1999 Volume 77 Issue 1B Pages 217-234
Soil moisture and water balance for global and regional scales have been calculated using a land-surface process model (SiB2) forced by observed and model assimilated data. The simulated runoff for each grid cell has been provided as input to a global river routing model, in order to simulate river discharge rates. The simulated soil moisture and water balance have been compared with available observations for their annual mean and seasonal cycles and for global, basin and grid point scales. The global distributions of the annual-mean soil moisture and wetness have been reasonably simulated. There were large inter-annual variations of soil moisture in both the simulations and observations at local stations. The simulated annual discharges for major river basins agree reasonably well with observations, but with some underestimates for large discharges and some overestimates for small discharges. The seasonal cycle of river discharges has been well simulated for specific basins in the tropics, midlatitudes, and high latitudes, although for some basins the annual mean is underestimated. In the tropics, the seasonal cycles of soil moisture and the surface water balance are dominated by the precipitation cycle. In mid- and high latitudes, soil moisture and the water balance are affected by both the temperature and precipitation cycles, and by the snow accumulation/melting cycle. The range of seasonal soil moisture variations becomes smaller with increasing latitude. The seasonal cycles of soil moisture for selected grid points have been compared with selected station observations. Even though there are differences in forcing and in some specific surface boundary parameters at the stations, the simulated soil moisture agrees well with multiyear observations at a majority of the stations. However, for almost all the selected grid cells, the seasonal variations are smaller, the snow melt and soil drying processes are late by about one month, and the soil is relatively wet in summer, compared with observations. These errors can be partly attributed to the unrealistically cool temperatures provided to the model as forcing data, favoring less surface evaporation and a later seasonal cycle, especially for mid- and high latitudes.