Inversion Techniques on Etna’s Volcanic Emissions and the Impact of Aeolus on Quantitative Dispersion Modeling

Forecasting volcanic ash transport is crucial for aviation, but its accuracy is subject to both the prevailing wind fields and the knowledge of the source term of the eruption, i.e., variation of emission rate and column height with time. In this study, we use data from the high spectral resolution lidar (HSRL) in space, Aeolus, to examine their impact on the estimation of the emission rates of volcanic particles through inversion techniques. For the inverse modelling, we couple the output of the FLEXPART Lagrangian particle dispersion model with lidar observations towards estimating the emission rates of volcanic particles released from an Etna eruption. The case study used here is the Etna eruption on the 12 March 2021, well captured by the ground-based lidar station of the PANGEA observatory located at the remote island of Antikythera in Greece, downwind of the Etna volcano. It is concluded that the inversion algorithm with Aeolus wind fields assimilation optimizes both the vertical emission distribution and the Etna emission rates.