论文

基于葵花8号新一代静止气象卫星的夜间雾识别

  • 王宏斌 ,
  • 张志薇 ,
  • 刘端阳 ,
  • 袁成松 ,
  • 周林义 ,
  • 钱玮
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  • 中国气象局交通气象重点开放实验室, 江苏省气象科学研究所, 江苏 南京 210009;江苏省气象服务中心, 江苏 南京 210008;江苏省气象台, 江苏 南京 210008

收稿日期: 2017-12-26

  网络出版日期: 2018-12-28

基金资助

江苏省自然科学青年基金项目(BK20161073);国家自然科学基金项目(41575135);科技部国家大气污染专项(JFYS2016ZY01002213-03);北极阁基金项目(BJG201505)

Detection of Fog at Night by Using the New Geostationary Satellite Himawari-8

  • WANG Hongbin ,
  • ZHANG Zhiwei ,
  • LIU Duanyang ,
  • YUAN Chengsong ,
  • ZHOU Linyi ,
  • QIAN Wei
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  • Key Laboratory of Transportation Meteorology of China Meteorological Administration, Jiangsu Institute of Meteorological Sciences, Nanjing 210009, Jiangsu, China;Jiangsu Meteorological Service Center, Nanjing 210008, Jiangsu, China;Jiangsu Meteorological Observatory, Nanjing 210008, Jiangsu, China

Received date: 2017-12-26

  Online published: 2018-12-28

摘要

基于葵花8号新一代静止气象卫星的高时空分辨率多通道数据,利用3.9 μm与11.2 μm通道亮温差法(BTD3.9~11.2)和3.9 μm伪比辐射率法(ems3.9)开展了中国地区夜间不同等级雾的识别,确定了各站点和网格点上对不同等级雾两种方法的参数最优阈值;并利用地面站点观测资料和CALIPSO星载激光雷达产品对陆地和海上雾的识别结果进行了验证。结果表明:(1)通道亮温差法和3.9 μm伪比辐射率法均可以较准确地识别出不同等级的雾,3.9 μm伪比辐射率法准确率略优;随能见度的下降,两种方法识别准确率都明显提升,虚警率明显下降。能见度小于50 m时,通道亮温差法(3.9 μm伪比辐射率法)识别雾的击中率HR、虚警率FARKSS评分分别为0.89(0.90)、0.15(0.15)和0.74(0.75)。(2)剔除云影响后,4个雾等级下两种方法对雾识别的HRKSS评分均有明显提升,FAR均有明显下降。能见度小于1 000 m时,剔除云后通道亮温差法(3.9 μm伪比辐射率法)的HR由0.71(0.74)提高到0.81(0.85),FAR由0.27(0.28)降低到0.12(0.13),KSS评分由0.44(0.46)提高到0.69(0.72),KSS评分提高0.23(0.26)。(3)3个个例分析表明,基于通道亮温差法、3.9 μm伪比辐射率法以及RGB合成图均可清晰识别出大部分雾区,雾区和非雾区的BTD3.9~11.2(ems3.9)差异明显,强浓雾区BTD3.9~11.2(ems3.9)约为-5℃(0.75);基于葵花8卫星海雾的识别结果与CALIPSO星载激光雷达VFM反演产品一致。

本文引用格式

王宏斌 , 张志薇 , 刘端阳 , 袁成松 , 周林义 , 钱玮 . 基于葵花8号新一代静止气象卫星的夜间雾识别[J]. 高原气象, 2018 , 37(6) : 1749 -1764 . DOI: 10.7522/j.issn.1000-0534.2018.00037

Abstract

Himawari-8 is the new geostationary satellite of the Japan Meteorological Agency (JMA) and carries the Advanced Himawari Imager (AHI), which is greatly improved over past imagers in terms of its number of bands and its temporal/spatial resolution. In this work, two different methods for the detection of the different levels of fog at night by using the Himawari-8 were developed in China. The two different methods are the method of the difference between the 11.2 μm and 3.9 μm brightness temperatures (BTD3.9~11.2) and the method of 3.9 μm Pseudo-Emissivity (ems3.9). The 3.9 μm Pseudo-Emissivity is the ratio of the observed 3.9 μm radiance and the 3.9 μm blackbody radiance calculated using the 11.2 μm brightness temperature. We identified the parameters optimal threshold at the 2 400 stations and the grid points using the BTD3.9~11.2 and ems3.9 for different levels of fog. Results on land and sea from the two methods were compared with surface observations from 2 400 weather stations in China and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) VFM (Vertical Feature Mask) products. The results showed that both the method of BTD3.9~11.2 and the method of ems3.9 can accurately identify the different levels of fog and the accuracy of ems3.9 method is slightly better than the BTD3.9~11.2. The accuracy of two methods has increased significantly and the false alarm rate has significantly decreased with the decrease of the visibility. When the visibility was less than 50 m, the HR, FAR and KSS of the BTD3.9~11.2 method (the ems3.9 method) were 0.89 (0.90), 0.15 (0.15) and 0.74 (0.75), respectively. When mid-or high-level clouds were removed using surface temperature of the ground observations, the HR and KSS of two methods for the different levels of fog has increased significantly, and the FAR has significantly decreased. When the visibility was less than 1 000 m, the HR of the BTD3.9~11.2 method (the ems3.9 method) was increased to 0.81(0.85) from 0.71 (0.74), the FAR was decreased to 0.12 (0.13) from 0.27 (0.28), and the KSS was increased to 0.69 (0.72) from 0.44 (0.46). The KSS of two method increased by 0.23 and 0.26, respectively. Three cases analysis showed that the fog area can be clearly identified by using the BTD3.9~11.2, ems3.9 and RGB composite image. The results of the detection of sea fog by using Himawari-8 data and using CALIPSO VFM products have consistency.

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