Laser & Optoelectronics Progress, Volume. 58, Issue 24, 2428002(2021)

Aerosol Optical Properties of Typical Areas of the World Based on CALIPSO Satellite Remote Sensing Data

Qianjun Mao*, Suisui Jin, and Hengxing Zhang
Author Affiliations
  • School of Urban Construction, Wuhan University of Science and Technology, Wuhan, Hubei 430065, China
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    Spatial distribution characteristics and seasonal attributes of aerosol optical properties in typical regions around the world are studied through the statistical analysis of multiple aerosol optical parameters using two-level aerosol layer products provided by the cloud-aerosol lidar and infrared pathfinder satellite observation (CALIPSO) satellite remote sensing data from 2009 to 2018. Results show that the monthly averages of the aerosol optical depth (AOD) in Saudi Arabia and India are unimodal, reaching a peak from June to July; the monthly average changes of the AOD in China and Central Africa are bimodal, with the highest values appearing from April to June and from December to January. The regional difference between the particulate depolarization ratio (PDR) and color ratio (CR) is the degree of irregularity of particles, which is the largest in Brazil with a PDR value of 0.5--0.7. In China, India, and Indonesia, fine-mode particles are mainly encountered with a CR value of 0.1--0.2. During the DJF and MAM periods, the nonspherical trend of particles in Saudi Arabia was the strongest, and during the JJA and SON periods, the particles in Saudi Arabia and Central Africa had the largest particle size with a CR value ranging from 0.756 to 0.829. The irregularity of aerosol particles in each region shows an increasing trend, and the variation range of the trend coefficient is 0.01--0.025; the increasing trend is most obvious in Brazil, and the particle size shows a weak downward trend.

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    Qianjun Mao, Suisui Jin, Hengxing Zhang. Aerosol Optical Properties of Typical Areas of the World Based on CALIPSO Satellite Remote Sensing Data[J]. Laser & Optoelectronics Progress, 2021, 58(24): 2428002

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jan. 11, 2021

    Accepted: Feb. 12, 2021

    Published Online: Dec. 3, 2021

    The Author Email: Mao Qianjun (maoqianjun@163.com)

    DOI:10.3788/LOP202158.2428002

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