J4 ›› 2009, Vol. 27 ›› Issue (2): 111-117.

• 论文 • 上一篇    下一篇

山西沙尘天气的相关气候因子分析及预测模型的建立

刘瑞兰任国玉吴占华   

  1. 1.山西省朔州市气象局,山西 朔州 036001; 2.中国气象局气候研究开放实验室,国家气候中心,北京 100081
  • 出版日期:2009-06-30 发布日期:2009-06-30
  • 作者简介:刘瑞兰(1969-) ,女,山西朔州人,工程师,主要从事短期气候预测和天气气候研究工作.E-mai:l liurl691113@ 163. com

Analysis on Correlation C limatic Factors and Establishm ent of the PredictionM odel for Dust Storm Events in ShanxiProvince

 LIU Rui-Lan1, LIN Guo-Yu2, TUN Tie-Hua1   

  1. (1. ShuozhouMeteorologicalBureau ofShanxiProvince, Shuozhou036001, China;2. Laboratory forClimate Studies, NationalClimate Center, CMA, Beijing100081,China)
  • Online:2009-06-30 Published:2009-06-30

摘要:

对山西沙尘天气与蒙古国的降水、我国北方积雪日数、青藏高原积雪日数和表征气候异常变化信号的大气—海洋环流因子SOI指数的关系进行了分析,揭示了全球准周期性变化对沙尘天气趋势的主导性作用。得出蒙古国西部前一年降水对山西省的沙尘天气具有较好的指示性;青藏高原前一年冬季积雪日数和山西省的年沙尘日数呈较好的负相关性;当前冬青藏高原积雪日数多时,山西省少沙尘,反之,多沙尘。就我国北方特别是山西省上游地区的积雪日数而言,指示性比较强的区域分布在内蒙古、甘肃、新疆。这些区域内某些站点前一年冬季的平均积雪日数多时,山西省少沙尘,反之,多沙尘。此外,山西沙尘还与SOI指数有显著的滞后2 a的正响应关系,与SOI有滞后两年正相关的站点主要分布在中东部和东北部。在要素相关分析的基础上,综合各类因子制作了山西省沙尘预测模型,以期为沙尘天气的短期预测工作提供一些参考依据。

关键词: 沙尘天气, 气候因子, 预测模型

Abstract:

The relationship between dust storm days in ShanxiProvince and precipitation inMongolia, snow days on Qinghai-Xizang Plateau, snow days in northern China, circulation factors such as SOIwas analyzed in this paper. Results show that the quasi-periodic variation of global atmosphere and oceans plays an important role in development and change of dust storm events. Precipitation in the lastyear in thewestofMongolia is an indicator fordust storm weather in ShanxiProvince. There exists significantnegative correlation between yearly duststorm days in Shanxi and snow days in previouswinteron theQinghai-XizangPlateau and in InnerMongolia.Two years lag positive correlation between duststorm days and SOI index is also found. Stationswith significantcorrelationwith SOI index are generally located in the central and eastern parts ofShanxiProvince. Based on the correlation analysis, a conceptionmodel is put forward, and a prediction equation is builtby using stepwise linear regressionmethod. It could be used in prediction ofdust storm frequency in ShanxiProvince.

Key words: dust event, climatic factor, predictionmodel