Aerosol optical property measurement using the orbiting high-spectral-resolution lidar on board the DQ-1 satellite: retrieval and validation.

Zha, Chenxing; Bu, Lingbing; Li, Zhi; Wang, Qin; Mubarak, Ahmad; Liyanage, Pasindu; Liu, Jiqiao; Chen, Weibiao

The Atmospheric Environment Monitoring Satellite (AEMS), also called Daqi-1 or DQ-1, was launched in April 2022; one of its main payloads is a high-spectral-resolution lidar (HSRL) system. This new system enables the accurate measurements of global aerosol optical properties, which can be used in the geoscientific community after the retirement of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. Developing a suitable retrieval algorithm and validating retrieved results are necessary. This research demonstrates a retrieval algorithm for aerosol optical properties using the DQ-1 HSRL system. This method has retrieved the aerosol linear depolarization ratio, backscatter coefficient, extinction coefficient, and optical depth. For validation purposes, we compared retrieved results with those obtained through CALIPSO. The results indicate that the profiles of the two datasets are in good agreement, with DQ-1 showing an improved signal-to-noise ratio (SNR). Optical property profiles from National Aeronautics and Space Administration (NASA) Micro-Pulse Lidar Network (MPLNET) stations were selected for validation with the DQ-1 measurements, resulting in a relative error of 25 %. Between June 2022 and December 2022, aerosol optical depth measurements using the DQ-1 satellite and the AErosol RObotic NETwork (AERONET) were correlated and yielded a value of R2 equal to 0.803. We use the DQ-1 dataset to initially investigate the transport processes of the Saharan dust and the South Atlantic volcanic aerosols. These validations and applications show that the DQ-1 HSRL system can accurately measure global aerosols and has significant potential for Earth scientific applications.

OPTICAL measurements; AEROSOLS; OPTICAL properties; SIGNAL-to-noise ratio; BATHYMETRY

Atmospheric Measurement Techniques, 2024, Vol 17, Issue 14, p4425

1867-1381

Academic Journal

10.5194/amt-17-4425-2024