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Remote Sens. 2016, 8(9), 765; doi:10.3390/rs8090765

The Sensitivity of AOD Retrieval to Aerosol Type and Vertical Distribution over Land with MODIS Data

1
Department of Geoscience and Remote Sensing (GRS), Delft University of Technology (TUDelft), Stevinweg 1, 2628 CN Delft, The Netherlands
2
Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA De Bilt, The Netherlands
*
Author to whom correspondence should be addressed.
Academic Editors: Zhongbo Su, Yijian Zeng, Zoltan Vekerdy, Alexander A. Kokhanovsky, Richard Müller and Prasad S. Thenkabail
Received: 26 July 2016 / Revised: 10 September 2016 / Accepted: 13 September 2016 / Published: 17 September 2016
View Full-Text   |   Download PDF [809 KB, uploaded 19 September 2016]   |  

Abstract

This study is to evaluate the sensitivity of Aerosol Optical Depth (AOD τ) to aerosol vertical profile and type, using the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 algorithm over land. Four experiments were performed, using different aerosol properties including 3 possible non-dust aerosol models and 14 vertical distributions. The algorithm intrinsic uncertainty was investigated as well as the interplay effect of aerosol vertical profile and type on the retrieval. The results show that the AOD retrieval is highly sensitive to aerosol vertical profile and type. With 4 aerosol vertical distributions, the algorithm with a fixed vertical distribution gives about 5% error in the AOD retrieval with aerosol loading τ 0 . 5 . With pure aerosols (smoke and dust), the retrieval of AOD shows errors ranging from 2% to 30% for a series of vertical distributions. Errors in aerosol type assumption in the algorithm can lead to errors of up to 8% in the AOD retrieval. The interplay effect can give the AOD retrieval errors by over 6%. In addition, intrinsic algorithm errors were found, with a value of >3% when τ> 3.0. This is due to the incorrect estimation of the surface reflectance. The results suggest that the MODIS algorithm can be improved by considering a realistic aerosol model and its vertical profile, and even further improved by reducing the algorithm intrinsic errors. View Full-Text
Keywords: Aerosol Optical Depth (AOD); satellite data; simulation; retrieval; aerosol type; aerosol vertical distribution Aerosol Optical Depth (AOD); satellite data; simulation; retrieval; aerosol type; aerosol vertical distribution
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Wu, Y.; de Graaf, M.; Menenti, M. The Sensitivity of AOD Retrieval to Aerosol Type and Vertical Distribution over Land with MODIS Data. Remote Sens. 2016, 8, 765.

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