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.
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