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吉林省雾霾和雾霾事件的时空特征及评估方法

  

  1. 1.Jilin Meteorological Observatory, Changchun 130062, China;
    2.Liaoning Meteorological Disaster Monitoring and Warning Center, Shenyang 110166, China
  • 收稿日期:2014-05-28 出版日期:2015-04-30 发布日期:2014-09-19
  • 作者简介:袭祝香(1963- ),女,高级工程师,主要从事气象灾害评估研究. E-mail:xzx6310@126.com
  • 基金资助:

    中国气象局关键技术集成与推广项目(CMAGJ2014M13)资助

Temporal and Spatial Characteristics of Fog/Haze and Fog/Haze Event and Its Evaluation Methods in Jilin Province

1.吉林省气象台,吉林 长春 130062;2.辽宁省气象灾害监测预警中心,辽宁 沈阳 110166   

  1. 1.Jilin Meteorological Observatory, Changchun 130062, China;
    2.Liaoning Meteorological Disaster Monitoring and Warning Center, Shenyang 110166, China
  • Received:2014-05-28 Online:2015-04-30 Published:2014-09-19

摘要:

利用1961~2013年吉林省50站逐日资料,建立了雾霾事件综合指数。在此基础上,采用百分位数、累计距平、耿贝尔极值分布等方法分析了吉林省雾霾和雾霾事件的时空分布特征,建立雾霾事件评估指标。结果表明:吉林省年平均雾霾日数呈由西北向东南增加的空间分布特征;雾霾和雾霾事件8~9月发生频率较高,强雾霾事件主要出现在10~11月;雾霾和雾霾事件1967~1995年为偏多阶段,1996~2013年处于偏少阶段;1990年代以后雾霾和雾霾事件呈减少趋势。利用历史排位、等级评估及历史气候重现期评估指标等方法对雾霾事件进行的评估结果较为客观,便于业务应用。

关键词: 雾霾事件, 特征分析, 综合指数, 等级评估, 气候重现期

Abstract:

Based on the daily data at 50 meteorological stations in Jilin Province from 1961 to 2013, the comprehensive index of fog/haze event was established, firstly. And on this basis the temporal and spatial characteristics of fog/haze and fog/haze event in Jilin Province were analyzed by using the percentile, cumulative anomaly, Gumbel extreme value distribution methods, etc, and the evaluation index of fog/haze event was given. The results showed that the average annual fog/haze days in Jilin Province increased from northwest to southeast. The frequencies of fog/haze and fog/haze event were higher from August to September, and the strong fog/haze events mainly appeared in October and November. The fog/haze and fog/haze event were more during 1967-1995, while were less during 1996-2013. Since the 1990s, the fog/haze and fog/haze event had decreasing trend. The evaluation result of the fog/haze event from 20 to 23 October 2013 in Jilin based on the grades, orders, return period of abnormal climate methods was more objective, and the evaluation method was easily to apply in business.

Key words: fog/haze event, characteristics analysis, comprehensive index, grade evaluation, climate return period

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