地球系统科学论坛第645期
“地理环境遥感”系列学术报告之大气遥感(3)
应地理系王伦澈、陶明辉教授邀请,中国科学院遥感与数字地球研究所胡斯勒图研究员来我校访问并做学术报告
报告时间:2019年3月27日下午4:00
报告地点:地质斋(主楼308)
报告题目:基于葵花8卫星的全天候地表短波辐射估算研究-污染物对地表辐射影响
个人简介:胡斯勒图,中国科学院遥感与数字地球研究所研究员、博士生导师,中科院“百人计划”入选者。2010 年获日本千叶大学理学博士学位, 曾任日本东海大学特别研究员。主要从事冰云粒子光散射计算,云水参数和地表辐射遥感反演研究。自 2010 年开始负责开发了日本宇宙航空研究开发机构(JAXA) 的气候观测卫星 GCOM-C 和新一代静止卫星 Himawari-8(葵花 8)的大气云水 产品,并参与撰写了该产品算法技术档案(ATBD)。开发了 5 种典型卷云冰晶模 型的光散射属性数据库,提出的 Voronoi 非球形冰晶模型被葵花 8、GCOM-C、 EarthCARE/MSI 等国际卫星计划官方算法采用。发表论文 50 余篇(SCI 论文 30余篇),是 Remote Sensing of Environment,IEEE Transection on Geoscience and Remote Sensing 等遥感领域国际 TOP 期刊审稿人。曾获得国家优秀自费留学生奖、日中科学技术交流协会研究奖和资深演讲人奖等。
报告简介:Optical properties of clouds and heavy aerosol retrieved from satellite measurements are most important in the calculation of the surface solar radiation (SSR) of the ground surface.To obtain high spatial (5km) and temporal resolution (10 minutes) of SSR data from the new generation geostationary satellite Himwari-8, we established the cloud properties retrieval algorithm (Letu et al., 2018) to produce an input data of the SSR calculation algorithm. Then we developed a LUT-based algorithm to estimate SSR from the retrieval of cloud property parameters (cloud phase, cloud optical thickness and cloud effective particle radius) and aerosol optical thickness. Furthermore, the SSR is estimated by inputting the cloud and aerosol parameters, and other auxiliary data (e.g., solar zenith angle, surface albedo). To generate and optimize the LUT for SSR, sensitivity analysis of SSR to solar geometry (solar zenith angle), atmospheric conditions and surface condition (surface albedo) is conducted.
Furthermore, shortwave radiative flux simulated from Himawari-8 satellite products is compared to ground-based observations in Xianghe and Xuzhou sites of China. In clear and cloudy sky with clean atmospheric conditions, the shortwave radiative fluxes using satellite products agree well with ground-based measurements. However, in cloudy sky with polluted atmospheric conditions, the fluxes using satellite products are overestimated by about 18 % as compared to the ground-based measurements. Aerosols below the cloud layer can bias the retrieval of the cloud optical and microphysical properties (e.g., optical thickness and effective particle radius) and lead to the overestimation of the shortwave radiation at ground level.
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地理与信息工程学院
2019年3月