摘要:大气可预报性研究是开展天气、气候预测的基础科学问题。全球变暖背景下，近年暴雨和强对流等中小尺度灾害性天气频发，如何深入认识其可预报性问题成为了天气领域研究热点，也是制约数值天气预报模式能力提升的重要因素。本文在简要回顾国内外大气可预报性研究历程的基础上，重点对近二十年（1999～2018）国际上关于暴雨和强对流可预报性方面的最新研究进展进行了系统的综述和归纳。主要包括：中小尺度可预报性研究的主要方法和评估手段及其与传统大尺度天气可预报性研究的差异，初始误差增长机制的几种主要观点及其争论（误差升尺度、误差降尺度、升降尺度并存），数值模式误差和对流环境误差对实际预报性的影响，以及最近的中尺度可预报性科学观测试验进展等。最后，对暴雨、强对流可预报性研究存在的问题、未来发展方向进行了简要的讨论和展望。
关键词:暴雨/
强对流/
误差增长/
集合预报/
可预报性
Abstract:Atmospheric predictability research is the basis for weather and climate prediction. Under the background of global warming, meso/micro-scale extreme weather events such as heavy rain and severe convection have occurred more frequently in recent years, and their predictability has attracted wide attention. After briefly reviewing the history of atmospheric predictability research, this paper systematically reviews the latest advances in the predictability of heavy rain and strong convection over the last 20 years (1999–2018). The main research methods for meso/micro-scale predictability and their differences with traditional large-scale weather predictability methods are first discussed. Then, the primary initial error growth mechanism (error upscaling under deep moist convection) is elaborated in detail, and some arguments (error downscaling, error upscaling, and downscaling coexisting) are discussed. The effects of errors in NWP (Numerical Weather Prediction) models and convective environments on the practical predictability are also highlighted, and some recent mesoscale predictability experiments are reviewed. Finally, this paper briefly discusses the current problems, challenges, and future directions of the predictability research of heavy rain and severe convection.
Key words:Heavy rain/
Severe convection/
Error growth/
Ensemble forecast/
Predictability
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