Estimating the Volcanic Ash Fall Rate from the Mount Sinabung Eruption on February 19, 2018 Using Weather Radar

Abstract

This paper presents a theoretical method for estimating volcanic ash fall rate from the eruption of Sinabung Volcano on February 19, 2018 using an X-band multi-parameter radar (X-MP radar). The X-MP radar was run in a sectoral range height indicator (SRHI) scan mode for 6° angular range (azimuth of 221°–226°) and at an elevation angle of 7° to 40° angular range. The distance of the radar is approximately 8 km in the Southeastern direction of the vent of Mount Sinabung. Based on a three-dimensional (3-D) image of the radar reflectivity factor, the ash column height was established to be more than 7.7 km, and in-depth information on detectable tephra could be obtained. This paper aims to present the microphysical parameters of volcanic ash measured by X-MP radar, which are the tephra concentration and the fall-out rate. These parameters were calculated in a two-step stepwise approach microphysical model using the scaled gamma distribution. The first step was ash classification based on a set of training data on synthetic ash and its estimated reflectivity factor. Using a naïve Bayesian classification, the measured reflectivity factors from the eruption were classified into the classification model. The second step was estimating the volcanic ash concentration and the fall-out rate by power-law function. The model estimated a maximum of approximately 12.9 g·m-3of ash concentration from the coarse ash class (mean diameterDn= 0.1 mm) and a minimum of approximately 0.8 megatons of volcanic ash mass accumulation from the eruption.

Real-Time Tephra Detection and Dispersal Forecasting by a Ground-Based Weather Radar

“…Detailed explanations for each of the dual-polarized system's radar parameters have been discussed in [22]. The Z H parameter is widely used for tephra classification [8,9,19,20], and ρ produces the least false alarm in unwanted clutter identification [23]. Both Z H and ρ were used to remove unwanted clutter, and only the filtered Z H was used for tephra detection and tracking, as explained in Sections 2.2 and 2.3 and Appendix A.…”

“…The main assumptions of this method are that tephra particles have a spherical shape and that the scattering of electromagnetic waves follows the Rayleigh theorem [8,9]. Only coarse ash to lapilli regimes were identified by this type of radar [19,20], resulting in two different tephra class regimes: fine (F) and coarse (C) particles. These two terms should be distinguished from finer ash and coarser ash regimes, mentioned in Section 1, as our classification identified class F as a class for particle diameter ranging from 0.015 mm to 0.35 mm and class C for particle diameter ranging from 0.35 mm to 6 mm.…”

“…These two terms should be distinguished from finer ash and coarser ash regimes, mentioned in Section 1, as our classification identified class F as a class for particle diameter ranging from 0.015 mm to 0.35 mm and class C for particle diameter ranging from 0.35 mm to 6 mm. This range was generated based on the previous study [8,9,19,20]. Table A1 presents detailed information about tephra classification.…”

“…Contrarily, a weather radar scans the atmospheric information near surface level (<3000 m height) and relies on particle scattering theorem. Using solely radar data, some studies have managed to derive the real-time GSD and tephra concentration [8][9][10][11]19]. The radar estimates are valuable parameters in tephra dispersal modelling by the radar nowcasting approach.…”

“…First, we overcome previous limitations of unwanted clutter contaminating radar scanning data [20] by applying an automatic noise cancellation. Then, we coupled the modified tephra-radar retrieved model [8,9,19,20] with the EPS of radar nowcasting. The evaluation was done by comparing the radar-based tephra properties (i.e., concentration and grain size) with ground-based data and satellite imagery.…”