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中国科学院大学学报 ›› 2019, Vol. 36 ›› Issue (5): 671-681.DOI: 10.7523/j.issn.2095-6134.2019.05.013

• 环境科学与地理学 • 上一篇    下一篇

基于葵花8号卫星数据的气溶胶反演算法及其在雾霾过程监测中的应用

牛晓君1, 唐家奎1, 张自力2, 崔林丽3, 幸炜鹏1, 宋艺1   

  1. 1. 中国科学院大学资源与环境学院, 北京 100049;
    2. 浙江省环境监测中心, 杭州 310015;
    3. 上海市气象科学研究所, 上海 200030
  • 收稿日期:2018-03-22 修回日期:2018-05-22 发布日期:2019-09-15
  • 通讯作者: 唐家奎
  • 基金资助:
    中国科学院战略性先导科技专项资助(XDA20050103)和国家自然科学基金(41571352)资助

The method of aerosol retrieval using Himawari-8 satellite data and its application in monitoring haze process

NIU Xiaojun1, TANG Jiakui1, ZHANG Zili2, CUI Linli3, XING Weipeng1, SONG Yi1   

  1. 1. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China;
    2. Zhejiang Province Environmental Monitoring Center, Hangzhou 310015, China;
    3. Shanghai Institute of Meteorological Science, Shanghai 200030, China
  • Received:2018-03-22 Revised:2018-05-22 Published:2019-09-15

摘要: 雾霾灾害的发生具有时空动态变化特征。葵花8号卫星是日本气象厅发射的新一代静止气象卫星,具有观测范围广、观测频率高、空间分辨率高等特点,非常适合雾霾过程的动态监测。本文提出利用葵花卫星可见光波段数据及地表反射率比值反演气溶胶光学厚度的新算法,并在北京区域选择2017年5月17日和18日两个雾霾日进行反演实验。反演结果分别与国际AERONET 3个站点Beijing、Beijing-CAMS和Beijing-PKU站观测数据,葵花官方气溶胶产品,MODIS官方气溶胶产品对比分析。结果表明,本文提出算法的反演结果,在反演精度、有效反演空间范围、有效反演时间范围、空间分辨率等方面均为最优。最后通过对北京区域两个雾霾日小时级气溶胶AOD反演结果的时空分析,探讨雾霾过程的时空动态变化。从AOD反演结果时间序列图像中,清楚地看到雾霾污染中心的移动方向及加重或减轻的动态变化状况,说明应用葵花卫星数据反演气溶胶对雾霾过程的监测具有较大的应用潜力。

关键词: 葵花8号卫星, 气溶胶, 雾霾, 光学厚度

Abstract: Haze disaster is characterized by spatio-temporally dynamic changes.Himawari-8 is a new generation of geostationary meteorological satellite launched by Japan Meteorological Agency, and it is very suitable for haze process dynamic monitoring due to its observational ability in wide range, high frequency, and high spatial resolution. A new algorithm was proposed to retrieve aerosol optical thickness using the ratio of Himawari-8 visible band surface reflectivity, and the retrieval evaluation experiments were carried out on May 17, 2017 and May 18, 2017, the two haze days, in Beijing area. The retrieval results showed that the proposed method is the best in retrieval accuracy, retrieval effective spatial and temporal ranges, and spatial resolution by comparing the results with the observation data of the three international AERONET sites of Beijing, Beijing-CAMS, and Beijing-PKU, the Himawari-8 official aerosol products, and the MODIS official aerosol products. Finally, based on the analysis of hourly-level AOD retrieval results on the two haze dates, temporal changes of the haze process in Beijing area were discussed. Based on the retrieval images of the time series, we clearly observe the moving direction of the pollution center and the increasingly or decreasingly dynamic changes of the haze, which shows that the proposed Himawari-8 algorithm has potential application for the dynamic monitoring of haze process.

Key words: Himawari-8 satellite, aerosol, haze, AOD

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