Further Confirmation of the Robustness of the Kalnay and Cai (2004) Nature paper on the Importance of the Land Surface With Respect to the Surface Temperature Trend Assessments

On several weblogs, we have discussed new research papers on the role of land surface processes on the surface temperature trend assessments (e.g. see and see).

Another new paper has appeared on March 24, 2006 that further confirms the important role of land surface processes in significantly influencing long term surface temperature trends;

Kalnay, Eugenia, Cai, Ming; Li, Hong, and Tobin, Jayakar: Estimation of the impact of land-surface forcings on temperature trends in eastern United States J. Geophys. Res., Vol. 111, No. D6, D06106

The abstract of the paper states,

“We use the “observation minus reanalysisâ€? difference (OMR) method to estimate the impact of land-use changes by computing the difference between the trends of the surface temperature observations (which reflect all the sources of climate forcing, including surface effects) and the NCEP-NCAR reanalysis surface temperatures (only influenced by the assimilated atmospheric temperature trends). This includes not only urbanization effects but also changes in agricultural practices, such as irrigation and deforestation, as well as other near-surface forcings related to industrialization, such as aerosols. We slightly correct previous results by including the year 1979 within the satellite decades and by excluding stations in the West Coast of the United States. The OMR estimate for surface impact on the mean temperature is similar to that obtained using satellite observations of night light to discriminate between rural and urban stations, with regions of large positive and negative trends, in contrast with the urban corrections based on population density, which are uniformly positive and much smaller. The OMR seasonal cycle results suggest that the impact of the greenhouse gases dominates in the winter, whereas it appears that the impact of surface forcings dominates in the summer. The impact of the USHCN adjustments for nonclimatic trends in the observations does not affect the geographical distribution of the OMR trends. The effect of using a model with constant CO2 in the reanalysis, the use of other reanalyses, and the possible use of the reanalyses to correct for nonclimatic jumps in the observations are also discussed. ”

This paper provides an in-depth confirmation of the robustness of the conclusions of the 2004 Kalnay and Cai Nature paper. As was stated in the Climate Science weblog of December 1, 2005 with respect the earlier paper by Young-Kwon Lim, Ming Cai, Eugenia Kalnay, and Liming Zhou;

“The paper provides evidence on the robustness of the conclusions in the 2003 Kalnay and Cai paper entitled ‘Impact of urbanization and land-use on climate change’ (Nature, 423, 528-531); Corrigendum, which was (incorrectly as it now turns out) criticized in Nature in subsequent issues (Vose et al. 2003; Trenberth 2003 with reply by Cai and Kalnay 2003 ; subscription required) .”

The new Kalnay et al paper published on March 24, 2006 provides even further refutation of the comments by Vose et al and by Trenberth. Their paper provides additional evidence on the value of applying the NCEP Reanalysis to the assessment of long term climate trends, as they summarize in the following text extracted from their paper (see, subscription required);

“Since nonclimatic corrections are substantial, we suggest that reanalyses could be used to provide an alternative estimation of the nonclimatic adjustments taking advantage of the fact that they provide an accurate estimate of the expected value of the surface observations (absent sudden changes). If this method compares well with that used in the USHCN data set, it can be extended to other areas of the world where such careful corrections are not available”.

Their winter time attribution to greenhouse gases, however, also needs to be related to the results that we have found that a nighttime boundary layer decrease in cooling, for any reason, will result in an amplified near-surface air temperature increase. Attributing to greenhouse gases (by default) neglects the possible contributing influence due to increased nighttime cloud cover and or aerosols (e.g. see).

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