Climate skeptics confuse time and space

Climatologies — gridded datasets of,  for example, mean monthly or annual temperature or precipitation — are very useful in large scale ecological work. I use the World Ocean Atlas extensively in my work on marine climate proxies and the New et al (2002) data from the Climate Research Unit for work on terrestrial proxies. However, there are always variables that one might like to include in an analysis that are not available.

Beckmann et al (2014) fill one of these gaps with a UVB climatology derived from satellite data. UVB, which causes sunburn and skin cancer in humans, is ecologically important, with effects at various scales from physiological to population dynamics. This new climatology will be useful, not least to the EECRG’s PARASOL project.

Beckmann et al assess the amount of new information in their climatology by correlating it with existing climatologies for temperature and precipitation, both globally and locally. At the global scale they find that UVB correlates with mean annual temperature, but is otherwise largely independent of existing climatologies, and at a local scale the correlation between UVB and temperature can either be positive or negative because of topographic effects.

It was that finding that UVB correlates with mean annual temperature that excited the climate skeptics at the Hockeyschtick and WUWT. HS writes, and Watts copies:

A paper published today in Methods in Ecology and Evolution describes a new satellite dataset of solar UV-B radiation for use in ecological studies. According to the authors, “UV-B surfaces were correlated with global mean temperature and annual mean radiation data, but exhibited variable spatial associations across the globe.” The finding is notable, since climate scientists dismiss the role of the Sun in climate change by only looking at the tiny 0.1% variations in total solar irradiance [TSI] over solar cycles, ignoring the large variations in solar UV of up to 100% over solar cycles, and which according to this paper, correlates to global mean temperature. Thus, the role of the Sun and solar amplification mechanisms on climate is only at the earliest stages of understanding.

And both mislead their audience. Again. I guess that neither would have had access to the journal (nor do I – there are other means of getting papers), but a sentence in the abstract makes it very clear that this is a spatial rather than temporal analysis.

“We correlated our data sets with selected variables of existing bioclimatic surfaces for land and … ocean regions to test for relations to known gradients and patterns.”

Nick Stokes, undertaking his Sisyphean labour, pointed out that Watts was wrong. Needless to say, Watts has not corrected his article.

Beckmann et al (2014) glUV: a global UV-B radiation data set for macroecological studies. Methods in Ecology and Evolution 5, 372–383

About richard telford

Ecologist with interests in quantitative methods and palaeoenvironments
This entry was posted in climate, Fake climate sceptics, Peer reviewed literature, Silliness, solar variability, WUWT and tagged , . Bookmark the permalink.

8 Responses to Climate skeptics confuse time and space

  1. Fragmeister says:

    I notice that when Nick Stokes pointed out the flaw in Watts’s understanding, he was greeted with a sarcastic comment from Watts about pay walls and high priests. Can’t he pay for it himself, or one of his adoring flock? Of course not, they might find out something they’d rather not know.

    • Nick endures a lot at WUWT, yet manages to avoid being banned when he points out that Watts has got it wrong again.
      If Watts was really interested, all he has to do is ask the author for a copy. Most authors will send a pdf immediately.


    The post has been updated with this comment:

    Based upon the comment by Nick Stokes above regarding this paper:

    “The words you have highlighted from the abstract (in your title),
    “UV-B surfaces were correlated with global mean temperature and annual mean radiation data” have two possible meanings. We’re used to thinking of time correlation of spatial means. But it can equally mean spatial correlation of time means. Since they have cited a dataset of spatially distributed time mean temperatures, and used LISA to get the spatial correlations, it’s clear that they are using the second interpretation.”

    Nick was able to determine this from a read of the full paper, therefore, I requested confirmation and a copy of the full paper from the authors, received this morning. The authors confirm the paper shows a correlation between spatial UV-B and spatial mean annual temperature and that they did not test for temporal correlations. Thus, the abstract was incorrectly/misleadingly worded as finding

    “UV-B surfaces were correlated with global mean temperature”

    when it would have been more correct to state

    “UV-B surfaces were correlated with spatial mean temperature”

    as use of the term “global” to describe a spatial mean temperature is inappropriate.

    Thus, based upon the now-clarified, albeit inappropriate, wording of the abstract, the claim of this post that UV-B has been demonstrated to be correlated to “global mean temperature” is withdrawn.

    Nonetheless, there may or may not be a correlation between the two and it should be investigated for some of the following reasons:

    1. Solar UV varies up to 100% over solar cycles

    2. Solar UV greatly affects
    a) ozone production, which can also act as one of many solar amplification mechanisms
    b) temperatures of the stratosphere, mesosphere, and thermosphere
    c) photosynthesis and other large effects on the biosphere as shown by this paper

    3. UV is the most energetic portion of the solar spectrum, and penetrates the deepest into the ocean in comparison to the rest of the solar spectrum. Therefore, it has the greatest effect upon ocean heating compared to any other portion of the solar spectrum, and likely is more efficient in heating land as well.

    4. For these reasons, and others, the various portions of the solar spectrum can have vastly differing effects on climate and change far more than the TSI. It is woefully inadequate to dismiss this by only incorporating the tiny 0.1% changes in TSI in climate models.

    • I’m glad that you have realised you made a mistake and have corrected it. I note that Watts has not yet done so.

      The sentence that confused you, against the wealth of evidence in the abstract, keywords and supplementary material that this was a spatial analysis is only ambiguous if you have preconceived idea of what the paper is about. If they authors had a time series they would have written about time series and trends not about surfaces, and they would have published in a climate or geophysical journal rather than an ecological journal (if they had published about correlations in time between UV and temperature in such a journal it would be a major hint that something was wrong). Your suggested alteration is hopeless because the paper considers correlations at two spatial scales – global scale (hence global in that sentence) and at a local scale – and the patterns are different.

      • richard telford says, “Your suggested alteration is hopeless because the paper considers correlations at two spatial scales – global scale (hence global in that sentence) and at a local scale…”

        False: Email reply from the lead author of the paper confirms that my suggested alteration is in fact correct and use of the term “global” in that sentence was therefore misleading:

        “The phrase in the abstract “UV-B surfaces were correlated with global mean temperature and annual mean radiation data” might imply that we correlated one UV-B value with one temperature value only – correct? This is not the case. The correlation has been undertaken point-by-point. So yes, you are correct spatial UV-B levels were correlated to the spatial mean temperatures. It would have been clearer to use “annual mean temperature” instead of “global mean temperature”. Unfortunately its too late now to change it … anyway, thanks for pointing it out!”

      • If you read your comment you will see that the author suggested “annual” not “spatial” as the most suitable adjective. I contend that you would still have found “annual” to be ambiguous.

  3. I see, you now profess the ability to read minds. Your arrogance is astonishing, but all too typical of CAGW alarmists.

    You said my proposed alteration was “hopeless” and have refused to admit YOU were absolutely incorrect to say that my proposed alteration “spatial UV-B levels were correlated to the spatial mean temperatures” was “hopeless” because “global scale (hence global in that sentence) and at a local scale – and the patterns are different.” False – the authors only correlated spatial mean temperatures, not global scale temperatures, to UB-B, and have thanked me for clarifying the misleading use of “global” in the abstract.

    You still refuse to apologize or correct this post even though the lead author of the paper agrees with my alteration to correct the misleading wording of the abstract, and now contend to know what I would say if the abstract had been properly worded.


  4. There is nothing to correct or apologise for in this post. You made a stupid mistake, which I have acknowledged that you have corrected.

    You call yourself a sceptic, yet you would accept a paper published in an ecological journal reporting a correlation between UVB and global temperature even though the UVB record is short (it could not reasonably be expected to be longer than the satellite temperature or ice extend records), and there is no correlation between sunspots and temperature over the last few years, so a correlation between UVB and temperature would be unexpected.

    This should have set off many red flags, instead you grasp one slightly ambiguous word in an otherwise entirely clear abstract. How can a so-called sceptic be so credulous?

    In (geo)statistics a global analysis is one that uses all the data, in contrast to a local analysis.

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