scholarly journals Modelling the size distribution of aggregated volcanic ash and implications for operational atmospheric dispersion modelling

2021 ◽  
Author(s):  
Frances Beckett ◽  
Eduardo Rossi ◽  
Benjamin Devenish ◽  
Claire Witham ◽  
Costanza Bonadonna
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Volcanic Ash ◽  
Dispersion Model ◽  
Aviation Industry ◽  
Eruption Column ◽  
Model Simulations ◽  
Aggregation Scheme ◽  
Ash Cloud

Abstract. We have developed an aggregation scheme for use with the Lagrangian atmospheric transport and dispersion model NAME, which is used by the London Volcanic Ash Advisory Centre (VAAC) to provide advice and guidance on the location of volcanic ash clouds to the aviation industry. The aggregation scheme uses the fixed pivot technique to solve the Smoluchowski coagulation equations to simulate aggregation processes in an eruption column. This represents the first attempt at modelling explicitly the change in the grain size distribution (GSD) of the ash due to aggregation in a model which is used for operational response. To understand the sensitivity of the output aggregated grain size distribution (AGSD) to the model parameters we conducted a simple parametric study and scaling analysis. We find that the modelled AGSD is sensitive to the density distribution and grain size distribution assigned to the non-aggregated ash at the source. Our ability to accurately forecast the long-range transport of volcanic ash clouds is, therefore, still limited by real-time information on the physical characteristics of the ash. We assess the impact of using the AGSD on model simulations of the Eyjafjallajökull 2010 ash cloud, and consider the implications for operational forecasting. Using the time-evolving AGSD at the top of the eruption column to initialise dispersion model simulations had little impact on the modelled extent and mass loadings in the distal ash cloud. Our aggregation scheme does not account for the density of the aggregates; however, if we assume that the aggregates have the same density of single grains of equivalent size the modelled extent of the Eyjafjallajökull ash cloud with high concentrations of ash, significant for aviation, is reduced by ~3 %. If we assume that the aggregates have a lower density (500 kg m−3) than the single grains of which they are composed and make-up 75 % of the mass in the ash cloud the extent is 1.2 times larger.

scholarly journals FPLUME-1.0: An integral volcanic plume model accounting for ash aggregation

2016 ◽  
Vol 9 (1) ◽  
pp. 431-450 ◽  
Author(s):  
A. Folch ◽  
A. Costa ◽  
G. Macedonio
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Risk Mitigation ◽  
Source Parameters ◽  
Air Entrainment ◽  
Phase Changes ◽  
Column Height ◽  
Volcanic Plume ◽  
Eruption Column

Abstract. Eruption source parameters (ESP) characterizing volcanic eruption plumes are crucial inputs for atmospheric tephra dispersal models, used for hazard assessment and risk mitigation. We present FPLUME-1.0, a steady-state 1-D (one-dimensional) cross-section-averaged eruption column model based on the buoyant plume theory (BPT). The model accounts for plume bending by wind, entrainment of ambient moisture, effects of water phase changes, particle fallout and re-entrainment, a new parameterization for the air entrainment coefficients and a model for wet aggregation of ash particles in the presence of liquid water or ice. In the occurrence of wet aggregation, the model predicts an effective grain size distribution depleted in fines with respect to that erupted at the vent. Given a wind profile, the model can be used to determine the column height from the eruption mass flow rate or vice versa. The ultimate goal is to improve ash cloud dispersal forecasts by better constraining the ESP (column height, eruption rate and vertical distribution of mass) and the effective particle grain size distribution resulting from eventual wet aggregation within the plume. As test cases we apply the model to the eruptive phase-B of the 4 April 1982 El Chichón volcano eruption (México) and the 6 May 2010 Eyjafjallajökull eruption phase (Iceland). The modular structure of the code facilitates the implementation in the future code versions of more quantitative ash aggregation parameterization as further observations and experiment data will be available for better constraining ash aggregation processes.

scholarly journals FPLUME-1.0: An integrated volcanic plume model accounting for ash aggregation

2015 ◽  
Vol 8 (9) ◽  
pp. 8009-8062 ◽  
Author(s):  
A. Folch ◽  
A. Costa ◽  
G. Macedonio
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Risk Mitigation ◽  
Source Parameters ◽  
Air Entrainment ◽  
Phase Changes ◽  
Column Height ◽  
Volcanic Plume ◽  
Eruption Column

Abstract. Eruption Source Parameters (ESP) characterizing volcanic eruption plumes are crucial inputs for atmospheric tephra dispersal models, used for hazard assessment and risk mitigation. We present FPLUME-1.0, a steady-state 1-D cross-section averaged eruption column model based on the Buoyant Plume Theory (BPT). The model accounts for plume bent over by wind, entrainment of ambient moisture, effects of water phase changes, particle fallout and re-entrainment, a new parameterization for the air entrainment coefficients and a model for wet aggregation of ash particles in presence of liquid water or ice. In the occurrence of wet aggregation, the model predicts an "effective" grain size distribution depleted in fines with respect to that erupted at the vent. Given a wind profile, the model can be used to determine the column height from the eruption mass flow rate or vice-versa. The ultimate goal is to improve ash cloud dispersal forecasts by better constraining the ESP (column height, eruption rate and vertical distribution of mass) and the "effective" particle grain size distribution resulting from eventual wet aggregation within the plume. As test cases we apply the model to the eruptive phase-B of the 4 April 1982 El Chichón volcano eruption (México) and the 6 May 2010 Eyjafjallajökull eruption phase (Iceland).

scholarly journals Grain size distribution uncertainty quantification in volcanic ash dispersal and deposition from weak plumes

2016 ◽  
Vol 121 (2) ◽  
pp. 538-557 ◽  
Author(s):  
Federica Pardini ◽  
Antonio Spanu ◽  
Mattia de' Michieli Vitturi ◽  
Maria Vittoria Salvetti ◽  
Augusto Neri
Keyword(s):  
Grain Size ◽  
Uncertainty Quantification ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Volcanic Ash ◽  
Ash Dispersal

scholarly journals Lightning Effects on the Grain Size Distribution of Volcanic Ash

2019 ◽  
Vol 46 (6) ◽  
pp. 3133-3141 ◽  
Author(s):  
K. Genareau ◽  
K. L. Wallace ◽  
P. Gharghabi ◽  
J. Gafford
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Volcanic Ash

scholarly journals Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 567 ◽  
Author(s):  
Sara Osman ◽  
Frances Beckett ◽  
Alison Rust ◽  
Eveanjelene Snee
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Volcanic Ash ◽  
Sensitivity Study ◽  
Dispersion Modelling ◽  
Grain Size Distributions ◽  
Ash Dispersion ◽  
The Impact ◽  
Coarse To Fine

The size distribution of volcanic ash is rarely measured in real time and Volcanic Ash Advisory Centres (VAACs) often rely on a default particle size distribution (PSD) to initialise their dispersion models when forecasting the movement of ash clouds. We conducted a sensitivity study to investigate the impact of PSD on model output and consider how best to apply default PSDs in operational dispersion modelling. Compiled grain size data confirm that, when considering particles likely to be in the distal ash cloud (< 125 µm diameter), magma composition and eruption size are the dominant controls on grain size distribution. Constraining the PSD is challenging but we find that the grain size of deposits from large hydromagmatic eruptions remains relatively constant with distance, suggesting that total (whole-deposit) grain size distributions (TGSDs) for these eruptions could be estimated from a few samples. We investigated the sensitivity of modelled ash mass loadings (in the air and on the ground) to input PSDs based on coarse to fine TGSDs from our dataset. We found clear differences between modelled mass loadings and the extent of the plume. Comparing TGSDs based on ground-only and ground-plus-satellite data for the Eyjafjallajökull 2010 eruption, we found that basing input PSDs on TGSDs from deposits alone (likely missing the finest particles) led to lower modelled peak ash concentrations and a smaller plume.

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