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On the development of the GRAPES—A new generation of the national operational NWP system in China

  • Progress/Atmospheric Sciences
  • Published:
Chinese Science Bulletin

Abstract

Numerical weather prediction (NWP) has become one of the most important means for weather forecasts in the world. It also mirrors a nation’s comprehensive strength in meteorology. In 2000, China Meteorological Administration (CMA) established the National Innovative Base for Meteorological Numerical Prediction in the Chinese Academy of Meteorological Sciences (CAMS), to work on developing a new generation of the national operational NWP system—Global/Regional Assimilation and PrEdiction System (GRAPES), to enhance meteorological services in China in the new century. In recent years, the GRAPES has witnessed a fast development. The GRAPES has been set up as an integration of the model framework, data assimilation, regional and global NWP system, which can be commonly used for both operation and research. In this paper, a brief review is made for illustrating the GRAPES system, including the advanced designs of the GRAPES, its diverse applications in multi-fields, and efficiencies of the regional and global GRAPES in operational applications based on hindcast results.

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Authors and Affiliations

  1. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China

    RenHe Zhang & XueShun Shen

Authors
  1. RenHe Zhang
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  2. XueShun Shen
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Corresponding author

Correspondence to RenHe Zhang.

Additional information

Supported by Key Technologies Research & Development Program (Grant No. 2001BA607B), National Key Technology Research and Development Program (Grant No. 2006BAC02B02) and National Basic Research Program of China (Grant No. 2004CB418300)

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Zhang, R., Shen, X. On the development of the GRAPES—A new generation of the national operational NWP system in China. Chin. Sci. Bull. 53, 3429–3432 (2008). https://doi.org/10.1007/s11434-008-0462-7

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  • DOI: https://doi.org/10.1007/s11434-008-0462-7

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