A Simplified Method for Retrieving Aerosol Optical Thickness Using Visibility Data between 1980 and 2014, A Case Study in China

Zhao Yang Zhang, Man Sing Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)


Analysis of long-Term variations of aerosol optical thickness (AOT) is essential to understand the climate change and earth radiation budget. A simplified method was developed in this study to derive the AOT using more than thirty-year surface visibility and aerosol vertical distribution from LiDAR climatology of vertical aerosol structure for space-based LiDAR simulation studies data. Moderate resolution imaging spectroradiometer (MODIS) TERRA and AQUA daily measurements were used to evaluate the performance of the inferred AOT. Results show that the correlations of monthly AOT between MODIS measurements and inferred data are higher than 0.59 and the annual AOT values have stronger correlations (r > 0.82) than monthly data. The inferred AOT can capture the general spatial distribution similar to satellite images with long-Term scale. The correlation of seasonal variation between two datasets is also higher than 0.77. The root mean squared error of inferred AOT relative to MODIS AOT is about 0.22 and 0.11 for monthly and yearly data, respectively. Analysis using singular value decomposition shows that the inferred AOT is consistent with MODIS measurements during 2002-2014 spatially and temporally. The average annual AOT in over 200 stations in China between 1980 and 2014 shows generally upward trends. Results from this paper can be used for further analysis of the aerosol effects on climate change in a regional scale.
Original languageEnglish
Article number7986976
Pages (from-to)4409-4416
Number of pages8
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Issue number10
Publication statusPublished - 1 Oct 2017


  • Aerosol optical thickness (AOT)
  • singular value decomposition (SVD)
  • visibility

ASJC Scopus subject areas

  • Computers in Earth Sciences
  • Atmospheric Science

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