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Spaceborne high-spectral-resolution lidar ACDL/DQ-1 measurements of the particulate backscatter coefficient in the global ocean.

Authors :
Yang, Yichen
Zhou, Yudi
Stachlewska, Iwona S.
Hu, Yongxiang
Lu, Xiaomei
Chen, Weibiao
Liu, Jiqiao
Sun, Wenbo
Yang, Suhui
Tao, Yuting
Lin, Lei
Lv, Weige
Jiang, Lingying
Wu, Lan
Liu, Chong
Liu, Dong
Source :
Remote Sensing of Environment. Dec2024, Vol. 315, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Spaceborne lidars have demonstrated outstanding global ocean observation in terms of sampling at day- and night-time and penetrating thin cloud and aerosol layers. A spaceborne high-spectral-resolution lidar (HSRL) has the potential to provide accurate optical properties by decreasing the number of assumptions in the retrieval algorithm in comparison with classical elastic spaceborne lidar. In this paper, we report the first ocean application from both particulate and molecular scattering measurements of spaceborne HSRL, namely Aerosol and Carbon Detection Lidar (ACDL) onboard China DQ-1 satellite. We use the ACDL/DQ-1 HSRL to quantify particulate backscatter coefficient b bp in the global ocean, with a novel algorithm exploiting the column-integrated particulate and molecular signals. The ACDL-derived b bp data agree well with MODIS-derived data through along-track and global comparisons. It also presents high correlations with the Argo floats in-situ data under various spatial and temporal matching windows. The ACDL/DQ-1 is anticipated to become an important part of the global ocean satellite observations addressing some limitations of traditional passive ocean colour observation. • A novel algorithm is developed for the spaceborne lidar ocean retrievals. • Particulate backscatter is depicted by spaceborne high-spectral-resolution lidar. • Characteristics of particulate backscatter in different regions are shown. • The retrieved data are in good agreement with ocean colour and in situ data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00344257
Volume :
315
Database :
Academic Search Index
Journal :
Remote Sensing of Environment
Publication Type :
Academic Journal
Accession number :
180854400
Full Text :
https://doi.org/10.1016/j.rse.2024.114444