Abstract

In this study, AERONET (Aerosol Robotic Network) and EARLINET (European Aerosol Research Lidar Network) data from 17 collocated lidar and sun photometer stations were used to characterize the optical properties of aerosol and their types for the 2008–2018 period in various regions of Europe. The analysis was done on six cluster domains defined using circulation types around each station and their common circulation features. As concluded from the lidar photometer measurements, the typical aerosol particles observed during 2008–2018 over Europe were medium-sized, medium absorbing particles with low spectral dependence. The highest mean values for the lidar ratio at 532 nm were recorded over Northeastern Europe and were associated with Smoke particles, while the lowest mean values for the Angstrom exponent were identified over the Southwest cluster and were associated with Dust and Marine particles. Smoke (37%) and Continental (25%) aerosol types were the predominant aerosol types in Europe, followed by Continental Polluted (17%), Dust (10%), and Marine/Cloud (10%) types. The seasonal variability was insignificant at the continental scale, showing a small increase in the percentage of Smoke during spring and a small increase of Dust during autumn. The aerosol optical depth (AOD) slightly decreased with time, while the Angstrom exponent oscillated between “hot and smoky” years (2011–2015) on the one hand and “dusty” years (2008–2010) and “wet” years (2017–2018) on the other hand. The high variability from year to year showed that aerosol transport in the troposphere became more and more important in the overall balance of the columnar aerosol load.

Highlights

  • Aerosols influence the planetary radiation budget in both direct and indirect ways by absorbing and scattering solar radiation or by changing cloud properties [1]

  • Neural Network Aerosol Typing Algorithm Based on Lidar Data: NATALI Software

  • Aerosols over Europe were characterized based on lidar and photometer observations collected between 2008 and 2018 by the EARLINET (European Aerosol Research Lidar Network) and AERONET (Aerosol Robotic Network)

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Summary

Introduction

Aerosols influence the planetary radiation budget in both direct and indirect ways by absorbing and scattering solar radiation or by changing cloud properties [1]. More automatic approaches have been explored in recent studies dedicated to aerosol typing using optical parameters retrieved from ground-based or satellite lidar measurements [5,7,9,19,20]. In this study, both AERONET and EARLINET data were used to characterize the optical properties of aerosol for the 2008–2018 period in various regions of Europe.

Data and Methodology
Observational Data
Neural Network Aerosol Typing Algorithm Based on Lidar Data
Clusterization Based on Typical Atmospheric Circulation
Optical
Aerosol Types over Europe
Conclusions
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