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气象:2021,47(6):671-684
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国家级水文气象预报业务技术进展与挑战
包红军,张恒德,许凤雯,狄靖月,王蒙,曹爽,杨寅,李宇梅,刘海知
(国家气象中心,北京 100081; 中国气象局-河海大学水文气象研究联合实验室,北京 100081)
Progress and Challenge of National Level Operational Technology for Hydrometeorological Forecasting
BAO Hongjun,ZHANG Hengde,XU Fengwen,DI Jingyue,WANG Meng,CAO Shuang,YANG Yin,LI Yumei,LIU Haizhi
(National Meteorological Centre, Beijing 100081; CMA-HHU Joint Laboratory for Hydrometeorological Studies, Beijing 100081)
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投稿时间:2020-08-20    修订日期:2021-02-03
中文摘要: 近年来,国家级水文气象预报业务已经取得了明显进展,但与国外先进水平相比还有一定的差距。总结了近十年来国内外水文气象预报业务现状和技术进展,目前国家级的技术支撑状况和所面临的挑战,并提出未来发展计划。目前,水文气象预报技术主要是以基于统计学的致灾阈值模型和分布式水文模型等为主,结合大数据分析与人工智能的气象—水文—地质耦合预报模式将在水文气象预报中发挥重要作用。流域天—空—地基监测、水文气象灾害机理研究和多尺度分析是水文气象预报的重要基础;基于无缝隙精细化智能网格降水的水文气象预报技术及水文集合预报模式是水文气象预报的发展方向。
Abstract:The forecasting operation of quantitative hydrometeorology with accurate spatio temporal distribution is to meet the demands of the national disaster prevention and mitigation, major projects support, expanding impacted forecasting and risk warning. Although great progresses in the hydrometeorological forecasting have been made in National Meteorological Centre in the recent years, there are still many gaps compared with the advanced forecasting technology in foreign countries. The current development of technique and operation status of the hydrometeorological forecasting was reviewed in this paper. In addition, the current challenges facing China were summarized and the corresponding measures and further development plans were proposed. At present, the main techniques on hydrometeorological forecasting can be classified as two types: the rainfall threshold model based on statistical theory and the distributed hydrological model. Moreover, the atmospheric hydrological geological model based on big data analysis and artificial intelligence technique will play important roles in the hydrometeorological forecasting. Hydrometeorological monitoring with satellite, radar and gauge observations is the foundation of hydrometeorological forecasting. Hydrometeorological forecasting based on seamless fine intelligent and grid QPF and hydrometeorological ensemble forecasting model will be the important development directions of the hydrological forecasting in the future.
文章编号:     中图分类号:P49,P641    文献标志码:
基金项目:国家重点研发计划(2018YFC1508102、2016YFC0402702)、国家自然科学基金项目(41775111、41875131)、2019年国家气象中心现代化项目(QXXDH201912)、2020年国家气象中心青年基金项目(Q202004、Q202006)和2020年国家气象中心科技成果转化基金项目(K202004)共同资助
引用文本:
包红军,张恒德,许凤雯,狄靖月,王蒙,曹爽,杨寅,李宇梅,刘海知,2021.国家级水文气象预报业务技术进展与挑战[J].气象,47(6):671-684.
BAO Hongjun,ZHANG Hengde,XU Fengwen,DI Jingyue,WANG Meng,CAO Shuang,YANG Yin,LI Yumei,LIU Haizhi,2021.Progress and Challenge of National Level Operational Technology for Hydrometeorological Forecasting[J].Meteor Mon,47(6):671-684.