A new data set of global high-resolution soil wetness for 1987-1988 has been prepared as part of the Global Soil Wetness Project (GSWP). To produce these dat, the Simplified Simple Biosphere (SSiB) land surface model has been driven offline by observed and assimilated meteorological data to produce a two-year global climatology of soil wetness at 1° x 1° resolution. This GSWP data set is potentially of higher quality than any previously available data sets. We are testing the impact of the GSWP data for climate simulations using the COLA general circulation model (GCM) coupled to the SSiB land surface process model (LSP).
There are two principle questions which we hope to address with our preliminary GCM.LSP sensitivity experiments. First, does the inclusion of presumably more realistic GSWP soil wetness significantly improve the simulation and predictability of summer season climate? We use the 1987-1988 GSWP product as a specified boundary condition in seasonal simulations (June-August), and we compare to existing GCM/LSP integrations where soil wetness is initialized from operational analyses and allowed to evolve feely in the coupled system. In both sets of integrations, identical observed observed sea surface temperatures are specified. Results show that the GSWP soil wetness id significantly different from that of the coupled model's own climatology, and produces a better simulation of precipitation anomaly patterns over monsoon regions and the summer hemisphere extratropics. However, there is little improvement in the systematic error of the coupled model. Improvements can be attributed to changes in the surface fluxes induced by th edifferent soil wetness.
Second, does teh interannual variability in a multi-year soil wetness data set contribute to interannual variability in climate simulations? A paraalel set of GCM.LSP integrations has been produced using specified GSWP soil wetness from the "wrong" (other) year (i.E. 1988 soil wetness applied in 1987 integrations, and vice versa). The use of soil wetness data from the wrong year significantly degrades teh simulation of precipitation anomaly patterns. This indicates that interannual variability in soil wetness is important to climate. The value of a multi-year soil wetness data set is verified.
Complete copies of this report are available from:Center for Ocean-Land-Atmosphere Studies
last update: 10 November 1997
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