7B.5 Impact of Assimilating GOES-Imager Radiance with A Rapid Refresh Assimilation System for Convection-Permitting Forecast over Mexico

Yang, Chun, Nanjing University of Information Science & Technology (NUIST), Zhiquan Liu, National Center for Atmospheric Research, Feng Gao, Peter Childs, Panasonic Weather Solution, and Jinzhong Min, NUIST

The GOES-Imager data provide continuous images of the evolutionary pattern of severe weather phenomena with its high spatial and temporal resolution. The capability to assimilate the GOES-Imager radiances has been developed within the WRFDA system. Compared to the benchmark experiment with no GOES-Imager radiance DA, the impact of assimilating GOES-Imager clear-sky radiances on the analysis and forecast of convective process over Mexico in 7-10 March 2016 was assessed through analysis/forecast cycling experiments using rapid refresh assimilation system with hybrid-3DEnVar scheme. With GOES-Imager DA, better analyses were obtained in terms of the humidity, temperature and water vapor channel simulated brightness temperature distribution. Positive forecast impacts from assimilating GOES-Imager radiances were seen when verified against the TAMDAR observations, GOES-Imager observations and Mexico station precipitation data.