崔春光, 杜牧云, 肖艳姣
Study on the Technique of Data Assimilation and Nowcasting of Severe Convective Weather
Cui Chunguang, Du Muyun, Xiao Yanjiao
(Institute of Heavy Rain, CMA)
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投稿时间:2020-08-03    修订日期:2021-03-02
中文摘要: 强对流天气的精准预报依然具有极大难度和挑战性。为了提高强天气监测预报服务能力,科技部政府间国际科技合作重点专项“灾害性天气资料同化与临近预报系统开发”项目组开展了以下研究工作:(1)研发了新的中气旋和龙卷涡旋特征识别算法,并在十几个龙卷风实例中成功地识别出龙卷涡旋特征;从多普勒天气雷达体扫数据中提取了诸多参数(超过30个)开展分类强对流天气(下击暴流、龙卷、冰雹和短时强降水)自动识别预警技术研究。(2)快速更新循环预报系统可以有效地提高模式初值的质量,非常适合于短时天气预报应用。为进一步提高强雷暴预报的精度,提出了一种新的基于雷达反演水汽的伪水汽同化方法,以更好地初始化对流尺度的数值天气模式。(3)旨在克服目前中尺度数值模式在对流尺度定量降水短时预报方面的不足,弥补基于“外推”的临近预报技术在2 h以上定量降水预报能力快速下降的缺陷而研发的融合技术具有提高短时临近降水预报能力的潜力。
Abstract:It is still extremely difficult and challenging for accurate prediction of convective weather systems. In order to improve the service ability in strong weather monitoring and prediction, the following studies have been carried out recently: (1) The new mesocyclone and tornado vortex feature recognition algorithms are developed and proved to be successfully in identifying tornado vortex characteristics in more than a dozen tornado cases. Extracted from Doppler radar volume scan data, more than thirty parameters have been used in the study on the automatic recognition and warning technology of classified severe convective weather (downburst, tornado, hail and short-time strong precipitation).. (2) Rapid update cycle forecast system can effectively improve the quality of model initial values that is very suitable for short-time forecast application. For the sake of improving severe thunderstorm prediction, a novel pseudo-observation and assimilation approach involving water vapor mass mixing ratio is proposed to better initialize numerical weather prediction (NWP) at convection-resolving scales. (3) The blending technology which is expected to overcome the deficiency of the quantitative precipitation forecast (QPF) by a mesoscale NWP model for the short term at convective scales and the rapidly descending skill of rainfall forecast based on radar extrapolation method beyond the first few hours is under development, and also has potential in enhancing the ability of rainfall forecast within the nowcasting period.
文章编号:202008030271     中图分类号:P456    文献标志码:
崔春光 中国气象局武汉暴雨研究所 武汉市东湖新技术开发区金融港二路6号
杜牧云 中国气象局武汉暴雨研究所 武汉市东湖新技术开发区金融港二路6号
肖艳姣 中国气象局武汉暴雨研究所 
Author NameAffiliationAddress
Cui Chunguang Institute of Heavy Rain, CMA 武汉市东湖新技术开发区金融港二路6号
Du Muyun  武汉市东湖新技术开发区金融港二路6号
Xiao Yanjiao  
崔春光,杜牧云,肖艳姣,.Study on the Technique of Data Assimilation and Nowcasting of Severe Convective Weather[J].Meteor Mon,():-.
Cui Chunguang,Du Muyun,Xiao Yanjiao,.Study on the Technique of Data Assimilation and Nowcasting of Severe Convective Weather[J].Meteor Mon,():-.