Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements

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Standard

Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements. / Tong, Yan; Feng, Lian; Sun, Kun; Tang, Jing.

I: Remote Sensing, Bind 12, Nr. 14, 2330, 2020.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Tong, Y, Feng, L, Sun, K & Tang, J 2020, 'Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements', Remote Sensing, bind 12, nr. 14, 2330. https://doi.org/10.3390/rs12142330

APA

Tong, Y., Feng, L., Sun, K., & Tang, J. (2020). Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements. Remote Sensing, 12(14), [2330]. https://doi.org/10.3390/rs12142330

Vancouver

Tong Y, Feng L, Sun K, Tang J. Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements. Remote Sensing. 2020;12(14). 2330. https://doi.org/10.3390/rs12142330

Author

Tong, Yan ; Feng, Lian ; Sun, Kun ; Tang, Jing. / Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements. I: Remote Sensing. 2020 ; Bind 12, Nr. 14.

Bibtex

@article{2059e26c474c4bfeb610e5e5a12b3b4f,
title = "Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements",
abstract = "Assessments of long-term changes of air quality and global radiative forcing at a large scale heavily rely on satellite aerosol optical depth (AOD) datasets, particularly their temporal binning products. Although some attempts focusing on the validation of long-term satellite AOD have been conducted, there is still a lack of comprehensive quantification and understanding of the representativeness of satellite AOD at different temporal binning scales. Here, we evaluated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products at various temporal scales by comparing the MODIS AOD datasets from both the Terra and Aqua satellites with the entire global AErosol RObotic NETwork (AERONET) observation archive between 2000 and 2017. The uncertainty levels of the MODIS hourly and daily AOD products were similarly high, indicating that MODIS AOD retrievals could be used to represent daily aerosol conditions. The MODIS data showed the reduced quality when integrated from the daily to monthly scale, where the relative mean bias (RMB) changed from 1.09 to 1.21 for MODIS Terra and from 1.04 to 1.17 for MODIS Aqua, respectively. The limitation of valid data availability within a month appeared to be the primary reason for the increased uncertainties in the monthly binning products, and the monthly data associated uncertainties could be reduced when the number of valid AOD retrievals reached 15 times in one month. At all three temporal scales, the uncertainty levels of satellite AOD products decreased with increasing AOD values. The results of this study could provide crucial information for satellite AOD users to better understand the reliability of different temporal AOD binning products and associated uncertainties in their derived long-term trends.",
keywords = "representativeness, uncertainty, AOD product, temporal binning product, MODIS, AERONET, LEVEL PM2.5 CONCENTRATIONS, SINGLE-SCATTERING ALBEDO, LONG-TERM TREND, DARK-TARGET, AIR-QUALITY, VIIRS AOD, SATELLITE, RETRIEVALS, LAND, VALIDATION",
author = "Yan Tong and Lian Feng and Kun Sun and Jing Tang",
year = "2020",
doi = "10.3390/rs12142330",
language = "English",
volume = "12",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "M D P I AG",
number = "14",

}

RIS

TY - JOUR

T1 - Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements

AU - Tong, Yan

AU - Feng, Lian

AU - Sun, Kun

AU - Tang, Jing

PY - 2020

Y1 - 2020

N2 - Assessments of long-term changes of air quality and global radiative forcing at a large scale heavily rely on satellite aerosol optical depth (AOD) datasets, particularly their temporal binning products. Although some attempts focusing on the validation of long-term satellite AOD have been conducted, there is still a lack of comprehensive quantification and understanding of the representativeness of satellite AOD at different temporal binning scales. Here, we evaluated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products at various temporal scales by comparing the MODIS AOD datasets from both the Terra and Aqua satellites with the entire global AErosol RObotic NETwork (AERONET) observation archive between 2000 and 2017. The uncertainty levels of the MODIS hourly and daily AOD products were similarly high, indicating that MODIS AOD retrievals could be used to represent daily aerosol conditions. The MODIS data showed the reduced quality when integrated from the daily to monthly scale, where the relative mean bias (RMB) changed from 1.09 to 1.21 for MODIS Terra and from 1.04 to 1.17 for MODIS Aqua, respectively. The limitation of valid data availability within a month appeared to be the primary reason for the increased uncertainties in the monthly binning products, and the monthly data associated uncertainties could be reduced when the number of valid AOD retrievals reached 15 times in one month. At all three temporal scales, the uncertainty levels of satellite AOD products decreased with increasing AOD values. The results of this study could provide crucial information for satellite AOD users to better understand the reliability of different temporal AOD binning products and associated uncertainties in their derived long-term trends.

AB - Assessments of long-term changes of air quality and global radiative forcing at a large scale heavily rely on satellite aerosol optical depth (AOD) datasets, particularly their temporal binning products. Although some attempts focusing on the validation of long-term satellite AOD have been conducted, there is still a lack of comprehensive quantification and understanding of the representativeness of satellite AOD at different temporal binning scales. Here, we evaluated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products at various temporal scales by comparing the MODIS AOD datasets from both the Terra and Aqua satellites with the entire global AErosol RObotic NETwork (AERONET) observation archive between 2000 and 2017. The uncertainty levels of the MODIS hourly and daily AOD products were similarly high, indicating that MODIS AOD retrievals could be used to represent daily aerosol conditions. The MODIS data showed the reduced quality when integrated from the daily to monthly scale, where the relative mean bias (RMB) changed from 1.09 to 1.21 for MODIS Terra and from 1.04 to 1.17 for MODIS Aqua, respectively. The limitation of valid data availability within a month appeared to be the primary reason for the increased uncertainties in the monthly binning products, and the monthly data associated uncertainties could be reduced when the number of valid AOD retrievals reached 15 times in one month. At all three temporal scales, the uncertainty levels of satellite AOD products decreased with increasing AOD values. The results of this study could provide crucial information for satellite AOD users to better understand the reliability of different temporal AOD binning products and associated uncertainties in their derived long-term trends.

KW - representativeness

KW - uncertainty

KW - AOD product

KW - temporal binning product

KW - MODIS

KW - AERONET

KW - LEVEL PM2.5 CONCENTRATIONS

KW - SINGLE-SCATTERING ALBEDO

KW - LONG-TERM TREND

KW - DARK-TARGET

KW - AIR-QUALITY

KW - VIIRS AOD

KW - SATELLITE

KW - RETRIEVALS

KW - LAND

KW - VALIDATION

U2 - 10.3390/rs12142330

DO - 10.3390/rs12142330

M3 - Journal article

VL - 12

JO - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 14

M1 - 2330

ER -

ID: 246821875