Use of precipitation data for diabatic initialization to improve the tropical analysis of divergence and moisture

Summary First, we review the present status of diabatic initialization used for numerical weather prediction and conclude that the deficiency of diabatic initialization mostly stems from the shortcoming in evaluating diabatic heating rates accurately, particularly the release of latent heat by cumulus convection. This indicates the need to adjust the initial conditions for physical processes, and Krishnamurti and his colleagues introduced in 1984 the concept of physical initialization. Since cumulus convection is most sensitive to input data among many physical processes, the adjustment of atmospheric input data to a prediction model to produce desired initial precipitation rates is referred to as cumulus initialization.In this article we describe a general approach to diabatic initialization with a special emphasis on cumulus initialization. We present the results of forecasting experiments with a version of the NCAR Community Climate Model (CCM) to demonstrate the efficacy of a cumulus initialization procedure to ameliorate the spinup problern of precipitation. Finally, we discuss application of the present methodology of cumulus initialization for a stability-dependent mass-flux cumulus parameterization of CCM2 to pave the way to complete the diabatic normal mode initialization package for CCM2. Note that the present cumulus initialization scheme can be used to assimilate into the atmospheric analysis of the tropics the precipitation rates estimated by satellite radiometric imagery data.With 8 FiguresThe National Center for Atmospheric Research is sponsored by the National Science Foundation