THE INFLUENCE OF SUBGRID-SCALE SPATIAL VARIABILITY ON PRECIPITATION AND SOIL MOISTURE IN AN ATMOSPHERIC GCM

Summary

ABSTRACT A new land surface hydrological parameterization for atmospheric General Circulation Models is introduced. The model incorporates physically-based relations for the partitioning of atmospheric energy and moisture forcing. Using statistical-dynamical derived-distribution techniques, closed-form and computationally-efficient expressions are developed for the inclusion of subgrid-scale spatial variability into parameterizations for atmospheric models. Numerical experiments with a General Circulation model show improved water balance estimates.

INTRODUCTION

Atmospheric General Circulation Models (GCMs) integrate the relevant conservation and state equations over grids (in the case of models using finite-difference schemes) or up to wave-numbers (in the case of models using spectral-solution techniques) that explicitly resolve processes whose dynamics occur at spatial scales on the order of hundreds of kilometres or larger. All physical processes whose characteristic scales are smaller are therefore either only implicitly represented or parameterized within the GCM. Radiative heating and cooling, turbulent diffusion, local convection, water phase transitions and hydrological processes are all examples of processes that are critical in the forcing of atmospheric motions, yet they are only parameterized in GCMs. The capability of GCMs of reproducing regional features of the climatic system and of capturing the significant feedbacks and interactions is thus partially dependent on the realism with which these physical processes are represented within the numerical model. In this paper the focus is on one of these processes, namely the land surface hydrology. As with other physics components in GCMs, the land surface hydrology is designed to capture the effective response of a system that depends on processes at a considerably finer scale than that of the GCM dynamics.