摘要
以黄渤海上空大气为目标研究区,基于AERONET观测网,获取该区域2015—2017年的气溶胶光学厚度(AOD)实测数据,并对可见红外成像辐射计VIIRS,中分辨率成像光谱仪MODIS,静止水色卫星成像仪GOCI与新一代地球同步气象卫星AHI H8的AOD遥感产品展开精度验证.同时,利用长时间的遥感影像探究并分析AOD在不同时空尺度下的分布特征与变化情况.结果表明:同其它AOD遥感产品相比,GOCI AOD展示出了高采样频率及高精度的特性.此外,在研究区域AOD的逐小时遥感影像中未发现明显的变化规律,而月平均图则显示出从黄渤海西部至中部再到东部AOD逐渐递减的趋势,且该趋势在研究区域不同的地方是具有差异的.不仅如此,本文还尝试分析影响AOD反演精度的潜在因子,发现其可能与地表反射率提取的准确度与预设气溶胶模型设置的合理性有关.
Based on the aerosol optical depth(AOD)observations from the Aerosol Robotic Network(AERONET),AOD products from multi-satellite in the Yellow and Bohai Seas from 2015 to 2017 have been validated.The satellite sensors included Visible Infrared Imaging Radiometer Suite(VIIRS),Moderate Resolution Imaging Spectroradiometer(MODIS),Geostationary Ocean Color Imager(GOCI)and Advanced Himawari Imager Himawari-8(AHI H8).Furthermore,the spatiotemporal distributions and variations of AOD over the Yellow and Bohai Seas has been analyzed.Compared with other AOD products,the GOCI AOD products showed not only the high sampling frequency but the high precision.Obviously diurnal variations have not been observed in the hourly AOD products.The monthly averaged distributions of AOD decreases gradually from the coast of the Yellow and Bohai Seas to the central and eastern parts.Various variation trend has been shown in different places.Moreover,the potential factors affecting the accuracy of AOD products has been discussed and found that the accuracy of AOD products likely related to the accuracy of surface reflectance retrieval and the settings of the aerosol models.
作者
毛颖
郑君亮
丘仲锋
Muhammad Bilal
MAO Ying;ZHENG Junliang;QIU Zhongfeng;Muhammad Bilal(Meteorological Disasters Defending Technique Centre of Fujian Province,Fuzhou 350001;Fujian Key Laboratory of Severe Weather,Fuzhou 350001;School of Marine Sciences,Nanjing University of Information Science&Technology,Nanjing 210044)
出处
《环境科学学报》
CAS
CSCD
北大核心
2021年第7期2550-2559,共10页
Acta Scientiae Circumstantiae
基金
国家自然科学基金(No.41976165)。
关键词
海洋环境科学
气溶胶光学厚度
黄渤海
遥感
逐时变化
月变化
marine environmental science
aerosol optical depth(AOD)
Yellow Sea and Bohai Sea
remote sensing
diurnal variation
monthly variation