| 基于FY-3/MERSI卫星资料的霾判识方法研究 |
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| 引用本文： | 高玲，张兴赢，吴荣华，张碧辉. 2023. 基于FY-3 MERSI多光谱通道的霾判识研究. 气象学报，81（2）：340-352. DOI: 10.11676/qxxb2023.20220079 |
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| 作者姓名： | 高玲 张兴赢 吴荣华 张碧辉 |
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| 作者单位： | 1.国家卫星气象中心（国家空间天气监测预警中心）/中国遥感卫星辐射测量和定标重点开放实验室/许健民气象卫星创新中心，北京，100081;2.国家气象中心，北京，100081 |
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| 基金项目： | 国家重点研发计划项目（2019YFC0214601） |
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| 摘 要： | 受高人为排放和不利天气条件共同作用，中国秋、冬季霾事件频发，具有影响范围大、程度重、持续时间长的特点。为对离散的地面站观测形成有效补充，本研究充分利用卫星大范围监测优势，依据云、冰雪、霾、亮/暗地表散射及发射特性不同波长的依赖性，建立了基于多通道信息组合的霾区快速判识方法。通过引入空气分子散射订正，有效消除此前霾判识工作中大角度条件下的误判，极大缩小了阈值的变化范围，为霾区的自动识别奠定了基础。将该判识方法应用于中国风云三号D星（FY-3D）搭载的中分辨率光谱成像仪（MEdium-Resolution Spectral Imager，MERSI），实现了霾区自动判识。通过与2020年10月—2021年2月秋、冬季地面气象站天气现象记录为霾以及地面环境监测站点中PM2.5小时平均浓度大于75 μg/m3的数据进行对比，结果表明：FY-3D的霾判识结果与天气现象记录结果的一致率为91.1%，与PM2.5表征结果的一致率为85.6%。气象观测中霾识别依靠的是大气消光能力，卫星霾判识也是通过气溶胶的消光特性来实现，因此两者特征更为一致。
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| 关 键 词： | 霾区 瑞利散射 气溶胶 风云三号 中分辨率光谱成像仪 |
| 收稿时间： | 2022-06-09 |
| 修稿时间： | 2022-08-30 |
Study on identification index of haze spectrum by FY-3/MERSI satellite data |
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| Gao Ling， Zhang Xingying， Wu Ronghua， Zhang Bihui. 2023. Haze detection based on combined information from multi-spectral channels of FY-3/MERSI. Acta Meteorologica Sinica， 81（2）:340-352. DOI: 10.11676/qxxb2023.20220079 |
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| Authors: | GAO Ling ZHANG Xingying WU Ronghua ZHANG Bihui |
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| Affiliation: | 1.National Satellite Meteorological Centre （National Space Weather Monitoring and Early Warning Centre），Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites，Innovation Centre for FengYun Meteorological Satellite （FYSIC），Beijing 100081，China;2.National Meteorological Centre，Beijing 100081，China |
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| Abstract: | Affected by high anthropogenic emissions and adverse weather conditions, heavy haze events over large areas and long durations occur frequently in the autumn and winter in China. To overcome the disadvantage of discrete ground-based observations on large scale monitoring, this study uses satellites to realize rapid and automatic haze detection based on combination of multi-channel information that shows different scatter and emission characteristics of cloud, ice, snow, haze, dark and bright surface under different wavelengths. Through the correction of air molecular scattering in haze detection, the misjudgment under large-angle conditions in the previous work is effectively eliminated. It also greatly reduces the variation range of threshold, which is very helpful for automatic haze detection. The haze detection method proposed in this study has been applied to MEdium-Resolution Spectral Imager-Ⅱ (MERSI-Ⅱ) of Fengyun-3D (FY-3D) from October 2020 to February 2021, and the spatial distribution of haze identification region is consistent with that of gray areas on true color images. The validation has been done using ground-based meteorological observations of haze weather and environmental observations of PM2.5 concentrations over 75 μg/m3. The validation results show that the consistency between the haze identification results of FY-3D and observations of ground meteorological stations is 91.1%, and the consistency between the haze identification results of FY-3D and observations of ground environmental stations is 85.6%. As haze observations by meteorological stations depend on the extinction of the atmosphere while satellites observations also rely on this physical characteristics, it is reasonable that the two are more consistent. |
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| Keywords: | Haze region Rayleigh scatter Aerosol Fengyun-3 MEdium-Resolution Spectral Imager |
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