Study on Ensemble-Based Forecast of Extremely Heavy Rainfalls in China: Experiments for July 2011 Cases

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  • Funds:

    Supported by the National Natural Science Foundation of China (41075035), National Science and Technology Support Program of China (2009BAC51B00), National Basic Research and Development (973) Program of China (2012CB417204), and China Meteorological Administration Special Public Welfare Research Fund (GYHY200906007).

  • doi: 10.1007/s13351-013-0203-y

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  • According to the Anderson-Darling principle, a method for forecast of extremely heavy rainfall (abbreviated as extreme rainfall/precipitation) was developed based on the ensemble forecast data of the T213 global ensemble prediction system (EPS) of the China Meteorological Administration (CMA). Using the T213 forecast precipitation data during 2007-2010 and the observed rainfall data in June-August of 2001-2010, characteristics of the cumulative distribution functions (CDFs) of the observed and the T213 EPS forecast precipitation were analyzed. Accordingly, in the light of the continuous differences of the CDFs between model climate and EPS forecasts, a mathematical model of Extreme Precipitation Forecast Index (EPFI) was established and applied to forecast experiments of several extreme rainfall events in China during 17-31 July 2011. The results show that the EPFI has taken advantage of the tail information of the model climatic CDF and provided agreeable forecasts of extreme rainfalls. The EPFI based on the T213 EPS is useful for issuing early warnings of extreme rainfalls 3-7 days in advance. With extension of the forecast lead time, the EPFI becomes less skillful. The results also demonstrate that the rationality of the model climate CDF was of vital importance to the skill of EPFI.
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Study on Ensemble-Based Forecast of Extremely Heavy Rainfalls in China: Experiments for July 2011 Cases

  • 1. Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research,Institute of Heavy Rain,China Meteorological Administration,Wuhan 430074;
    Chengdu University of Information Technology,Chengdu 610225;
    Numerical Weather Prediction Center,Beijing 100081;
    Chengdu University of Information Technology,Chengdu 610225;
    Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research,Institute of Heavy Rain,China Meteorological Administration,Wuhan 430074;
    Chengdu University of Information Technology,Chengdu 610225
Funds: Supported by the National Natural Science Foundation of China (41075035), National Science and Technology Support Program of China (2009BAC51B00), National Basic Research and Development (973) Program of China (2012CB417204), and China Meteorological Administration Special Public Welfare Research Fund (GYHY200906007).

Abstract: According to the Anderson-Darling principle, a method for forecast of extremely heavy rainfall (abbreviated as extreme rainfall/precipitation) was developed based on the ensemble forecast data of the T213 global ensemble prediction system (EPS) of the China Meteorological Administration (CMA). Using the T213 forecast precipitation data during 2007-2010 and the observed rainfall data in June-August of 2001-2010, characteristics of the cumulative distribution functions (CDFs) of the observed and the T213 EPS forecast precipitation were analyzed. Accordingly, in the light of the continuous differences of the CDFs between model climate and EPS forecasts, a mathematical model of Extreme Precipitation Forecast Index (EPFI) was established and applied to forecast experiments of several extreme rainfall events in China during 17-31 July 2011. The results show that the EPFI has taken advantage of the tail information of the model climatic CDF and provided agreeable forecasts of extreme rainfalls. The EPFI based on the T213 EPS is useful for issuing early warnings of extreme rainfalls 3-7 days in advance. With extension of the forecast lead time, the EPFI becomes less skillful. The results also demonstrate that the rationality of the model climate CDF was of vital importance to the skill of EPFI.

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