Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies

We present a quantitative network design (QND) study of the Arctic sea ice–ocean system using a software tool that can evaluate hypothetical observational networks in a variational data assimilation system. For a demonstration, we evaluate two idealised flight transects derived from NASA's Oper...

Full description

Bibliographic Details
Published in:The Cryosphere
Main Authors: Kaminski, T., Kauker, F., Eicken, H., Karcher, M.
Format: Article in Journal/Newspaper
Language:unknown
Published: Zenodo 2015
Subjects:
Online Access:https://doi.org/10.5194/tc-9-1721-2015
id ftzenodo:oai:zenodo.org:48621
record_format openpolar
spelling ftzenodo:oai:zenodo.org:48621 2024-09-15T18:01:59+00:00 Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies Kaminski, T. Kauker, F. Eicken, H. Karcher, M. 2015-08-27 https://doi.org/10.5194/tc-9-1721-2015 unknown Zenodo https://zenodo.org/communities/fp7postgrantoapilotoutputs https://zenodo.org/communities/eu https://doi.org/10.5194/tc-9-1721-2015 oai:zenodo.org:48621 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode The Cryosphere, 9, 1721-1733, (2015-08-27) quantitative network design data assimilation sea ice Arctic sampling strategies info:eu-repo/semantics/article 2015 ftzenodo https://doi.org/10.5194/tc-9-1721-2015 2024-07-27T05:42:35Z We present a quantitative network design (QND) study of the Arctic sea ice–ocean system using a software tool that can evaluate hypothetical observational networks in a variational data assimilation system. For a demonstration, we evaluate two idealised flight transects derived from NASA's Operation IceBridge airborne ice surveys in terms of their potential to improve 10-day to 5-month sea ice forecasts. As target regions for the forecasts we select the Chukchi Sea, an area particularly relevant for maritime traffic and offshore resource exploration, as well as two areas related to the Barnett ice severity index (BSI), a standard measure of shipping conditions along the Alaskan coast that is routinely issued by ice services. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. We demonstrate how observations of sea ice and snow thickness can constrain ice and snow variables in a target region and quantify the complementarity of combining two flight transects. We further quantify the benefit of improved atmospheric forecasts and a well-calibrated model. €850 APC fee funded by the EC FP7 Post-Grant Open Access Pilot. Article in Journal/Newspaper Chukchi Chukchi Sea Sea ice The Cryosphere Zenodo The Cryosphere 9 4 1721 1733
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
topic quantitative network design
data assimilation
sea ice
Arctic
sampling strategies
spellingShingle quantitative network design
data assimilation
sea ice
Arctic
sampling strategies
Kaminski, T.
Kauker, F.
Eicken, H.
Karcher, M.
Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies
topic_facet quantitative network design
data assimilation
sea ice
Arctic
sampling strategies
description We present a quantitative network design (QND) study of the Arctic sea ice–ocean system using a software tool that can evaluate hypothetical observational networks in a variational data assimilation system. For a demonstration, we evaluate two idealised flight transects derived from NASA's Operation IceBridge airborne ice surveys in terms of their potential to improve 10-day to 5-month sea ice forecasts. As target regions for the forecasts we select the Chukchi Sea, an area particularly relevant for maritime traffic and offshore resource exploration, as well as two areas related to the Barnett ice severity index (BSI), a standard measure of shipping conditions along the Alaskan coast that is routinely issued by ice services. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. We demonstrate how observations of sea ice and snow thickness can constrain ice and snow variables in a target region and quantify the complementarity of combining two flight transects. We further quantify the benefit of improved atmospheric forecasts and a well-calibrated model. €850 APC fee funded by the EC FP7 Post-Grant Open Access Pilot.
format Article in Journal/Newspaper
author Kaminski, T.
Kauker, F.
Eicken, H.
Karcher, M.
author_facet Kaminski, T.
Kauker, F.
Eicken, H.
Karcher, M.
author_sort Kaminski, T.
title Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies
title_short Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies
title_full Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies
title_fullStr Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies
title_full_unstemmed Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies
title_sort exploring the utility of quantitative network design in evaluating arctic sea ice thickness sampling strategies
publisher Zenodo
publishDate 2015
url https://doi.org/10.5194/tc-9-1721-2015
genre Chukchi
Chukchi Sea
Sea ice
The Cryosphere
genre_facet Chukchi
Chukchi Sea
Sea ice
The Cryosphere
op_source The Cryosphere, 9, 1721-1733, (2015-08-27)
op_relation https://zenodo.org/communities/fp7postgrantoapilotoutputs
https://zenodo.org/communities/eu
https://doi.org/10.5194/tc-9-1721-2015
oai:zenodo.org:48621
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/10.5194/tc-9-1721-2015
container_title The Cryosphere
container_volume 9
container_issue 4
container_start_page 1721
op_container_end_page 1733
_version_ 1810439058234540032