摘要
2022年气象联合基金资助数值预报模式关键技术、灾害天气监测预报理论与方法和人工智能气象应用技术三个核心领域,共接收申请64项,其中不同单位属性的合作申请占87.5%。申请书关键词分析发现,气象联合基金与地球科学部“天气及气候系统与可持续发展”领域重点项目既有较强的联系,又有明显的区别。气象联合基金评审过程与地球科学部常规重点基金评审过程相似。经过通讯评审和会评,共资助14项重点支持项目,资助率21.9%,平均资助强度264.6万元/项,年均资助强度超过了地球科学部常规重点项目的资助强度。
In 2022,the Meteorological Joint Fund(MJF)supported three key research fields:the key technology of numerical prediction model,the theory and method of disaster weather monitoring and prediction,and the artificial intelligence meteorological application technology.Accordingly,the National Natural Science Foundation of China(NSFC)received 64 MJF applications comprising 87.5%cooperation applications with different unit attributes,and mail/panel reviews were conducted.Keyword analyses of the application revealed that MJF and the key programs in the“weather,climate,and associated sustainable development”field,Department of Earth Sciences(DES),had strong links and obvious differences.The review process of MJF is similar to the key conventional programs of DES,NSFC.NSFC funded 14 key supporting projects with a success rate of 21.9%,and the average annual funding intensity of the MJF exceeded that of DES,NSFC.
作者
何建军
张宇
刘哲
杨蕾
任颖
葛非
郭郁葱
李婧
Jianjun HE;Yu ZHANG;Zhe LIU;Lei YANG;Ying REN;Fei GE;Yucong GUO;Jing LI(Department of Earth Sciences,National Natural Science Foundation of China,Beijing 100085;Department of Science&Technology and Climate Change,China Meteorological Administration,Beijing 100081)
出处
《大气科学》
CSCD
北大核心
2023年第3期920-924,共5页
Chinese Journal of Atmospheric Sciences
关键词
多元投入
气象联合基金
大气科学
国家需求
Multiple inputs
Meteorological Joint fund
Atmospheric science
National demand