The proposed research is in the area "mesoscale precipitation initialization" for improving hurricane and monsoon (heavy rain) forecasts. This entails the development of physical initialization (for nowcasting of rain rates using TRMM datasets) and using Newtonian relaxation and variational data assimilation methods already being developed at FSU. A comparison of these methods and studies of impacts of the initialization for high resolution short range (2-3 days) forecast will be an additional goal. Furthermore, an application of these findings will be incorporated into high resolution state-of-the-art mesoscale models to construct a multimodel mesoscale superensemble to enhance the prediction of hurricane intensity and precipitation. We propose to do the following: Assimilation of brightness temperatures by ECMWF and total precipitable water by NCEP/EMC for improving precipitation initialization has limitations. If those products are validated against the NASA TRMM (2A12 or 3B42) we find rather large errors in nowcasting of rain. The Newtonian relaxation appears to directly nudge TRMM rainfall products much more effectively. (Note: In our current TRMM research, we note that the correlation of model rain versus those from TRMM estimates are of the order 0.90 for the Newtonian relaxation where those values were as low as 0.30 for the variational data assimilation.) These differences between variational data assimilations based precipitation initialization and those based on FSUs Newtonian relaxation will be examined. These results extend to short range forecasts. The major proposed research will be on mesoscale modeling (including physical initialization of rain rates) for studies of hurricane and heavy rain related floods over the monsoon region. This will utilize the FSU Global Spectral Model at a horizontal resolution of T255 with a grid separation of ~ 50 km. Two regional mesoscale models WRF and HWRF (also subject to physical initialization) will be run at horizontal resolutions less than 5 km and will be driven by global model forecasts. Specifically we will address sensitivities for improving mesoscale forecasts from satellite based datasets (precipitation, moisture profiling, QuikSCAT winds and high resolution SSTs), data assimilation and model physics (especially related to precipitation processes). The final component of the proposed work will deal with the study of interaction among the diurnal wave and synoptic scale waves to improve the diurnal modulation of precipitation within heavy rainfall monsoon events, tropical disturbances and hurricanes. These results would help us to better forecast hurricane intensity. The proposed research addresses NASA objectives under the PMM in the category "precipitation variability and its relationship to climate diagnostics and change" with emphasis on development of new data analysis and modeling techniques for detecting acceleration in water cycling through the atmosphere and the Earth's surface.
