During an eruptive event, the near-real-time monitoring of volcanic explosion onset and its mass flow rate (MFR) is a key factor to predict ash plume dispersion and to mitigate risk to air traffic. Microwave (MW) weather radars have proved to be a fundamental instrument to derive eruptive source parameters. We extend this capability to include an early-warning detection scheme within the overall volcanic ash radar retrieval methodology. This scheme, called the volcanic ash detection (VAD) algorithm, is based on a hybrid technique using both fuzzy logic and conditional probability. Examples of VAD applications are shown for some case studies, including the Icelandic Grímsvötn eruption in 2011, the Eyjafjallajökull eruption in 2010, and the Italian Mt. Etna volcano eruption in 2013. Estimates of the eruption onset from the radar-based VAD module are compared with infrasonic array data. One-dimensional numerical simulations and analytical model estimates of MFR are also discussed and intercompared with sensor-based retrievals. Results confirm in all cases the potential ofMWweather radar for ash plumemonitoring in near real time and its complementarity with infrasonic array for early-warning system design.

Near-real-time detection of tephra eruption onset and mass flow rate using microwave weather radar and infrasonic arrays / Marzano, FRANK SILVIO; Picciotti, Errico; Di Fabio, Saverio; Montopoli, Mario; Mereu, Luigi; Degruyter, Wim; Bonadonna, Costanza; Ripepe, Maurizio. - In: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING. - ISSN 0196-2892. - STAMPA. - 54:11(2016), pp. 6292-6306. [10.1109/TGRS.2016.2578282]

Near-real-time detection of tephra eruption onset and mass flow rate using microwave weather radar and infrasonic arrays

MARZANO, FRANK SILVIO;MONTOPOLI, MARIO;MEREU, LUIGI;
2016

Abstract

During an eruptive event, the near-real-time monitoring of volcanic explosion onset and its mass flow rate (MFR) is a key factor to predict ash plume dispersion and to mitigate risk to air traffic. Microwave (MW) weather radars have proved to be a fundamental instrument to derive eruptive source parameters. We extend this capability to include an early-warning detection scheme within the overall volcanic ash radar retrieval methodology. This scheme, called the volcanic ash detection (VAD) algorithm, is based on a hybrid technique using both fuzzy logic and conditional probability. Examples of VAD applications are shown for some case studies, including the Icelandic Grímsvötn eruption in 2011, the Eyjafjallajökull eruption in 2010, and the Italian Mt. Etna volcano eruption in 2013. Estimates of the eruption onset from the radar-based VAD module are compared with infrasonic array data. One-dimensional numerical simulations and analytical model estimates of MFR are also discussed and intercompared with sensor-based retrievals. Results confirm in all cases the potential ofMWweather radar for ash plumemonitoring in near real time and its complementarity with infrasonic array for early-warning system design.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/961378
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