I had an e-mail discussion about it. A copy of one of his messages is attached. In the message, he states that the statistical model—a straight line with AR(1) noise—is “simply inadequate”. (He still believes that the world is warming, primarily due to computer simulations of the global climate system.)
Although the AR(1)-based model is known to be inadequate, no one knows what statistical model should be used. There have been various papers in the peer-reviewed literature that suggest possible resolutions, but so far no alternative model has found much acceptance.
When I heard about the Berkeley Earth Surface Temperature project, I got the impression that it was going to address the statistical issues. So I was extremely curious to see what statistical model would be adopted. I assumed that strong statistical expertise would be brought to the project, and I was trusting that, at a minimum, there would be a big improvement on the AR(1)-based model. Indeed, I said this in an interview with The Register last June.
BEST did not adopt the AR(1)-based model; nor, however, did it adopt a model that deals with some of the complexity that AR(1) fails to capture. Instead, BEST chose a model a model that is much more simplistic than even AR(1), a model which allows essentially no structure in the time series. In particular, the model that BEST adopted assumes that this year has no effect on next year. That assumption is clearly invalid on climatological grounds. It is also easily seen to be invalid on statistical grounds. Hence the conclusions of the statistical analysis done by BEST are unfounded.
All this occurred even though understanding the crucial question—what statistical model should be used?—requires only an introductory level of understanding in time series. The question is so basic that it is discussed by the introductory text of Shumway & Stoffer, cited above. Another text that does similarly is Introductory Time Series with R by P.S.P. Cowpertwait & A.V. Metcalfe (2009); a section from that text is attached. (The section argues that, from a statistical perspective, a pure AR(4) model is appropriate for global temperatures.) Neither Shumway & Stoffer nor Cowpertwait & Metcalfe have an agenda on global warming, to my knowledge. Rather, they are just writing introductory texts on time series and giving students practical examples; each text includes the series of global temperatures as one of those examples.
There are also textbooks that are devoted to the statistical analysis of climatic data and that discuss time-series modeling in detail. My bookshelf includes the following.
Climate Time Series Analysis (Mudelsee, 2010)
Statistical Analysis in Climate Research (von Storch & Zwiers, 2003)
Statistical Methods in the Atmospheric Sciences (Wilks, 2005)
Univariate Time Series in Geosciences (Gilgen, 2006)
Considering the second paper, on Urban Heat Islands, the conclusion there is that there has been some urban cooling. That conclusion contradicts over a century of research as well as common experience. It is almost certainly incorrect. And if such an unexpected conclusion is correct, then every feasible effort should be made to show the reader that it must be correct.
I suggest an alternative explanation. First note that the stations that your analysis describes as “very rural” are in fact simply “places that are not dominated by the built environment”. In other words, there might well be, and probably is, substantial urbanization at those stations. Second, note that Roy Spencer has presented evidence that the effects of urbanization on temperature grow logarithmically with population size.
The Global Average Urban Heat Island Effect in 2000 Estimated from Station Temperatures and Population Density Data
Putting those two notes together, we might expect that the UHI effect will be larger at the sites classified as “very rural” than at the sites classified as urban. And that is indeed what your analysis shows. Of course, if this alternative explanation is correct, then we cannot draw any inferences about the size of UHI effects on the average temperature measurements, using the approach taken in your paper.
There are other, smaller, problems with your paper. In particular, the Discussion section states the following.
We observe the opposite of an urban heating effect over the period 1950 to 2010, with a slope of -0.19 ± 0.19 °C/100yr. This is not statistically consistent with prior estimates, but it does verify that the effect is very small....
If the two estimates are not consistent, then they contradict each other. In other words, at least one of them must be wrong. Hence one estimate cannot be used “verify” an inference drawn from the other. This has nothing to do with statistics. It is logic.
Sincerely, Doug
* * * * * * * * * * * *
Douglas J. Keenan
http://www.informath.org
From: Richard Muller
To: James Astill
Cc: Elizabeth Muller
Sent: 17 October 2011, 23:33
Subject: Re: BEST papers
Dear James,
You've received a copy of an email that DJ Keenan wrote to me and Charlotte. He raises lots of issues that require addressing, some that reflect misunderstanding, and some of which just reflect disagreements among experts in the field of statistics. Since these issues are bound to arise again and again, we are preparing an FAQ that we will put on our web site.
Keenan states that he had not yet read our long paper on statistical methods. I think if he reads this he is more likely to appreciate the sophistication and care that we took in the analysis. David Brillinger, our chief advisor on statistics, warned us that by avoiding the jargon of statistics, we would mislead statisticians to think we had a naive approach. But we decided to write in a more casual style, specifically to be able to reach the wider world of geophysicists and climate scientists who don't understand the jargon. Again, if Keenan reads the methods paper, he will have a deeper appreciation of what we have done.
It is also important to recognize that we are not creating a new field of science, but are adding to one that has a long history. In the past I've discovered that if you avoid using the methods of the past, the key scientists in the field don't understand what you have done. As my favorite example, I cite a paper I wrote in which I did data were unevenly spaced in time, so I did a Lomb periodogram; the paper was rejected by referees who argued that I was using an "obscure" approach and should have simply done the traditional interpolation followed by Blackman-Tukey analysis. In the future I did it their way, always being careful however to also do a Lomb analysis to make sure there were no differences.
His initial comment is on the smoothing of data. There are certainly statisticians who vigorously oppose this approach, but there have been top statisticians who support it. Included in that list are David Brillinger, and his mentor, the great John Tukey. Tukey revolutionize the field of data analysis for science and his methods dominate many fields of physical science.
Tukey argued that smoothing was a version of "pre-whitening", a valuable way to remove from the data behavior that was real but not of primary interest. Another of his methods was sequential analysis, in which the low frequency variations were identified, fit using a maximum likelihood method, and then subtracted from the data using a filter prior to the analysis of the frequencies of interest. He showed that this pre-whitening would lead to a more robust result. This is effectively what we did in the Decadal variations paper. The long time scale changes were not the focus of our study, so we did a maximum-likelihood fit, removed them, and examined the residuals.
Keenan quotes: "If, in a moment of insanity, you do smooth time series data and you do use it as input to other analyses, you dramatically increase the probability of fooling yourself! This is because smoothing induces spurious signals—signals that look real to other analytical methods." Then he draws a conclusion that does not follow from this quote; he says: "This problem seems to invalidate much of the statistical analysis in your paper."
He is, of course, being illogical. Just because smoothing can increase the probability of our fooling ourselves doesn't mean that we did. There is real value to smoothing data, and yes, you have to beware of the traps, but if you are then there is a real advantage to doing that. I wrote about this in detail in my technical book on the subject, "Ice Ages and Astronomical Causes." Much of this book is devoted to pointing out the traps and pitfalls that others in the field fell into.
Keenan goes on to say, "In statistical analyses, an inference is not drawn directly from data. Rather, a statistical model is fit to the data, and inferences are drawn from the model." I agree wholeheartedly! He may be confused because we adopted the language of physics and geophysics rather than that of statistics. He goes on to say that "This invalidates much of the analysis done on global warming." If we are to move ahead, it does no good simply to denigrate most of the previous work. So we do our work with more care, using valid statistical methods, but write our papers in such a way that the prior workers in the field will understand what we say. Our hope, in part, is to advance the methods of the field.
Unfortunately, Keenan's conclusion is that there has been virtually no valid work in the climate field, that what is needed is a better model, and he does not know what that model should be. He says, "To summarize, most research on global warming relies on a statistical model that should not be used. This invalidates much of the analysis done on global warming. I published an op-ed piece in the Wall Street Journal to explain these issues, in plain English, this year."
Here is his quote basically concluding that no analysis of global warming is valid under his statistical standards: "Although the AR(1)-based model is known to be inadequate, no one knows what statistical model should be used. There have been various papers in the peer-reviewed literature that suggest possible resolutions, but so far no alternative model has found much acceptance."
What he is saying is that statistical methods are unable to be used to show that there is global warming or cooling or anything else. That is a very strong conclusion, and it reflects, in my mind, his exaggerated pedantry for statistical methods. He can and will criticize every paper published in the past and the future on the same grounds. We might as well give up in our attempts to evaluate global warming until we find a "model" that Keenan will approve -- but he offers no help in doing that.
In fact, a quick survey of his website shows that his list of publications consists almost exclusively of analysis that shows other papers are wrong. I strongly suspect that Keenan would have rejected any model we had used.
He gives some specific complaints. He quotes our paper, where we say, "We observe the opposite of an urban heating effect over the period 1950 to 2010, with a slope of -0.19 ± 0.19 °C/100yr. This is not statistically consistent with prior estimates, but it does verify that the effect is very small...."
He then complains,
If the two estimates are not consistent, then they contradict each other. In other words, at least one of them must be wrong. Hence one estimate cannot be used “verify” an inference drawn from the other. This has nothing to do with statistics. It is logic.
He is misinterpreting our statement. Our conclusion is based on our analysis. We believe it is correct. The fact that it is inconsistent with prior estimates does imply that one is wrong. Of course, we think it is the prior estimates. We do not believe that the prior estimates were more than back-of-the-envelope "guestimates", and so there is no "statistical" contradiction.
He complains,
Considering the second paper, on Urban Heat Islands, the conclusion there is that there has been some urban cooling. That conclusion contradicts over a century of research as well as common experience. It is almost certainly incorrect. And if such an unexpected conclusion is correct, then every feasible effort should be made to show the reader that it must be correct.
He is drawing a strong a conclusion for an effect that is only significant to one standard deviation! He never would have let us claim that -0.19 ± 0.19 °C/100yr indicates urban cooling. I am surprised that a statistician would argue that such a statistically insignificant effect indicates cooling.
Please be careful whom you share this email with. We are truly interested in winning over the other analysts in the field, and I worry that if they were to read portions of this email out of context that they might interpret it the wrong way.
Rich
From: D.J. Keenan
To: James Astill
Sent: 18 October, 2011 17:53
Subject: Re: BEST papers
James,
On the most crucial point, it seems that Rich and I are in agreement. Here is a quote from his reply.
Keenan goes on to say, "In statistical analyses, an inference is not drawn directly from data. Rather, a statistical model is fit to the data, and inferences are drawn from the model." I agree wholeheartedly!
And so the question is this: was the statistical model that was adopted for their analysis a reasonable choice? If not, then--since their conclusions are based upon that model--their conclusions must be unfounded.
In fact, the statistical model that they adopted has been rejected by essentially everyone. In particular, it has been rejected by both the IPCC and the CCSP, as cited in my previous message. I know of no work that presents argumentation to support their choice of model: they have just adopted the model without any attempt at justification, which is clearly wrong.
(It has been known for decades that the statistical model that they adopted should not be used. Although the statistical problems with the model were clear, for a long time, no one knew the physical reason. Then in 1976, Klaus Hasselmann published a paper that explained the reason. The paper is famous and has since been cited more than 1000 times.)
We could have a discussion about what statistical model should be adopted. It is certain, though, that the model BEST adopted should be rejected. Ergo, their conclusions are unfounded.
Regarding smoothing, the situation here requires only little statistics to understand. Consider the example given by Matt Briggs at
Do NOT smooth time series before computing forecast skill
We take two series, each entirely random. We compute the correlation of the two series: that will tend to be around 0. Then we smooth each series, and we compute the correlation of the two smoothed series: that will tend to be greater than before. The more we smooth the two series, the greater the correlation. Yet we started out with purely random series. This is not a matter of opinion; it is factual. Yet the BEST work computes the correlation of smoothed series.
The reply uses rhetorical techniques to avoid that, stating "Just because smoothing can increase the probability of our fooling ourselves doesn't mean that we did". The statement is true, but it does not rebut the above point.
Considering the UHI paper, my message included the following.
There are other, smaller, problems with your paper. In particular, the Discussion section states the following.
We observe the opposite of an urban heating effect over the period 1950 to 2010, with a slope of -0.19 ± 0.19 °C/100yr. This is not statistically consistent with prior estimates, but it does verify that the effect is very small....
If the two estimates are not consistent, then they contradict each other. In other words, at least one of them must be wrong. Hence one estimate cannot be used “verify” an inference drawn from the other. This has nothing to do with statistics. It is logic.
The reply claims "The fact that [their paper's conclusion] is inconsistent with prior estimates does imply that one is wrong". The claim is obviously absurd.
The reply also criticizes me for "drawing a strong a conclusion for an effect that is only significant to one standard deviation". I did not draw that conclusion, their paper suggested it: saying that the effect was "opposite in sign to that expected if the urban heat island effect was adding anomalous warming" and that "natural explanations might require some recent form of “urban cooling”", and then describing possible causes, such as "For example, if an asphalt surface is replaced by concrete, we might expect the solar absorption to decrease, leading to a net cooling effect".
Note that the reply does not address the alternative explanation that my message proposed for their UHI results. That explanation, which is based on the analysis of Roy Spencer (cited in my message), implies that we cannot draw any inferences about the size of UHI effects on the average temperature measurements, using the approach taken in their paper.
I has a quick look at their Methods paper. It affects none of my criticisms.
Rich also cites his book on the causes of the ice ages. Kindly read my op-ed piece in the Wall Street Journal, and especially consider the discussion of Figures 6 and 7. His book claims to analyze the data in Figure 6: the book's purpose is to propose a mechanism to explain why the similarity of the two lines is so weak. In fact, to understand the mechanism, it is only necessary to do a simple subtraction--as my piece explains. In short, the analysis is his book is extraordinarily incompetent--and it takes only an understanding of subtraction to see this.
This person who did the data analysis in that book is the person in charge of data analysis at BEST. The data analysis in the BEST papers would not pass in a third-year undergraduate course in statistical time series.
Lastly, a general comment on the surface temperature records might be appropriate. We have satellite records for the last few decades, and they closely agree with the surface records. We also have good evidence that the world was cooler 100-150 years ago than it is today. Primarily for those reasons, I think that the surface temperature records--from NASA, NOAA, Hadley/CRU, and now BEST--are probably roughly right.
Cheers, Doug
From: James Astill
To: D.J. Keenan
Sent: 18 October 2011, 17:57
Subject: Re: BEST papers
Dear Doug
Many thanks. Are you saying that, though you mistrust the BEST methodology to a great degree, you agree with their most important conclusion, re the surface temperature record?
best
James
James Astill
Energy & Environment Editor
From: D.J. Keenan
To: James Astill
Sent: 18 October 2011, 18:41
Subject: Re: BEST papers
James,
Yes, I agree that the BEST surface temperature record is very probably roughly right, at least over the last 120 years or so. This is for the general shape of their curve, not their estimates of uncertainties.
Cheers, Doug
From: D.J. Keenan
To: James Astill
Sent: 20 October, 2011 13:11
Subject: Re: BEST papers
James,
Someone just sent me the BEST press release, and asked for my comments on it. The press release begins with the following statement.
Global warming is real, according to a major study released today. Despite issues raised by climate change skeptics, the Berkeley Earth Surface Temperature study finds reliable evidence of a rise in the average world land temperature of approximately 1°C since the mid-1950s.
The second sentence may be true. The first sentence, however, is not implied by the second sentence, nor does it follow from the analyses in the research papers.
Demonstrating that "global warming is real" requires much more than demonstrating that average world land temperature rose by 1°C since the mid-1950s. As an illustration, the temperature in 2010 was higher than the temperature in 2009, but that on its own does not provide evidence for global warming: the increase in temperatures could obviously be due to random fluctuations. Similarly, the increase in temperatures since the mid 1950s could be due to random fluctuations.
In order to demonstrate that the increase in temperatures since the mid 1950s is not due to random fluctuations, it is necessary to do valid statistical analysis of the temperatures. The BEST team has not done such.
I want to emphasize something. Suppose someone says "2+2=5". Then it is not merely my opinion that what they have said is wrong; rather, what they have said is wrong. Similarly, it is not merely my opinion that the BEST statistical analysis is seriously invalid; rather, the BEST statistical analysis is seriously invalid.
Cheers, Doug
From: James Astill
To: D.J. Keenan
Sent: 20 October 2011, 13:19
Subject: Re: BEST papers
Dear Doug
Many thanks for all your thoughts on this. It'll be interesting to see how the BEST papers fare in the review process. Please keep in touch.
best
jamesJames Astill
Energy & Environment Editor
A story about BEST was published in the October 22nd edition of The Economist. The story, authored by James Astill, makes no mention of the above points. It is subheaded “A new analysis of the temperature record leaves little room for the doubters. The world is warming”. Its opening sentence is “For those who question whether global warming is really happening, it is necessary to believe that the instrumental temperature record is wrong”.
Reader Comments (79)
BEST... strawman ever!
wow
WOW, buy popcorn - wholesale!
This is going to take some digesting, could be well above my pay grade but I will enjoy trying.
Green Sand,
I might pick up some popcorn when i'm out buying a new snow shovel this weekend
With Doug all the way here. The global gridded trends are in all likelihood roughly right (excepting GISS perhaps). If there was ever a reason to do another comprehensive series, it would be to address the logical structure of obtaining the land series from the thermometers. I guess BEST did not take the chance.
James Astill just waited for the punch-line, took it the way he wanted and wrote his piece. For him, the end message that likely emerged from the exchange was: 'there is a lot of disagreement, but in the end, things are just fine'.
The headline “A new analysis of the temperature record leaves little room for the doubters. The world is warming”, explains all.
Who doubts, or has ever doubted this planet has warmed over the past 150 years????
I suppose only straw-men do!
BEST was deliberately trying to blow-down a straw-man arguement, because that is all they realised they could do with the data at hand.
In the end this was not science, this was virtual science ............... and Judith Curry put her name to this.
Hands up all those who really believed that the BEST project was likely to have more than a tenuous link with reality?
Oh! I thought as much.
Pass me another couple of bottles of snake oil.
"Roll up folks! A rare chance to purchase a bottle of The Universal Panacea........."
"Global warming is real" a no-doubt carefully chosen phrase, given that years of brainwashing have given the casual observer (most people) the notion that Global Warming = Global Warming Caused By Humans.
I do not agree with the comment about applying statistics to smoothed data. I have been exposed to statistical signal processing for many years and have used it extensively. There is extensive theory in this area. It is correct to say that if you naively treat a time series with poorly thought out signal processing procedures and then you naively apply standard statistical techniques to the result, you will be wrong. The problem is that statisticians are not signal processers in my experience and, with the greatest respect, are not particularly comfortable with it.
just amazed that so many people in the media do not know that global temperature is not necessarily just the land temperature!
It's sort of tragic the self-knowledge inherent in 'We made no independent assessment of that'. If he understands that attribution is the real question, then it is tragic that he's allowing the use of his words and his work as he appears to be doing to denigrate scepticism.
Say it ain't so, Richard.
========
Doug and Bish - thanks for this backstory post. A sad indictment on the current state of journalism.
Doug - If indeed Mr Astill does "keep in touch", please can you ask him to expand on his closing sentence:
"That means the world is warming fast."
I'd like to know his benchmark for "fast" and how it compares to the present rate of change.
We should have known that the quiet phase where 'we were winning' that it would require some sort of coordinated onslaught from the panick-stricken meeja.
Unfortunately there are enough in our own ranks who do actually deny global warming at all for this straw man to stick, and it's easy to make people with such extreme views look foolish. The tactic of choosing a small subset and acting as if it's a representative enemy is akin to demonising all Germans because of the Nazis.
Godwins anybody?
This is great stuff - you're now climbing all over each other to claim that you all agree the planet's warming, and that's always been your opinion.
I wonder how long it'll be until you all start talking about "7 inches of global warming fell last night" just like a considerable number of you did last winter. Including Andrew Montford. The old, 'it's cold, therefore AGW is wrong' argument.
This blog has been littered with peope claiming that warming has stopped going back to the year dot. Nearly all of them unchallenged by their fellow posters. I'd make a fair wager that beyond the next couple of times, that the status quo will quickly resume, and claims for lack of warming will be allowed to sit here unchallenged.
Re: artwest
Control the language and you control the argument.
I happen to think that the planet has more than likely warmed over the past 150 years (or even the last 50) but if somebody where to say to me "Global warming is real" then I would disagree with them. The obvious troll like response they then come up with is: "So you don’t think the planet has warmed over the past 50 years then?". The problem is the context of the statement. It's fairly obvious that what they mean by "Global warming is real" is that is caused by human activity.
The same is true of climate change. I happen to think that the climate changes over any time scale you care to measure it on. I don’t think humans are the primary cause of it.
Damn. Mention trolls and one appears!!!
ZDB, sure it warmed, attributable to who knows what. Now it's cooling, also attributable to who knows what.
============
I think you're getting mixed up Zed. I've always been a lukewarmer. You do seem to have a problem treating people here as individuals with their own unique identities and opinions. You prefer to take every single posting as representative of all, it makes it easier to shove them into your itellectual gas chamber.
Briggs qutoing Muller:
"The temperature-station quality is largely awful. The most important stations in the U.S. are included in the Department of Energy’s Historical Climatology Network. A careful survey of these stations by a team led by meteorologist Anthony Watts showed that 70% of these stations have such poor siting that, by the U.S. government’s own measure, they result in temperature uncertainties of between two and five degrees Celsius or more. We do not know how much worse are the stations in the developing world.
Using data from all these poor stations, the U.N.’s Intergovernmental Panel on Climate Change estimates an average global 0.64oC temperature rise in the past 50 years, “most” of which the IPCC says is due to humans. Yet the margin of error for the stations is at least three times larger than the estimated warming."
http://wmbriggs.com/blog/?p=4525
The USHCN data changes significantly when the effects of "homogenization" are removed and one works, instead, with the Time of Observation corrected raw data. Looking at individual state data a logarithmic correlation with population has an r^2 of about 0.14 for a significant number of individual states. (See for example Idaho .
Further if one looks at the different regions of the United States the rise in temperatures over the years is much more evident in the West Coast. There has been little temperature rise in the Middle states, and there was in the 1950's quite a drop in temperature along the East Coast.
I went and read the discussion thread way back in May. This is what I told BBD
"
That said, it is very well evident that the UHI cannot be the sole origin of all the warming that has been observed during the satellite period. Hand in hand however, it is not clear to me, (a) as to who actually believed this to be true (b) whether you have not simply assumed that disproving this rather artificial point would simply negate all meaningful effects, if any, of the UHI
"
The above question is not addressed by the Wickam and Curry (BEST) paper. One can look at the: "does the UHI affect global anomaly as measured currently' in any number of ways - one would probably get the same answer.
Thanks Doug - another clear explanation. If only the climatologists had paid attention in school...
The instant co-ordinated media blitz, with Muller's WSJ piece, the Economist article etc etc etc all hitting the streets within 24 hours (all based on an unpublished, non peer-reviewed, draft paper) - makes it crystal clear that the entire BEST project was a planned pre-Durban political stunt and that Anthony Watts was cynically duped into collaborating.
Bizarrely, though, Mullers admission that only 2/3s of locations show a warming trend and the other 1/3 show cooling seems to make "global" warming a bit of s stretch.
Combine with the assertion that UHI now works in reverse - I think there's a lot of entertainment to come out of this project yet.
One can obtain a general sense of Muller's tawdry, 'unbiased' approach to science from his web site: http://www.mullerandassociates.com/.
"GreenGov™ is a service offered by Muller & Associates for Governments, International Organizations, non profits, and other organizations that work with Government."
It is really an interesting paper, first of all because the main author seems to be of the opinion that the deniers, like me, are assuming that it hasn't been warming. More charitably, I suppose he's tried to identify the UHI effect in the signal and can't find it. As he will be good enough to show his data and workings others will check and confirm/challenge his results. Apart from that it shows a steady increase in temperature from 1800, I'm not sure which thermometer records he chose for that period, but they must have been scarce. I wonder why he didn't go further back, or indeed start further forward.
I am surprised that he thought that telling us it's getting warmer would rid us of our ridiculous scepticism, has he not been following the debate ( a euphemism for slanging match in this case) who precisely does he believe holds the view that it hasn't been warming? Anyone with half a brain knows that it's been warming and cooling since time immemorial. There are those who believe the temperature has always been the same, and should remain so, but that's caused by not mugging up on the facts.
In 2003 we had a very hot summer in Europe and some 4000 deaths were attributed to the heat, with one voice the assemble faithful blamed this on global warming, now they have to tell us that snow and cold winters are a sympton of global warming, to persuade our politicians to spend literally trillions of pounds on averting a crisis that only exists on the inside of climate models, and the brainless faithful.
If Doug Keenan is correct they've scored another spectacular own goal.
the raw data is crap and any studies done with said raw data will certainly not be scottish ...
If, as it seems, this study is based on the same set of temperature stations used by NASA GISS, NOAA and HadCru then it reflects all the same inconsistencies in the station count over the period covered. EM Smith pointed out in his analysis that this varied from a high of over 7000 to c1200 from 1990 on, with only c200 common between the pre and post 1990 periods. He claimed that this introduced a splicing artifact in the reported temperature trend around 1990. The Muir Russell and Oxburgh enquiries did not examine this, although the former was invited to do so. On this basis, I do not see how this study takes us much further forward, quite apart from the dispute over the appropriate statistical methods that should be applied.
I see ZedsDedHed is back with a stunning prediction.
I am sure that there are deniers who do not believe that the temperature of the Earth has changed. The Best study isn't wildly different from any other series, since they are using the same data.
I notice that the authors point out that the attribution of the temperature rise to human activity may have been overstated.
What Z doesn't appreciate is that there are some considerable and reasonable grounds for scepticism of the anthropogenic global warming hypothesis.
The hypothesis will not doubt either survive or disappear in the acid bath of experiement. In the latter case, I am sure there will other things for Z to worry about.
Doug:
Excellent piece of analysis. Muller is blowing smoke and sounds like a stock promoter: "I did it before and nobody said I was wrong, so I should be able to do it again." I suspect things are going to get really interesting at Judith's blog.
UHI This is what I always suspected from the sociopath warmists:
they "addressed" UHI by exacerbating it and lacing it deeper and further into their cherrypicked sites.
The Jones UHI paper on UHI in china is one more such thing. China is the last place to go study UHI as everything is in reverse and mixed up there compare to our western notions : rural is not really rural , cities are quite different from our cities , a rural site is where, you know, 2 million people live around who just bought a new oven and fridge ; cities is where they had their coke smelters which they are busy shutting down etc.
I just posted a link to Douglas Keenan's review comments at Climate Etc. I encourage Mr. Keenan to drop in at Climate Etc (Judith Curry's blog) and add his thoughts to the continuing discussion over there.
RG
Foxgoose
This may be intended to cast doubt on the globality of the MWP or the LIA and the conclusion is: "This time it's different" but it surely raises the question of to what extent you can properly talk about "global" warming.I'd be a bit wary of calling "dupe" at this point though Muller's behaviour does look questionable especially when you consider that if you can wrong-foot Fall et al you not only catch Watts in your net but Christy and Pielke Sr at the same time.
I've not commented before on the discrepancy between two-thirds of the stations and the other one-third because I haven't had time to check the links but I was aware that there was some doubt about the globality of warming.
It has always seemed to me that to talk about the earth's climate as a whole is a misleading concept since the climate in the south of France is different from Paris is different from the Alps is different from Lincolnshire is different from Northumberland is different from Edinburgh is different from the Scottish Highlands. And that's just 1,000 miles across Europe!
WUWT has a paper up by a Swedish climatologist from Lund University (http://tinyurl.com/3o2ddow):
If the global mean temperature for 2011 turns out to be 1C warmer than that for 1911 what does that actually tell you about the the earth's climate (always assuming that your 1911 measurement is accurate enough to be lost in the noise)?
Personally I don't think the BEST papers tell us anything we didn't know before. The press releases appear designed merely to knock down a straw man, namely that sceptics claim that the earth hasn't warmed in the last 100 years which is not the position of any sceptic I know. So there is a media blitz which gives the likes of Beddington the chance to say that the work "adds to the evidence about how climate change is happening" which it doesn't — Muller specifially does not draw any conclusions about the how or the why — and so far the papers have not even been published and reviews are still ongoing.
It will be interesting to see where this goes.
Best Paper itself - basically no one still knows the cause of warming, and they clearly show natural oscillations at work:
Paper:
http://www.berkeleyearth.org/Resources/Berkeley_Earth_Decadal_Variations
If the long-‐term AMO changes have been driven by greenhouse gases then the AMO region may serve as a positive feedback that amplifies the effect of greenhouse gas forcing over land. On the other hand, some of the long-‐term change in the AMO could be driven by natural variability,e.g. fluctuations in thermohaline flow.
In that case the human component of global warming may be somewhat overestimated.
@ Oldtimer & Mike Jackson - I tend to agree that Muller's work is effectively just a re-hash of dubious data, and put this in a comment on the 'BEST paper out' thread earlier today, mainly to flag up John Daly's summary of what's wrong with the surface record. The many stations he lists in his appendix certainly throw doubt on the warming being global (or alarming).
It will be interesting if Steve and Ross take a look at the statistical work. It may be that they will find a "Mullermatic" aboard this little vessel.
A mate of mine, sent me the BBC's link to this. Because they put the MBH98 Hockey Stick diagram next to it, he assumed that it proved that this was correct.
Is the pre-publication of BEST, the first part of a marketing campaign to publicise COP17?
Apparently, 30,000 delegates (again) are about to descend on Durban.
Or is the recent spate of MSM articles promoting BEST as the end of climate scepticism, simply another shrill alarmist shriek? Could it have gone through peer-review by 27th November? Was it pushed out sharpish as a response to the damning "Delinquent Teenager" in the weeks before COP17? Is there going to be a story at COP17? Is one being manufactured?
I thought the whole point of the BEST paper was to look carefuly at the collected data and validate that.
Have they validated the data?
Or did they validate the conclusions already drawn from the data?
So the small effect of SOLAR influence that is shown as noise on a straight line in the linear model is actually massively understated against the empirically evidenced solar cycle, or have I missed the point.
If I just completely accept the BEST analysis, and I'm not qualified to disagree, it still doesn't answer my basic quibble. The doomsday scenarios to which we are treated in the press tacitly equate all warming with CO2. Plainly (to me anyway) global temperature fluctuates. Some part of cooling periods and some part of warming periods will be 'natural' or 'from causes which have always been with us'.
Ten years ago warming seemed to be accelerating. The relatively stable period since would seem to indicate that some portion of that warming was 'natural' or from causes other than CO2. Acknowledgement of this is what I never see, and in fact much effort seems to go into producing papers which minimise natural fluctuation.
The final problem for me is the ludicrous cost/benefit of policy responses so far. When the carbon tax passed in Australia the other day a young fella was on TV saying "it feels like my wedding day and my 21st birthday all in one". In a past existence he would no doubt have been numbered amongst the flagellants, for all the effect that or this had. But the cry is ever "at least we're doing something".
Shub @ Oct 21, 2011 at 4:24 PM
Emphasis added:
Why are we still going back to UHI? It's not significant. Nobody is buying this anymore. Time to move on.
Doug Keenan says:
...implies that we cannot draw any inferences about the size of UHI effects on the average temperature measurements, using the approach taken in their paper.
It would seem that UHI was not adequately addressed, and so remains contentious.
Personally, the only people I see saying UHI is not significant are the proponents of catastrophic warming, other eminent scientists are suspicious of this statement and present good reasons UHI may be significant.
Why are Jones' CRU and Hansen's NASA calibrating (adulterating) the data all the time ?
why do they leave out thousands of sites ?
why stick to a 0.3% relevant observation (land surface) in the overall energetic system ?
why wld we hv to draw warming conclusions from a speck of the evidence actually?
BBd
I hv not read from you yet why you deem , scientifically, the land surface record to be relevant for the overlal system about 500 times bigger?
Do you hv any science for that?
a report (with names and a date between brackets) wld be very helpful.
thank you.
lol
I read through the UHI paper and was more than a little surprised that Muller et al apparently compared these two sets of stations:
"very rural" and "all (including very rural)". This procedure, comparing something to itself plus other stuff seemed odd.
How odd? Well, consider the following:
Imagine 5 "very rural" stations with average temps of +1,0,0,-1,1 for an average temp of 1/5=.2
Now consider 5 "not rural" stations with average temps of +2,+1,+3,0,-1 for an average 5/5=1.0
Quite a difference.
However that difference is reduced if you calculate the average of the "Not rural" plus the "very rural" which would be 6/10=.6
Now, obviously these are simplified made up values; but the point is that there was no need to add the "very rural" stations back into "the rest" if you are trying to compare trends. And, in fact, it appears to be a logical error.
also, while we r@ it , i wld like to no y a GEOMETRICAL average of temperatures and "anomalies", and their variation (inaccuracies) would be in ANY way representative to the calorific ("warming") content of a thermodynamical system as complex as earth.
if BBD could, please,
provide the peer reviewed articles (names and a date , preferably post 2000 , between brackets () )
thnks
much obliged
yah, BBD is in the habit of calculating 'the energy in the system' from thermometer readings.
You want to quantify UHI? Measure UHI.
UHI is but an argument as to what was the EXACT number of angels on the pinhead of the past.
The ending of the LIA and its consequences to the present day seem, to this non-climatologist, to be more of an issue!
Doncha love it when they do an analysis of the US temp records with raw data and announce that it is good and 2/3 are positive trend, THEN they do their temp series with all the data after filtering and their own Homogenization and special sauce to merge all those short records which adds very small warming??? Wonder if they did the adjustment for Shelter to MMTS changes right this time???
Check out this old thread with comments between MikeC and Steven Mosher. I never knew SM was a warmer before that!! He fought this like Nick Stokes!!!
http://rankexploits.com/musings/2010/a-cooling-bias-due-to-mmts/
> I reproduce it here with permission.
From whom?