Articles | Volume 21, issue 10
https://doi.org/10.5194/nhess-21-2973-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-21-2973-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
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05 Oct 2021
Research article | Highlight paper |
| 05 Oct 2021
| 05 Oct 2021
An ensemble of state-of-the-art ash dispersion models: towards probabilistic forecasts to increase the resilience of air traffic against volcanic eruptions
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Barbara Scherllin-Pirscher
Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Vienna, 1190, Austria
Delia Arnold Arias
Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Vienna, 1190, Austria
Rocio Baro
Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Vienna, 1190, Austria
Guillaume Bigeard
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Luca Bugliaro
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Oberpfaffenhofen, Germany
Ana Carvalho
Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, 601 76, Sweden
Laaziz El Amraoui
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Kurt Eschbacher
Paris Lodron University of Salzburg (PLUS), Salzburg, 5020, Austria
Marcus Hirtl
Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Vienna, 1190, Austria
Christian Maurer
Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Vienna, 1190, Austria
Marie D. Mulder
Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Vienna, 1190, Austria
Dennis Piontek
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Oberpfaffenhofen, Germany
Lennart Robertson
Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, 601 76, Sweden
Carl-Herbert Rokitansky
Paris Lodron University of Salzburg (PLUS), Salzburg, 5020, Austria
Fritz Zobl
Paris Lodron University of Salzburg (PLUS), Salzburg, 5020, Austria
Raimund Zopp
Flightkeys GmbH, Vienna, 1060, Austria
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Cited
9 citations as recorded by crossref.
- Large Uncertainties Are Pervasive in Long-Term Frequency-Magnitude Relationships for Volcanoes in Southeast Asia J. Hayes et al. 10.3389/feart.2022.895756
- Modelling the volcanic ash plume from Eyjafjallajökull eruption (May 2010) over Europe: evaluation of the benefit of source term improvements and of the assimilation of aerosol measurements M. Plu et al. 10.5194/nhess-21-3731-2021
- Airspace Contamination by Volcanic Ash from Sequences of Etna Paroxysms: Coupling the WRF-Chem Dispersion Model with Near-Source L-Band Radar Observations U. Rizza et al. 10.3390/rs15153760
- VADUGS: a neural network for the remote sensing of volcanic ash with MSG/SEVIRI trained with synthetic thermal satellite observations simulated with a radiative transfer model L. Bugliaro et al. 10.5194/nhess-22-1029-2022
- EUNADICS-AV early warning system dedicated to supporting aviation in the case of a crisis from natural airborne hazards and radionuclide clouds H. Brenot et al. 10.5194/nhess-21-3367-2021
- Assessment of eruption source parameters using infrasound and plume modelling: a case study from the 2021 eruption of Mt. Etna, Italy S. De Angelis et al. 10.1038/s41598-023-46160-6
- Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers D. Piontek et al. 10.3390/rs15051247
- The New Volcanic Ash Satellite Retrieval VACOS Using MSG/SEVIRI and Artificial Neural Networks: 2. Validation D. Piontek et al. 10.3390/rs13163128
- Ensemble-Based Forecast of Volcanic Clouds Using FALL3D-8.1 A. Folch et al. 10.3389/feart.2021.741841
7 citations as recorded by crossref.
- Large Uncertainties Are Pervasive in Long-Term Frequency-Magnitude Relationships for Volcanoes in Southeast Asia J. Hayes et al. 10.3389/feart.2022.895756
- Modelling the volcanic ash plume from Eyjafjallajökull eruption (May 2010) over Europe: evaluation of the benefit of source term improvements and of the assimilation of aerosol measurements M. Plu et al. 10.5194/nhess-21-3731-2021
- Airspace Contamination by Volcanic Ash from Sequences of Etna Paroxysms: Coupling the WRF-Chem Dispersion Model with Near-Source L-Band Radar Observations U. Rizza et al. 10.3390/rs15153760
- VADUGS: a neural network for the remote sensing of volcanic ash with MSG/SEVIRI trained with synthetic thermal satellite observations simulated with a radiative transfer model L. Bugliaro et al. 10.5194/nhess-22-1029-2022
- EUNADICS-AV early warning system dedicated to supporting aviation in the case of a crisis from natural airborne hazards and radionuclide clouds H. Brenot et al. 10.5194/nhess-21-3367-2021
- Assessment of eruption source parameters using infrasound and plume modelling: a case study from the 2021 eruption of Mt. Etna, Italy S. De Angelis et al. 10.1038/s41598-023-46160-6
- Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers D. Piontek et al. 10.3390/rs15051247
Latest update: 26 Apr 2024
Short summary
Past volcanic eruptions that spread out ash over large areas, like Eyjafjallajökull in 2010, forced the cancellation of thousands of flights and had huge economic consequences.
In this article, an international team in the H2020 EU-funded EUNADICS-AV project has designed a probabilistic model approach to quantify ash concentrations. This approach is evaluated against measurements, and its potential use to mitigate the impact of future large-scale eruptions is discussed.
Past volcanic eruptions that spread out ash over large areas, like Eyjafjallajökull in 2010,...
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