J5.4
Development of GRAPES Hourly Assimilation System

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Monday, 24 January 2011: 2:15 PM
Development of GRAPES Hourly Assimilation System
2B (Washington State Convention Center)
Chen Zi-tong, CMA, Guangzhou, China

Based on the Chinese new generation NWP system GRAPES, an hourly assimilation and forecast cycle was developed. The key components are the GRAPES non-hydrostatic prognostic model, featuring the semi-implicit semi-Lagrangian time integration in gridded mesh, and the three dimensional variational data assimilation. The observational data being assimilated include radio soundings, surface and ship observations, aircraft data, weather radar (radial wind and VAD wind), satellite derived winds and ground-based GPS data. The radar reflectivity data are also used to get the mixing ratio of hydrometeors in clouds which are then fed to the model by Newtonian relaxation ( nudging) in order to improve the cloud description at the model start. In cases of tropical storms, a bogus vortex is introduced using BDA and relocation techniques. All raw data are preprocessed before being used in the assimilation in order to keep good quality and reasonable spatial density of the observational data. This preprocessing includes data quality control and screening taking into account the credibility of various observation data, and their spatial distribution. The analysis increments, which will be added to the forecasts initiating one hour before are obtained by 3DVAR. After this step, a diabatic digital filter initialization DDFI is implemented to control the noisy oscillation. The current horizontal resolutions of the forecast model are 0.12°lat/long for a domain of 2500 km and 0.03°lat/long for a domain of 1000km. The system is run operationally in the South China Regional Meteorological Center and provides analysis and forecast products to support the routine nowcasting of rainstorm or other convective systems. The verification of operational implementation shows positive impacts on the improvement of the severe weather forecast within 6 hours.