Particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0
A particle-filter-based inversion system is presented, which enables us to derive time- and altitude-resolved volcanic ash emission fluxes along with its uncertainty. The system assimilates observations of volcanic ash column mass loading as retrieved from geostationary satellites. It aims to estima...
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ftdoajarticles:oai:doaj.org/article:ca57df5fe0b74da188f2af8f7ec8f3c8 2023-05-15T16:09:32+02:00 Particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0 P. Franke A. C. Lange H. Elbern 2022-02-01T00:00:00Z https://doi.org/10.5194/gmd-15-1037-2022 https://doaj.org/article/ca57df5fe0b74da188f2af8f7ec8f3c8 EN eng Copernicus Publications https://gmd.copernicus.org/articles/15/1037/2022/gmd-15-1037-2022.pdf https://doaj.org/toc/1991-959X https://doaj.org/toc/1991-9603 doi:10.5194/gmd-15-1037-2022 1991-959X 1991-9603 https://doaj.org/article/ca57df5fe0b74da188f2af8f7ec8f3c8 Geoscientific Model Development, Vol 15, Pp 1037-1060 (2022) Geology QE1-996.5 article 2022 ftdoajarticles https://doi.org/10.5194/gmd-15-1037-2022 2022-12-31T16:26:54Z A particle-filter-based inversion system is presented, which enables us to derive time- and altitude-resolved volcanic ash emission fluxes along with its uncertainty. The system assimilates observations of volcanic ash column mass loading as retrieved from geostationary satellites. It aims to estimate the temporally varying emission profile endowed with error margins. In addition, we analyze the dependency of our estimate on wind field characteristics, notably vertical shear, within variable observation intervals. Thus, the proposed system addresses the special challenge of analyzing the vertical profile of volcanic ash clouds given only 2D high temporal-resolution column mass loading data as retrieved by geostationary satellites. The underlying method rests on a linear combination of height–time emission finite elements of arbitrary resolution, each of which is assigned to a model run subject to ensemble-based space–time source inversion. Employing a modular concept, this setup builds the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem). It comprises a particle smoother in combination with a discrete-grid ensemble extension of the Nelder–Mead minimization method. The ensemble version of the EURopean Air pollution Dispersion – Inverse Model (EURAD-IM) is integrated into ESIAS-chem but can be replaced by other models. As initial validation of ESIAS-chem, the system is applied to simulated artificial observations of both ash-contaminated and ash-free atmospheric columns using identical-twin experiments. Thus, in this idealized initial performance test the underlying meteorological uncertainty is neglected. The inversion system is applied to two notional sub-Plinian eruptions of the Eyjafjallajökull volcano, Iceland, with strong ash emission changes with time and injection heights. It demonstrates the ability of ESIAS-chem to retrieve the volcanic ash emission fluxes from the assimilation of column mass loading data only. However, the analyzed emission profiles strongly differ in their ... Article in Journal/Newspaper Eyjafjallajökull Iceland Directory of Open Access Journals: DOAJ Articles Geoscientific Model Development 15 3 1037 1060 |
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Geology QE1-996.5 |
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Geology QE1-996.5 P. Franke A. C. Lange H. Elbern Particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0 |
topic_facet |
Geology QE1-996.5 |
description |
A particle-filter-based inversion system is presented, which enables us to derive time- and altitude-resolved volcanic ash emission fluxes along with its uncertainty. The system assimilates observations of volcanic ash column mass loading as retrieved from geostationary satellites. It aims to estimate the temporally varying emission profile endowed with error margins. In addition, we analyze the dependency of our estimate on wind field characteristics, notably vertical shear, within variable observation intervals. Thus, the proposed system addresses the special challenge of analyzing the vertical profile of volcanic ash clouds given only 2D high temporal-resolution column mass loading data as retrieved by geostationary satellites. The underlying method rests on a linear combination of height–time emission finite elements of arbitrary resolution, each of which is assigned to a model run subject to ensemble-based space–time source inversion. Employing a modular concept, this setup builds the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem). It comprises a particle smoother in combination with a discrete-grid ensemble extension of the Nelder–Mead minimization method. The ensemble version of the EURopean Air pollution Dispersion – Inverse Model (EURAD-IM) is integrated into ESIAS-chem but can be replaced by other models. As initial validation of ESIAS-chem, the system is applied to simulated artificial observations of both ash-contaminated and ash-free atmospheric columns using identical-twin experiments. Thus, in this idealized initial performance test the underlying meteorological uncertainty is neglected. The inversion system is applied to two notional sub-Plinian eruptions of the Eyjafjallajökull volcano, Iceland, with strong ash emission changes with time and injection heights. It demonstrates the ability of ESIAS-chem to retrieve the volcanic ash emission fluxes from the assimilation of column mass loading data only. However, the analyzed emission profiles strongly differ in their ... |
format |
Article in Journal/Newspaper |
author |
P. Franke A. C. Lange H. Elbern |
author_facet |
P. Franke A. C. Lange H. Elbern |
author_sort |
P. Franke |
title |
Particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0 |
title_short |
Particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0 |
title_full |
Particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0 |
title_fullStr |
Particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0 |
title_full_unstemmed |
Particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0 |
title_sort |
particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-plinian eyjafjallajökull eruption using the ensemble for stochastic integration of atmospheric simulations (esias-chem) version 1.0 |
publisher |
Copernicus Publications |
publishDate |
2022 |
url |
https://doi.org/10.5194/gmd-15-1037-2022 https://doaj.org/article/ca57df5fe0b74da188f2af8f7ec8f3c8 |
genre |
Eyjafjallajökull Iceland |
genre_facet |
Eyjafjallajökull Iceland |
op_source |
Geoscientific Model Development, Vol 15, Pp 1037-1060 (2022) |
op_relation |
https://gmd.copernicus.org/articles/15/1037/2022/gmd-15-1037-2022.pdf https://doaj.org/toc/1991-959X https://doaj.org/toc/1991-9603 doi:10.5194/gmd-15-1037-2022 1991-959X 1991-9603 https://doaj.org/article/ca57df5fe0b74da188f2af8f7ec8f3c8 |
op_doi |
https://doi.org/10.5194/gmd-15-1037-2022 |
container_title |
Geoscientific Model Development |
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15 |
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3 |
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1037 |
op_container_end_page |
1060 |
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