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We have developed an aggregation scheme for use with the Lagrangian atmospheric transport and dispersion model NAME (Numerical Atmospheric Dispersion modelling Environment), 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 GSD to the model parameters, we conducted a simple parametric study and scaling analysis. We find that the modelled aggregated GSD is sensitive to the density distribution and grain size distribution assigned to the non-aggregated particles 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 aggregated GSD on model simulations of the 2010 Eyjafjallajökull ash cloud and consider the implications for operational forecasting. Using the time-evolving aggregated GSD at the top of the eruption column to initialize 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 area of the Eyjafjallajökull ash cloud with high concentrations of ash, significant for aviation, is reduced by ∼ 2 %, 24 h after the start of the release. 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 1.1 times larger.

Volcanic eruptions can emit large quantities of sulphur dioxide (SO2) into the atmosphere, which can be harmful to people and the environment. Aircraft encounters with a volcanic SO2 cloud could represent a health hazard to crew and passengers onboard, depending on the dose of SO2 encountered. The recommended SO2 concentration threshold set by the World Health Organisation (WHO) is 500 µg/m3 over 10 minutes. In this study we have assessed concentration levels of volcanic SO2 in the atmosphere following eight historic eruptions and use dispersion model simulations to calculate when and where the WHO threshold is exceeded. The time and area of exceedance varies and depends on the eruption characteristics: the amount, duration and height of the SO2 release. The WHO threshold is exceeded for all historic eruptions considered. In several cases, the area delineated by the WHO threshold, that is the SO2 hazard, can be considerably larger than the volcanic ash hazard area for the same eruption. SO2 hazard areas also often extend over a longer period of time compared to the equivalent ash advisories. For example, following the 2019 eruption of Raikoke, the SO2 hazard area reached up to 1.7 million km2 and the WHO concentration value was exceeded for about two weeks, while volcanic ash was considered hazardous to aviation for about five days. These results will help the aviation industry to better understand the potential risks to their passengers and crew from volcanic SO2, and aid in defining concentration thresholds for any potential volcanic SO2 forecasts for aviation.

Volcanic ash can act as ice-nucleating particles (INPs), which by triggering freezing of supercooled water droplets in the atmosphere, can profoundly influence clouds and thereby climate [1]. Volcanoes worldwide sporadically emit large amounts of ash into the atmosphere including at middle to high latitudes (30-90° N/S) where, importantly, other major types of INPs such as windblown Saharan dust from low latitudes are less abundant. A recent study found that windblown Icelandic dust of volcanic and glacio-fluvial origin could episodically dominate INP concentrations between 3 to 5.5 km above sea level over the North Atlantic and Arctic [2]. However, it remains unexplored how volcanic ash emissions from explosive eruptions, which typically occur every 3 to 5 years in Iceland, affect INP concentrations in these regions. Here we investigated the Eyjafjallajökull eruption from 14 April to 22 May 2010 and Eyjafjallajökull ash resuspension events (by wind) thereafter as sources of INPs to the atmosphere. Specifically, by combining ash concentration and temperature data from Lagrangian particle dispersion model simulations (Numerical Atmospheric dispersion Modelling Environment [3]) with a laboratory-derived parameterisation of the ice-nucleating activity of this ash [2,4-5], we calculated INP concentrations up to 10 km above sea level across the Northern Hemisphere during and following the Eyjafjallajökull eruption. In late April 2010, the erupted ash produced INP concentrations >0.01 L-1 (potentially capable of affecting cloud liquid water content) in up to ~14 vol% of air masses at temperatures between 0 and -35 °C and latitudes between 45 and 90° N. In contrast, the contribution of resuspended ash to the atmospheric INP population in subsequent months was up to several orders of magnitude smaller, partly because resuspended ash particles more seldomly reached altitudes where temperatures were low enough for ice nucleation. Findings of this case study and perspectives on further integrating model and laboratory data to improve understanding of the impacts of volcanic ash on clouds and climate will be discussed.[1] Murray, B. J., Carslaw, K. S, Field, P. R. (2021) Atmospheric Chemistry and Physics, 21, 665-679, doi:10.5194/acp-21-665-2021.[2] Sanchez-Marroquin, A., Arnalds, O., Baustian-Dorsi, K. J., Browse, J., Dagsson-Waldhauserova, P., Harrison, A. D., Maters, E. C., Pringle, K. J., Vergara-Temprado, J., Burke, I. T., McQuaid, J. B., Carslaw, K. S., Murray, B. J. (2020) Science Advances, 6, eaba8137, doi:10.1126/sciadv.aba8137.[3] Jones, A., Thomson, D., Hort, M., Devenish, B. (2007) In: Borrego, C., Norman, A.-L. (Eds) Air Pollution Modelling and its Application XVII, Springer, Boston, 580-589, doi:10.1007/978-0-387-68854-1_62[4] Hoyle, C. R., Pinti, V., Welti, A., Zobrist, B., Marcolli, C., Luo, B., Höskuldsson, Á., Mattsson, H. B., Stetzer, O., Thorsteinsson, T., Larsen, G., Peter, T. (2011) Atmospheric Chemistry and Physics, 11, 9911-9926, doi:10.5194/acp-11-9911-2011.[5] Steinke, I., Möhler, O., Kiselev, A., Niemand, M., Saathoff, H., Schnaiter, M., Skrotzki, J., Hoose, C., Leisner, T. (2011) Atmospheric Chemistry and Physics, 11, 12945-12958, doi:10.5194/acp-11-12945-2011.

Many volcanoes around the world are persistently active with continuous degassing for years or even centuries, sometimes exceeding historic records. Such long-term stability contrasts with short-term instability, reflected in eruptive episodes that punctuate passive degassing. These two aspects of persistent activity, long-term stability as opposed to short-term instability, are often conceptualized through two distinct model frameworks: Exchange-flow in volcanic conduits is commonly invoked to explain the long-term thermal balance and sustained passive degassing, while the ascent of large gas slugs is called upon to understand explosive eruptions. While typically considered separately, we propose here that both flow processes could occur jointly in the conduits of persistently active volcanoes and in transient connections between subvolcanic melt lenses. To understand the dynamic interplay between exchange flow and slug ascent, we link analogue laboratory experiments with direct numerical simulations. We find that the two flows superimpose without creating major disruptions when only considering the ascent of a single gas slug. However, the sequential ascent of multiple gas slugs is disruptive to the ambient exchange flow, because it may entail continual buildup of buoyant magma at depth. While our study focuses on the laboratory scale, we propose that the dependence of exchange-flow stability on sequential slug ascent is relevant for understanding why explosive sequences are sometimes followed by effusive eruptions. Taken together, our work suggests that integrating exchange flow and slug ascent could provide a more complete understanding of persistently active volcanoes than either model framework offers in isolation.

Volcanic aerosol simulations with interactive stratospheric aerosol models mostly neglect ash particles, due to a general assumption they sediment out of the volcanic plume within the first few weeks and have limited impacts on the progression of the volcanic aerosol cloud (Niemeier et al., 2009). However, observations, such as ground-based and airborne lidar (Vaughan et al., 1994; Browell et al., 1993), along with impactor measurements (Pueschel et al., 1994) in the months after the Mount Pinatubo eruption suggest the base of the aerosol cloud contained ash particles coated in sulphuric acid for around 9 months after the eruption occurred. Impactor measurements from flights following the 1963 Agung and 1982 El Chichon eruptions also show ash remained present for many months after the eruption (Mossop, 1964; Gooding et al., 1983). More recently, satellite, in situ and optical particle counter measurements after the 2014 Mount Kelud eruption showed ash particles ~0.3 µm in size accounting for 20-28% of the volcanic cloud AOD 3 months following the eruption (Vernier et al., 2016; Deshler, 2016). This evidence suggests that sub-micron ash particles may persist for longer in the atmosphere than is often assumed. We explore how the presence of these sub-micron ash particles affects the progression of a major tropical volcanic aerosol cloud, showing results from simulations with a new configuration of the composition-climate model UM-UKCA, adapted to co-emit fine-ash alongside SO2. In the UM-UKCA simulations, internally mixed ash-sulphuric particles are transported within the existing coarse-insoluble mode of the GLOMAP-mode aerosol scheme. Size fractions of 0.1, 0.316 and 1 µm diameter ash were tested for the 1991 Mount Pinatubo eruption with an ultra-fine ash mass co-emission of 0.05 and 0.5 Tg, based on 0.1% and 1% of an assumed fine ash emission of 50Tg. Whereas the 0.316 and 1 µm sized particles sedimented out of the stratosphere within the first 90 days after the eruption, the 0.1 µm persisted within the lower portion of volcanic cloud for ~9 months, retaining over half its original mass (0.035 Tg) February 1992. We investigate model experiments with different injection heights for the co-emitted SO2 and ash, analysing the vertical profile of the ultra-fine ash compared to the sulphate aerosol, and explore the effects on the volcanic aerosol cloud in terms of its overall optical depth and vertical profile of extinction. The analysis demonstrates that although fine-ash is more persistent than previous modelling studies suggest, these particles have only modest impacts with the radiative heating effect the dominant pathway, with the sub-micron particles not scavenging sufficiently. Future work will explore simulations with a further adapted UM-UKCA model with an additional “super-coarse” insoluble mode resolving the super-micron ash, then both components of the fine-ash resolved to test the magnitude of sulfate scavenging effect.

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.

A 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., Generally it is thought that ash aggregation leads to reduced atmospheric travel distances. Here, the authors show that the rafting effect can increase dispersal range by up to 3.7 times for particles between 300–500 μm, compared to sedimentation of individual clasts.

It has been 10 years since the ash cloud from the eruption of Eyjafjallajökull 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’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.

Most volcanic ash produced during explosive volcanic eruptions sediments as aggregates of various types that typically have a greater fall velocity than the particles of which they are composed. As a result, aggregation processes are commonly known to affect the sedimentation of fine ash by considerably reducing its residence time in the atmosphere. Nonetheless, speculations also exist in the literature that aggregation does not always result in a premature sedimentation of their constitute particles but that it can also result in a delayed sedimentation (i.e. the so-called rafting effect). However, previous studies have considered rafting as a highly improbable phenomenon due to a biased representation of aggregate shapes.Here we provide the first theoretical evidence that rafting may not only occur, but it is probably more common than previously thought, helping to elucidate often unexplained field observations. Starting from field evidence of rafted aggregates at Sakurajima Volcano (Japan), we clarify the conditions for which aggregation of volcanic ash results either in a premature or a delayed sedimentation.Moreover, using the Lagrangian dispersion model NAME, we show the practical consequences of rafting on the final sedimentation distance of aggregates with different morphological features. As an application we chose the case study of the 2010 eruption of Eyjafjallajökull volcano (Iceland), for which rafting can increase the travel distances of ash These findings have fundamental implications both for real-time forecasting and long-term hazard assessment of volcanic ash dispersal and sedimentation and for weather modelling. The constraints on rafting presented and discussed in this work will help the scientific community to clarify the often unexpected role of aggregation in creating a delayed sedimentation of coarse ash.

Modelling atmospheric volcanic ash dispersion is a critical tool in mitigating the impact of large explosive eruptions; it is also useful for understanding and reconstructing past events. Most atmospheric dispersion models include a sedimentation velocity term that is sensitive to the physical properties of the particle, but many do not use particle shape as an input parameter; instead particles are assumed to be spherical. There are many empirical and semi-empirical shape-dependent drag laws. We measure the velocity of scaled analogue particles over the range of flow conditions anticipated for volcanic ash dispersion to test published formulae against an independent dataset. We use a semi-empirical formula we determined to be accurate for non-spheres to investigate the sensitivity of the modelled transport of an ash cloud to particle shape, using the atmospheric dispersion model NAME and a shape parameter we measure for non-spherical ash particles from Katla volcano, Iceland. We find that model particle trajectories are sensitive to particle shape for particles >1–3 μm diameter; the sedimentation velocity of smaller particles is low compared to atmospheric vertical velocities. Sensitivity to shape increases with size such that 100 μm particles can travel 44% further from the source when they are highly non-spherical (sphericity = 0.5). Despite the sensitivity of the fall velocity of large particles to their shape, however, forecasts of distal ash concentration using particle size distributions of 0.1–100 μm and 0.1–250 μm show relatively good agreement between a spherical and non-spherical case for the first 36 h after an eruption. The vertical structure of an ash cloud is more sensitive to particle shape than the horizontal extent. Model particle trajectories are also sensitive to particle size, and we find a discrepancy between different particle size parameters for non-spherical ash: particle long axis L, used in cryptotephra studies, was on average twice the equivalent-volume sphere diameter dv, used in dispersion modelling, for tephra samples from Katla volcano, Iceland. This discrepancy in size measurements could explain the observed travel distance of large distal cryptotephra shards.

Volcanic ash is dispersed in the atmosphere according to meteorology and particle properties, including size and shape. However, the multiple definitions of size and shape for non‐spherical particles affect our ability to use physical particle properties to understand tephra transport. Moreover, although particles

The sedimentation rate of volcanic ash through the atmosphere influences its travel distance, with important implications for aviation and health. The fall velocity of a particle depends on its size and density, but also shape, and volcanic ash is not spherical. To capture the sedimentation of ash, atmospheric dispersion models use empirical drag equations calibrated using geometric shape descriptors. However, particle shape data are scarce and there is no standard method of shape measurement. In addition, shape measurements are not always available during an eruption, when dispersion models are used operationally to forecast ash hazard. We assess the variability in the shape of volcanic ash from Icelandic eruptions using X-ray computed tomography. To consider how good different drag equations and shape descriptors are at representing the sedimentation of volcanic ash we compare calculated fall velocities to measured fall velocities of volcanic ash in air in a settling column. We then suggest the best drag equations and shape descriptors for use in atmospheric dispersion models. We find that shape-dependent drag equations produce more accurate results than a spherical approximation. However, accurate drag calculations based on the shape descriptor sphericity, which is a function of surface area, require the imaging resolution to be within the range of 102 - 105 voxels per particle (where a voxel is a volumetric pixel) as surface area is sensitive to imaging resolution. We suggest that the large-scale form of the particle impacts sedimentation more than small-scale surface roughness. Shape descriptors based on ratios between principal axis lengths are more practical as they are less variable among particle size classes and much less sensitive to imaging resolution. Finally, we use particle shape data from this study and literature sources to make recommendations on default values for use with atmospheric dispersion models where no shape data are available.

There is a large discrepancy between the size of volcanic ash particles measured on the ground at least 500 km from their source volcano (known as cryptotephra) and those reported by satellite remote sensing (effective radius of 0.5–9 μm; 95% of particles < 17 μm diameter). Here we present new results from the fields of tephrochronology (a dating technique based on volcanic ash layers), dispersion modelling and satellite remote sensing in an attempt to understand why. A literature review and measurements of prehistoric and recent eruptions were used to characterise the size range of cryptotephra grains. Icelandic cryptotephra deposited in NW Europe has lognormal particle size distributions (PSDs) with median lengths of 20–70 μm (geometric standard deviation: 1.40–1.66; 95th percentile length: 42–126 μm). Grain-size range estimates from the literature are similar. We modelled the settling of volcanic ash using measured fall velocities of ash particles, a release height typical of moderate Icelandic eruptions (10 km), and a wind speed typical for NW Europe (10 m s−1), to show that an ash cloud can transport particles up to 80 μm diameter up to 850 km in 24 h. Thus, even moderately sized Icelandic eruptions can be expected to deposit cryptotephra on mainland Europe. Using simulated satellite infrared data for dispersion-model-derived ash clouds, we demonstrate a systematic bias towards small grain sizes in retrievals of volcanic ash clouds that contain large proportions of cryptotephra-sized grains. As the median radius of the simulated PSD increases, fewer ash-containing pixels are correctly identified. Where retrievals are made of simulated clouds with mass median radii larger than ~ 10 μm, the mean retrieved reff plateaus at around 9 μm. Assuming Mie scattering by dense spheres when interpreting satellite infrared brightness temperature difference (BTD) data puts an upper limit on retrieved particle sizes. If larger, irregularly shaped ash grains can also produce a BTD effect, this will result in further underestimation of grain size, e.g. in coarse ash clouds close to a volcano.

Recent eruptions in Iceland and Chile have demonstrated that volcanic ash problems persist long after an eruption. For this reason, ash dispersion models are being extended to include ash remobilization. Critical to these models is knowledge of the ash source and the particle sizes that can be mobilized under different wind and moisture conditions. Here we characterize the physical and chemical characteristics of ash deposited on new snow in Reykjavik, Iceland, following a blizzard on 6 March 2013. Morphological, textural, and compositional analyses indicate resuspension from multiple eruptive deposits, including both Grimsvotn (2011) and Eyjafjallajokull (2010) eruptions. Grain size measurements show a mode of 32–63 µm, with particles as large as 177 µm; there is little mass in the very fine fraction, ≤10 µm (PM10). We compare our observations to predictions using the Lagrangian particle dispersion model, NAME (UK Met Office). The model output is consistent with observations in that it forecasts resuspension from both Eyjafjallajokull and Grimsvotn source regions, and shows ash deposition coincident with the timing of observed deposition in Reykjavik. The modeled deposit in Reykjavik predicts, however, a substantially lower proportion of Grimsvotn ash than observed. This discrepancy has highlighted the need to reassess the assumptions used in the simulations, particularly regarding the source area and precipitation thresholds. Furthermore, we suggest that modification of ash deposits in the form of erosion, redeposition, compaction, or cementation may influence the dynamics of resuspension over time, thus influencing the ability of model simulations to accurately forecast remobilization events.

On 16–17 September 2013 strong surface winds over tephra deposits in southern Iceland led to the resuspension and subsequent advection of significant quantities of volcanic ash. The resulting resuspended ash cloud was transported to the south-east over the North Atlantic Ocean and, due to clear skies at the time, was exceptionally well observed in satellite imagery. We use satellite-based measurements in combination with radiative transfer and dispersion modelling to quantify the total mass of ash resuspended during this event. Typically ash clouds from explosive eruptions are identified in satellite measurements from a negative brightness temperature difference (BTD) signal; however this technique assumes that the ash resides at high levels in the atmosphere. Due to a temperature inversion in the troposphere over southern Iceland during 16 September 2013, the resuspended ash cloud was constrained to altitudes of

We present an experimental study of a buoyancy-driven, low-Reynolds-number (Re < 1) exchange flow of two Newtonian fluids in a vertical cylindrical pipe (length 1 m and diameter 38.4 mm) connecting two fluid reservoirs. The denser, more viscous fluid was golden syrup and the less dense, less viscous fluid was a golden syrup–water solution; the ratio of the viscosities of the two fluids (β) ranged from 2 to 1180. Flows were initiated by removing a bung in the base of the upper reservoir or sliding out a gate positioned at the top, middle or bottom of the pipe. We observe the flows over long time durations (up to 356 h), and define the development of the flow with reference to a non-dimensional time (τ). The initial transient development of the flow was dependent on which of the two fluids initially filled the pipe, but this did not systematically affect the flow regime observed at τ ≫ 1. Two distinct flow regimes were observed: axisymmetric core-annular flow (CAF), in which the less viscous fluid occupies a cylindrical core and the denser fluid flows downwards in an annulus, and side-by-side (SBS) flow where both fluids are in contact with the pipe and there is a single interface between them. CAF formed at β ≥ 75 and SBS flow at β ≤ 117. In several experiments, for 5 ≤ β ≤ 59, a slowly developing transitional SBS (TSBS) flow was observed where SBS flow and CAF occurred simultaneously with SBS in the lower portion of the pipe; SBS existed throughout most of the pipe and in one case grew with time to entirely fill the pipe. Velocity profiles determined by tracking tracer particles show that the observed CAFs are adequately described by the formulation of Huppert & Hallworth (J. Fluid Mech., vol. 578, 2007, pp. 95–112). Experimental SBS velocity profiles are not well produced by the formulation of Kerswell (J. Fluid Mech., 10.1017/jfm.2011.190), possibly because the latter is restricted to flows whose cross-section has an interface of constant curvature. Despite the variations in flow regime, volume fluxes can be described by a power-law function of β, Q1 = 0.059 β−0.74. A comparison of experimental data with the theoretical approaches of Huppert Hallworth (2007) and Kerswell (2011) indicates that fluids are not arranged in the regime that maximises volume flux (e.g. SBS or CAF), nor do they adopt the geometry that maximises volume flux within that particular regime.

There is a large discrepancy between the size of volcanic ash particles measured from deposits on the ground (known as cryptotephra; 20–125 μm in length) and those reported by satellite remote sensing (effective radii of 0.5–9 μm; 95% of particles < 17 μm diameter). We use results from the fields of tephrochronology (a dating technique based on volcanic ash layers), dispersion modelling and satellite remote sensing in an attempt to understand from where it arises. We show that Icelandic cryptotephras deposited in NW Europe have lognormal particle size distributions (PSDs) with median lengths of 20–70 μm (geometric standard deviation: 1.40–1.66; 95th percentile length: 42–126 microns). This is consistent with semi-quantitative grainsize range estimates from the literature. Using measured fall velocities of ash particles, a release height typical of moderate Icelandic eruptions (10 km) and a wind speed typical for NW Europe (10 m s−1), we find that an ash cloud can transport particles < 80 μm diameter up to 850 km in 24 h, so that even moderately sized Icelandic eruptions can deposit cryptotephra on mainland Europe. The proportion of cryptotephra in airborne clouds is unknown. We used simulated satellite data of dispersion-model-derived ash clouds to investigate the effect of PSD on satellite retrievals and show that as the median radius of the input PSD increases, fewer ash-containing pixels are correctly identified. Where retrievals are made of simulated clouds with mass median radii larger than ~ 10 μm, the mean retrieved reff plateaus at around 9 μm. This is a systematic bias in the retrieval algorithm that would cause the grainsize of distal clouds containing significant cryptotephra to be underestimated. This cannot explain discrepancies in coarser proximal clouds, however, which may be because the complex physics of scattering by highly irregularly-shaped grains is inadequately represented by assuming that particles are dense spheres.

This study examines the sensitivity of atmospheric dispersion model forecasts of volcanic ash clouds to the physical characteristics assigned to the particles. We show that the particle size distribution (PSD) used to initialise a dispersion model has a significant impact on the forecast of the mass loading of the ash particles in the atmosphere. This is because the modeled fall velocity of the particles is sensitive to the particle diameter. Forecasts of the long-range transport of the ash cloud consider particles with diameters between 0.1 μm and 100 μm. The fall velocity of particles with diameter 100 μm is over 5 orders of magnitude greater than a particle with diameter 0.1 μm, and 30 μm particles fall 88% slower and travel up to 5× further than a 100 μm particle. Identifying the PSD of the ash cloud at the source, which is required to initialise a model, is difficult. Further, aggregation processes are currently not explicitly modeled in operational dispersion models due to the high computational costs associated with aggregation schemes. We show that using a modified total grain size distribution (TGSD) that effectively accounts for aggregation processes improves the modeled PSD of the ash cloud and deposits from the eruption of Eyjafjallajokull in 2010. Knowledge of the TGSD of an eruption is therefore critical for reducing uncertainty in quantitative forecasts of ash cloud dispersion. The density and shape assigned to the model particles have a lesser but still significant impact on the calculated fall velocity. Accounting for the density distribution and sphericity of ash from the eruption of Eyjafjallajokull in 2010, modeled particles can travel up to 84% further than particles with default particle characteristics that assume the particles are spherical and have a fixed density.

It has been 10 years since the ash cloud from the eruption of Eyjafjallaj&ouml, kull 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.