Combined sun-photometer/lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 Campaign

Abstract

Abstract. The European Aerosol Research Lidar Network (EARLINET), part of the Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS), organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. Besides the standard operational processing of the lidar data in EARLINET, for seven EARLINET sites having co-located sun-photometric observations in AERONET, a network exercise was held in order to derive profiles of the concentration and effective-column size distributions of the aerosols in the atmosphere, by applying the GRASP/GARRLiC inversion algorithm. The objective of this network exercise was to explore the possibility to identify the anthropogenic component and to monitor its spatial and temporal characteristics in the COVID-19 lockdown and relaxation period. While the number of cases are far from being statistically significant so as to provide a conclusive description of the atmospheric aerosols over Europe during this period, this network exercise was fundamental to derive a common methodology for applying GRASP/GARRLiC on a network of instruments with different characteristics. The limits of the approach are discussed, in particular the missing information close to the ground in the lidar measurements due to the instrument geometry, and the sensitivity of the GRASP/GARRLiC retrieval to the settings used, especially for cases with low AOD as the ones we show here. We found that this sensitivity is well-characterized in the GRASP/GARRLiC products, since it is included in their retrieval uncertainties.

Multiwave Matrix Polarization Lidar

“…In addition to H 2 O in different phase states, a huge number of solid and liquid particles are constantly added to the earth's atmosphere as a result of natural processes such as dust storms, volcano eruptions, forest fires, soil erosion, etc. [1][2][3].…”