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中国沙漠 ›› 2008, Vol. 28 ›› Issue (2): 377-380.

• 天气与气候 • 上一篇    下一篇

石家庄地区沙尘天气分析

柴东红1; 宋晓辉2; 李国翠3; 尤凤春4

  

  1. 1.河北省气象台, 河北 石家庄 050021; 2.邯郸市气象台,河北 邯郸 056001; 3.石家庄市气象台, 河北 石家庄 050081; 4.北京市气象台, 北京 100089
  • 收稿日期:2006-12-29 修回日期:2007-03-12 出版日期:2008-03-20 发布日期:2008-03-20

Analysis and Forecast of Sand-Dust Weather in Shijiazhuang

CHAI Dong-hong1; SONG Xiao-hui2; LI Guo-cui3; LONG Feng-chun4

  

  1. 1.Hebei Meteorological Observatory, Shijiazhuang 050021, China; 2.Handan Meteorological Observatory, Handan 056001, Shijiazhuang, China; 3.Shijiazhuang Meteorological Observatory, Shijiazhuang 050081, China; 4.Beijing Meteorological Observatory, Beijing 100089, China
  • Received:2006-12-29 Revised:2007-03-12 Online:2008-03-20 Published:2008-03-20

摘要:

针对近年来石家庄地区所出现的沙尘天气,利用17个县市的历史资料,从时空分布、出现原因、天气形势等几方面进行了分析。结果发现:近年石家庄沙尘天气总体减少,春季最多。扬沙和沙尘暴的地理分布取决于沙尘源的地理分布,而浮尘的地理分布则是与上游效应、风向和地形密切相关。上游效应对石家庄沙尘天气的形成有重要作用。产生沙尘的天气形势大部分与大风相同。

关键词: 沙尘天气, 特征, 上游效应, 预报

Abstract:

Based on the historical data from the 17 counties, an analysis was conducted from the aspects of time-space distribution, occurring reason, and weather situation of sand-dust weather in recent years in Shijiazhuang District. The sand-dust weather events mostly concentrated in Spring, and the frequency generally reduced in recent years. The geographic distribution of dust-blowing and sand-dust storm events depend on the distribution of dust sources, but the distribution of dust-floating event closely relate to the upstream effect, wind direction and landform. The upstream effect plays an important role on the formation of sand-dust weather in Shijiazhuang District. The weather situations that generate sand-dust weather are same with that generate strong wind. The key to forecast sand-dust weather is drought and rainless in prophase and fourth to fifth grade strong wind in the future; key to forecast dust-floating weather is upstream effect; key to forecast sand-dust storm weather is upper air jet and strong air mass convection.

Key words: dust-blowing weather, feature, upstream effects, forecast

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