Improved cloud and snow screening in MAIAC aerosol retrievals using spectral and spatial analysis

An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations...

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Bibliographic Details
Main Authors: A. Lyapustin, Y. Wang, I. Laszlo, S. Korkin
Format: Article
Language:English
Published: Copernicus Publications 2012-04-01
Series:Atmospheric Measurement Techniques
Online Access:http://www.atmos-meas-tech.net/5/843/2012/amt-5-843-2012.pdf
Description
Summary:An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.
ISSN:1867-1381
1867-8548