Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files ...

The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated and...

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Main Authors: Ungermann, Mischa, Tremblay, L Bruno, Martin, Torge, Losch, Martin
Format: Dataset
Language:English
Published: PANGAEA 2017
Subjects:
Online Access:https://dx.doi.org/10.1594/pangaea.865445
https://doi.pangaea.de/10.1594/PANGAEA.865445
id ftdatacite:10.1594/pangaea.865445
record_format openpolar
spelling ftdatacite:10.1594/pangaea.865445 2024-09-15T17:53:59+00:00 Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files ... Ungermann, Mischa Tremblay, L Bruno Martin, Torge Losch, Martin 2017 text/tab-separated-values https://dx.doi.org/10.1594/pangaea.865445 https://doi.pangaea.de/10.1594/PANGAEA.865445 en eng PANGAEA https://dx.doi.org/10.1002/2016jc012128 https://dx.doi.org/10.1175/1520-0485(1979)009<0815:adtsim>2.0.co;2 https://dx.doi.org/10.1029/jc080i033p04514 Creative Commons Attribution 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 File content File name File format File size Uniform resource locator/link to file dataset Supplementary Dataset Dataset 2017 ftdatacite https://doi.org/10.1594/pangaea.86544510.1002/2016jc01212810.1175/1520-0485(1979)009<0815:adtsim>2.0.co;210.1029/jc080i033p04514 2024-08-01T10:57:37Z The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated and observed sea ice concentration, thickness and drift speed with an semi-automatic parameter optimization routine. The standard ITD and ice strength parameterization lead to larger errors when compared to the simple single-category model with an ice strength parameterization based on the mean ice thickness. Interestingly, the simpler ice strength formulation, which depends linearly on the mean ice thickness, also reduces the model-observation error when using an ITD. For the ice strength parameterization that makes use of the ITD, the effective ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to overall thicker ice that is more easily deformed. ... : Monthly mean values for sea ice thickness, concentration, drift and ice strength from model simulations. The model area covers the Arctic Ocean; thickness, concentration and drift are given from 1979 to 2009, ice strength is given from 1999 to 2011. The different model configurations are as described in the article. ... Dataset Arctic Ocean Sea ice DataCite
institution Open Polar
collection DataCite
op_collection_id ftdatacite
language English
topic File content
File name
File format
File size
Uniform resource locator/link to file
spellingShingle File content
File name
File format
File size
Uniform resource locator/link to file
Ungermann, Mischa
Tremblay, L Bruno
Martin, Torge
Losch, Martin
Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files ...
topic_facet File content
File name
File format
File size
Uniform resource locator/link to file
description The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated and observed sea ice concentration, thickness and drift speed with an semi-automatic parameter optimization routine. The standard ITD and ice strength parameterization lead to larger errors when compared to the simple single-category model with an ice strength parameterization based on the mean ice thickness. Interestingly, the simpler ice strength formulation, which depends linearly on the mean ice thickness, also reduces the model-observation error when using an ITD. For the ice strength parameterization that makes use of the ITD, the effective ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to overall thicker ice that is more easily deformed. ... : Monthly mean values for sea ice thickness, concentration, drift and ice strength from model simulations. The model area covers the Arctic Ocean; thickness, concentration and drift are given from 1979 to 2009, ice strength is given from 1999 to 2011. The different model configurations are as described in the article. ...
format Dataset
author Ungermann, Mischa
Tremblay, L Bruno
Martin, Torge
Losch, Martin
author_facet Ungermann, Mischa
Tremblay, L Bruno
Martin, Torge
Losch, Martin
author_sort Ungermann, Mischa
title Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files ...
title_short Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files ...
title_full Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files ...
title_fullStr Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files ...
title_full_unstemmed Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files ...
title_sort sea ice thickness distribution (itd) model for the arctic, links to netcdf files ...
publisher PANGAEA
publishDate 2017
url https://dx.doi.org/10.1594/pangaea.865445
https://doi.pangaea.de/10.1594/PANGAEA.865445
genre Arctic Ocean
Sea ice
genre_facet Arctic Ocean
Sea ice
op_relation https://dx.doi.org/10.1002/2016jc012128
https://dx.doi.org/10.1175/1520-0485(1979)009<0815:adtsim>2.0.co;2
https://dx.doi.org/10.1029/jc080i033p04514
op_rights Creative Commons Attribution 3.0 Unported
https://creativecommons.org/licenses/by/3.0/legalcode
cc-by-3.0
op_doi https://doi.org/10.1594/pangaea.86544510.1002/2016jc01212810.1175/1520-0485(1979)009<0815:adtsim>2.0.co;210.1029/jc080i033p04514
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