Abstract

Lidar observations are very useful to analyse dispersed volcanic clouds in the troposphere mainly because of their high range resolution, providing morphological as well as microphysical (size and mass) properties. In this work, we analyse the volcanic cloud of 18 May 2016 at Mt. Etna, in Italy, retrieved by polarimetric dual-wavelength Lidar measurements. We use the AMPLE (Aerosol Multi-Wavelength Polarization Lidar Experiment) system, located in Catania, about 25 km from the Etna summit craters, pointing at a thin volcanic cloud layer, clearly visible and dispersed from the summit craters at the altitude between 2 and 4 km and 6 and 7 km above the sea level. Both the backscattering and linear depolarization profiles at 355 nm (UV, ultraviolet) and 532 nm (VIS, visible) wavelengths, respectively, were obtained using different angles at 20°, 30°, 40° and 90°. The proposed approach inverts the Lidar measurements with a physically based inversion methodology named Volcanic Ash Lidar Retrieval (VALR), based on Maximum-Likelihood (ML). VALRML can provide estimates of volcanic ash mean size and mass concentration at a resolution of few tens of meters. We also compared those results with two methods: Single-variate Regression (SR) and Multi-variate Regression (MR). SR uses the backscattering coefficient or backscattering and depolarization coefficients of one wavelength (UV or VIS in our cases). The MR method uses the backscattering coefficient of both wavelengths (UV and VIS). In absence of in situ airborne validation data, the discrepancy among the different retrieval techniques is estimated with respect to the VALR ML algorithm. The VALR ML analysis provides ash concentrations between about 0.1 μg/m3 and 1 mg/m3 and particle mean sizes of 0.1 μm and 6 μm, respectively. Results show that, for the SR method differences are less than <10%, using the backscattering coefficient only and backscattering and depolarization coefficients. Moreover, we find differences of 20–30% respect to VALR ML, considering well-known parametric retrieval methods. VALR algorithms show how a physics-based inversion approaches can effectively exploit the spectral-polarimetric Lidar AMPLE capability.

Highlights

  • One of the major hazards associated with volcanic explosive eruptions is the injection of volcanic ash into the atmosphere and its subsequent dispersion and deposition

  • The capability of Light detection and ranging (Lidar) systems to detect the finest particles in volcanic plume and reliably estimate the ash concentration mainly depends on instrumental characteristics and the type of volcanic explosive activity

  • We summarize the ash mass concentration and/or mean diameter estimates obtained from the previously described retrieval algorithms, and we show the main differences among the various estimates

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Summary

Introduction

One of the major hazards associated with volcanic explosive eruptions is the injection of volcanic ash into the atmosphere and its subsequent dispersion and deposition. Volcanic ash mainly affects aviation safety, the impact could be reduced using real time observations and characterization of eruptive activity [1]. Lidar systems are powerful techniques for monitoring dispersed particles in the troposphere and lower stratosphere because of their profiling capability at very high range resolution. In order to mitigate from the impact associated with volcanic ash, Lidar observations allow to perform immediate and accurate detection of volcanic plumes, quantify volcanic ash concentration and characterize optical properties of volcanic particles [1], improving modelling of dispersed volcanic ash clouds [5,6]. The capability of Lidar systems to detect the finest particles in volcanic plume and reliably estimate the ash concentration mainly depends on instrumental characteristics and the type of volcanic explosive activity

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