Operational technology advances in meteorological early warning for flash flood disasters
BAO Hongjun, CAO Yong, LIN Jian, YANG Yin, DI Jingyue, XU Fengwen, LIU Couhua
1. National Meteorological Center, China Meteorological Administration, Beijing 100081; 2. The Joint Laboratory of Hydrometeorological Research of China Meteorological Administration and Hohai University, Beijing 100081
Abstract:A review of operational technology advances in meteorological early warning for flash flood disaster is presented with regional characteristics of torrential rain in China, quantitative precipitation evaluation and forecasting, meteorological early warning for flash flood disaster, and operation of meteorological early warning for flash flood disaster. Results show that multi-source precipitation merging model, based on GIS and characteristics of short duration precipitation for different hydrometeorological divisions, is an important way for flash flood monitoring; nowcasting and short-term quantitative precipitation forecasting combined with machine learning, radar extrapolation, rapid assimilation and forecasting, distributed hydrological model controlling volume method with coupling conceptual runoff generation module and physical routing module, dynamic rainfall thresholds are the main methods to improve the meteorological warning accuracy for flash flood disaster. The breadth and depth of the risk survey for flash flood disaster is the precondition of promoting the operational capability of meteorological early warning of flash flood disaster.
包红军, 曹勇, 林建, 杨寅, 狄靖月, 许凤雯, 刘凑华. 山洪灾害气象预警业务技术进展[J]. 中国防汛抗旱, 2020, 30(9-10): 40-47.
BAO Hongjun, CAO Yong, LIN Jian, YANG Yin, DI Jingyue, XU Fengwen, LIU Couhua. Operational technology advances in meteorological early warning for flash flood disasters. journal1, 2020, 30(9-10): 40-47.
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