UPDATE (January 25, 2014): I updated the title, replacing data with reanalysis. It must be kept in mind that GHCN-CAMS is a reanalysis (output of a climate model that uses data as inputs) and not simply data.
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>On the GISSTemp +0.71C: Slightly higher than January. thread at Lucia’s The Blackboard, I replied to a comment with, “There’s simply no gridded absolute land surface temperature data that I’ve found.” I received an email a few days later, advising me the KNMI Climate Explorer did, in fact, include an absolute Land Surface Temperature dataset, which is a merger of GHCN and CAMS station data. Refer to Figure 1. It’s identified on the KNMI Climate Explorer webpage as the CPC GHCN/CAMS t2m analysis, and it’s presented in the Fan and Dool (2007) paper “A global monthly land surface air temperature analysis for 1948-present.”
THINGS TO CONSIDER
In addition to the obvious difference (absolute temperature versus anomalies), there are also some other things to consider when using this dataset. The abstract of Fan and Dool (2007) includes, “The study also reveals that there are clear biases between the observed surface air temperature and the existing Reanalysis data sets, and they vary in space and seasons.”
On page 4, line 16 of the paper, they caution, “The readers are advised that the resulting temperature data set to be described in this paper was NOT constructed first and foremost for climate change studies. While the GHCN component of the data has gone through most quality checks one would like to see, the CAMS component of the data (much more numerous than GHCN over the last few years) is less strictly quality controlled.”
HOW SIGNIFICANT ARE THE BIASES?
That will depend on how you define significant. Figures 2 through 4 are comparison graphs with linear trends of the GHCN+CAMS land surface air temperature anomalies, identified as GHCN-CAMS T2m, and the three major land surface temperature products: CRUTEM3, GISTEMP (1200km smoothing), and NCDC. In all three instances, the linear trend from 1948 to present of the GHCN-CAMS T2m anomalies exceeds linear trends of the more commonly used datasets.
THE DIVERGENCES INCREASE IN RECENT YEARS
Figures 5 through 7 illustrate the differences between the GHCN-CAMS T2m anomalies and those of CRUTEM3, GISTEMP (1200km smoothing), and NCDC datasets.
STATION LOCATION AND DENSITY
Figure 8 is Figure 2 from Fan and Dool (2007), showing the locations and number of surface stations per grid. Refer to the text at the bottom of the illustration for the description.
ANNUAL MAXIMUM, AVERAGE, AND MINIMUM
And for those interested, the annual maximum, minimums and averages of the GHCN-CAMS T2m data from 1948 through 2009 are shown in Figure 9, as are their linear trends.
Thanks for the heads-up, Geert Jan.
All of the data used in this post are available through the KNMI Climate Explorer: