Background
The authors note that "the standard interpretation of global climate data is that extraneous effects, such as urbanization and other land surface effects, and data quality problems due to inhomogeneities in the temperature series, are removed by adjustment algorithms, and therefore do not bias the large-scale trends."

What was done
Working with data from all available land-based grid cells around the world, McKitrick and Michaels evaluated this widely-accepted but largely-unverified assumption by testing "the null hypothesis that the spatial pattern of temperature trends in a widely used gridded climate data set is independent of socioeconomic determinants of surface processes and data inhomogeneities."

What was learned
In the words of the two researchers, this hypothesis "is strongly rejected, indicating that extraneous (nonclimatic) signals contaminate gridded climate data." In addition, they find that "the patterns of contamination are detectable in both rich and poor countries and are relatively stronger in countries where real income is growing." Finally, they report that using a regression model to filter out the extraneous non-climatic effects revealed by their analysis "reduces the estimated 1980-2002 global average temperature trend over land by about half."

What it means
McKitrick and Michaels say their findings show that "trends in gridded climate data are, in part, driven by the varying socioeconomic characteristics of the regions of origin, implying a residual contamination remains even after adjustment algorithms have been applied." As a result, one can logically conclude that Al Gore's so-called "climate crisis" is -- at worst -- only half as catastrophic as he routinely contends. Or maybe it doesn't exist at all, as the much-reduced real temperature increase of the past quarter-century may be simply a natural run-of-the-mill climatic fluctuation that may soon level out or even reverse itself.