Using AIRS hyperspectral observations to optimize dust refractive index in infrared spectrum

Authors :: Xiaoguang Xu
Jun Wang
Yi Wang
Source :: Optical Sensors and Sensing Congress (ES, FTS, HISE, Sensors).
Publication Year :: 2019
Publisher :: OSA, 2019.
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.

Subjects :: Lidar
Infrared
Physics::Optics
Hyperspectral imaging
Environmental science
Climate model
Astrophysics::Cosmology and Extragalactic Astrophysics
Astrophysics::Earth and Planetary Astrophysics
Radiative forcing
Refractive index
Physics::Atmospheric and Oceanic Physics
Astrophysics::Galaxy Astrophysics
Remote sensing

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