Velocity profiles inside volcanic clouds from three-dimensional scanning microwave dual-polarization Doppler radars

In this work, velocity profiles within a volcanic tephra cloud obtained by dual-polarization Doppler radar acquisitions with three-dimensional (3-D) mechanical scanning capability are analyzed. A method for segmenting the radar volumes into three velocity regimes: vertical updraft, vertical fallout, and horizontal wind advection within a volcanic tephra cloud using dual-polarization Doppler radar moments is proposed. The horizontal and vertical velocity components within the regimes are retrieved using a novel procedure that makes assumptions concerning the characteristics of the winds inside these regimes. The vertical velocities retrieved are combined with 1-D simulations to derive additional parameters including particle fallout, mass flux, and particle sizes. The explosive event occurred on 23 November 2013 at the Mount Etna volcano (Sicily, Italy), is considered a demonstrative case in which to analyze the radar Doppler signal inside the tephra column. The X-band radar (3 cm wavelength) in the Catania, Italy, airport observed the 3-D scenes of the Etna tephra cloud ~32 km from the volcano vent every 10 min. From the radar-derived vertical velocity profiles of updraft, particle fallout, and horizontal transportation, an exit velocity of 150 m/s, mass flux rate of 1.37 o 107 kg/s, particle fallout velocity of 18 m/s, and diameters of precipitating tephra particles equal to 0.8 cm are estimated on average. These numbers are shown to be consistent with theoretical 1-D simulations of plume dynamics and local reports at the ground, respectively. A thickness of 3 ± 0.36 km for the downwind ash cloud is also inferred by differentiating the radar-derived cloud top and the height of transition between the convective and buoyancy regions, the latter being inferred by the estimated vertical updraft velocity profile. The unique nature of the case study as well as the novelty of the segmentation and retrieval methods presented potentially give new insights into the analysis of volcanic cloud dynamics.