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基于Himawari-8数据的日间海雾检测方法 被引量:13

Daytime Sea Fog Detection Method Using Himawari-8 Data
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摘要 新一代静止轨道气象卫星Himawari-8静止气象卫星具有空间分辨率高可持续性观测的特点,对海雾监测具有重要的意义.星载激光雷达(Cloud-aerosol lidar with orthogonal polarization, CALIOP)可以探测大气的垂直剖面信息.利用CALIOP数据进行海雾检测,获得4类样本点:中高云、低云、海雾和海表样本点,并将这些样本点用于Himawari-8日间海雾检测的通道选择和动态阈值设定的研究中,建立一套Himawari-8日间海雾检测算法.利用CALIOP和中国气象局国家卫星气象中心的气象卫星雾监测报告数据对海雾检测方法进行验证.对比CALIOP数据,海雾检出率63.42%,漏检样本点中晴空海表占比71.54%;对比雾监测产品,海雾检测率89.7%.结果表明,提出的海雾检测算法是可行的. A new generation of stationary orbit meteorological satellite Himawari-8 AHI is a multispectral earth observation sensor with high temporal and spatial resolutions, which is of great significance to the monitoring of sea fog. The vertical structure of the atmosphere at high-resolution can be detected by cloudaerosol lidar with orthogonal polarization(CALIOP). CALIOP data were used to classify the observed objects into four types: sea-surface, sea fog, stratus and middle/high-cloud. These samples were then used to the spectral analysis of the Himawari-8 channels and the spectral properties were obtained. A daytime sea fog detection algorithm based on Himawari-8 data was proposed through the study of the spectral properties. Both CALIOP data and fog-monitoring product from NSMC were used to validate the detection results. Compared with the CALIOP fog detection, the probability of sea fog detection is 63.42%, and 71.54% of the missing samples are the misjudgements of sea surfaces. Based on the fog-monitoring product, the probability of sea fog detection is 89.7%. The results show that the proposed algorithm is feasible.
作者 张培 吴东 ZHANG Pei;WU Dong(College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China;Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Scienceand Technology, Qingdao 266200, China)
出处 《大气与环境光学学报》 CAS CSCD 2019年第3期211-220,共10页 Journal of Atmospheric and Environmental Optics
基金 国家自然科学基金,41376180~~
关键词 Himawari-8 CALIOP 日间海雾检测 动态阈值 Himawari-8 CALIOP daytime sea fog detection dynamic threshold
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