Aerosol profiling through bottom-to-top atmosphere from the synergetic observations of sun-sky photometer, spectrometer and lidar

Aerosols play an important role in atmospheric chemistry and physics. They also negatively affect human and ecosystem health. Although the aerosol in lower atmosphere is essentially important, accurately characterizing their vertical distribution in the lower troposphere remains challenging due to the "overlap" limitations of ground-based lidars. Aerosol vertical distribution in the lower troposphere (below 3 km) is often monitored using MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) technique of absorption induced by oxygen collision complex (O₂O₂). The missing Information about columnar aerosol properties is typically taken, with some simplification, from the closest AERONET sun-sky photometer measurements.

This study investigates the possibility of aerosol profile retrievals from synergetic ground-based observations by AERONET sun-sky photometer, Pandonia Global Network spectrometer and lidar/ceilometer system. We consider standard AERONET sun-sky photometer measurements at 440, 675, 870, and 1020 nm, as well as, available additional observations at 340, 380, 500, and 1640 nm.

We use GRASP (Generalized Retrieval of Atmosphere and Surface Properties, Dubovik et al., 2021) to implement the retrieval of vertical aerosol properties from multi-axis differential slant column densities of O₂O₂, lidar signal (i.e., ceilometer, EALINET, ADNET, etc.), and radiance measurements (almucantar/hybrid scanning). This presentation demonstrates the developed approach applied for several collocated sites (i.e., Rotterdam de Slufter, Warsaw, etc) and discusses potential advantages of retrieval of aerosol vertical profiles from synergy of the MAX-DOAS, AERONET, and lidar.

 

Reference:

Dubovik, O., D. Fuertes, P. Litvinov, et al., “A Comprehensive Description of Multi- Term LSM for Applying Multiple a Priori Constraints in Problems of Atmospheric Remote Sensing: GRASP Algorithm, Concept, and Applications”, Front. Remote Sens. 2:706851. doi: 10.3389/frsen.2021.706851, 2021.