摘要
FY-4A上搭载的多通道扫描成像辐射计(AGRI)无论是时间分辨率还是空间分辨率与我国第一代静止气象卫星风云二号上搭载的扫描辐射计(VISSR)相比都有了明显的改进。本文基于FY-4A AGRI成像仪IDDI(红外差值沙尘指数)和新的昼夜沙尘遥感改进算法开展2021年中国北方沙尘过程连续遥感监测处理,并系统分析了2021年3个典型个例的沙尘暴特征和影响区域。结果表明:(1) 3次典型沙尘过程对我国北方各省份的影响面积总计最低达到260万km~2以上,最高达到300万km~2以上,4月14—17日的沙尘暴影响面积最大。(2)2021年沙尘高发区在新疆南部、甘肃河西走廊以北以及内蒙古西部。与2019、2020年同期相比,2021年我国北方沙尘发生频次更高、影响范围更大。(3)新一代FY-4A静止卫星对我国沙尘过程年际变化具备更加完整的监测能力。
Advanced Geosynchronous Radiation Imager(AGRI) mounted on FY-4 A significantly improved both temporal and spatial resolution compared with Visible and Infrared Spin-Scan Radiometer(VISSR) mounted on the Chinese first-generation geostationary meteorological satellite Fengyun-2.Based on FY-4 A AGRI imager Infrared Difference Dust Index(IDDI) and a new improved day-night sand-dust remote sensing algorithm,this paper carries out continuous remote sensing monitoring of dust processes in the northern China and systematically analyzes the characteristics and affected areas of three typical sandstorms in 2021.The total impact area of the three typical sand-dust processes in the northern provinces of China reaches a minimum of more than 2.6 million square kilometres and a maximum of more than 3 million square kilometres.The dust storm from April 14 to 17 affected the largest area.The result shows that in 2021,the areas with high sand and dust occurrences were in the southern Xinjiang,north of the Hexi Corridor in Gansu,and western Inner Mongolia.Compared with the same period in 2019 and 2020,the occurrence of sand and dust storms in the northern China in 2021 had a higher frequency and a larger influence area.The results show that the new generation of FY-4 A geostationary satellite has a more complete ability to monitor the interannual variation of dust processes in China.
作者
高泽田
胡秀清
张小曳
王亚强
GAO Zetian;HU Xiuqing;ZHANG Xiaoye;WANG Yaqiang(Chinese Academy of Meteorological Sciences,Beijing 100081;National Satellite Meteorological Center,Beijing 100081)
出处
《气象科技》
2022年第4期536-544,共9页
Meteorological Science and Technology
基金
国家自然科学基金(42090030,41871249)
国家重点研发计划课题(2018YFB0504901)资助。