Climate and Dynamics
Estimation of the impact of land-surface forcings on temperature trends in eastern United States
Article first published online: 24 MAR 2006
Copyright 2006 by the American Geophysical Union.
Journal of Geophysical Research: Atmospheres (1984–2012)
Volume 111, Issue D6, 27 March 2006
How to Cite
2006), Estimation of the impact of land-surface forcings on temperature trends in eastern United States, J. Geophys. Res., 111, D06106, doi:10.1029/2005JD006555., , , and (
- Issue published online: 24 MAR 2006
- Article first published online: 24 MAR 2006
- Manuscript Accepted: 7 NOV 2005
- Manuscript Revised: 21 SEP 2005
- Manuscript Received: 3 AUG 2005
- climate change;
- land use;
 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 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.