Abstract

In this research, different satellite observation data were assimilated into the Weather Research and Forecasting Model (WRF) by using Three-dimensional Variational Data Assimilation System (3DVAR) and its impact on heavy rainfall forecasts was analyzed. The assimilation data include microwave radiance observations from the Advanced Microwave Sounding Unit-A (AMSU-A) and Global Positioning System Radio Occultation (GPS RO) from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) and Challenging Mini satellite Payload (CHAMP) missions. The experiment were conducted in four sets, first without data assimilation, second with only GPS RO data, third with only radiance data and the last one used GPS RO combine with radiance data assimilation. Then all results were compared with the NCEP FNL (Final) Operational Global Analysis and the observation data from Thai Meteorological Department (TMD) stations. It was found that the Radiance assimilation have larger impacts than the GPS RO assimilation. The results of GPS RO assimilation have more positive impacts than the others.

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