Satellite radiance assimilation using the 3D-var technique for the heavy rainfall over the Indian region

Abstract

The present study evaluates the impact of satellite radiance assimilation on the predictability of the WRF model. The 3D-VAR system of the WRF model was used to assimilate satellite radiance data at the initial condition. Four thunderstorm cases were considered, which occurred over Kolkata, India. A set of two numerical experiments, namely CNTL (no-assimilation) and SAT (satellite radiance assimilation), were carried out, and the WRF model was integrated for 24 hours. The assimilation of satellite radiance had improved the wind and moisture fields at the initial condition, which led to evolve the conducive atmosphere further. Results showed that even though thunderstorms are a small-scale system, assimilation of satellite radiance had shown significant improvement in the simulation of the location, evolution, and intensity of thunderstorms. Temporal evolution of surface parameters (such as 2-m temperature and rainfall) was closer to observation (AWS) in SAT experiment. Further, the SAT experiments were able to produce stronger updrafts/downdrafts and increased moisture content deep into the atmosphere. These findings suggest that satellite radiance data assimilation significantly impacts initial conditions, providing a conducive atmosphere.