Volcanic emission estimates from the inversion of ACTRIS lidar observations and their use for quantitative dispersion modelling

Abstract. Modeling the dispersion of volcanic particles following explosive eruptions is critical for aviation safety. To constrain the dispersion of volcanic plumes and assess hazards, calculations rely on accurate characterization of the eruptions source term e.g., variation of emission rate and column height with time and the prevailing wind fields. This study introduces an inverse modeling framework that integrates a Lagrangian dispersion model with lidar observations to estimate emission rates of volcanic particles released during an Etna eruption. The methodology consists of using the FLEXPART model to generate source-receptor relationships between the volcano and a lidar system that observed the ensuing volcanic plume, which then are used to derive the emission rates using the observational data. We leverage data from the ACTRIS Polly^XT lidar that operates at the PANhellenic GEophysical observatory of Antikythera. The inversion algorithm utilizes lidar observations and an empirical a-priori emission profile to estimate the volcanic particle source strength, accounting for altitude and time evolution of the plume. Additionally, to study the impact wind fields have on volcanic ash forecasting, the experiment is repeated using fields that assimilate Aeolus wind lidar data. Our approach applied to the 12 March 2021 Etna eruption, accurately captures a dense aerosol layer between 8 and 12.5 km. Results show a minimal difference of the order of 2 % between the observed and the simulated ash concentrations. The presented inversion algorithm coupled with Aeolus data, optimizes both the vertical emission distribution and Etna emission rates, advancing our understanding and preparedness for volcanic events.