Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling

Probabilistic forecasting of volcanic ash dispersion involves simulating an ensemble of realistic event scenarios to estimate the probability of a particular hazard threshold being exceeded. Although the number of samples that make up the ensemble, how they are chosen, and the desired threshold all...

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Published in:Bulletin of Volcanology
Main Authors: Phillips, Jeremy C, Williams, Shannon L, Lee, Anthony W L, Jenkins, Susanna
Format: Article in Journal/Newspaper
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/1983/9a5e3845-c6e6-4e44-ab52-9971753a507d
https://research-information.bris.ac.uk/en/publications/9a5e3845-c6e6-4e44-ab52-9971753a507d
https://doi.org/10.1007/s00445-023-01664-x
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spelling ftubristolcris:oai:research-information.bris.ac.uk:publications/9a5e3845-c6e6-4e44-ab52-9971753a507d 2024-02-11T10:05:12+01:00 Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling Phillips, Jeremy C Williams, Shannon L Lee, Anthony W L Jenkins, Susanna 2023-10-31 https://hdl.handle.net/1983/9a5e3845-c6e6-4e44-ab52-9971753a507d https://research-information.bris.ac.uk/en/publications/9a5e3845-c6e6-4e44-ab52-9971753a507d https://doi.org/10.1007/s00445-023-01664-x eng eng info:eu-repo/semantics/openAccess Phillips , J C , Williams , S L , Lee , A W L & Jenkins , S 2023 , ' Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling ' , Bulletin of Volcanology , vol. 85 , no. 11 , 68 . https://doi.org/10.1007/s00445-023-01664-x article 2023 ftubristolcris https://doi.org/10.1007/s00445-023-01664-x 2024-01-18T23:32:49Z Probabilistic forecasting of volcanic ash dispersion involves simulating an ensemble of realistic event scenarios to estimate the probability of a particular hazard threshold being exceeded. Although the number of samples that make up the ensemble, how they are chosen, and the desired threshold all set the uncertainty of (or confidence in) the estimated exceedance probability, current practice does not quantify and communicate the uncertainty in ensemble predictions. In this study, we use standard statistical methods to estimate the variance in probabilistic ensembles and use this measure of uncertainty to assess different sampling strategies for the wind field, using the example of volcanic ash transport from a representative explosive eruption in Iceland. For stochastic (random) sampling of the wind field, we show how the variance is reduced with increasing ensemble size and how the variance depends on the desired hazard threshold and the proximity of a target site to the volcanic source. We demonstrate how estimated variances can be used to compare different ensemble designs, by comparing stochastic forecasts with forecasts obtained from a stratified sampling approach using a set of 29 Northern European weather regimes, known as Grosswetterlagen (GWL). Sampling wind fields from within the GWL regimes reduces the number of samples needed to achieve the same variance as compared to conventional stochastic sampling. Our results show that uncertainty in volcanic ash dispersion forecasts can be straightforwardly calculated and communicated, and highlight the need for the volcanic ash forecasting community and operational end-users to jointly choose acceptable levels of variance for ash forecasts in the future. Article in Journal/Newspaper Iceland University of Bristol: Bristol Research Bulletin of Volcanology 85 11
institution Open Polar
collection University of Bristol: Bristol Research
op_collection_id ftubristolcris
language English
description Probabilistic forecasting of volcanic ash dispersion involves simulating an ensemble of realistic event scenarios to estimate the probability of a particular hazard threshold being exceeded. Although the number of samples that make up the ensemble, how they are chosen, and the desired threshold all set the uncertainty of (or confidence in) the estimated exceedance probability, current practice does not quantify and communicate the uncertainty in ensemble predictions. In this study, we use standard statistical methods to estimate the variance in probabilistic ensembles and use this measure of uncertainty to assess different sampling strategies for the wind field, using the example of volcanic ash transport from a representative explosive eruption in Iceland. For stochastic (random) sampling of the wind field, we show how the variance is reduced with increasing ensemble size and how the variance depends on the desired hazard threshold and the proximity of a target site to the volcanic source. We demonstrate how estimated variances can be used to compare different ensemble designs, by comparing stochastic forecasts with forecasts obtained from a stratified sampling approach using a set of 29 Northern European weather regimes, known as Grosswetterlagen (GWL). Sampling wind fields from within the GWL regimes reduces the number of samples needed to achieve the same variance as compared to conventional stochastic sampling. Our results show that uncertainty in volcanic ash dispersion forecasts can be straightforwardly calculated and communicated, and highlight the need for the volcanic ash forecasting community and operational end-users to jointly choose acceptable levels of variance for ash forecasts in the future.
format Article in Journal/Newspaper
author Phillips, Jeremy C
Williams, Shannon L
Lee, Anthony W L
Jenkins, Susanna
spellingShingle Phillips, Jeremy C
Williams, Shannon L
Lee, Anthony W L
Jenkins, Susanna
Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling
author_facet Phillips, Jeremy C
Williams, Shannon L
Lee, Anthony W L
Jenkins, Susanna
author_sort Phillips, Jeremy C
title Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling
title_short Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling
title_full Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling
title_fullStr Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling
title_full_unstemmed Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling
title_sort quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling
publishDate 2023
url https://hdl.handle.net/1983/9a5e3845-c6e6-4e44-ab52-9971753a507d
https://research-information.bris.ac.uk/en/publications/9a5e3845-c6e6-4e44-ab52-9971753a507d
https://doi.org/10.1007/s00445-023-01664-x
genre Iceland
genre_facet Iceland
op_source Phillips , J C , Williams , S L , Lee , A W L & Jenkins , S 2023 , ' Quantifying uncertainty in probabilistic volcanic ash hazard forecasts, with an application to weather pattern based wind field sampling ' , Bulletin of Volcanology , vol. 85 , no. 11 , 68 . https://doi.org/10.1007/s00445-023-01664-x
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1007/s00445-023-01664-x
container_title Bulletin of Volcanology
container_volume 85
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