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Aerosol and cloud data processing and optical property retrieval algorithms for the spaceborne ACDL/DQ-1.

Authors :
Dai, Guangyao
Wu, Songhua
Long, Wenrui
Liu, Jiqiao
Xie, Yuan
Sun, Kangwen
Meng, Fanqian
Song, Xiaoquan
Huang, Zhongwei
Chen, Weibiao
Source :
Atmospheric Measurement Techniques. 2024, Vol. 17 Issue 7, p1879-1890. 12p.
Publication Year :
2024

Abstract

The new-generation atmospheric environment monitoring satellite DQ-1, launched successfully in April 2022, carries the Aerosol and Carbon Detection Lidar (ACDL), which is capable of globally profiling aerosol and cloud optical properties with high accuracy. The ACDL/DQ-1 is a high-spectral-resolution lidar (HSRL) that separates molecular backscatter signals using an iodine filter and has 532 nm polarization detection and dual-wavelength detection at 532 and 1064 nm, which can be utilized to derive aerosol optical properties. The methods have been specifically developed for data processing and optical property retrieval according to the specific characteristics of the ACDL system and are introduced in detail in this paper. Considering the different signal characteristics and different background noise behaviors of each channel during daytime and nighttime, the procedures of data pre-processing, denoising process and quality control are applied to the original measurement signals. The aerosol and cloud optical property products of the ACDL/DQ-1, including the total depolarization ratio, backscatter coefficient, extinction coefficient, lidar ratio and color ratio, can be calculated by the retrieval algorithms presented in this paper. Two measurement cases with use of the ACDL/DQ-1 on 27 June 2022 and the global averaged aerosol optical depth (AOD) from 1 June to 4 August 2022 are provided and analyzed, demonstrating the measurement capability of the ACDL/DQ-1. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18671381
Volume :
17
Issue :
7
Database :
Academic Search Index
Journal :
Atmospheric Measurement Techniques
Publication Type :
Academic Journal
Accession number :
176758489
Full Text :
https://doi.org/10.5194/amt-17-1879-2024