Advances in Earth Science ›› 2019, Vol. 34 ›› Issue (7): 706-716. doi: 10.11867/j.issn.1001-8166.2019.07.0706

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Progress in Researches on Ensemble Forecasting of Extreme Weather Based on Numerical Models

Li Gao 1( ),Jing Chen 1,Jiawen Zheng 1, 2,Quanliang Chen 2   

  1. 1. CMA Numerical Prediction Center,National Meteorological Center,Beijing 100081, China
    2. College of Atmospheric Science/Plateau Atmosphere and Environment Laboratory of Sichuan Province,Chengdu University of Information Technology,Chengdu 610225, China
  • Received:2019-02-12 Revised:2019-05-25 Online:2019-07-10 Published:2019-07-29
  • About author:Gao Li (1978-), female, Alashan Zuoqi, Inner Mongolia Autonomous Region, Senior engineer. Research areas include weather dynamics and ensemble forecasting. E-mail:
  • Supported by:
    ect supported by the National Science and Technology Supporting Program “Research and development of medium-range probabilistic forecast techniques”(2015BAC03B01);The National Natural Science Foundation of China “Medium-range weather predictability and ensemble-based probabilistic forecasting method of extreme temperature event in China”(41875138)

Li Gao,Jing Chen,Jiawen Zheng,Quanliang Chen. Progress in Researches on Ensemble Forecasting of Extreme Weather Based on Numerical Models[J]. Advances in Earth Science, 2019, 34(7): 706-716.

Under the background of climate change, extreme weather events (e.g., heavy rainfall, heat wave, and cold damage) in China have been occurring more frequently with an increasing trend of induced meteorological disasters. Therefore, it is of great importance to carry out research on forecasting of extreme weather. This paper systematically reviewed the primary methodology of extreme weather forecast, current status in development of ensemble weather forecasting based on numerical models and their applications to forecast of extreme weather, as well as progress in approaches for correcting ensemble probabilistic forecast. Nowadays, the forecasting of extreme weather has been generally dominated by methodology using dynamical models. That is to say, the dynamical forecasting methods based on ensemble probabilistic forecast information have become prevailing in current operational extreme weather forecast worldwide. It can be clearly found that the current major directions of research and development in this field are the application of ensemble forecasts based on numerical models to forecasting of extreme weather, and its improvement through bias correction of ensemble probabilistic forecast. Based on a relatively comprehensive review in this paper, some suggestions with respect to development of extreme weather forecast in future were further given in terms of the issues of how to propose effective approaches on improving level of identification and forecasting of extreme events.

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