Progress in Severe Convective Weather Forecasting in China since the 1950s
Progress in Severe Convective Weather Forecasting in China since the 1950s
复制标题
20世纪50年代以来中国强对流天气预报的进展
DOI：
10.1007/s13351-020-9146-2
复制
发表时间：
2020-08
影响因子：
3.2
通讯作者：
Han Xuqing
中科院分区：
文献类型：
--
作者：
Zhang Xiaoling;Sun Jianhua;Zheng Yongguang;Zhang Yuanchun;Ma Ruoyun;Yang Xinlin;Zhou Kanghui;Han Xuqing
我国地处亚洲季风区，经常发生强对流天气，如短时暴雨、雷暴大风、冰雹和偶尔的龙卷风。我国超临界水预报工作的进展与气象观测网，特别是天气雷达网和气象卫星网的建设和发展密切相关。20世纪50年代后期，一些县级气象局开始根据云和地面气象变量的观测进行冰雹的经验预报。从1959年第一台天气雷达建成至今，我国经过半个多世纪的发展，形成了现代化的全国范围内的超低空综合业务监测预警系统。2009年建立了可操作的SCW预报，包括实时监测、有效期为数十分钟的警报、有效期为数小时的观察和覆盖长达三天的提前期的展望。开展了雷暴、SDHR、雷暴大风和冰雹的业务监测和预报。随着对流分辨数值模式（CRNM）的发展、天气雷达网的升级、新一代气象卫星的发射、对中小尺度系统的认识以及人工智能技术和CRNM预报的进一步应用，未来业务SCW预报的性能将不断提高。
Located in the Asian monsoon region, China frequently experiences severe convective weather (SCW), such as short-duration heavy rainfall (SDHR), thunderstorm high winds, hails, and occasional tornadoes. Progress in SCW forecasting in China is closely related to the construction and development of meteorological observation networks, especially weather radar and meteorological satellite networks. In the late 1950s, some county-level meteorological bureaus began to conduct empirical hail forecasting based on observations of clouds and surface meteorological variables. It took over half a century to develop a modern comprehensive operational monitoring and warning system for SCW forecast nationwide since the setup of the first weather radar in 1959. The operational SCW forecasting, including real-time monitoring, warnings valid for tens of minutes, watches valid for several hours, and outlooks covering lead times of up to three days, was established in 2009. Operational monitoring and forecasting of thunderstorms, SDHR, thunderstorm high winds, and hails have been carried out. The performance of operational SCW forecasting will be continually improved in the future with the development of convection-resolving numerical models (CRNMs), the upgrade of weather radar networks, the launch of new-generation meteorological satellites, better understanding of meso-γ and microscale SCW systems, and further application of artificial intelligence technology and CRNM predictions.
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影响因子：
2.2
作者：
A. O. England;H. Laurent
通讯作者：
A. O. England;H. Laurent
影响因子：
3.2
作者：
Zhou, Kanghui;Zheng, Yongguang;Zhang, Xiaoling
通讯作者：
Zhang, Xiaoling
影响因子：
--
作者：
Jiong Chen;Yongguang Zheng;Xiaoling Zhang;Peijun Zhu
通讯作者：
Jiong Chen;Yongguang Zheng;Xiaoling Zhang;Peijun Zhu
DOI：
--
发表时间：
2013
期刊：
--
影响因子：
--
作者：
郑永光;陈炯
通讯作者：
郑永光;陈炯
影响因子：
--
作者：
Yeung Linus
通讯作者：
Yeung Linus