A methodology to evaluate the aerosol effective radius based on MODIS aerosol products applicable to other satellite platforms

A strategy to evaluate the effective radius (r eff) as a function of aerosol retrievals is provided in this work. This methodology is based on the MODerate resolution Imaging Spectroradiometer (MODIS) aerosol products, using the 0.66 and 0.87 µm bands. These data have been studied from February 2000...

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Bibliographic Details
Published in:International Journal of Remote Sensing
Main Authors: García, Omaira E., Díaz, Ana M., Expósito, Francisco J., Díaz, Juan P., Gelado, María D., Guirado, Carmen
Other Authors: GELADO CABALLERO, MARIA DOLORES, Guirado-Fuentes, Carmen, Exposito, Francisco, Garcia, Omaira, Gelado-Caballero, M.D., 10244893900, 57200925055, 6701925357, 7401604360, 6506058559, 56888921400, 3413552, 1121982, 964181, 6318761, 2134468, 3493866
Language:English
Published: 0143-1161 2009
Subjects:
2502 Climatología
North East Atlantic
Online Access:http://hdl.handle.net/10553/48037
https://doi.org/10.1080/01431160802549302
Description
Summary:A strategy to evaluate the effective radius (r eff) as a function of aerosol retrievals is provided in this work. This methodology is based on the MODerate resolution Imaging Spectroradiometer (MODIS) aerosol products, using the 0.66 and 0.87 µm bands. These data have been studied from February 2000 to December 2005 in a grid situated at Subtropical North‐east Atlantic region. To reduce the number of MODIS useful variables a Factorial Analysis by Principal Components has been applied, decreasing the aerosol parameters from 18 to five. With these parameters, backscattering ratios and asymmetry factors at 0.66 and 0.87 µm besides the Ångström parameter, a lineal multivariate analysis technique has been applied to find the combination of variables that better evaluate the r eff. The standard error for the predicted value of r eff is ±0.09 µm. The expression obtained here has the advantage that it can be applied to other remote sensors like AVHRR/NOAA, HRV/SPOT, TM/LANDSAT, and so on, with long time series.

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