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The Sensitivity of AOD Retrieval to Aerosol Type and Vertical Distribution over Land with MODIS Data. / Wu, Yerong; de Graaf, Martin; Menenti, Massimo.

In: Remote Sensing, Vol. 8, No. 9, 765, 2016, p. 1-16.

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Wu, Yerong ; de Graaf, Martin ; Menenti, Massimo. / The Sensitivity of AOD Retrieval to Aerosol Type and Vertical Distribution over Land with MODIS Data. In: Remote Sensing. 2016 ; Vol. 8, No. 9. pp. 1-16.

BibTeX

@article{7a812b22873342f0a21ee1466f1c4a9d,
title = "The Sensitivity of AOD Retrieval to Aerosol Type and Vertical Distribution over Land with MODIS Data",
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.",
keywords = "Aerosol Optical Depth (AOD), satellite data, simulation, retrieval, aerosol type, aerosol vertical distribution, OA-Fund TU Delft",
author = "Yerong Wu and {de Graaf}, Martin and Massimo Menenti",
year = "2016",
doi = "10.3390/rs8090765",
language = "English",
volume = "8",
pages = "1--16",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "MDPI",
number = "9",

}

RIS

TY - JOUR

T1 - The Sensitivity of AOD Retrieval to Aerosol Type and Vertical Distribution over Land with MODIS Data

AU - Wu, Yerong

AU - de Graaf, Martin

AU - Menenti, Massimo

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Aerosol Optical Depth (AOD)

KW - satellite data

KW - simulation

KW - retrieval

KW - aerosol type

KW - aerosol vertical distribution

KW - OA-Fund TU Delft

UR - http://resolver.tudelft.nl/uuid:7a812b22-8733-42f0-a21e-e1466f1c4a9d

U2 - 10.3390/rs8090765

DO - 10.3390/rs8090765

M3 - Article

VL - 8

SP - 1

EP - 16

JO - Remote Sensing

T2 - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 9

M1 - 765

ER -

ID: 8088893