Spectral derivative analysis of solar spectroradiometric measurements: Theoretical basis

Abstract

Spectral derivative analysis, a commonly used tool in analytical spectroscopy, is described forstudying cirrus clouds and aerosols using hyperspectral, remote sensing data. The methodology employsspectral measurements from the 2006 Biomass-burning Aerosols in Southeast Asiafield study to demonstrate theapproach. Spectral peaks associated with thefirst two derivatives of measured/modeled transmitted spectralfluxes are examined in terms of their shapes, magnitudes,and positions from 350 to 750 nm, where variability islargest. Differences in spectral features between media aremainly associated with particle size and imaginary termof the complex refractive index. Differences in derivativespectra permit cirrus to be conservatively detected atoptical depths near the optical thin limit of ~0.03 and yield valuable insight into the composition and hygroscopicnature of aerosols. Biomass-burning smoke aerosols/cirrus generally exhibit positive/negative slopes, respectively,across the 500–700 nm spectral band. The effect of cirrus in combined media is to increase/decrease the slope ascloud optical thickness decreases/increases. For thick cirrus, the slope tends to 0. An algorithm is also presentedwhich employs a two modelfit of derivative spectra for determining relative contributions of aerosols/clouds tomeasured data, thus enabling the optical thickness of the media to be partitioned. For the cases examined,aerosols/clouds explain ~83%/17% of the spectral signatures, respectively, yielding a mean cirrus cloud opticalthickness of 0.08 ± 0.03, which compared reasonably wellwith those retrieved from a collocated Micropulse LidarNetwork Instrument (0.09 ± 0.04). This method permitsextracting the maximum informational content fromhyperspectral data for atmospheric remote sensing applications.