沈学顺,王建捷,李泽椿,陈德辉,龚建东. 2020. 中国数值天气预报的自主创新发展[J]. 气象学报, 78(3):451-476, doi:10.11676/qxxb2020.030
中国数值天气预报的自主创新发展
China's independent and innovative development of numerical weather prediction
投稿时间:2019-09-02  修订日期:2019-12-31
DOI:10.11676/qxxb2020.030
中文关键词:  数值天气预报  GRAPES  半隐式半拉格朗日格点模式  物理过程  卫星资料同化  四维变分同化
英文关键词:Numerical weather prediction  GRAPES  Semi-implicit semi-Lagrangian grid point model  Physical processes  Satellite data assimilation  Four dimensional assimilation
基金项目:国家重点研发计划项目(2017YFC1501900)、中国工程院中国工程科技中长期发展战略研究“面向2035的国家经济建设发展与国家安全需求中的气象保障工程”(2019-ZCQ-06)
作者单位E-mail
沈学顺 国家气象中心北京100081
中国气象局数值预报中心北京100081
中国气象科学研究院灾害天气国家重点实验室北京100081 
 
王建捷 国家气象中心北京100081
中国气象局数值预报中心北京100081 
wangjj@cma.gov.cn 
李泽椿 国家气象中心北京100081  
陈德辉 国家气象中心北京100081
中国气象局数值预报中心北京100081 
 
龚建东 国家气象中心北京100081
中国气象局数值预报中心北京100081 
 
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中文摘要:
      数值天气预报是天气预报业务和防灾、减灾的核心科技。中国数值天气预报研究和业务应用一直受到高度重视,在理论、方法和数值模式研究方面取得了有广泛国际影响的研究成果。在回顾新中国数值天气预报自主创新研究成果的基础上,重点对GRAPES(Global Regional Assimilation and PrEdiction System)半隐式半拉格朗日格点模式与物理过程的研发和业务应用的状况以及所取得的重要科学进展进行了综述。近年来,通过自主研发建立了中国数值天气预报业务体系—GRAPES体系。首次以自主技术实现了从区域3—10 km到全球25—50 km分辨率的确定性预报和集合预报系统,并在模式动力框架、四维变分同化和卫星资料同化技术等方面有所突破,建立了大气化学数值天气预报、台风数值预报和海浪预报等系统。自主研发的数值天气预报体系的建立是长期坚持既定科学技术方向以及研究和业务紧密结合、经验不断积累的结果,是中国自主发展数值天气预报技术的重要起点。
英文摘要:
      Numerical weather prediction (NWP) is the core technology of weather forecast and disaster prevention and mitigation. China's NWP research and operational applications have been attached great importance by the meteorological society. Great achievements have been made in the theories, methods and numerical model developments in China, which have a wide range of international impacts. The scientific and technological progresses of NWP since 1949 was summarized. The main part of this paper then devotes to presenting the current status and recent progresses of the domestically developed NWP system, i.e., GRAPES (Global Regional Assimilation and PrEdiction System). In the recent 10 years, a new operational NWP system has been established through independent research and development. This system includes both regional and global deterministic and ensemble prediction models with the resolutions ranging from 3 to 10 km for regional and 25 to 50 km for global forecasts. New progresses have been made in dynamic core, 4-dimensional variational assimilation and satellite data assimilation. The GRAPES system also is extended to drive the atmospheric chemistry model and ocean wave model.
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