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Simulating AOGCM Soil Moisture Using an Off-Line Thornthwaite Potential Evapotranspiration–Based Land Surface Scheme. Part I: Control Runs
Author(s) -
Adam R. Cornwell,
L. D. Danny Harvey
Publication year - 2008
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/2007jcli1675.1
Subject(s) - evapotranspiration , forcing (mathematics) , environmental science , water content , precipitation , climatology , atmospheric sciences , moisture , surface runoff , climate model , meteorology , climate change , geology , ecology , oceanography , physics , geotechnical engineering , biology
Atmosphere–ocean general circulation models (AOGCMs) employ very different land surface schemes (LSSs) and, as a result, their predictions of land surface quantities are often difficult to compare. Some of the disagreement in quantities such as soil moisture is likely due to differences in the atmospheric component; however, previous intercomparison studies have determined that different LSSs can produce very different results even when supplied with identical atmospheric forcing. A simple off-line LSS is presented that can reproduce the soil moisture simulations of various AOGCMs, based on their modeled temperature and precipitation. The scheme makes use of the well-established Thornthwaite method for estimating potential evapotranspiration combined with a variation of the Manabe “bucket” model. The model can be tuned to reproduce the control climate soil moisture of an AOGCM by adjusting the ease with which runoff and evapotranspiration continue as the moisture level in the bucket goes down. This produces a set of parameter values that provides a good fit to each of several AOGCM control climates. In addition, the parameter values can be set to imitate the LSS from one AOGCM while the model is forced with atmospheric data from another, thus providing an estimate of the magnitude of variation caused by the differences in land surface parameterization and by differences in atmospheric forcing. In general, the authors find that differences in LSSs account for about half of the difference in soil moisture as simulated by different AOGCMs, and the differences in atmospheric forcing account for the other half of the difference. However, the LSS can be more important than differences in atmospheric forcing in some regions (such as the United States) and less important in others (such as East Africa).

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