Abstract
Real-time estimation of eruptive source parameters during explosive volcanic eruptions is a major challenge in terms of hazard evaluation and risk assessment as these inputs are essential for tephra dispersal models to forecast the impact of ash plumes and tephra deposits. In this aim, taking advantage of the 23.5 cm wavelength Doppler radar (VOLDORAD 2B) monitoring Etna volcano, we analyzed 47 paroxysms produced between 2011 and 2015, characterized by lava fountains generating tephra plumes that reached up to 15 km a.s.l. Range gating of the radar beam allows the identification of the active summit craters in real-time, no matter the meteorological conditions. The radar echoes help to mark (i) the onset of the paroxysm when unstable lava fountains, taking over Strombolian activity, continuously supply the developing tephra plume, then (ii) the transition to stable fountains (climax), and (iii) the end of the climax, therefore providing paroxysm durations. We developed a new methodology to retrieve in real-time a Mass Eruption Rate (MER) proxy from the radar echo power and maximum Doppler velocity measured near the emission source. The increase in MER proxies is found to precede by several minutes the time variations of plume heights inferred from visible and X-Band radar imagery. A calibration of the MER proxy against ascent models based on observed plume heights leads to radar-derived climax MER from 2.96 × 104 to 3.26 × 106 kg s−1. The Total Erupted Mass (TEM) of tephra was computed by integrating over beam volumes and paroxysm duration, allowing quantitative comparisons of the relative amounts of emitted tephra among the different paroxysms. When the climactic phase can be identified, it is found to frequently release 76% of the TEM. Calibrated TEMs are found to be larger than those retrieved by satellite and X-band radar observations, deposit analyses, ground-based infrared imagery, or dispersion modeling. Our methodology, potentially applicable to every Doppler radar, provides mass load parameters that represent a powerful all-weather tool for the quantitative monitoring and real-time hazard assessment of tephra plumes at Etna or any other volcano with radar monitoring.
Highlights
Quantifying the so-called eruptive source parameters (Bonadonna et al, 2015) of tephra plumes is critical for hazard assessment of explosive volcanic eruptions and associated risk mitigation, as well as for a better understanding of the dynamics of eruption columns and plumes
We present a new methodology to compute a proxy for the erupted mass only from the measured radar parameters. This methodology has potentially powerful application in realtime monitoring at Etna, and at any volcano monitored by Doppler radars
Forty-seven out of the 49 paroxysmal episodes of fountainfed tephra plumes produced by Etna between January 2011 and December 2015 were analyzed using the high rate data of the 23.5-cm wavelength Doppler radar (VOLDORAD 2B) monitoring the explosive activity of the summit craters
Summary
Quantifying the so-called eruptive source parameters (Bonadonna et al, 2015) of tephra plumes is critical for hazard assessment of explosive volcanic eruptions and associated risk mitigation, as well as for a better understanding of the dynamics of eruption columns and plumes. The different eruptive source parameters are: the location of the eruptive vent, the start time and duration of an eruption, the plume height, the Mass Eruption Rate (MER), and the Total Grain Size Distribution (TGSD). These parameters are used by the Volcanic Ash Advisory Centers (VAACs) to initialize Volcanic Ash Dispersion and Transportation Models (VATDMs) in near real-time. A challenging objective is to measure the MER in real-time It is generally derived from empirical relationships between observed top heights of strong plumes and corresponding MERs inferred from scaling laws (Wilson et al, 1978; Sparks et al, 1997; Mastin et al, 2009). MERs estimated from post-eruption deposits analyses themselves hold uncertainties highly dependent upon the selected methodology (Andronico et al, 2014a; Bonadonna et al, 2015; Spanu et al, 2016)
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