Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology

Code for the paper:Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology Current code includes the data assimilation scheme: iterative ensemble Kalman filterand general experiment setup including the ensemble prior of air drag co...

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Bibliographic Details
Main Author: Yumeng Chen
Format: Article in Journal/Newspaper
Language:unknown
Published: Zenodo 2023
Subjects:
data assimilation
parameter estimation
sea ice
Sea ice
Online Access:https://doi.org/10.5281/zenodo.8224997
id ftzenodo:oai:zenodo.org:8224997
record_format openpolar
spelling ftzenodo:oai:zenodo.org:8224997 2024-09-15T18:34:11+00:00 Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology Yumeng Chen 2023-08-08 https://doi.org/10.5281/zenodo.8224997 unknown Zenodo https://doi.org/10.5281/zenodo.8224996 https://doi.org/10.5281/zenodo.8224997 oai:zenodo.org:8224997 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode data assimilation parameter estimation sea ice info:eu-repo/semantics/article 2023 ftzenodo https://doi.org/10.5281/zenodo.822499710.5281/zenodo.8224996 2024-07-25T13:56:28Z Code for the paper:Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology Current code includes the data assimilation scheme: iterative ensemble Kalman filterand general experiment setup including the ensemble prior of air drag coefficient and damage parameter, the synthetic observation generation. However, the code in general heavily relies on the dynamics-only MEB sea ice model, which can be only available upon request. Article in Journal/Newspaper Sea ice Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
topic data assimilation
parameter estimation
sea ice
spellingShingle data assimilation
parameter estimation
sea ice
Yumeng Chen
Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology
topic_facet data assimilation
parameter estimation
sea ice
description Code for the paper:Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology Current code includes the data assimilation scheme: iterative ensemble Kalman filterand general experiment setup including the ensemble prior of air drag coefficient and damage parameter, the synthetic observation generation. However, the code in general heavily relies on the dynamics-only MEB sea ice model, which can be only available upon request.
format Article in Journal/Newspaper
author Yumeng Chen
author_facet Yumeng Chen
author_sort Yumeng Chen
title Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology
title_short Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology
title_full Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology
title_fullStr Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology
title_full_unstemmed Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology
title_sort multivariate state and parameter estimation with data assimilation on sea-ice models using a maxwell-elasto-brittle rheology
publisher Zenodo
publishDate 2023
url https://doi.org/10.5281/zenodo.8224997
genre Sea ice
genre_facet Sea ice
op_relation https://doi.org/10.5281/zenodo.8224996
https://doi.org/10.5281/zenodo.8224997
oai:zenodo.org:8224997
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.822499710.5281/zenodo.8224996
_version_ 1810475953621565440

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