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Jing Tang

Researcher

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

Author

  • Yan Tong
  • Lian Feng
  • Kun Sun
  • Jing Tang

Summary, in English

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.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • MERGE: ModElling the Regional and Global Earth system

Publishing year

2020-07-20

Language

English

Publication/Series

Remote Sensing

Volume

12

Issue

14

Document type

Journal article

Publisher

MDPI AG

Topic

  • Meteorology and Atmospheric Sciences
  • Geosciences, Multidisciplinary
  • Other Earth and Related Environmental Sciences

Keywords

  • AOD product
  • AERONET
  • MODIS
  • temporal binning product

Status

Published

ISBN/ISSN/Other

  • ISSN: 2072-4292