Volcanic plumes and wind: Jetstream interaction examples and implications for air traffic

Bursik, Marcus; Kobs, S.; Burns, Annika; Braitseva, O A; Bazanova, L. I.; Мелекесцев, И. В.; Kurbatov, Andrei V.; Pieri, David C.

doi:10.1016/j.jvolgeores.2009.01.021

Cited by 35 publications

(24 citation statements)

References 11 publications

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“…In particular, as the plume decelerates as it nears the level of neutral buoyancy, the wind field will inevitably cause a bending over of the plume trajectory as the maximum altitude is approached (Figure ). Furthermore, it is not appropriate to represent the wind profile as a linear shear throughout the atmosphere, and for larger eruptions, with plumes that ascend above the troposphere, there may be interaction with jet streams where the wind speed is locally high [ Bursik , ; Bursik et al ., ]. While any profile of the wind could be used, for small and moderately sized eruptions that do not rise significantly above the troposphere and where the wind field can be taken to increase linearly with altitude, the parameter

W_{s}

is appropriate to assess the strength of the wind.…”

Section: Integral Model Of Dry Volcanic Eruption Columns In a Crosswindmentioning

confidence: 99%

“…There is a degree of scatter in the data, some of which could be attributed to varying atmospheric conditions, for example, the variation in atmospheric lapse rates and altitude of atmospheric layers with latitude, which are known to influence rise heights of volcanic plumes [Woods, 1995;Sparks et al, 1997]. In addition, by adopting the wind speed at a single altitude to characterize the atmospheric wind conditions, we are unable to describe atmospheric wind structures, such as jet streams, which may have a significant influence on the ascent of the plume [Bursik, 2001;Bursik et al, 2009]. However, despite these limitations, we find that the dataset records a systematic dependence of volcanic plume height on atmospheric wind speed for a given source mass flux (Figure 3).…”

Section: Comparison Of Model Predictions To Observationsmentioning

confidence: 99%

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Interaction between volcanic plumes and wind during the 2010 Eyjafjallajökull eruption, Iceland

et al. 2013

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[1] Estimates of volcanic source mass flux, currently deduced from observations of plume height, are crucial for ash dispersion models for aviation and population hazard. This study addresses the role of the atmospheric wind in determining the height at which volcanic plumes spread in the atmosphere and the relationship between source mass flux and plume height in a wind field. We present a predictive model of volcanic plumes that describes the bending over of the plume trajectory in a crosswind and show that model predictions are in accord with a dataset of historic eruptions if the profile of atmospheric wind shear is described. The wind restricts the rise height of volcanic plumes such that obtaining equivalent rise heights for a plume in a windy environment would require an order of magnitude increase in the source mass flux over a plume in a quiescent environment. Our model calculations are used to calibrate a semi-empirical relationship between the plume height and the source mass flux that explicitly includes the atmospheric wind speed. We demonstrate that the model can account for the variations in plume height observed during the first explosive phase of the 2010 Eyjafjallajökull eruption using independently measured wind speeds and show that changes in the observed plume height are better explained by changing meteorology than abrupt changes in the source mass flux. This study shows that unless the wind is properly accounted for, estimates of the source mass flux during an explosive eruption are likely to be very significant underpredictions of the volcanic source conditions.

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W_{s}

is appropriate to assess the strength of the wind.…”

Section: Integral Model Of Dry Volcanic Eruption Columns In a Crosswindmentioning

confidence: 99%

Section: Comparison Of Model Predictions To Observationsmentioning

confidence: 99%

Interaction between volcanic plumes and wind during the 2010 Eyjafjallajökull eruption, Iceland

et al. 2013

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“…The use of source parameters and representative atmospheric parameters means that these algebraic relationship do not capture the complexity of behaviour found when solving the system of differential equations. For examples, the effects of different stratification in the troposphere and stratosphere (Woods, 1988;Glaze and Baloga, 1996), change of phase of water vapour (Woods, 1993;Glaze et al, 1997;Woodhouse et al, 2013), and local variations in the wind speed with height (Bursik, 2001;Bursik et al, 2009), cannot be explored with the algebraic relationships. Nonetheless, they do provide insight into the sensitivity of the plume height to variations in source conditions.…”

Section: Discussionmentioning

confidence: 99%

A global sensitivity analysis of the PlumeRise model of volcanic plumes

Woodhouse

Hogg

Phillips

2016

Journal of Volcanology and Geothermal Research

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Integral models of volcanic plumes allow predictions of plume dynamics to be made and the rapid estimation of volcanic source conditions from observations of the plume height by model inversion. Here we introduce PlumeRise, an integral model of volcanic plumes that incorporates a description of the state of the atmosphere, includes the effects of wind and the phase change of water, and has been developed as a freely available web-based tool. The model can be used to estimate the height of a volcanic plume when the source conditions are specified, or to infer the strength of the source from an observed plume height through a model inversion. The predictions of the volcanic plume dynamics produced by the model are analysed in four case studies in which the atmospheric conditions and the strength of the source are varied. A global sensitivity analysis of the model to a selection of model inputs is performed and the results are analysed using parallel coordinate plots for visualisation and variance-based sensitivity indices to quantify the sensitivity of model outputs. We find that if the atmospheric conditions do not vary widely then there is a small set of model inputs that strongly influence the model predictions. When estimating the height of the plume, the source mass flux has a controlling influence on the model prediction, while variations in the plume height strongly effect the inferred value of the source mass flux when performing inversion studies. The values taken for the entrainment coefficients have a particularly important effect on the quantitative predictions. The dependencies of the model outputs to variations in the inputs are discussed and compared to simple algebraic expressions that relate source conditions to the height of the plume.

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“…conditions as given by atmospheric sounding or NWP data. It has been tested against plume rise height data, and against dispersal data [10]. Details of the volcanic source parameters along with assumptions and probability distributions used are presented in [9,28].…”

Section: Introductionmentioning

confidence: 99%

Forecasting Volcanic Plume Hazards With Fast UQ

Stefanescu

Patra

Bursik

et al. 2015

Procedia Computer Science

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This paper introduces a numerically-stable multiscale scheme to efficiently generate probabilistic hazard maps for volcanic ash transport using models of transport, dispersion and wind. The scheme relies on graph-based algorithms and low-rank approximations of the adjacency matrix of the graph. This procedure involves representing both the parameter space and physical space by a weighted graph. A combination of clustering and low rank approximation is then used to create a good approximation of the original graph. By performing a multiscale data sampling, a well-conditioned basis of a low rank Gaussian kernel matrix, is identified and used for out-of-sample extensions used in generating the hazard maps.

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Volcanic plumes and wind: Jetstream interaction examples and implications for air traffic

Cited by 35 publications

References 11 publications

Interaction between volcanic plumes and wind during the 2010 Eyjafjallajökull eruption, Iceland

Interaction between volcanic plumes and wind during the 2010 Eyjafjallajökull eruption, Iceland

A global sensitivity analysis of the PlumeRise model of volcanic plumes

Forecasting Volcanic Plume Hazards With Fast UQ

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