Uncertainty quantification and validation of data assimilation methods for an ice sheet model : application to a Greenland marine-terminated glacier, Upernavik Isstrøm
This thesis addresses the significant challenge of estimating future sea-level rise driven by ongoing polar ice sheet mass loss due to current climate change. The uncertainties surrounding this projection are substantial, with potential contributions ranging from 0.5 to over 1.5 meters by 2100. Thes...
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Format: | Doctoral or Postdoctoral Thesis |
Language: | French |
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2023
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ftunigrenoble:oai:HAL:tel-04658964v1 2024-09-15T18:07:46+00:00 Uncertainty quantification and validation of data assimilation methods for an ice sheet model : application to a Greenland marine-terminated glacier, Upernavik Isstrøm Quantification d'incertitudes et validation de méthodes d'assimilation de données pour un modèle de calotte polaire : application à un glacier à terminaison marine groenlandais Upernavik Isstrøm Jager, Eliot Institut des Géosciences de l’Environnement (IGE) Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ) Université Grenoble Alpes (UGA) Université Grenoble Alpes 2020-. Fabien Gillet-Chaulet Nicolas Champollion Jérémie Mouginot 2023-12-07 https://theses.hal.science/tel-04658964 https://theses.hal.science/tel-04658964/document https://theses.hal.science/tel-04658964/file/JAGER_2023_archivage.pdf fr fre HAL CCSD NNT: 2023GRALI107 tel-04658964 https://theses.hal.science/tel-04658964 https://theses.hal.science/tel-04658964/document https://theses.hal.science/tel-04658964/file/JAGER_2023_archivage.pdf info:eu-repo/semantics/OpenAccess https://theses.hal.science/tel-04658964 Géophysique [physics.geo-ph]. Université Grenoble Alpes [2020-.], 2023. Français. ⟨NNT : 2023GRALI107⟩ Ensemble method Ice sheet dynamics Modeling Calibration Uncertainty quantification Validation Dynamique glaciaire Modélisation Méthode d'ensemble Quantification d'incertitudes [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] info:eu-repo/semantics/doctoralThesis Theses 2023 ftunigrenoble 2024-07-29T23:39:57Z This thesis addresses the significant challenge of estimating future sea-level rise driven by ongoing polar ice sheet mass loss due to current climate change. The uncertainties surrounding this projection are substantial, with potential contributions ranging from 0.5 to over 1.5 meters by 2100. These uncertainties primarily stem from limited observations regarding the current state of polar ice sheet and their interactions with the atmosphere and ocean, known as forcings. However, the growing availability of satellite data presents new opportunities. This thesis pursues two primary objectives regarding their utilization: firstly, evaluating the ability of polar ice sheet models to replicate this data over several decades, and secondly, exploring methods to reduce uncertainties related to future sea-level rise.To address these challenges and refine our methods, we focused on Upernavik Isstrøm, a tidewater glacier, employing an ice sheet model (Elmer/Ice). We developed an initialisation method that accounts for model uncertainties (parameters, initial geometry, forcings) through an ensemble approach. This method enables a model calibrating a friction parameter using inverse methods to reproduce past observations of velocity and elevations changes. To achieve this, the friction parameterisation of the model must consider the subglacial hydrology effect. When the glacier front retreats, it brings more subglacial water upstream, lubricating the contact with the bedrock. Failing to account for this effect prevents the model from replicating observed acceleration. In the next step, we propagated the ensemble of members obtained at the end of the simulation into the future. This involved incorporating future forcing uncertainties, such as greenhouse gas emission scenarios, climate model uncertainties, and oceanic forcing uncertainties. We also developed a calibration approach to give more weight to model members that best replicated past observations while ensuring the model did not overfit, to see if this refines ... Doctoral or Postdoctoral Thesis glacier Greenland groenlandais Ice Sheet Tidewater Upernavik Université Grenoble Alpes: HAL |
institution |
Open Polar |
collection |
Université Grenoble Alpes: HAL |
op_collection_id |
ftunigrenoble |
language |
French |
topic |
Ensemble method Ice sheet dynamics Modeling Calibration Uncertainty quantification Validation Dynamique glaciaire Modélisation Méthode d'ensemble Quantification d'incertitudes [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] |
spellingShingle |
Ensemble method Ice sheet dynamics Modeling Calibration Uncertainty quantification Validation Dynamique glaciaire Modélisation Méthode d'ensemble Quantification d'incertitudes [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] Jager, Eliot Uncertainty quantification and validation of data assimilation methods for an ice sheet model : application to a Greenland marine-terminated glacier, Upernavik Isstrøm |
topic_facet |
Ensemble method Ice sheet dynamics Modeling Calibration Uncertainty quantification Validation Dynamique glaciaire Modélisation Méthode d'ensemble Quantification d'incertitudes [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] |
description |
This thesis addresses the significant challenge of estimating future sea-level rise driven by ongoing polar ice sheet mass loss due to current climate change. The uncertainties surrounding this projection are substantial, with potential contributions ranging from 0.5 to over 1.5 meters by 2100. These uncertainties primarily stem from limited observations regarding the current state of polar ice sheet and their interactions with the atmosphere and ocean, known as forcings. However, the growing availability of satellite data presents new opportunities. This thesis pursues two primary objectives regarding their utilization: firstly, evaluating the ability of polar ice sheet models to replicate this data over several decades, and secondly, exploring methods to reduce uncertainties related to future sea-level rise.To address these challenges and refine our methods, we focused on Upernavik Isstrøm, a tidewater glacier, employing an ice sheet model (Elmer/Ice). We developed an initialisation method that accounts for model uncertainties (parameters, initial geometry, forcings) through an ensemble approach. This method enables a model calibrating a friction parameter using inverse methods to reproduce past observations of velocity and elevations changes. To achieve this, the friction parameterisation of the model must consider the subglacial hydrology effect. When the glacier front retreats, it brings more subglacial water upstream, lubricating the contact with the bedrock. Failing to account for this effect prevents the model from replicating observed acceleration. In the next step, we propagated the ensemble of members obtained at the end of the simulation into the future. This involved incorporating future forcing uncertainties, such as greenhouse gas emission scenarios, climate model uncertainties, and oceanic forcing uncertainties. We also developed a calibration approach to give more weight to model members that best replicated past observations while ensuring the model did not overfit, to see if this refines ... |
author2 |
Institut des Géosciences de l’Environnement (IGE) Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ) Université Grenoble Alpes (UGA) Université Grenoble Alpes 2020-. Fabien Gillet-Chaulet Nicolas Champollion Jérémie Mouginot |
format |
Doctoral or Postdoctoral Thesis |
author |
Jager, Eliot |
author_facet |
Jager, Eliot |
author_sort |
Jager, Eliot |
title |
Uncertainty quantification and validation of data assimilation methods for an ice sheet model : application to a Greenland marine-terminated glacier, Upernavik Isstrøm |
title_short |
Uncertainty quantification and validation of data assimilation methods for an ice sheet model : application to a Greenland marine-terminated glacier, Upernavik Isstrøm |
title_full |
Uncertainty quantification and validation of data assimilation methods for an ice sheet model : application to a Greenland marine-terminated glacier, Upernavik Isstrøm |
title_fullStr |
Uncertainty quantification and validation of data assimilation methods for an ice sheet model : application to a Greenland marine-terminated glacier, Upernavik Isstrøm |
title_full_unstemmed |
Uncertainty quantification and validation of data assimilation methods for an ice sheet model : application to a Greenland marine-terminated glacier, Upernavik Isstrøm |
title_sort |
uncertainty quantification and validation of data assimilation methods for an ice sheet model : application to a greenland marine-terminated glacier, upernavik isstrøm |
publisher |
HAL CCSD |
publishDate |
2023 |
url |
https://theses.hal.science/tel-04658964 https://theses.hal.science/tel-04658964/document https://theses.hal.science/tel-04658964/file/JAGER_2023_archivage.pdf |
genre |
glacier Greenland groenlandais Ice Sheet Tidewater Upernavik |
genre_facet |
glacier Greenland groenlandais Ice Sheet Tidewater Upernavik |
op_source |
https://theses.hal.science/tel-04658964 Géophysique [physics.geo-ph]. Université Grenoble Alpes [2020-.], 2023. Français. ⟨NNT : 2023GRALI107⟩ |
op_relation |
NNT: 2023GRALI107 tel-04658964 https://theses.hal.science/tel-04658964 https://theses.hal.science/tel-04658964/document https://theses.hal.science/tel-04658964/file/JAGER_2023_archivage.pdf |
op_rights |
info:eu-repo/semantics/OpenAccess |
_version_ |
1810445131784912896 |