Estimation of the impact of land‐surface forcings on temperature trends in eastern United States

Abstract

[1] We use the ''observation minus reanalysis'' 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 CO 2 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.

Impact of land use/land cover change on changes in surface solar radiation in eastern China since the reform and opening up

“…R-2, which is used in this study, is designed to improve upon the NCEP/NCAR reanalysis used in the data of Kalnay and Cai (2003) by fixing the errors and by updating the parameterizations of the physical processes. Admittedly, it is not possible to definitively attribute the OMR differences solely to the near-surface forcings (Kalnay et al 2006). The results obtained in this study are much more illustrative rather than definitive.…”

“…Therefore, OMR is believed to be attributable primarily to urbanization and other changes in land use (Kalnay and Cai 2003). These effects include not only urbanization effects but also changes in agricultural practices, such as irrigation and deforestation, in addition to those of near-surface aerosols and precipitation associated with urbanization and industrialization (Kalnay et al 2006). These factors are all parts of LULCC, either as biogeophysical or biogeochemical processes.…”

Impacts of land use land cover on temperature trends over the continental United States: assessment using the North American Regional Reanalysis

“…Recent studies have used the 'observation minus reanalysis' (OMR) method to estimate the impact of land use changes by computing the difference between the trends of surface temperature observations and reanalysis datasets (Kalnay and Cai, 2003;Zhou et al, 2004;Frauenfeld et al, 2005;Lim et al, 2005Lim et al, , 2008Kalnay et al, 2006, Pielke et al, 2007bNuñez et al, 2008). The OMR method is effective because some reanalyses do not assimilate surface temperature over land and therefore are not directly sensitive to near surface properties.…”

“…Likewise, the reanalysis can be used to detect non-climatic biases that are introduced by changes in observation practices and station locations (Kalnay et al, 2006, Pielke et al, 2007a, 2007b.…”

Modelling the impact of urbanisation on regional climate in the Greater London Area

“…However, quantifying the urban effect on climate (especially at a regional scale) is challenging. Many studies exist which attempt to determine how land cover changes have affected local and regional climate (Gallo et al, 1996;Kalnay et al, 2006). These use a variety of different methodologies including the analysis of trends in urban measurements at a single station, the measurement of the urban-rural temperature difference, analysis of transects across urban areas and measurements using satellite observations.…”