Is There A Sampling Bias In The BEST Analysis Reported By Richard Muller?

In his testimony Richard Muller (which I posted on Friday April 2 2011), indicated that he used 2% of the available surface stations that measure temperatures in the BEST assessment of long-term trends. It is important to realize that the sampling is still biased if a preponderance of his data sources comes from a subset of actual landscape types.  The sampling will necessarily be skewed towards those sites.

If the BEST data came from a different distribution of locations than the GHCNv.2, however, then his results would add important new insight into the temperature trend analyses. If they have the same spatial distribution, however, they would not add anything beyond confirming that NCDC, GISS and CRU were properly using the collected raw data.

We discuss this bias in station locations in our paper

Montandon, L.M., S. Fall, R.A. Pielke Sr., and D. Niyogi, 2011: Distribution of landscape types in the Global Historical Climatology Network. Earth Interactions, 15:6, doi: 10.1175/2010EI371

The abstract reads [highlight added]

“The Global Historical Climate Network version 2 (GHCNv.2) surface temperature dataset is widely used for reconstructions such as the global average surface temperature (GAST) anomaly. Because land use and land cover (LULC) affect temperatures, it is important to examine the spatial distribution and the LULC representation of GHCNv.2 stations. Here, nightlight imagery, two LULC datasets, and a population and cropland historical reconstruction are used to estimate the present and historical worldwide occurrence of LULC types and the number of GHCNv.2 stations within each. Results show that the GHCNv.2 station locations are biased toward urban and cropland (>50% stations versus 18.4% of the world’s land) and past century reclaimed cropland areas (35% stations versus 3.4% land). However, widely occurring LULC such as open shrubland, bare, snow/ice, and evergreen broadleaf forests are underrepresented (14% stations versus 48.1% land), as well as nonurban areas that have remained uncultivated in the past century (14.2% stations versus 43.2% land). Results from the temperature trends over the different landscapes confirm that the temperature trends are different for different LULC and that the GHCNv.2 stations network might be missing on long-term larger positive trends. This opens the possibility that the temperature increases of Earth’s land surface in the last century would be higher than what the GHCNv.2-based GAST analyses report.”

This derived surface temperature trends is higher than what BEST found.  However, this also means that the divergence between the surface temperature trends and the lower tropopsheric temperature trends that we found in

Klotzbach, P.J., R.A. Pielke Sr., R.A. Pielke Jr., J.R. Christy, and R.T. McNider, 2009: An alternative explanation for differential temperature trends at the surface and in the lower troposphere. J. Geophys. Res., 114, D21102, doi:10.1029/2009JD011841.

is even higher.  This difference suggests that unresolved issues, including a likely systematic warm bias,  remains in the analysis of long term surface temperature trends.

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