We use the Observation minus Reanalysis (OMR) surface temperature trends method suggested by Kalnay and Cai (Nature, 2003) to provide an estimate of the impact of surface effects on regional warming (or cooling). It takes advantage of the insensitivity of the NCEP-NCAR Reanalysis (NNR) to land surface type, and eliminates the natural variability due to changes in circulation (since they are also included in the reanalysis), thus separating surface effects from greenhouse warming. Kalnay et al. (JGR, 2006) showed that over the US the OMR average is small, but it has different regional signs, in good agreement with the regions of “urban heating and cooling” obtained by Hansen et al (JGR 2001).
Lim et al. (GRL, 2005) compared two global observation-based data sets (CRU and GHCN) and two different global reanalyses (NCEP-NCAR and ERA40) and MODIS-derived land classes. The results (Figure 3) showed that the OMR trends have a strong dependence on the land-type, and that the OMR land-type dependence is similar using either the NCEP-NCAR or the ERA-40 Reanalyses. Not unexpectedly, the ERA40 trends have about half the amplitude, since this reanalysis uses air surface temperature observations indirectly (from an off-line OI analysis of surface temperature) to initialize the soil temperature and moisture, so that the ERA40 surface temperature are partially influenced by surface observations that are dependent on land surface properties. The results show that OMR warming over barren areas is larger than most other land types, and that urban areas show a large warming second only to barren areas. Croplands with agricultural activity show a larger warming than natural broadleaf forests. The overall assessment indicates surface warming is larger for areas that are barren, anthropogenically developed, or covered with needle-leaf forests. Lim et al (2006, submitted to JAMC) extended this study to establish the dependence of OMR on NDVI (and hence on the Leaf Area Index, LAI), and once again found very robust results. The results indicate that that OMR decreases with NDVI. Areas with little vegetation suffer from warming higher than their “fair GHG share”, whereas for highly vegetated zones, the OMR is small or negative.