Overview of Chinese New Generation NWP System GRAPES

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Tuesday, 25 January 2011: 8:30 AM
Overview of Chinese New Generation NWP System GRAPES
615-617 (Washington State Convention Center)
Jishan Xue, Chinese Academy of Meteorological Sciences, Beijing, China

This paper briefly introduces the Global and Regional Assimilation and Prediction System (GRAPES in short) which is Chinese new generation numerical weather prediction system completed in recent years. The non-hydrostatic prognostic model with semi-Lagrangian and semi -implicit scheme for time integration is designed to meet the needs of running in very high spatial resolution efficiently. The system may be set up in global or limited area domains depending on the operational requirements, and a number of options of model physical schemes are provided to match the configuration of the model. The variational approach, currently 3DVar and to be upgraded to 4DVar, is adopted with stresses at application of various remote sensing observational data. Based on the prototype of GRAPES, a global and a regional NWP system have been run in routine operation in the National Meteorological Center of CMA. The system is also implemented in some of Chinese regional meteorological centers. The verification of their operational products shows some improvement in forecast skill mainly due to the applications of abundant satellite data and the improvements of model physics . In addition to operational uses in global and regional short and medium range weather predictions, an hourly assimilation system is also developed based on GRAPES to fuse all available high density observational data for use of nowcasting of rainstorms and other convective systems. GRAPES prognostic model is also used to study the sand storm, air quality of mega cities and lightning by coupling with atmospheric chemistry and atmospheric electricity models. Planned upgrades of GRAPES in the near future include implementation of 4DVar, new dynamic core with Ying-Yang grid and more sophisticated physical parameterization schemes. The higher spatial resolution is also expected with more computer resources in CMA to be available.