中国当代强对流天气研究与业务进展

对当代中国几十年来强对流天气研究和业务进展做了阐述,主要包括强对流系统产生的环境背景和主要组织形态,以及具体强对流天气的有利环境条件、触发机制、卫星云图特征、多普勒天气雷达回波特征以及预报、预警技术等诸方面。总体来看,中国学者对强对流以及不同类型强对流天气(强冰雹、龙卷、雷暴大风)发生、发展的环流背景以及通过雷达和卫星观测到的组织结构及其演变特征都已有了明确认识,研究了对流系统的多种触发机制,深入认识了超级单体、飑线等对流系统的环境条件、组织结构特征和维持机制,了解了中国中尺度对流系统的组织形态和气候分布特征,获得了强冰雹、龙卷、下击暴流和雷暴大风等的雷达、卫星和闪电等的多尺度观测特征、形成机制和现场灾害调查特征,发展了各类强对流天气识别、监测和分析方法以及基于"配料法"和深度学习方法等的预报、预警技术等。因此,强对流天气业务预报水平已得到显著提升。

Advances in severe convective weather research and operational service in China

This article reviews advances in severe convective weather research and operational service in China during the past several decades. It emphasizes the synoptic situations favorable for severe convective weather, the major organization modes of severe convective storms, the favorable environmental conditions and the characteristics of weather radar echoes and satellite imageries of severe convective weather, as well as the forecasting and nowcasting techniques of the weather. As a whole, Chinese scientists have profoundly understood synoptic patterns, organizations and evolution characteristics from radar and satellite observations, and mechanisms of different types of convective weather in China. They have studied and have deeply understood multiple types of triggering mechanism for convection, and the environmental conditions, the structures and modes, and the maintenance mechanisms for supercell storms and squall lines. They also have obtained the organization modes and climatological distributions of mesoscale convective systems and different types of convective weather in China, and the multiscale characteristics and formation mechanisms for large hail, tornadoes, downbursts and damaging convective wind gusts based on radar, satellite and lightning observations, and damage survey features. For operational weather forecasting, they have developed various methods and techniques for identifying severe weather and for mesoanalysis. Many different types of nowcasting and forecasting techniques for severe weather forecast such as "ingredients-based" and deep learning have been developed. As a result, the performance of operational severe convective weather forecasts in China has been significantly improved.