Evaluation of the assimilation of conventional and satellite-based observations in simulating heavy rainfall event using WRFDA over the North-West Himalayan region

Abstract

Present work elucidates the impact of 3DVAR data assimilation technique for the simulation of one of the heavy rainfall events reported over Kotdwara region in the North-West Himalayan (NWH) region on 4th August 2017. We have examined the impact of conventional and satellite-based radiance datasets on the simulated results with and without assimilating the observations into the Weather Research and Forecasting (WRF) model. Three experiments have been designed with 3 nested domains of variable resolutions, one without assimilation (referred as control experiment) and other two experiments after assimilating conventional and satellite radiances observations (refer as DA-OBS and DA-SAT respectively). In the present study, assimilation of surface, upper air and the satellite-based radiance observations has been carried out for the outermost domain with horizontal resolution of 9 km. Statistical analysis suggests that the correlation coefficient is high (0.55) and root mean square error (RMSE) is low (17.12) for DA-SAT experiment as compared to other two experiments. Substantial improvement in the location, pattern and intensity of extreme rainfall event is noted after assimilation of both conventional and satellite observations with respect to the observed rainfall data. However, it is noted that the assimilation of satellite radiances has greater impact in simulating better intensity of the heavy rainfall event as compared to the assimilation of conventional observations. Plausible reason behind this could be the non-availability of the conventional observations close to the extreme rainfall event affected region.