Mesoscale Assimilation of TRMM Data with 4DVAR: Preliminary Results

Surface rainfall data, derived from the TRMM Microwave Image (TMI), are assimilated into the PSU/NCAR MM5 model using a 4DVAR technique. Preliminary experiments are performed to incorporate TRMM rainfall data into a hurricane initialization. It is found that the rainfall data assimilation is sensitive to the error characteristics of the data and the physics in the adjoint model. In addition, assimilating the rainfall data alone produces a more realistic eye and rain bands in the hurricane but cannot ensure improvements of hurricane intensity forecasts. Numerical results indicate that it is necessary to incorporate TRMM rainfall data together with other types of data such as wind data into the model, in which case the inclusion of the rainfall data will further improve the intensity forecast of the hurricane. This fact might imply that some proper constraints will be needed for the rainfall assimilation. Relevant results and issues will be presented.