Mesoscale Moisture Initialization for Monsoon and Hurricane Forecasts

Abstract

Abstract This paper addresses physical initialization of precipitation rates for a mesoscale numerical weather prediction model. This entails a slight modification of the vertical profile of the humidity variable that provides a close match between the satellite and model-based rain rates. This is based on the premise that the rain rate from a cumulus parameterization scheme such as the Arakawa–Schubert scheme is most sensitive to the vertical profiles of moist static stability. It is possible to adjust the vertical profile of moisture by a small linear perturbation by making it wetter (or drier) in the lower levels and the opposite at levels immediately above. This can provide a change in the moist static stability in order to achieve the desired rain rate. The procedure is invoked in a preforecast period between hours −24 and 0 following Krishnamurti et al. The present study is the authors’ first attempt to bring in this feature in a mesoscale model. They first noted that the procedure does indeed provide a much closer match between the satellite estimate of initial rain and that from the physical initialization for a mesoscale model. They have examined the impacts of this procedure for the initialization and short-range forecasts of a monsoon rainfall event and a hurricane. In both of these examples it became possible to improve the forecasts of rains compared with those from control runs that did not include the initialization of rains. Among these two examples, the results for the monsoon forecasts that deployed a uniform resolution of 25 km and the Grell and Devenyi scheme over the entire domain had the largest positive impact. The hurricane forecasts example also show improvement over the control run but with less impact, which may be due to heavy rains from explicit clouds in the nonhydrostatic model. Here the results did convey a strong positive impact from the use of the physical initialization; however, forecasts of very heavy rains carry smaller equitable threat scores. These require development of a more robust precipitation initialization procedure.