Synthetic Signatures of Volcanic Ash Cloud Particles From X-Band Dual-Polarization Radar

Abstract

Weather radar retrieval, in terms of detection, estimation, and sensitivity, of volcanic ash plumes is dependent not only on the radar system specifications but also on the range and ash cloud distribution. The minimum detectable signal can be increased, for a given radar and ash plume scenario, by decreasing the observation range and increasing the operational frequency and also by exploiting possible polarimetric capabilities. For short- range observations in proximity of the volcano vent, a compact portable system with relatively low power transmitter may be evaluated as a suitable compromise between observational and technological requirements. This paper, starting from the results of a previous study and from the aforementioned issues, is aimed at quantitatively assessing the optimal choices for a portable X-band system with a dual-polarization capability for real-time ash cloud remote sensing. The physical-electromagnetic model of ash particle distributions is systematically reviewed and extended to include nonspherical particle shapes, vesicular composition, silicate content, and orientation phenomena. The radar backscattering response at X-band is simulated and analyzed in terms of self-consistent polarimetric signatures for ash classification purposes and correlation with ash concentration for quantitative retrieval aims. An X-band radar system sensitivity analysis to ash concentration, as a function of radar specifications, range, and ash category, is carried out in trying to assess the expected system performances and limitations

A Multi-Sensor Approach for Volcanic Ash Cloud Retrieval and Eruption Characterization: The 23 November 2013 Etna Lava Fountain

“…In Figure 7, the temporal variation in the average gamma-modelled number density distribution for each radar volume is drawn. The number density distributions show a significant variation over the range of average sizes from 25 µm-2 mm, which is consistent with the radar detection limit investigated by theoretical models in previous studies [32]. However, particle sizes lower than 25 µm are outside the radar's detection limit, and so, the curves of the multi-temporal gamma-modelled distributions coincide in that particle range.…”

“…The volcanic ash radar retrieval (VARR) procedure, developed in Marzano et al, 2006 [30], and subsequently applied to polarimetric data by Vulpiani et al [27] and Montopoli et al [28], is used to define the microphysical characteristics of an ash cloud from radar data. The VARR is based on forward electromagnetic simulations of ash particles in the microwave region assuming a Gamma size distribution model of oblate particles with the random orientation, axis ratio, permittivity and canting angle as specified in [31,32]. Next, the forward simulations are used to parameterise R e and C a as a function of reflectivity Z HH for a set of predefined ash categories assigned to each radar grid cell through a Bayesian classification step.…”

Interpretation of observed microwave signatures from ground dual polarization radar and space multi-frequency radiometer for the 2011 Grímsvötn volcanic eruption

“…The generation of the synthetic data set is obtained by letting the ash particle size distribution parameters and the particle orientation, supposed to be spheroids, to vary in a random way. Additional information like ash particle density, axis ratio, and dielectric constant are set up following values listed in Table II in Marzano et al (2012a). Automatic discrimination of ash classes with respect to size (fine, coarse, small and lapilli) implies the capability of classifying the radar volume reflectivity measurements into one of the four mentioned classes.…”

The Eyjafjöll explosive volcanic eruption from a microwave weather radar perspective

“…Note that dual-polarization weather radars can offer the potential to measure not only Z H , but also vertically-polarized reflectivity and differential phase shift which may be useful to better characterize ash particle properties and non-spherical shape (Marzano et al, 2011b). Weather radar volume samples, as in Eq.…”