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<p>Forecasting of the airborne and ground accumulation of tephra emitted by volcanic explosive eruptions mainly relies on the use of numerical models. Such models require a variety of inputs including the eruptive source parameters (ESPs), e.g., tephra plume height, mass eruption rate, and total grain size distributions (TGSDs). These parameters are ideally determined in real time or, when this is not possible, are derived based on a range of distributions associated with the same or analogue volcanoes. With more than 50 paroxysms produced in less than 1&#xa0;year in 2021 at Etna volcano (Italy), we took advantage of the large set of remote sensing sensors operating around the volcano to evaluate their capacities at providing real-time TGSD estimates, one of the most challenging ESP. In this study, we developed a methodology that combines grain size distribution obtained by satellite-based infrared and Doppler radar data. Our results show that the median of the real-time TGSD is consistent with deposit-based TGSDs, although overall sorting is poorly reproduced. To overcome this limitation, we introduce a mixed TGSD derived with the Rosin–Rammler equation, combining sensor-based medians with mean sorting coefficients from deposit-based data. This approach reproduces both median and sorting with <i>R</i><sup>2</sup> values of 0.74–0.93, offering a robust alternative to past-eruption TGSDs for operational tephra-deposit modeling. The methodology is readily applicable not only to Etna but also to other volcanoes monitored by weather radar and satellite imagery.</p>

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Near real-time total grain size distributions of explosive eruptions at Mount Etna (Sicily)

  • 期刊论文

  • 发表日期：

    2026年3月3日

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  • Valentin Freret-Lorgeril,
  • Costanza Bonadonna,
  • Lorenzo Guerrieri,
  • Simona Scollo,
  • Luigi Mereu,
  • Stefano Corradini,
  • Frank Silvio Marzano

摘要

Forecasting of the airborne and ground accumulation of tephra emitted by volcanic explosive eruptions mainly relies on the use of numerical models. Such models require a variety of inputs including the eruptive source parameters (ESPs), e.g., tephra plume height, mass eruption rate, and total grain size distributions (TGSDs). These parameters are ideally determined in real time or, when this is not possible, are derived based on a range of distributions associated with the same or analogue volcanoes. With more than 50 paroxysms produced in less than 1 year in 2021 at Etna volcano (Italy), we took advantage of the large set of remote sensing sensors operating around the volcano to evaluate their capacities at providing real-time TGSD estimates, one of the most challenging ESP. In this study, we developed a methodology that combines grain size distribution obtained by satellite-based infrared and Doppler radar data. Our results show that the median of the real-time TGSD is consistent with deposit-based TGSDs, although overall sorting is poorly reproduced. To overcome this limitation, we introduce a mixed TGSD derived with the Rosin–Rammler equation, combining sensor-based medians with mean sorting coefficients from deposit-based data. This approach reproduces both median and sorting with R2 values of 0.74–0.93, offering a robust alternative to past-eruption TGSDs for operational tephra-deposit modeling. The methodology is readily applicable not only to Etna but also to other volcanoes monitored by weather radar and satellite imagery.