{"title":"Using AIRS hyperspectral observations to optimize dust refractive index in infrared spectrum","authors":"Yi Wang, Jun Wang, Xiaoguang Xu","doi":"10.1364/HISE.2019.HTH1B.1","DOIUrl":null,"url":null,"abstract":"Climate models lack accurate dust refractive index measurements for estimating radiative forcing. AIRS hyperspectral observations are used to optimize dust refractive index in infrared spectrum through integration of PCA and inverse modelling techniques.","PeriodicalId":174423,"journal":{"name":"Optical Sensors and Sensing Congress (ES, FTS, HISE, Sensors)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optical Sensors and Sensing Congress (ES, FTS, HISE, Sensors)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/HISE.2019.HTH1B.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Climate models lack accurate dust refractive index measurements for estimating radiative forcing. AIRS hyperspectral observations are used to optimize dust refractive index in infrared spectrum through integration of PCA and inverse modelling techniques.
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