Assessing GCM Sensitivity to Soil Wetness Using GSWP Data

Abstract

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 this data, the Simplified Simple Biosphere (SSiB) land surface process model (LSP) has been integrated offline, driven by observed and assimilated meteorological data to produce a two-year global climatology of soil wetness at 1°×1° resolution. GSWP data set has potentially higher quality data than those previously available. We are testing the impact of the GSWP data for climate simulations using the Center for Ocean-Land-Atmosphere Studies (COLA) general circulation model (GCM), coupled to the SSiB LSP.
There are two principle questions which we will 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 compared to existing GCM/LSP integrations, where soil wetness is initialized from operational analyses and allowed to evolve freely in the coupled system. In both sets of integrations, identical observed sea surface temperatures are specified. Results show that the GSWP soil wetness is 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 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 parallel 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 1987 integrations, and vice versa). The use of soil wetness data from the wrong year significantly degrades the simulation of precipitation anomaly patterns. This indicates that interannual variability in soil wetness is important to climate. However, differences in precipitation due to SST variability generally dominated those apparently caused by soil wetness variations.