Assessing GCM sensitivity to soil wetness using GSWP data

A new data set of global high-resolution soil wetness for 1987-1988 has bee n prepared as part of the Global Soil Wetness Project (GSWP). To produce th is data, the Simplified Simple Biosphere (SSiB) land surface process model (LSP) has been integrated offline, driven by observed and assimilated meteo rological data to produce a two-year global climatology of soil wetness at 1 degrees x 1 degrees resolution. GSWP data set has potentially higher qual ity data than those previously available. We are testing the impact of the GSWP data for climate simulations using the Center for Ocean-Land-Atmospher e Studies (COLA) general circulation model (GCM), coupled to the SSiB LSP. There are two principle questions which we will address with our preliminar y GCM/LSP sensitivity experiments. First, does the inclusion of presumably more realistic GSWP soil wetness significantly improve the simulation and p redictability of summer season climate? We use the 1987-1988 GSWP product a s a specified boundary condition in seasonal simulations (June-August), and compared to existing GCM/LSP integrations, where soil wetness is initializ ed from operational analyses and allowed to evolve freely in the coupled sy stem. In both sets of integrations, identical observed sea surface temperat ures are specified. Results show that the GSWP soil wetness is significantl y 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 improvemen t in the systematic error of the coupled model. Improvements can be attribu ted to changes in surface fluxes induced by the different soil wetness. Second, does the interannual variability in a multi-year soil wetness data set contribute to interannual variability in climate simulations? A paralle l set of GCM/LSP integrations have been produced using specified GSWP soil wetness from the "wrong" (other) year (i.e., 1988 soil wetness applied in 1 987 integrations, and vice versa). The use of soil wetness data from the wr ong year significantly degrades the simulation of precipitation anomaly pat terns. This indicates that interannual variability in soil wetness is impor tant to climate. However, differences in precipitation due to SST variabili ty generally dominated those apparently caused by soil wetness variations.