Satellite Radiance Data Assimilation Using the WRF-3DVAR System for Tropical Storm Dianmu (2021) Forecasts

This study investigated the impact of assimilation satellite radiance observations in a three-dimensional variational data system (3DVAR) that could improve tracking and intensity forecasts Tropical Storm Dianmu 2021, which occurred over parts southeast mainland Asia. The weather research forecasting (WRF) model was used to conduct experiments storm. Four sets numerical were performed using WRF. In first, control experiment, only conventional Binary Universal Form for Representation Meteorological Data (PREPBUFR) from National Centers Environmental Prediction (NCEP) assimilated. second experiment (RDA1) with PREPBUFR Advanced Microwave Unit-A (AMSU-A), Technology Sounder (ATMS). High-resolution Infrared Radiation (HIRS-4) third (RDA2). fourth (ALL-OBS) all (AMSU-A, ATMS, HIRS-4). community radiative transfer on forward operator assimilation, along quality bias correction procedures, before assimilating data. To evaluate experiments, forecast starting 00 UTC 23 September produced 72 h. results showed ALL-OBS improved short-term up ~24 h lead time, as compared considering observations. When assimilated into model, storm’s landfall position, intensity, structure accurately predicted. deterministic forecast, errors consistently less than 40 km within 24 case exhibited significant positive updates initial conditions storm forecasting.