Open AccessQuantifying the influence of anthropogenic surface processes and inhomogeneities on gridded global climate data
Author(s) -
McKitrick Ross R.,
Michaels Patrick J.
Publication year - 2007
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2007jd008465
Subject(s) - spurious relationship , environmental science , climatology , climate change , climate model , endogeneity , geopotential height , econometrics , atmospheric sciences , meteorology , precipitation , statistics , geography , mathematics , geology , oceanography
Local land surface modification and variations in data quality affect temperature trends in surface‐measured data. Such effects are considered extraneous for the purpose of measuring climate change, and providers of climate data must develop adjustments to filter them out. If done correctly, temperature trends in climate data should be uncorrelated with socioeconomic variables that determine these extraneous factors. This hypothesis can be tested, which is the main aim of this paper. Using a new database for all available land‐based grid cells around the world we test 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. The hypothesis is strongly rejected ( P = 7.1 × 10 −14 ), indicating that extraneous (nonclimatic) signals contaminate gridded climate data. The patterns of contamination are detectable in both rich and poor countries and are relatively stronger in countries where real income is growing. We apply a battery of model specification tests to rule out spurious correlations and endogeneity bias. We conclude that the data contamination likely leads to an overstatement of actual trends over land. Using the regression model to filter the extraneous, nonclimatic effects reduces the estimated 1980–2002 global average temperature trend over land by about half.