主办单位：中国气象局沈阳大气环境研究所
国际刊号：ISSN 1673-503X
国内刊号：CN 21-1531/P
气象与环境学报

气象与环境学报 ›› 2011, Vol. 27 ›› Issue (3): 1-5.doi:

• 论文 •    下一篇

低频环流系统的一种统计预报方法

杨玮1 何金海1 孙国武2 孔春燕3   

  1. 1.南京信息工程大学江苏省气象灾害重点实验室，江苏 南京 230044；2.中国气象局兰州干旱气象研究所，甘肃 兰州 730020；3.上海市气候中心，上海 200030
  • 收稿日期:2011-01-05 修回日期:2011-03-19 出版日期:2011-06-30 发布日期:2011-03-19

A statistical forecasting method of low-frequency circulation systems

YANG Wei1 HE Jin-hai1 SUN Guo-wu2 KONG Chun-yan3   

  1. 1. Key Laboratory of Meteorological Disaster in Jiangsu Province, Nanjing University of Information Science and Technology, Nanjing 210044, China; 2. Lanzhou Institute of Arid Meteorology, China Meteorological Administration, Lanzhou 730020, China; 3. Shanghai Climate Centre, Shanghai 200030, China
  • Received:2011-01-05 Revised:2011-03-19 Online:2011-06-30 Published:2011-03-19

PDF (PC)

766

被引次数

40

摘要： 根据实时MICAPS资料，采用经验正交函数分解和滤波方法，统计分析了欧亚大陆上空700 hPa水汽输送通量流函数和势函数主要低频分量的分布特征。结果表明：存在流函数和势函数低频环流系统变化的关键区。根据关键区环流系统演变，确定了与上海地区未来10-30 d强降水过程相对应的预报指标。以上海地区2010年7月的降水过程预报为例概述了整个预报流程，并从物理机制上证明了低层（110°E，30°N）附近的辐合以及自低空至高空向东倾斜的上升运动是造成该次降水的主要成因。

关键词: 低频分量, 自回归模型, 强降水过程指标, 预报流程

Abstract: Based on the real-time MICAPS data, the distribution characteristics of the main components of low-frequency stream function and velocity potential function for moisture flux at 700 hPa over Eurasia were analyzed in terms of methods of an empirical orthogonal function (EOF) and a Butter-Worth filter. The results indicate that there exists the key area of low-frequency variations of stream function and velocity potential function. According to the evolution of low-frequency circulation systems in the key areas, some forecast indices of intensive rainfall events in future 10-30 days for shanghai are established. A prediction case of heavy rain in Shanghai in July of 2010 is displayed as an introduction to the whole forecast flow. The physical mechanism of this process proves that the convergence near lower level (110°E, 30°N) and upward motion inclining to the east from lower to upper levels are the main reasons causing the heavy rain.

Key words: Low-frequency components, Auto-regressive model, Indices of heavy rain events, Forecast flow

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