30 Mar 2022
30 Mar 2022
Status: a revised version of this preprint is currently under review for the journal AMT.

Performance Evaluation for Retrieving Aerosol Optical Depth from Directional Polarimetric Camera (DPC) based on GRASP Algorithm

Shikuan Jin1, Yingying Ma1,2, Cheng Chen4, Oleg Dubovik5, Jin Hong6, Boming Liu1, and Wei Gong2,3 Shikuan Jin et al.
  • 1State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, China
  • 2Collaborative Innovation Center for Geospatial Technology, Wuhan 430079, China
  • 3School of Electronic Information, Wuhan University, China
  • 4GRASP-SAS, Remote Sensing Developments, Cite Scientifique, University of Lille, 59655 Villeneuve d’Ascq, France
  • 5Univ. Lille, CNRS, UMR 8518 - LOA - Laboratoire d’Optique Atmosphérique, Lille, France
  • 6Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China

Abstract. Aerosol spatial distribution obtained from the satellite sensor is a critical point to understand regional aerosol environment, anthropogenic aerosol emissions, and global climate change. In this study, the performance of aerosol optical depth (AOD) retrieval from the Directional Polarimetric Camera (DPC)/GaoFen-5 by using the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm was evaluated on a global basis for the first time. The results showed that the DPC GRASP/Model scheme, which used several aerosol-type mixings, achieved good performance. By compared with AERONET observations, the correlation coefficient (R), normalized mean square error, and Expect Error (EE%) were 0.8982, 0.1008, and 83.16 %, respectively. The scattering angle, number of averaged pixels in retrieval units, and radiative and polarized fitting residuals showed impacts on the results of AOD retrieval in the DPC GRASP/Model. From the most of AERONET sites, the R and EE% were larger than ~0.9 and ~80 %. Compared with MODIS products, the spatial and temporal variations of AOD could be caught by the DPC observations with the GRASP/Model, and compared with the MODIS Dark Target algorithm, the DPC GRASP/Model AOD also showed a good performance. The above findings validated the ability of DPC sensor to monitor aerosols. It would contribute to the development of aerosol parameter retrieval from multi-angular polarized sensors in the future.

Shikuan Jin et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-91', Anonymous Referee #1, 04 Apr 2022
    • AC1: 'Reply on RC1', Shikuan Jin, 01 Jun 2022
  • RC2: 'Comment on amt-2022-91', Stefan Kinne, 08 Apr 2022
    • AC2: 'Reply on RC2', Shikuan Jin, 01 Jun 2022
  • RC3: 'Comment on amt-2022-91', Anonymous Referee #3, 18 Apr 2022
    • AC3: 'Reply on RC3', Shikuan Jin, 01 Jun 2022

Shikuan Jin et al.

Shikuan Jin et al.


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Short summary
Aerosols are closely related to precipitation, climate change and air quality, and have always been a research focus. In this study, we used international advanced aerosol algorithms (GRASP developed by Dr. Oleg Dubovik) to test the ability of DPC ( the first polarized multi-angle payload developed in China) images to obtain aerosol parameters. The results show that DPC/GRASP achieves good results. This research will aid the development of hardware and algorithms in the aerosol fiel.