Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters
Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determinin...
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ftdoajarticles:oai:doaj.org/article:2ad5f4b1b73c4ad4a0ddc3f425f8b45a 2023-05-15T16:09:39+02:00 Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters N. J. Harvey N. Huntley H. F. Dacre M. Goldstein D. Thomson H. Webster 2018-01-01T00:00:00Z https://doi.org/10.5194/nhess-18-41-2018 https://doaj.org/article/2ad5f4b1b73c4ad4a0ddc3f425f8b45a EN eng Copernicus Publications https://www.nat-hazards-earth-syst-sci.net/18/41/2018/nhess-18-41-2018.pdf https://doaj.org/toc/1561-8633 https://doaj.org/toc/1684-9981 doi:10.5194/nhess-18-41-2018 1561-8633 1684-9981 https://doaj.org/article/2ad5f4b1b73c4ad4a0ddc3f425f8b45a Natural Hazards and Earth System Sciences, Vol 18, Pp 41-63 (2018) Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 Geology QE1-996.5 article 2018 ftdoajarticles https://doi.org/10.5194/nhess-18-41-2018 2022-12-31T10:31:12Z Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME) to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations for a small operational ensemble of simulations. The use of an emulator ... Article in Journal/Newspaper Eyjafjallajökull Directory of Open Access Journals: DOAJ Articles Natural Hazards and Earth System Sciences 18 1 41 63 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 Geology QE1-996.5 |
spellingShingle |
Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 Geology QE1-996.5 N. J. Harvey N. Huntley H. F. Dacre M. Goldstein D. Thomson H. Webster Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters |
topic_facet |
Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 Geology QE1-996.5 |
description |
Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME) to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations for a small operational ensemble of simulations. The use of an emulator ... |
format |
Article in Journal/Newspaper |
author |
N. J. Harvey N. Huntley H. F. Dacre M. Goldstein D. Thomson H. Webster |
author_facet |
N. J. Harvey N. Huntley H. F. Dacre M. Goldstein D. Thomson H. Webster |
author_sort |
N. J. Harvey |
title |
Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters |
title_short |
Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters |
title_full |
Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters |
title_fullStr |
Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters |
title_full_unstemmed |
Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters |
title_sort |
multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters |
publisher |
Copernicus Publications |
publishDate |
2018 |
url |
https://doi.org/10.5194/nhess-18-41-2018 https://doaj.org/article/2ad5f4b1b73c4ad4a0ddc3f425f8b45a |
genre |
Eyjafjallajökull |
genre_facet |
Eyjafjallajökull |
op_source |
Natural Hazards and Earth System Sciences, Vol 18, Pp 41-63 (2018) |
op_relation |
https://www.nat-hazards-earth-syst-sci.net/18/41/2018/nhess-18-41-2018.pdf https://doaj.org/toc/1561-8633 https://doaj.org/toc/1684-9981 doi:10.5194/nhess-18-41-2018 1561-8633 1684-9981 https://doaj.org/article/2ad5f4b1b73c4ad4a0ddc3f425f8b45a |
op_doi |
https://doi.org/10.5194/nhess-18-41-2018 |
container_title |
Natural Hazards and Earth System Sciences |
container_volume |
18 |
container_issue |
1 |
container_start_page |
41 |
op_container_end_page |
63 |
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1766405508352180224 |