###
气象:2010,36(8):53-60
本文二维码信息
码上扫一扫!
雷达资料和数值模式产品融合技术研究
(1.南京信息工程大学, 南京 210044;2.上海中心气象台, 上海 200030)
A Study on Blending Radar and Numerical Weather Prediction Model Products
(1.Nanjing University of Information Science and Technology, Nanjing 210044;2.Shanghai Meteorological Center, Shanghai 200030)
摘要
图/表
参考文献
相似文献
本文已被:浏览 1477次   下载 2037
投稿时间:2009-09-22    修订日期:2010-03-25
中文摘要: 以雷达外推为基础,配合中尺度数值模式产品作为环境场,提出两种新的雷达资料和数值模式融合技术:动态权重融合法和趋势演变叠加法。且在动态权重融合法中提出用正弦权重、双曲正切权重以及实时滚动权重三种方法计算权重。使用上海及周边地区2009年6月21日的一次对流过程进行个例分析及误差检验,结果表明:利用这两种方法进行融合后的预报结果与雷达外推和数值模式预报结果相比均有所改进,特别是动态权重融合法中的正弦权重和双曲正切权重对于预报结果的改进尤为明显,融合后的结果更接近实况,表明动态权重融合法和趋势演变叠加法这两种方法是有效可行的,对短时临近预报技术研究有较高的参考价值。
Abstract:Two new techniques of dynamical weight blending and trend evolving superimposing have been proposed based on radar extrapolation, coordinating with numerical weather prediction as environment field. In dynamical weight blending, three ways to calculate weight are used: sine weight, hyperbolic tangent weight and real time scrolling weight. A convective process of Shanghai and surrounding areas on 21 June, 2009 has been used as an example to analyze and examine. The result shows that after blending, the prediction results are both improved compared to radar extrapolation and numerical weather prediction. The blending results of sine weight and hyperbolic tangent weight in dynamical weight blending are more close to observations. It shows that dynamical weight blending and trend evolving superimposing are effective and feasible and of great value to the study of short term forecast and nowcasting.
文章编号:     中图分类号:    文献标志码:
基金项目:上海世博会精细化气象服务系统建设项目:长三角地区短时临近预报一体化业务平台资助
引用文本:
杨丹丹,申双和,邵玲玲,邹兰军,2010.雷达资料和数值模式产品融合技术研究[J].气象,36(8):53-60.
YANG Dandan,SHEN Shuanghe,SHAO Lingling,ZOU Lanjun,2010.A Study on Blending Radar and Numerical Weather Prediction Model Products[J].Meteor Mon,36(8):53-60.