摘要
利用国产风云三号卫星MERSI传感器监测气溶胶对研究气候变化、监测环境质量等有重要意义.在深蓝算法基础上,利用AQUA星MODIS的蓝光波段地表反射率产品,剔除异常值后作为清晰天的地表反射率,完成地气解耦,实现了FY-3B星MERSI传感器的气溶胶反演算法的构建.误差分析表明,MODIS与MERSI波段响应差异带来的气溶胶反演误差基本控制在0.07以下.针对北京地区,2016年4月至2017年3月的反演实验显示,本文获得的结果能较好地体现气溶胶浓度的空间分布,与MODIS气溶胶产品、AERONET地基观测结果有着较好的一致性;与城市型气溶胶相比,采用大陆型气溶胶能获得更多的有效数据,与地面数据的相关性也更高,相关指数在0.7左右.
The retrieval of aerosol from Chinese Medium Resolution Spectral Image(MERSI)data of FY-3 B satellite is important for climate change,environmental quality and so on.In the paper,based on Deep Blue algorithm which was proposed by Hsu et al,the method of aerosol retrieval from FY-3 B MERSI data was developed as follow,1)after removing outliers by the average value of 5 points,the reflectance of clear day was received from MOD09 product of MODIS in 2015 in blue band;2)the relationship between aerosol optical depth(AOD)and atmospheric parameters was calculated by 6 S vector;3)after removing land surface contribution from MERSI’s signal by the reflectance of clear day in blue band,the AOD was received by the atmospheric information of MERSI.Error analyst shows that the AOD error from the difference of filter response between MODIS and MERSI is under 0.07.Aimed to Beijing area,the retrieval experiment from April 2016 to March 2017 showed that removing cloud,rain,fog and so on,there are 60 days which were received AOD from MERSI and AERONET Beijing site.It was shown that 1)our method received aerosol distribution well,and the result has a good agreement with MODIS aerosol products and ground-based measures,and the correlation coefficient was higher than 0.7;2)compared with urban aerosol,continental aerosol can receive more available data(60 points vs.16 points),and higher agreement(correlation coefficient:0.75 vs.0.62).
作者
赵永辉
郭新望
张明
曹霞
冯继锋
郑逢斌
ZHAO Yonghui;GUO Xinwang;ZHANG Ming;CAO Xia;FENG Jifeng;ZHENG Fengbin(Henan Province Environmental Monitoring Center,Zhengzhou 450004,China;Electronic Technology Group Corporation Twenty-seventh Research Institute,Zhengzhou 450047,China;Minsheng College,Henan University,Henan Kaifeng475004,China)
出处
《河南大学学报（自然科学版）》
CAS
2019年第4期459-467,共9页
Journal of Henan University:Natural Science
基金
国家自然科学基金资助项目(41571417)
