Retrieving latent heat vertical structure using precipitation and cloud profiles

Description

The latent heating is a major contributor to the convective heating (Q1). There is no observation of heating profiles available for evaluating GCM parameterized convective and stratiform heating rates and understanding impacts of the vertical and horizontal structure on climate mean state and variability. Many studies instead use the heating profiles estimated from the temperature and moisture budgets of NCEP and ECMWF reanalysis. Our novel approach, distinguished from existing schemes, is directly using observable precipitation and cloud profiles in combination with phase change partition parameterization of various kinds from the CRM simulations to produce the latent heating profiles. This hybrid latent heat algorithm separately deals with the condensation-evaporation heating (LHc_e), the deposition-sublimation heating (LHd_s), and the freezing-melting heating (LHf_m) for convective rain, stratiform rain, and shallow warm rain. Each component is based on physical processes, such as nucleation and autoconversion, by combining observable precipitation and cloud profiles. The partition of various components is derived from the CRM simulations. Although the proposed algorithm utilizes microphysical parameterizations from a specific CRM, the general LH vertical structure is primarily determined by the precipitation and cloud profiles observable from cloud and precipitation radars available at the ARM SGP site or from satellite platforms, and less sensitive to the specific CRM. The self-consistency tests of this algorithm show good agreements with the CRM-simulated LH at different spatial and temporal scales, even at simultaneous and pixel level. The applications of this algorithm are expected to provide new information for understanding the heating budget in the atmosphere and its impacts on the atmosphere circulations at various spatial and temporal scales.