James Delingpole Kludges Forth

I sometimes wonder whether James Delingpole writes just to wind people up, or whether he really believes what he is saying. For sure his “opinion pieces” if one may call validly them that, are full of shock ! And awe ! And blame ! And scandalous notions ! But if one strips away the outrage, is there anything really of substance there ? I suppose, on balance, that he puts way too much effort into his anti-science outpourings, so I guess he is serious about his stance, even if he’s way too crazed in his emotive language. Here he is falling once again for the Anthony Watts’ school of thought. Sensation gets the punters in, (at the last count over 2,800 comments), so I assume that his affronted manner is deliberate.

I’m sorry, it’s really tiring to read, but I think it’s instructive – about the state of climate change “scepticism” – or rather in this case “outright denial” – today. As a climate change denier, James Delingpole imitates his leaders in archetypal fashion. He focuses on a small proportion of all the reams and reams of global warming data, and ignores the bigger picture. Typical. He name calls and blames without any solid foundational evidence. And he gets to entirely the wrong conclusion without realising he’s gone badly wrong.

So, here’s a lesson for James Delingpole about global warming :-

1. The continential/contiguous states of the USA are not the whole world.

The temperature record of the continental/contiguous states of the United States of America (CONUS) in no way equates to overall global warming. There are other places in the world. You cannot extrapolate from the USA to the globe.

2. The surface station global warming data is not the only temperature data in the world.

There are records of ocean warming, for example, and measurements of temperature derived from satellite observations. Everything needs to have context to be seen in true relief.

3. Surface temperatures are not the most consistent measurement of global warming.

You have to go up a couple of kilometres to avoid surface wind effects, and localised heating from buildings and other infrastructure, before you can safely say you have overall consistency in your temperature readings. Surface station data needs treatment, or adjustment, or homogenisation.

[ Or as David Appell in his Quark Soup puts it, “Then there are the inconvenient facts that : (1) USA48 is 1.6% of the Earth’s surface area, and : (2) the trend of the USA48 lower troposphere, as measured by satellites as calculated by UAH, is 0.23 ± 0.08 °C from 1979 to present (95% confidence limit, no correction for autocorrelation). Satellite measurements almost completely avoid the urban heat island problem.” ]

James Delingpole claims, without any foundation whatsoever, “the National Oceanic and Atmospheric Administration (NOAA) – the US government body in charge of America’s temperature record, has systematically exaggerated the extent of late 20th century global warming. In fact, it has doubled it.”

No, James, that’s simply just not true. NOAA have not “systematically exaggerated” global warming temperatures. If you care to take a look at the actual research for once, you will find that the methods used to draw up analysis figures are rigorous, tested and verified. And peer reviewed. And actually published in a journal. Unlike Anthony Watts’ paper that you are bleating about :-



By contrast to NOAA’s integrity, let’s look a moment at what Anthony Watts has done, according to Tamino :-

“What Watts has shown is that he can get a lower warming trend for the continental USA than others get. All you have to do is systematically eliminate the data you don’t like, while ignoring things like station moves, instrument changes, and recording data at different times of day. Don’t you dare correct for known biases (unless of course doing so would make the estimate of global warming smaller)! And if the satellite data should be in better agreement with others than with yourself, don’t breathe a word about that.”

Ah. Cherrypicking. Where have we seen climate change deniers do that before ?

Yet more from James Delingpole, “But I think more likely it is a case of confirmation bias. The Warmists who comprise the climate scientist establishment spend so much time communicating with other warmists and so little time paying attention to the views of dissenting scientists such as Henrik Svensmark – or Fred Singer or Richard Lindzen or indeed Anthony Watts – that it simply hasn’t occurred to them that their temperature records need adjusting downwards not upwards.”

Actually, James, you’re wrong again. In fact the output of Henrik Svensmark, Richard Lindzen, Anthony Watts, Roger Pielke Sr, John Christy and a number of other climate change “sceptics” have indeed been paid attention to by the IPCC, the Intergovernmental Panel on Climate Change. For example, Svensmark in Chapter 2 of Working Group 1 of the Fourth Assessment Report, and Lindzen in Chapters 8 and 9 :-

http://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch2s2-references.html (Search “Svensmark”)
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch3s3-references.html (Search “Christy”, “Pielke”)
(Search “Lindzen”)
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch9s9-references.html (Search “Lindzen”)

In fact, some of these scientists have been contributing authors or even editors of the IPCC reports. Surprised ? You shouldn’t be, James. This is an academic spat you’ve waded into, with no intellectual equipment to help you comprehend what is going on.

So, Anthony Watts’ new paper is not yet peer-reviewed, and not published (and does not even have a fixed, agreed list of authors), and some have already started to pick it apart. Apparently, he has ignored certain crucial information about surface station temperature measurements :-


“Thus we now have three reasons, why the technical problems may cause a difference in the trends of the raw data: 1. Time of observation bias stronger in rural stations. 2. More problems due to the UHI [Urban Heat Island effect] in the bad stations. 3. Selection bias (bad/good stations at the end of the period may have been better/worse before). Sounds like the first two problems can be solved by homogenization. And the third problem is only a problem for this study, but not for the global temperature trend. Time for the Team Watts to start analyzing their data a bit more.”

Does the Anthony Watts data actually back up the claim made in the press release ?

“The new improved assessment, for the years 1979 to 2008, yields a trend of +0.155C per decade from the high quality sites, a +0.248 C per decade trend for poorly sited locations, and a trend of +0.309 C per decade after NOAA adjusts the data. ”

Well, it seems not.


“In his press release, Anthony Watts does not explicitly state that these trends are for raw data. The manuscript does state this important “detail”…” He lifts a table from Figure 17 of the Anthony Watts paper – and, correct me if I’m wrong, but the more “trustworthy” results are almost exactly that same as those from NOAA !

dana1981 and Kevin C on Skeptical Science, go so far as to say “Ultimately the paper concludes “that reported 1979-2008 U.S. temperature trends are spuriously doubled.” However, this conclusion is not supported by the analysis in the paper itself.” ! :-


To those who watch the development of climate change science closely, Anthony Watts’ revelations about surface station data problems are not exactly new :-

“In a previous survey, Watts found numerous problems with the placement of the monitoring stations, and a U.S. Government Accountability Report, published a year ago, found 42 percent of stations did not meet at least one standard regarding their location, such as being too close to extensive paved surfaces or obstructions such as buildings or trees. However, a study published in 2010 by NCDC researchers in response to these concerns, found no evidence that the temperature trend was inflated as a result, and other work has come to similar to conclusions, Gavin Schmidt, a climate scientists at NASA’s Goddard Institute for Space Studies, told LiveScience in an email. This is of course not the answer that Watts et al want to hear, and so they keep talking about it as if this work doesn’t exist,” Schmidt wrote. The controversy extends to a statistical process, called homogenization, which climate scientists use to correct for bias in the data, which Watts’ analysis says further inflates the warming trend. However, the homogenization methods used by NCDC have been heavily reviewed and ranked among the best internationally, according to Peterson. “There is no network in the world that does not have this problem, so scientists all over the world are working on this,” [NCDC Dr Thomas C.] Peterson said.”

And people appear to be used to unpicking and rebutting his claims. As @caerbannog666 tweeted, “How many lines of code does it take to prove Anthony Watts wrong? 65, if it’s python: http://skepticalscience.com/watts_new_paper_critique.html … (scroll down a bit for the code)”

Other self-styled climate change “sceptics”, such as Steve McIntyre and Roger Pielke Sr appear to be sliding away and distancing themselves from the Anthony Watts “pre-paper” – so why is James Delingpole so excited about it ? :-


Meanwhile, here’s real global warming data :-

And here’s what the mainstream climate change scientists made of Anthony Watts’ previous contributions :-


“Given the now extensive documentation by surfacestations.org [Watts, 2009] that the exposure characteristics of many USHCN stations are far from ideal, it is reasonable to question the role that poor exposure may have played in biasing CONUS temperature trends. However, our analysis and the earlier study by Peterson [2006] illustrate the need for data analysis in establishing the role of station exposure characteristics on temperature trends no matter how compelling the circumstantial evidence of bias may be. In other words, photos and site surveys do not preclude the need for data analysis, and concerns over exposure must be evaluated in light of other changes in observation practice such as new instrumentation. Indeed, our analysis does provide evidence of bias in poor exposure sites relative to good exposure sites; however, given the evidence provided by surfacestations.org that poor exposure sites are predominantly MMTS sites, this bias is consistent with previously documented changes associated with the widespread conversion to MMTS-type sensors in the USHCN. Moreover, the bias in unadjusted maximum temperature data from poor exposure sites relative to good exposure sites is, on average, negative while the bias in minimum temperatures is positive (though smaller in magnitude than the negative bias in maximum temperatures). The adjustments for instrument changes and station moves provided in version 2 of the USHCN monthly temperature data largely account for the impact of the MMTS transition, although an overall residual negative bias remains in the adjusted maximum temperature series. Still, the USHCN adjusted data averaged over the CONUS are well aligned with the averages derived from the USCRN for the past five years. The reason why station exposure does not play an obvious role in temperature trends probably warrants further investigation. It is possible that, in general, once a changeover to bad exposure has occurred, the magnitude of background trend parallels that at well exposed sites albeit with an offset. Such a phenomenon has been observed at urban stations whereby once a site has become fully urbanized, its trend is similar to those at surrounding rural sites [e.g., Boehm, 1998; Easterling et al., 2005]. This is not to say that exposure is irrelevant in all contexts or that adherence to siting standards is unimportant. Apart from potentially altering the degree to which a station’s mean value is representative of a region, poor siting in the USHCN may have altered the nature of the impact of the MMTS transition from what it would have been had good siting been maintained at all stations. Moreover, there may be more subtle artifacts associated with siting characteristics such as alterations to the seasonal cycle. Classification of USHCN exposure characteristics as well as observations from the very well sited USCRN stations should prove valuable in such studies. Nevertheless, we find no evidence that the CONUS average temperature trends are inflated due to poor station siting. Acknowledgments. The authors wish to thank Anthony Watts and the many volunteers at surfacestations.org for their considerable efforts in documenting the current site characteristics of USHCN stations.”

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