极端天气的数值模式集合预报研究进展

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

在气候变化背景下,极端天气事件(暴雨、高温热浪和低温冷害等)发生频次有不同程度增加的趋势,由极端事件造成的气象灾害也呈现增多趋势,因此开展极端天气的预报研究尤为重要。系统性回顾了极端天气预报的主要方法、数值模式集合天气预报发展现状及其在极端天气预报中的应用情况以及集合概率预报的订正方法研究进展。目前,极端天气的预报以动力数值模式方法为主导,即以集合概率预报信息为主要依据的动力预报方法成为当前国际上极端天气业务预报的主流方法。基于数值模式集合预报的极端天气预报应用和依靠概率预报偏差订正来改进极端预报,是当前该领域研究的重要发展方向。在全面回顾的基础上,围绕如何发展有效方法提升极端事件识别和预报水平,进一步提出未来极端天气集合预报发展的几点建议。

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.