Abstract
Using a subgrid distribution for the soil moisture content derived from a macroscale hydrologic model, it is investigated how lateral subgrid variations in the soil moisture content impact both the daily and the seasonal cycle of the spatially averaged surface flux densities and near-surface meteorology. In agreement with earlier studies it is found that in wet conditions the use of one uniform volumetric soil moisture content, referred to as the bulk approach, gives larger estimates of the latent heat flux density than a quasi-distributed approach where the lateral variation in the volumetric soil moisture content is taken into account. In dry conditions the bulk approach gives lower estimates of the latent heat flux density than the quasi-distributed approach. In this study, the differences between the flux density estimates obtained by both approaches appear even when the developing convective boundary layer is allowed to feed back on the surface. It is also shown that differences in the estimated surface flux densities lead to differences between the predicted atmospheric specific humidity and the predicted near-surface temperature. The differences due to the subgrid variations in the soil moisture content appear to impact the seasonal hydrologic balance. Especially for dry climates, the quasi-distributed approach predicts a more gradual decrease of the evapotranspiration during the dry season, resulting in a larger cumulative evapotranspiration over the dry season. Thus, taking account of the spatial heterogeneity of the soil moisture content is a prerequisite for a proper representation of the seasonal hydrological cycle within largescale atmospheric models.
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