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中国沙漠 ›› 2006, Vol. 26 ›› Issue (3): 478-483.

• 研究简报 • 上一篇    下一篇

季以上尺度预报春季区域性沙尘暴过程的方法研究

林 纾

  

  1. 兰州中心气象台, 甘肃 兰州 730020
  • 收稿日期:2005-01-07 修回日期:2005-04-01 出版日期:2006-05-20 发布日期:2006-05-20

Method of Forecasting Regional Sandstorm Process in Spring on Seasonal Scale

LIN Shu   

  1. Lanzhou Central Meteorological Observatory, Lanzhou 730020, China
  • Received:2005-01-07 Revised:2005-04-01 Online:2006-05-20 Published:2006-05-20

摘要: 应用1954—2003年甘肃省沙尘暴发生时间、站次资料和500 hPa NCEP/NCAR再分析资料,分析了春季候区域性沙尘暴的特征。选择影响甘肃省春季天气的500 hPa七个关键区,通过周期分析发现,这些关键区有30候左右的周期可以通过0.01的信度检验,表明500 hPa侯形势场在一定范围内的确存在30候(150 d)左右显著周期。给出春季区域性沙尘暴发生的典型场,计算它与历年10~12月逐候500 hPa距平场的相似系数,结果表明:准150 d韵律方法预测沙尘暴的历史概括率在71.5%~76.4%之间,最高概括率可达87.5%,最低也有60.0%,漏报率为19.8%~26.0%。尽管如此,可以认为该方法对甘肃省区域性沙尘暴,尤其对典型形势场所对应的沙尘暴天气过程有较高的预测能力。最后给出典型年前期500 hPa要素场的特征。

关键词: 沙尘暴, 过程预报, 周期分析, 相似系数

Abstract: With observation data on sandstorm time and stations, and reanalyzed data of 500 hPa NCEP/NCAR from 1954 to 2003 in Gansu province, we analyzed the regional sandstorm characters per five days in spring. Taking seven 500 hPa areas of spring in Gansu province as key studying regions we analyzed the periods of sandstorm weather. There were about 30 pentads (150 days) in these key regions having passed prominence test (α=0.01), which indicated that the 500 hPa geopotential height mean field in spring certainly existed obvious periods about 30 pentads in some extent. The typical fields where regional sandstorm frequently occurred in spring were decided to caculated the similarity coefficients with geopotential height anomaly fields of every pentads in October to December year after year. Result showed that the historical probability in sandstorm accurately forecasting with the \!nearly 30 pentads period method\" was within 71.5%~76.4%, the highest 87.5% and the lowest 60.0%, but the neglecting probability was still at 19.8%~26.0%. Nevertheless, the forecasting method has relatively high capability in forecasting regional sandstorm in Gansu province, especially the sandstorm events corresponding to typical geopotential height fields.

Key words: sandstorm, weather process forecasting, periods analysis, similarity coefficient

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