摘要
海雾与低云的分离是当前海雾遥感监测的难点,为提高日间海雾监测的准确度和实时性,本文针对2015—2020年在渤海、黄海和东海的11次海雾过程,在分析海雾与低云在云特性、可见光反射率、亮温和亮温差及纹理特征差异的基础上,使用Terra/Aqua卫星MODIS(moderate resolution imaging spectroradiometer)传感器及S-NPP/NOAA-20卫星VIIRS(visible infrared imaging radiometer suite)传感器的云和反射率产品,建立基于云特性的多源卫星日间海雾探测模型,有效分离了海雾与低云。利用CALIOP(cloud aerosol lidar with orthogonal polarization)后向散射和垂直特征对模型进行精度验证,MODIS(Terra)、MODIS(Aqua)、VIIRS(S-NPP)海雾识别的召回率最高为0.97、0.96、0.89,VIIRS(NOAA-20)与VIIRS(S-NPP)精度相当,与VIIRS(S-NPP)一致性超过0.8的VIIRS(NOAA-20)海雾监测结果达到93.15%,表明本文模型能够有效监测日间海雾;同时,基于本文模型,开展了MODIS与VIIRS数据的一致性研究,结果表明该模型对不同传感器有较强的适用性和稳定性,能够实现多源卫星对同一次海雾过程的协同观测。
The separation of sea fog and low clouds is the current difficulty of sea fog monitoring,in order to improve the accuracy and real-time of daytime sea fog monitoring,a model of multi-satellite daytime sea fog detection based on cloud properties is established by analyzing the difference in the features of cloud properties,visible reflectance,brightness temperature,brightness temperature difference and texture features in the infrared bands between sea fog and cloud using the cloud and reflectivity products of MODIS(moderate resolution imaging spectroradiometer)on Terra/Aqua and VIIRS(visible infrared imaging radiometer suite)on S-NPP/NOAA-20 during eleven sea fog events from 2015 to 2020,which effectively separate low clouds from sea fog.Model precision was validated based on the true value of sea fog identified by CALIOP(cloud aerosol lidar with orthogonal polarization)backscattering and vertical feature mask products.The results showed that the highest probability of detection for MODIS(Terra),MODIS(Aqua),and VIIRS(S-NPP)sea fog identification were 0.97,0.96,0.89,respectively.There are more than 93.15%of the VIIRS(NOAA-20)sea fog detection images that show 80%consistency with VIIRS(S-NPP),indicating that the model can effectively monitor daytime sea fog.Meanwhile,based on the model presented in this paper,the consistency study of MODIS and VIIRS data is carried out,and the results show that the model has strong applicability and stability for different sensors and can realize the synergistic observation of the same sea fog process by multiple source satellites.
作者
王钰
胡晨悦
丘仲锋
赵冬至
吴到懋
廖廓
WANG Yu;HU Chenyue;QIU Zhongfeng;ZHAO Dongzhi;WU Daomao;LIAO Kuo(Nanjing University of Information Science and Technology,Nanjing 210044,China;Suqian Environmental Monitoring Center,Suqian 223800,China;Fujian Institute of Meteorological Sciences,Fuzhou 350008,China)
出处
《热带海洋学报》
CAS
CSCD
北大核心
2023年第6期15-28,共14页
Journal of Tropical Oceanography
基金
国家自然科学基金(41976165)
风云卫星应用先行计划(2022)(FY-APP-2022.0610)。
