scholarly journals Annex to: Volcanic Ash Cloud Observation using Ground-based Ka-band Radar and Near-Infrared Lidar Ceilometer during the Eyjafjallajökull eruption

2015 ◽  
Vol 57 ◽  
Author(s):  
Frank S. Marzano ◽  
Luigi Mereu ◽  
Mario Montopoli ◽  
Domenico Cimini ◽  
Giovanni Martucci
Keyword(s):  
Volcanic Ash ◽  
Near Infrared ◽  
Volcanic Eruptions ◽  
Title Page ◽  
Ka Band ◽  
Volcanic Ash Cloud ◽  
Explosive Volcanic Eruptions ◽  
Ash Cloud

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>Volcanic ash plumes are formed during explosive volcanic eruptions. After advection over several thousands of kilometers, volcanic ash particles are highly fragmented, dispersed and aged with micron- sized sorting. This Annex describes the ash microphysical modeling and the simulated radar and lidar signatures. [...]</span></p></div></div></div>

scholarly journals The fate of volcanic ash: premature or delayed sedimentation?

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Eduardo Rossi ◽  
Gholamhossein Bagheri ◽  
Frances Beckett ◽  
Costanza Bonadonna
Keyword(s):  
Residence Time ◽  
Volcanic Ash ◽  
Volcanic Eruptions ◽  
Theoretical Description ◽  
Particle Sedimentation ◽  
Weather Modeling ◽  
Explosive Volcanic Eruptions ◽  
Travel Distances ◽  
Ash Dispersal

AbstractA large amount of volcanic ash produced during explosive volcanic eruptions has been found to sediment as aggregates of various types that typically reduce the associated residence time in the atmosphere (i.e., premature sedimentation). Nonetheless, speculations exist in the literature that aggregation has the potential to also delay particle sedimentation (rafting effect) even though it has been considered unlikely so far. Here, we present the first theoretical description of rafting that demonstrates how delayed sedimentation may not only occur but is probably more common than previously thought. The fate of volcanic ash is here quantified for all kind of observed aggregates. As an application to the case study of the 2010 eruption of Eyjafjallajökull volcano (Iceland), we also show how rafting can theoretically increase the travel distances of particles between 138–710 μm. These findings have fundamental implications for hazard assessment of volcanic ash dispersal as well as for weather modeling.

scholarly journals Volcanic ash cloud detection from space: a comparison between the RSTASHtechnique and the water vapour corrected BTD procedure

2011 ◽  
Vol 2 (3) ◽  
pp. 263-277 ◽  
Author(s):  
Alessandro Piscini ◽  
Stefano Corradini ◽  
Francesco Marchese ◽  
Luca Merucci ◽  
Nicola Pergola ◽  
...  
Keyword(s):  
Water Vapour ◽  
Volcanic Ash ◽  
Cloud Detection ◽  
Volcanic Ash Cloud ◽  
Ash Cloud

scholarly journals Volcanic ash modeling with the NMMB-MONARCH-ASH model: quantification of offline modeling errors

2018 ◽  
Vol 18 (6) ◽  
pp. 4019-4038 ◽  
Author(s):  
Alejandro Marti ◽  
Arnau Folch
Keyword(s):  
Volcanic Ash ◽  
Source Parameters ◽  
Atmospheric Dispersion ◽  
Volcanic Eruptions ◽  
Systematic Errors ◽  
Cloud Detection ◽  
Coupled Modeling ◽  
Evaluation Scores ◽  
Modeling Systems ◽  
Ash Cloud

Abstract. Volcanic ash modeling systems are used to simulate the atmospheric dispersion of volcanic ash and to generate forecasts that quantify the impacts from volcanic eruptions on infrastructures, air quality, aviation, and climate. The efficiency of response and mitigation actions is directly associated with the accuracy of the volcanic ash cloud detection and modeling systems. Operational forecasts build on offline coupled modeling systems in which meteorological variables are updated at the specified coupling intervals. Despite the concerns from other communities regarding the accuracy of this strategy, the quantification of the systematic errors and shortcomings associated with the offline modeling systems has received no attention. This paper employs the NMMB-MONARCH-ASH model to quantify these errors by employing different quantitative and categorical evaluation scores. The skills of the offline coupling strategy are compared against those from an online forecast considered to be the best estimate of the true outcome. Case studies are considered for a synthetic eruption with constant eruption source parameters and for two historical events, which suitably illustrate the severe aviation disruptive effects of European (2010 Eyjafjallajökull) and South American (2011 Cordón Caulle) volcanic eruptions. Evaluation scores indicate that systematic errors due to the offline modeling are of the same order of magnitude as those associated with the source term uncertainties. In particular, traditional offline forecasts employed in operational model setups can result in significant uncertainties, failing to reproduce, in the worst cases, up to 45–70 % of the ash cloud of an online forecast. These inconsistencies are anticipated to be even more relevant in scenarios in which the meteorological conditions change rapidly in time. The outcome of this paper encourages operational groups responsible for real-time advisories for aviation to consider employing computationally efficient online dispersal models.

scholarly journals Atmospheric Dispersion Modelling at the London VAAC: A Review of Developments since the 2010 Eyjafjallajökull Volcano Ash Cloud

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 352 ◽  
Author(s):  
Frances M. Beckett ◽  
Claire S. Witham ◽  
Susan J. Leadbetter ◽  
Ric Crocker ◽  
Helen N. Webster ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Dispersion Model ◽  
Source Parameters ◽  
Atmospheric Dispersion ◽  
Lessons Learned ◽  
Dispersion Modelling ◽  
Atmospheric Dispersion Modelling ◽  
Volcanic Ash Cloud ◽  
Atmospheric Dispersion Model ◽  
Ash Cloud

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.

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

2019 ◽  
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.

Near-real-time volcanic ash cloud detection: Experiences from the Alaska Volcano Observatory

2009 ◽  
Vol 186 (1-2) ◽  
pp. 79-90 ◽  
Author(s):  
P.W. Webley ◽  
J. Dehn ◽  
J. Lovick ◽  
K.G. Dean ◽  
J.E. Bailey ◽  
...  
Keyword(s):  
Real Time ◽  
Volcanic Ash ◽  
Cloud Detection ◽  
Volcano Observatory ◽  
Volcanic Ash Cloud ◽  
Ash Cloud
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