This proposal is directed to NASA's Precipitation Science program under the subprogram dealing with retrieval algorithms, validation, and multisatellite precipitation analysis. The first aspect of our proposed research deals with an investigation of the intraseasonal and interannual variability of convection over the South China Sea (SCS) during the east Asian summer monsoon using data from the South China Sea Monsoon Experiment (SCSMEX) and TRMM. The motivation for this work is the fact that TRMM latent heating algorithms have used SCSMEX data in their cloud models or SCSMEX budget results to validate their algorithms. We propose to use TRMM PR and TMI data to determine precipitation patterns, vertical structure, and stratiform rain fraction through the May and June stages of the east Asian monsoon for the years 1998 to present. Another part of our proposed research deals with the diurnal cycle of convection over the SCS and in the region of the 2004 North American Monsoon Experiment (NAME). Convection in both regions is dominated by the diurnal cycle, but the mechanisms are not well understood. We propose to use 8+ years of TRMM data to investigate the diurnal cycle and propagation characteristics of convection over the SCS during the east Asian summer monsoon and over the western part of Mexico and the Gulf of California during the North American summer monsoon. The third area of research deals with the determination of latent heating profiles and cloud-resolving model (CRM) forcing fields for NAME. There is currently an international effort underway to develop TRMM latent heating products. Given the limited number of field program datasets available to develop and/or validate these products, there is a need to assemble additional datasets for TRMM latent heating (LH) algorithms. In this part of the proposed research, we plan to prepare the 2004 NAME sounding dataset forcing fields for CRMs (to be used by Wei-Kuo Tao of NASA Goddard) and heat and moisture budget analyses at 4 and 6-h intervals over the NAME domain (to be used by Song Yang of NASA Goddard and others) to validate LH algorithms.
