An EARLINET early warning system for atmospheric aerosol aviation hazards

Abstract

A stand-alone lidar-based method for detecting airborne hazards for aviation in near real time (NRT) is presented. A polarization lidar allows for the identifica tion of irregular-shaped particles such as volcanic dust and desert dust. The Single Calculus Chain (SCC) of the Eu ropean Aerosol Research Lidar Network (EARLINET) de livers high-resolution preprocessed data: the calibrated to tal attenuated backscatter and the calibrated volume linear depolarization ratio time series. From these calibrated lidar signals, the particle backscatter coefficient and the particle depolarization ratio can be derived in temporally high reso lution and thus provide the basis of the NRT early warning system (EWS). In particular, an iterative method for the re trieval of the particle backscatter is implemented. This im proved capability was designed as a pilot that will produce alerts for imminent threats for aviation. The method is ap plied to data during two diverse aerosol scenarios: first, a record breaking desert dust intrusion in March 2018 over Fi nokalia, Greece, and, second, an intrusion of volcanic parti cles originating from Mount Etna, Italy, in June 2019 over Antikythera, Greece. Additionally, a devoted observational period including several EARLINET lidar systems demon strates the network’s preparedness to offer insight into natural hazards that affect the aviation sector.