Impact of satellite soundings on the simulation of heavy rainfall associated with tropical depressions

The present study is carried out to examine the impact of temperature and humidity profiles from moderate resolution imaging spectroradiometer (MODIS) or/and atmospheric infrared sounder (AIRS) on the numerical simulation of heavy rainfall events over the India. The Pennsylvania State University–National Centre for Atmospheric Research fifth-generation mesoscale model (MM5) and its three-dimensional variational (3D-Var) assimilation technique is used for the numerical simulations. The heavy rainfall events occurred during October 26–29, 2005, and October 27–30, 2006, were chosen for the numerical simulations. The results showed that there were large differences observed in the initial meteorological fields from control experiment (CNT; without satellite data) and assimilation experiments (MODIS (assimilating MODIS data), AIRS; (assimilating AIRS data); BOTH (assimilating MODIS and AIRS data together)). The assimilation of satellite data (MODIS, AIRS, and BOTH) improved the predicted thermal and moisture structure of the atmosphere when compared to CNT. Among the experiments, the predicted track of tropical depressions from MODIS was closer to the observed track. Assimilation of MODIS data also showed positive impact on the spatial distribution and intensity of predicted rainfall associated with the depressions. The statistical skill scores obtained for different experiments showed that assimilation of satellite data (MODIS, AIRS, and BOTH) improved the rainfall prediction skill when compared to CNT. Root mean square error in quantitative rainfall prediction is less in the experiment which assimilated MODIS data when compared to other experiments.