Preliminary sensitivity study of eruption source parameters for operational volcanic ash cloud transport and dispersion models — A case study of the August 1992 eruption of the Crater Peak vent, Mount Spurr, Alaska

It has been 10 years since the ash cloud from the eruption of Eyjafjallajökull caused unprecedented disruption to air traffic across Europe. During this event, the London Volcanic Ash Advisory Centre (VAAC) provided advice and guidance on the expected location of volcanic ash in the atmosphere using observations and the atmospheric dispersion model NAME (Numerical Atmospheric-Dispersion Modelling Environment). Rapid changes in regulatory response and procedures during the eruption introduced the requirement to also provide forecasts of ash concentrations, representing a step-change in the level of interrogation of the dispersion model output. Although disruptive, the longevity of the event afforded the scientific community the opportunity to observe and extensively study the transport and dispersion of a volcanic ash cloud. We present the development of the NAME atmospheric dispersion model and modifications to its application in the London VAAC forecasting system since 2010, based on the lessons learned. Our ability to represent both the vertical and horizontal transport of ash in the atmosphere and its removal have been improved through the introduction of new schemes to represent the sedimentation and wet deposition of volcanic ash, and updated schemes to represent deep moist atmospheric convection and parametrizations for plume spread due to unresolved mesoscale motions. A good simulation of the transport and dispersion of a volcanic ash cloud requires an accurate representation of the source and we have introduced more sophisticated approaches to representing the eruption source parameters, and their uncertainties, used to initialize NAME. Finally, upper air wind field data used by the dispersion model is now more accurate than it was in 2010. These developments have resulted in a more robust modelling system at the London VAAC, ready to provide forecasts and guidance during the next volcanic ash event.

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Volcanic ash forecast using ensemble-based data assimilation: the Ensemble Transform Kalman Filter coupled with FALL3D-7.2 model (ETKF-FALL3D, version 1.0)

10.5194/gmd-2019-95 ◽

2019 ◽

Cited By ~ 1

Author(s):

Soledad Osores ◽

Juan Ruiz ◽

Arnau Folch ◽

Estela Collini

Keyword(s):

Kalman Filter ◽

Data Assimilation ◽

Volcanic Ash ◽

Source Parameters ◽

Joint Estimation ◽

Volcanic Ash Cloud ◽

Ensemble Transform Kalman Filter ◽

Ensemble Transform ◽

Ash Cloud ◽

Ash Dispersal

Abstract. Quantitative volcanic ash cloud forecasts are prone to uncertainties coming from the source term quantification (e.g. eruption strength or vertical distribution of the emitted particles), with consequent implications on operational ash impact assessment. We present an ensemble-based data assimilation and forecast system for volcanic ash dispersal and deposition aimed at reducing uncertainties related to eruption source parameters. The FALL3D atmospheric dispersal model is coupled with the Ensemble Transform Kalman Filter (ETKF) data assimilation technique by combining ash mass loading observations with ash dispersal simulations in order to obtain a better joint estimation of 3D ash concentration and source parameters. The ETKF-FALL3D data assimilation system is evaluated performing Observation System Simulation Experiments (OSSE) in which synthetic observations of fine ash mass loadings are assimilated. The evaluation of the ETKF-FALL3D system considering reference states of steady and time-varying eruption source parameters shows that the assimilation process gives both better estimations of ash concentration and time-dependent optimized values of eruption source parameters. The joint estimation of concentrations and source parameters leads to a better analysis and forecast of the 3D ash concentrations. Results show the potential of the methodology to improve volcanic ash cloud forecasts in operational contexts.

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A multidisciplinary effort to assign realistic source parameters to models of volcanic ash-cloud transport and dispersion during eruptions

Journal of Volcanology and Geothermal Research ◽

10.1016/j.jvolgeores.2009.01.008 ◽

2009 ◽

Vol 186 (1-2) ◽

pp. 10-21 ◽

Cited By ~ 381

Author(s):

L.G. Mastin ◽

M. Guffanti ◽

R. Servranckx ◽

P. Webley ◽

S. Barsotti ◽

...

Keyword(s):

Volcanic Ash ◽

Source Parameters ◽

Volcanic Ash Cloud ◽

Ash Cloud

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The Development of Volcanic Ash Cloud Layers over Hours to Days Due to Atmospheric Turbulence Layering

Atmosphere ◽

10.3390/atmos12020285 ◽

2021 ◽

Vol 12 (2) ◽

pp. 285

Author(s):

Marcus Bursik ◽

Qingyuan Yang ◽

Adele Bear-Crozier ◽

Michael Pavolonis ◽

Andrew Tupper

Keyword(s):

Atmospheric Turbulence ◽

Layered Structure ◽

Turbulent Diffusion ◽

Volcanic Ash ◽

Vertical Motion ◽

Aviation Safety ◽

Dispersion Models ◽

Free Atmosphere ◽

Volcanic Ash Cloud ◽

Ash Cloud

Volcanic ash clouds often become multilayered and thin with distance from the vent. We explore one mechanism for the development of this layered structure. We review data on the characteristics of turbulence layering in the free atmosphere, as well as examples of observations of layered clouds both near-vent and distally. We then explore dispersion models that explicitly use the observed layered structure of atmospheric turbulence. The results suggest that the alternation of turbulent and quiescent atmospheric layers provides one mechanism for the development of multilayered ash clouds by modulating vertical particle motion. The largest particles, generally μ>100 μm, are little affected by turbulence. For particles in which both settling and turbulent diffusion are important to vertical motion, mostly in the range of 10–100 μμm, the greater turbulence intensity and more rapid turbulent diffusion in some layers causes these particles to spend greater time in the more turbulent layers, leading to a layering of concentration. The results may have important implications for ash cloud forecasting and aviation safety.

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Exploring forecast variability during volcanic ash cloud events

10.5194/egusphere-egu21-8620 ◽

2021 ◽

Author(s):

Frances Beckett ◽

Ralph Burton ◽

Fabio Dioguardi ◽

Claire Witham ◽

John Stevenson ◽

...

Keyword(s):

Real Time ◽

Volcanic Ash ◽

Atmospheric Transport ◽

Dispersion Model ◽

Meteorological Data ◽

Atmospheric Dispersion ◽

Dispersion Models ◽

British Geological Survey ◽

Volcanic Ash Cloud ◽

Ash Cloud

Atmospheric transport and dispersion models are used by Volcanic Ash Advisory Centers (VAACs) to provide timely information on volcanic ash clouds to mitigate the risk of aircraft encounters. Inaccuracies in dispersion model forecasts can occur due to the uncertainties associated with source terms, meteorological data and model parametrizations. Real-time validation of model forecasts against observations is therefore essential to ensure their reliability. Forecasts can also benefit from comparison to model output from other groups; through understanding how different modelling approaches, variations in model setups, model physics, and driving meteorological data, impact the predicted extent and concentration of ash. The Met Office, the National Centre for Atmospheric Science (NCAS) and the British Geological Survey (BGS) are working together to consider how we might compare data (both qualitatively and quantitatively) from the atmospheric dispersion models NAME, FALL3D and HYSPLIT, using meteorological data from the Met Office Unified Model and the NOAA Global Forecast System (providing an effective multi-model ensemble). Results from the model inter-comparison will be used to provide advice to the London VAAC to aid forecasting decisions in near real time during a volcanic ash cloud event. In order to facilitate this comparison, we developed a Python package (ash-model-plotting) to read outputs from the different models into a consistent structure. Here we present our framework for generating comparable plots across the different partners, with a focus on total column mass loading products. These are directly comparable to satellite data retrievals and therefore important for model validation. We also present outcomes from a recent modelling exercise and discuss next steps for further improving our forecast validation.

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Operational Response to Volcanic Ash Risks Using HOTVOLC Satellite-Based System and MOCAGE-Accident Model at the Toulouse VAAC

Atmosphere ◽

10.3390/atmos11080864 ◽

2020 ◽

Vol 11 (8) ◽

pp. 864

Author(s):

Mathieu Gouhier ◽

Mathieu Deslandes ◽

Yannick Guéhenneux ◽

Philippe Hereil ◽

Philippe Cacault ◽

...

Keyword(s):

Volcanic Ash ◽

Source Parameters ◽

Vertical Column ◽

Cloud Properties ◽

Eruptive Column ◽

Operational Management ◽

Remote Sensing Techniques ◽

Ash Cloud

In 2010, the Eyjafjallajökull volcano erupted, generating an ash cloud causing unprecedented disruption of European airspace. Despite an exceptional situation, both the London and Toulouse Volcanic Ash Advisory Centres (VAAC) provided critical information on the location of the cloud and on the concentration of ash, thus contributing to the crisis management. Since then, substantial efforts have been carried out by the scientific community in order to improve remote sensing techniques and numerical modeling. Satellite instruments have proven to be particularly relevant for the characterization of ash cloud properties and a great help in the operational management of volcanic risk. In this study, we present the satellite-based system HOTVOLC developed at the Observatoire de Physique du Globe de Clermont-Ferrand (OPGC) using Meteosat geostationary satellite and designed for real-time monitoring of active volcanoes. After a brief presentation of the system we provide details on newly developed satellite products dedicated to the ash cloud characterization. This includes, in particular, ash cloud altitude and vertical column densities (VCD). Then, from the Stromboli 2018 paroxysm, we show how HOTVOLC can be used in a timely manner to assist the Toulouse VAAC in the operational management of the eruptive crisis. In the second part of the study, we provide parametric tests of the MOCAGE-Accident model run by the Toulouse VAAC from the April 17 Eyjafjallajökull eruption. For this purpose, we tested a range of eruption source parameters including the Total Grain Size Distribution (TGSD), the eruptive column profile, the top plume height and mass eruption rate (MER), as well as the fine ash partitioning. Finally, we make a comparison on this case study between HOTVOLC and MOCAGE-Accident VCD.

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Erratum to ‘A multidisciplinary effort to assign realistic source parameters to models of volcanic ash-cloud transport and dispersion during eruptions’ by Mastin et al. [J. Volcanol. Geotherm. Res. 188(2009)1–21]

Journal of Volcanology and Geothermal Research ◽

10.1016/j.jvolgeores.2009.10.013 ◽

2010 ◽

Vol 191 (3-4) ◽

pp. 245 ◽

Cited By ~ 5

Author(s):

L.G. Mastin ◽

M. Guffanti ◽

R. Servranckx ◽

P. Webley ◽

S. Barsotti ◽

...

Keyword(s):

Volcanic Ash ◽

Source Parameters ◽

Volcanic Ash Cloud ◽

Ash Cloud

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Volcanic ash forecast using ensemble-based data assimilation: an ensemble transform Kalman filter coupled with the FALL3D-7.2 model (ETKF–FALL3D version 1.0)

Geoscientific Model Development ◽

10.5194/gmd-13-1-2020 ◽

2020 ◽

Vol 13 (1) ◽

pp. 1-22 ◽

Cited By ~ 2

Author(s):

Soledad Osores ◽

Juan Ruiz ◽

Arnau Folch ◽

Estela Collini

Keyword(s):

Kalman Filter ◽

Data Assimilation ◽

Volcanic Ash ◽

Source Parameters ◽

Joint Estimation ◽

Volcanic Ash Cloud ◽

Ensemble Transform Kalman Filter ◽

Ensemble Transform ◽

Ash Cloud ◽

Ash Dispersal

Abstract. Quantitative volcanic ash cloud forecasts are prone to uncertainties coming from the source term quantification (e.g., the eruption strength or vertical distribution of the emitted particles), with consequent implications for an operational ash impact assessment. We present an ensemble-based data assimilation and forecast system for volcanic ash dispersal and deposition aimed at reducing uncertainties related to eruption source parameters. The FALL3D atmospheric dispersal model is coupled with the ensemble transform Kalman filter (ETKF) data assimilation technique by combining ash mass loading observations with ash dispersal simulations in order to obtain a better joint estimation of the 3-D ash concentration and source parameters. The ETKF–FALL3D data assimilation system is evaluated by performing observing system simulation experiments (OSSEs) in which synthetic observations of fine ash mass loadings are assimilated. The evaluation of the ETKF–FALL3D system, considering reference states of steady and time-varying eruption source parameters, shows that the assimilation process gives both better estimations of ash concentration and time-dependent optimized values of eruption source parameters. The joint estimation of concentrations and source parameters leads to a better analysis and forecast of the 3-D ash concentrations. The results show the potential of the methodology to improve volcanic ash cloud forecasts in operational contexts.

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Dispersion Modelling at the London VAAC 10 Years after the Eyjafjallajökull Ash Cloud

10.5194/egusphere-egu2020-4774 ◽

2020 ◽

Author(s):

Frances Beckett ◽

Claire Witham ◽

Susan Leadbetter ◽

Ric Crocker ◽

Helen Webster ◽

...

Keyword(s):

Volcanic Ash ◽

Dispersion Model ◽

Meteorological Data ◽

Weather Prediction ◽

Source Parameters ◽

Atmospheric Dispersion ◽

Lessons Learned ◽

Volcanic Ash Cloud ◽

Atmospheric Dispersion Models ◽

Ash Cloud

It has been 10 years since the ash cloud from the eruption of Eyjafjallaj&#246;kull caused chaos to air traffic across Europe. Although disruptive, the longevity of the event afforded the scientific community the opportunity to observe and extensively study the transport and dispersion of a volcanic ash cloud. Here we present the development of the NAME atmospheric dispersion model and modifications to its application in the London VAAC forecasting system since 2010, based on the lessons learned.Our ability to represent both the vertical and horizontal transport of ash in the atmosphere and its removal have been improved through the introduction of new schemes to represent the sedimentation and wet deposition of volcanic ash, and updated schemes to represent deep atmospheric convection and parameterizations for plume spread due to unresolved mesoscale motions. A good simulation of the transport and dispersion of a volcanic ash cloud requires an accurate representation of the source and we have introduced more sophisticated approaches to representing the eruption source parameters, and their uncertainties, used to initialize NAME. Further, atmospheric dispersion models are driven by 3-dimensional meteorological data from Numerical Weather Prediction (NWP) models and the Met Office&#8217;s upper air wind field data is now more accurate than it was in 2010. These developments have resulted in a more robust modelling system at the London VAAC, ready to provide forecasts and guidance during the next volcanic ash event affecting their region.

Download Full-text