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京津地区一次强对流天气的初生预警技术研究 被引量:21

Forecasting Convective Initiation of a Convective Weather Event in Beijing-Tianjin Region
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摘要 基于日本MTSAT卫星数据,在Mecikalski等提出的8个指标计分统计方法的基础上,对京津地区的一次强对流天气过程的初生(CI)进行预警试验,并根据试验结果修改了部分指标的阈值。试验表明,经过阈值的适当修改,该方法可以有效地对京津地区的强对流初生提前30分钟进行预警。另外,使用主成分分析(PCA)方法,验证了8个指标中的每一个指标对于预警CI都有重要的作用。 Using a scoring method presented by Mecikalski et al,which uses eight indicators to forecast convective initiation(CI),a convective weather event in Beijing-Tianjin region was analyzed in the experiment based on the MTSAT satellite data.The experiment results show that after necessary modifications of the indicator thresholds,the above method is feasible to forecast CI ~30 min in advance in Beijing-Tianjin region.The principle component analysis(PCA) method also verifies that every indicator among the eight indicators plays an important role in forecasting CI.
出处 《北京大学学报(自然科学版)》 CAS CSCD 北大核心 2012年第1期42-46,共5页 Acta Scientiarum Naturalium Universitatis Pekinensis
基金 国家自然科学基金(41005024) 高等学校博士学科点专项科研基金(20100132120009) 山东省优秀中青年科学家科研奖励计划基金(BS2010DX034) 中央高校基本科研业务费用专项资助
关键词 强对流天气 对流初生 主成份分析(PCA) convective weather convective initiation(CI) principle component analysis(PCA)
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参考文献9

  • 1Mecikalski J R, Bedka K M. Forecasting convective initiation by monitoring the evolution cumulus in daytime GOES imagery. Mon 2006,134:49-78 of moving Wea Rev,.
  • 2Dixon M, Wiener G. TITAN: thunderstorm identification, tracking, analysis, and nowcasting a radar-based methodolgy. Journal of Atmospheric and Ocenie Technology, 1993, 10(6): 785-797.
  • 3Johnson J T, Mackeen P L, Witt A, et al. The Storm Cell Identification and Tracking algorithm: an enhanced WSR-88D algorithm. Weather and Forecasting, 1998, 13:263-276.
  • 4Jandwerker J. Cell tracking with TRACE3D - a new algorithm. Atmospheric Research, 2002, 61:15-34.
  • 5Maddox R A. Mesoscale convective complexes. Bull Amer Meteor Soc, 1980, 61(11): 1374-1387.
  • 6Schmetz J, Tjemkes S A, Gube M, et al. Monitoring deep convection and convective overshooting with METEOSAT. Adv Space Res, 1997, 19:433-441.
  • 7Wilks D S. Statistical methods in the atmospheric sciences. 2nd ed. Oxford: Academic Press, 2006:627.
  • 8Jolliffe I T. Principal component analysis. 2nd ed. New York: Springer, 2002:487.
  • 9Preisendorfer R W. Principal component analysis in meteorology and oceanography. New York: Elsevier, 1988:425.

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