Operational prediction of ash concentrations in the distal volcanic cloud from the 2010 Eyjafjallajökull eruption

Webster, Helen; Thomson, David J.; Johnson, Ben; Heard, Imogen P C; Turnbull, K.; Marenco, Franco; Kristiansen, Nina Iren; Dorsey, J. R.; Minikin, Andreas; Weinzierl, Bernadett; Schumann, U.; Sparks, R. S. J.; Loughlin, S. C.; Hort, Matthew C.; Leadbetter, Susan; Devenish, B. J.; Manning, Alistair J.; Witham, Claire; Haywood, Jim M.; Golding, Brian

doi:10.1029/2011jd016790

Cited by 128 publications

(157 citation statements)

References 42 publications

(88 reference statements)

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“…However, there are significant uncertainties in the detection of volcanic ash [3]. Moreover, even when ash is successfully detected, there are still significant challenges in estimating ash properties such as altitude and column loadings [4]. In view of these challenges, it is crucial to integrate the dispersion model simulations with satellite retrievals in order to gain a more coherent picture of the transport of ash.…”

Section: Introductionmentioning

confidence: 99%

A probabilistic inverse method for volcanic ash dispersion modelling

Zidikheri

Potts

2016

ANZIAMJ

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We present a new inverse modelling approach for integrating satellite detections of volcanic ash with dispersion models. We demonstrate the utility of this approach in estimating the ash column height in the February 2014 eruption of Mount Kelut in Java, Indonesia. We show that the inferred height is consistent with estimates obtained by other remote sensing techniques. This method may be used to obtain estimates of model parameters such as ash column height in cases where no such information is available or is subject to significant uncertainty.

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Section: Introductionmentioning

confidence: 99%

A probabilistic inverse method for volcanic ash dispersion modelling

Zidikheri

Potts

2016

ANZIAMJ

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“…Eruption Source Parameters may include vent location, plume height, eruption duration or start/stop time, mass eruption rate, particle size distribution, vertical distribution of mass with height above the vent and distal fine ash fraction (Mastin et al 2009). Uncertainty in any of the various source parameters can result in large errors in the resultant volcanic ash cloud forecasts (Webster et al 2012). Sensitivity analysis can identify the most critical parameters and demonstrate the range of outcomes under different conditions of uncertainty.…”

Section: Ash-cloud Detection and Forecastsmentioning

confidence: 99%

“…Two-way discussions are essential between volcano observatories and aviation information providers about the observations and information needed during eruption, formats required, challenges and limitations, as well as an explanation as to how the information will be used and who will receive outputs. For example, the Icelandic Met Office (Iceland's volcano observatory) and the UK Met Office (through the London VAAC) have established a specific format co-designed to suit volcano observatory operating capacities, VAAC needs, and reflect joint experience (Webster et al 2012). The VONA is a good starting point for such discussions.…”

Section: Volcano Monitoringmentioning

confidence: 99%

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Volcanic Ash and Aviation—The Challenges of Real-Time, Global Communication of a Natural Hazard

Lechner¹,

Tupper

Guffanti

et al. 2017

Advances in Volcanology

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More than 30 years after the first major aircraft encounters with volcanic ash over Indonesia in 1982, it remains challenging to inform aircraft in flight of the exact location of potentially dangerous ash clouds on their flight path, particularly shortly after the eruption has occurred. The difficulties include reliably forecasting and detecting the onset of significant explosive eruptions on a global basis, observing the dispersal of eruption clouds in real time, capturing their complex structure and constituents in atmospheric transport models, describing these observations and modelling results in a manner suitable for aviation users, delivering timely warning messages to the cockpit, flight planners and air traffic management systems, and the need for scientific development in order to undertake operational enhancements. The framework under which these issues are managed is the International Airways Volcano Watch responsible for observing, analysing, forecasting and communicating the aviation hazard (airborne ash), using agreed techniques and messages in defined formats. Continuous improvement of the IAVW framework is overseen by expert groups representing the operators of the system, the user community, and the science community. The IAVW represents a unique marriage of two scientific disciplines, volcanology and meteorology, with the aviation user community. There have been many multifaceted volcanic eruptions in complex meteorological conditions during the history of the IAVW. Each new eruption brings new insights into how the warning system can be improved, and each reinforces the lessons that have gone before. The management of these events has improved greatly since the major ash encounters in the 1980s, but discontinuities in the warning and communications system still occur. A good example is a 2014 ash encounter over Indonesia following the eruption of Kelut where the warnings did not reach the aircraft crew. Other events present enormous management challenges-for example the 2010 Eyjafjallajökull eruption in Iceland was, overall, less hazardous than many less publicised eruptions, but numerous small to moderate explosions over several weeks produced widespread disruption and a large economic impact. At the time of writing, while there has been hundreds of millions of US dollars in damage to aircraft from encounters with ash, there have been no fatalities resulting from aviation incidents in, or proximal to volcanic ash cloud. This reflects, at least in part, the hard work done in putting together a global warning system-although to some extent it also reflects a measure of good statistical fortune. In order to minimise the risk of aircraft encounters with volcanic ash clouds, the global effort continues. The future priorities for the IAVW are strongly focused on enhancing communication before, and at the very onset of a volcanic ash-producing event (typically the more dangerous stage), together with improved downstream information and warning systems to help reduce the economic impact of e...

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“…to update the source term whenever the eruption conditions vary, for inverse modeling of ash emissions (e.g. Marti et al, 2016;Webster et al, 2012), or to perform an ensemble forecast (e.g. Galmarini et al, Atmos.…”

Section: Introductionmentioning

confidence: 99%

Volcanic ash modeling with the NMMB-MONARCH-ASH model: quantification of off-line modeling errors

Marti¹,

Folch²

2017

Preprint

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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, 10 aviation, and climate. The efficiency of response and mitigation actions is directly associated to the accuracy of the volcanic ash cloud detection and modeling systems. Operational forecasts build on offline coupled modeling systems where 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 to the off-line modeling systems has 15 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 off-line coupling strategy are compared against those from an on-line 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 20 of European (2010 Eyjafjallajökull) and South-American (2011 Cordón Caulle) volcanic eruptions. Evaluation scores indicate that systematic errors credited by off-line modeling are of the same order of magnitude as those associated to the source term uncertainties. In particular, traditional off-line 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 on-line forecast. These 25 inconsistencies are anticipated to be even more relevant in scenarios where 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 on-line dispersal models. 30Atmos. Chem. Phys. Discuss.,

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Operational prediction of ash concentrations in the distal volcanic cloud from the 2010 Eyjafjallajökull eruption

Cited by 128 publications

References 42 publications

A probabilistic inverse method for volcanic ash dispersion modelling

A probabilistic inverse method for volcanic ash dispersion modelling

Volcanic Ash and Aviation—The Challenges of Real-Time, Global Communication of a Natural Hazard

Volcanic ash modeling with the NMMB-MONARCH-ASH model: quantification of off-line modeling errors

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