| 对流天气临近预报技术的发展与研究进展 |
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| 引用本文： | 陈明轩,俞小鼎,谭晓光,王迎春.对流天气临近预报技术的发展与研究进展[J].应用气象学报,2004,15(6):754-766. |
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| 作者姓名： | 陈明轩 俞小鼎 谭晓光 王迎春 |
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| 作者单位： | 1.中国气象局北京城市气象研究所, 北京 100089 |
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| 基金项目： | “十五”国家科技攻关计划课题“奥运气象保障技术研究”( 2 0 0 2BA90 4B0 5 )，北京市重大科技计划项目“奥运会气象保障科学技术试验与研究”(H0 2 0 62 0 1 90 0 91 )，“十五”国家科技攻关计划课题奥运科技专项“北京奥运会国际天气预报示范计划关键技术研究”( 2 0 |
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| 摘 要： | 目前，临近预报技术主要包括雷暴识别追踪和外推预报技术、数值预报技术以及以分析观测资料为主的概念模型预报技术等。其中，识别追踪和外推预报技术主要以雷达资料为基础，在这方面，交叉相关外推和回波特征追踪识别外推是比较成熟的技术，已经用于许多的临近预报业务系统中，其缺陷是预报时效较短，准确率也不是很高。随着精细数值天气预报技术和计算机技术的发展，利用多普勒天气雷达资料和其它中小尺度观测资料进行数值模式初始化，来预报雷暴的发生、发展和消亡已经成为一个研究的热点，该技术发展很快但还不成熟。概念模型预报技术主要是通过综合分析多种中小尺度观测资料，包括雷达和气象卫星资料等，在此基础上建立雷暴发生、发展和消亡的概念模型，特别是边界层辐合线和强对流的密切关系等，再结合数值模式分析预报和其它外推技术的结果，然后建立雷暴临近预报的专家系统，其不但可以获取雷暴和对流降水移动、发展的信息，还可以预报它们的生成和消亡。检验和定性评估也表明，将多种资料和技术集于一体的概念模型专家系统，其临近预报的准确率最高，时效也最长，是临近预报技术未来发展的主要趋势之一。NCAR的Auto Nowcaster系统是雷暴临近预报概念模型专家系统的一个典型代表。
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| 关 键 词： | 临近预报 算法 专家系统 |
| 收稿时间： | 2003-06-20 |
| 修稿时间： | 2003年6月20日 |
A Brief Review on the Development of Nowcasting for Convective Storms |
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| Chen Mingxuan,Yu Xiaoding,Tan Xiaoguang,Wang Yingchun.A Brief Review on the Development of Nowcasting for Convective Storms[J].Quarterly Journal of Applied Meteorology,2004,15(6):754-766. |
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| Authors: | Chen Mingxuan Yu Xiaoding Tan Xiaoguang Wang Yingchun |
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| Affiliation: | 1.Institute of Urban Meteorology, CMA, Beijing 1000892.China Meteorological Ad ministration Training Center, Beijing 100081 |
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| Abstract: | Nowadays, the nowcasting technique and research for convective storms have an exciting advancement along with the rapid development of Doppler weather radar and many else meso- and micro-scale meteorological observation instruments. At present, main nowcasting techniques comprise three aspects: identification, tracking and extrapolation forecast, numerical model forecast, knowledge-based forecast technique. Cross-correlation technique and echo feature identification and tracking algorithms are well-performed extrapolation techniques mainly based on weather radar data and are utilized by many operational nowcasting systems, but there are very short forecast period and low accuracy. Now the techniques that assimilate radar, mesonet and micro-scale data into fine meso- and micro-scale numerical models to nowcast initiation, evolution and dissipation of thunderstorms are very promising and robust. Techniques are progressing rapidly but not mature for operation. Knowledge-based nowcasting techniques are more observation-based. They combine and analyze a variety of fine meteorological data sources, including radar and satellite data, then theorize conceptual models of initiation, evolution and dissipation of thunderstorms, especially, the close relation between boundary layer convergence lines and enhanced convection, as well as integrate fine numerical models outputs initiated with or without radar data and extrapolation techniques results, then build expert system of thunderstorm nowcasting to gain information about not only the development but also the initiation and dissipation of thunderstorms and convective rainfall. Verification and qualitative assessment of forecast also show that the expert systems outperform all other techniques for operational nowcasting thunderstorms and convective precipitation in accuracy and period. The expert systems are one of the primary techniques for nowcasting convective storms evolution in the near future. Auto-Nowcaster developed by NCAR is one of the state-of-the-art expert systems for nowcasting thunderstorms. |
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| Keywords: | Nowcasting Algorithm Expert system |
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