Use of Atmospheric Infrared Sounder clear-sky and cloud-cleared radiances in the Weather Research and Forecasting 3DVAR assimilation system for mesoscale weather predictions over the Indian region

Abstract

[1] A set of assimilation experiments is conducted with the Three-Dimensional Variational (3DVAR) data assimilation system associated with the Weather Research and Forecasting (WRF) model. The purpose of the investigation is to assess the impact on forecast skill in response to assimilation of the Atmospheric Infrared Sounder (AIRS) clear-sky and cloud-cleared radiances over the Indian region. This is the first study that makes use of cloud-cleared radiances in the WRF system. Two sets of thirty-one 72 h forecasts are performed, all initialized at 00:00 UTC each day throughout the month of July 2010, to compare the model performance consequent to assimilation of clear-sky versus cloud-cleared radiances. A rigorous validation is produced against National Centers for Environmental Prediction analyzed wind, temperature, and moisture. In addition, the precipitation forecast skill is assessed against Tropical Rainfall Measuring Mission observations. The results show improvement in forecast skill consequent to the assimilation of cloud-cleared radiances (CCR). The implications of using CCR for operational weather forecasting appear to be significant. Since only a small fraction of AIRS channels are cloud-free, information obtained in cloudy regions, which is meteorologically very significant, is lost when assimilating only clear-sky radiances (CSR). On the contrary, assimilation of CCR allows a larger yield, which leads to improved model performance. The assimilation of CCR resulted in significantly improved rainfall prediction compared to that obtained from the use of CSR. The finding of this study clearly shows the advantage of CCR available from clear-sky as well as from partly cloudy regions as compared to CSR, which are available only in clear-sky regions.