Validation of soil moisture simulation in landsurface parameterisation schemes with HAPEX data

In the Soil Moisture Simulation Workshop, a number of numerical experiments was conducted with fourteen representative schemes and the results compared with HAPEX-MOBILHY data. This paper documents the general outcomes of the workshop, and provides the background information for the other papers presented in this special issue, which deal with more specific aspects of soil moisture simulation and the performance of individual schemes. The results show that soil moisture simulation in current landsurface schemes is profoundly different. After adjustment of landsurface parameters, the disagreement in soil moisture for a 1.6 m soil layer remains around 100 mm. Correspondingly, the differences in predicted annual cumulative evaporation as well as total runoff plus drainage are around 250 mm (annual precipitation being 856 mm for HAPEX-MOBILHY). The partitioning of surface available energy into sensible and latent heat fluxes is closely coupled to that of precipitation into evaporation and runoff plus drainage. These disagreements are related to different causes but attempts to establish the causality between the outcome and the responsible mechanism has had only limited success to date because of the non-linear interactions embedded in the schemes. This study implies that different schemes achieve different equilibrium states when forced with prescribed atmospheric conditions and that the time period to reach these states differs among schemes; and even when soil moisture is fairly well simulated, the processes (particularly evaporation and runoff plus drainage) controlling the simulation differ among schemes and at different times of the year. These results suggest that prescription of landsurface scheme physics and biochemistry may have to be a function of the type of predictions (short-term weather forecasting, mesoscale modelling or climate ensembles) required as well as the underlying scheme formulation and that scheme simulations should be validated for all components of the prediction.