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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Published in:Geoscientific Model Development
Main Authors: Franke, Philipp, Lange, Anne Caroline, Elbern, Hendrik
Format: Text
Language:English
Published: 2022
Subjects:
Online Access:https://doi.org/10.5194/gmd-15-1037-2022
https://gmd.copernicus.org/articles/15/1037/2022/
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spelling ftcopernicus:oai:publications.copernicus.org:gmd92759 2023-05-15T16:09:36+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 Franke, Philipp Lange, Anne Caroline Elbern, Hendrik 2022-02-03 application/pdf https://doi.org/10.5194/gmd-15-1037-2022 https://gmd.copernicus.org/articles/15/1037/2022/ eng eng doi:10.5194/gmd-15-1037-2022 https://gmd.copernicus.org/articles/15/1037/2022/ eISSN: 1991-9603 Text 2022 ftcopernicus https://doi.org/10.5194/gmd-15-1037-2022 2022-02-07T17:22:16Z 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 levels of accuracy depending of the strength of wind shear conditions. While the error is only 10 % –20 % for the estimated emission fluxes under strong wind conditions, it increases up to 60 % under weak wind shear conditions. In case of increasing wind shear, the performance of the analysis may benefit from extending the assimilation window, in which new observations potentially contribute valuable information to the analysis system. For our test cases using an artificial volcanic eruption, we found an assimilation window length of 18 h, i.e., 10 h after the eruption terminated, to be sufficient for analyzing the extent and location of the artificial ash cloud. In the performed test cases, the analysis ensemble predicts the location of high volcanic ash column mass loading in the atmosphere with a very high probability of > 95 % . Additionally, the analysis ensemble is able to provide a vertically resolved probability map of high volcanic ash concentrations to a high accuracy for both high and weak wind shear conditions. Text Eyjafjallajökull Iceland Copernicus Publications: E-Journals Geoscientific Model Development 15 3 1037 1060
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
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 levels of accuracy depending of the strength of wind shear conditions. While the error is only 10 % –20 % for the estimated emission fluxes under strong wind conditions, it increases up to 60 % under weak wind shear conditions. In case of increasing wind shear, the performance of the analysis may benefit from extending the assimilation window, in which new observations potentially contribute valuable information to the analysis system. For our test cases using an artificial volcanic eruption, we found an assimilation window length of 18 h, i.e., 10 h after the eruption terminated, to be sufficient for analyzing the extent and location of the artificial ash cloud. In the performed test cases, the analysis ensemble predicts the location of high volcanic ash column mass loading in the atmosphere with a very high probability of > 95 % . Additionally, the analysis ensemble is able to provide a vertically resolved probability map of high volcanic ash concentrations to a high accuracy for both high and weak wind shear conditions.
format Text
author Franke, Philipp
Lange, Anne Caroline
Elbern, Hendrik
spellingShingle Franke, Philipp
Lange, Anne Caroline
Elbern, Hendrik
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
author_facet Franke, Philipp
Lange, Anne Caroline
Elbern, Hendrik
author_sort Franke, Philipp
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
publishDate 2022
url https://doi.org/10.5194/gmd-15-1037-2022
https://gmd.copernicus.org/articles/15/1037/2022/
genre Eyjafjallajökull
Iceland
genre_facet Eyjafjallajökull
Iceland
op_source eISSN: 1991-9603
op_relation doi:10.5194/gmd-15-1037-2022
https://gmd.copernicus.org/articles/15/1037/2022/
op_doi https://doi.org/10.5194/gmd-15-1037-2022
container_title Geoscientific Model Development
container_volume 15
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