Arctic sea level data from tidal gauge and model simulations from 1948-2009
A suite of model simulations is used to investigate the spatiotemporal variability of the Arctic Ocean circulation and the observing systems required to capture it. A comparison with sea level observations shows that all model runs realistically simulate inter-annual sea level varia-bility, but the...
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ftpangaea:oai:pangaea.de:doi:10.1594/PANGAEA.912255 2024-10-13T14:03:41+00:00 Arctic sea level data from tidal gauge and model simulations from 1948-2009 Lyu, Guokun Serra, Nuno Stammer, Detlef LATITUDE: 90.000000 * LONGITUDE: 0.000000 application/zip, 205.6 MBytes https://doi.pangaea.de/10.1594/PANGAEA.912255 en eng PANGAEA Lyu, Guokun; Serra, Nuno; Zhou, Meng; Stammer, Detlef (2022): Arctic sea level variability from high-resolution model simulations and implications for the Arctic observing system. Ocean Science, 18(1), 51-66, https://doi.org/10.5194/os-18-51-2022 https://doi.pangaea.de/10.1594/PANGAEA.912255 CC-BY-4.0: Creative Commons Attribution 4.0 International (License comes into effect after moratorium ends) Access constraints: access rights needed info:eu-repo/semantics/restrictedAccess Institut für Meereskunde, Universität Hamburg Arctic Arctic sea level variability model simulation pan-Arctic tidal gauge dataset ftpangaea https://doi.org/10.5194/os-18-51-2022 2024-10-02T00:42:44Z A suite of model simulations is used to investigate the spatiotemporal variability of the Arctic Ocean circulation and the observing systems required to capture it. A comparison with sea level observations shows that all model runs realistically simulate inter-annual sea level varia-bility, but the simulated seasonal sea level variability and underlying changes in the model salinity need to be further improved. At periods <30 days, sea level variability is equivalent barotropic and strongly captured by bottom pressure observations. At the seasonal period, both barotropic and baroclinic processes contribute involving variations in the mass and densi-ty fields. Over the entire Arctic Ocean, steric height variability is dominated by halosteric effects in the upper layer. The salinity changes are related to sea ice processes, river runoff, and redistribution of the freshwater. At decadal timescales, sea level variations in the Canadi-an Basin relate to halosteric effects in the upper and intermediate layers. An adjoint sensitivi-ty analysis reveals that the decadal salinity variability is caused by anticyclonic/cyclonic wind stress, which accumulate/release freshwater in the upper layer and enhance/reduce geostrophic currents in the intermediate layer. The adjoint model simulations identify the importance of moorings and satellite altimetry on monitoring the Arctic salinity and circulation changes: while moorings capture more local salinity changes, the satellite altimetry may capture the influence of freshwater originating from the Bering Strait and the Eurasian Basin. Our study suggests that to capture basin-wide salinity changes, we need to deploy moorings in different positions spreading across the Arctic Ocean. Dataset Arctic Arctic Arctic Ocean Bering Strait Sea ice PANGAEA - Data Publisher for Earth & Environmental Science Arctic Arctic Ocean Bering Strait ENVELOPE(0.000000,0.000000,90.000000,90.000000) |
institution |
Open Polar |
collection |
PANGAEA - Data Publisher for Earth & Environmental Science |
op_collection_id |
ftpangaea |
language |
English |
topic |
Arctic Arctic sea level variability model simulation pan-Arctic tidal gauge |
spellingShingle |
Arctic Arctic sea level variability model simulation pan-Arctic tidal gauge Lyu, Guokun Serra, Nuno Stammer, Detlef Arctic sea level data from tidal gauge and model simulations from 1948-2009 |
topic_facet |
Arctic Arctic sea level variability model simulation pan-Arctic tidal gauge |
description |
A suite of model simulations is used to investigate the spatiotemporal variability of the Arctic Ocean circulation and the observing systems required to capture it. A comparison with sea level observations shows that all model runs realistically simulate inter-annual sea level varia-bility, but the simulated seasonal sea level variability and underlying changes in the model salinity need to be further improved. At periods <30 days, sea level variability is equivalent barotropic and strongly captured by bottom pressure observations. At the seasonal period, both barotropic and baroclinic processes contribute involving variations in the mass and densi-ty fields. Over the entire Arctic Ocean, steric height variability is dominated by halosteric effects in the upper layer. The salinity changes are related to sea ice processes, river runoff, and redistribution of the freshwater. At decadal timescales, sea level variations in the Canadi-an Basin relate to halosteric effects in the upper and intermediate layers. An adjoint sensitivi-ty analysis reveals that the decadal salinity variability is caused by anticyclonic/cyclonic wind stress, which accumulate/release freshwater in the upper layer and enhance/reduce geostrophic currents in the intermediate layer. The adjoint model simulations identify the importance of moorings and satellite altimetry on monitoring the Arctic salinity and circulation changes: while moorings capture more local salinity changes, the satellite altimetry may capture the influence of freshwater originating from the Bering Strait and the Eurasian Basin. Our study suggests that to capture basin-wide salinity changes, we need to deploy moorings in different positions spreading across the Arctic Ocean. |
format |
Dataset |
author |
Lyu, Guokun Serra, Nuno Stammer, Detlef |
author_facet |
Lyu, Guokun Serra, Nuno Stammer, Detlef |
author_sort |
Lyu, Guokun |
title |
Arctic sea level data from tidal gauge and model simulations from 1948-2009 |
title_short |
Arctic sea level data from tidal gauge and model simulations from 1948-2009 |
title_full |
Arctic sea level data from tidal gauge and model simulations from 1948-2009 |
title_fullStr |
Arctic sea level data from tidal gauge and model simulations from 1948-2009 |
title_full_unstemmed |
Arctic sea level data from tidal gauge and model simulations from 1948-2009 |
title_sort |
arctic sea level data from tidal gauge and model simulations from 1948-2009 |
publisher |
PANGAEA |
url |
https://doi.pangaea.de/10.1594/PANGAEA.912255 |
op_coverage |
LATITUDE: 90.000000 * LONGITUDE: 0.000000 |
long_lat |
ENVELOPE(0.000000,0.000000,90.000000,90.000000) |
geographic |
Arctic Arctic Ocean Bering Strait |
geographic_facet |
Arctic Arctic Ocean Bering Strait |
genre |
Arctic Arctic Arctic Ocean Bering Strait Sea ice |
genre_facet |
Arctic Arctic Arctic Ocean Bering Strait Sea ice |
op_source |
Institut für Meereskunde, Universität Hamburg |
op_relation |
Lyu, Guokun; Serra, Nuno; Zhou, Meng; Stammer, Detlef (2022): Arctic sea level variability from high-resolution model simulations and implications for the Arctic observing system. Ocean Science, 18(1), 51-66, https://doi.org/10.5194/os-18-51-2022 https://doi.pangaea.de/10.1594/PANGAEA.912255 |
op_rights |
CC-BY-4.0: Creative Commons Attribution 4.0 International (License comes into effect after moratorium ends) Access constraints: access rights needed info:eu-repo/semantics/restrictedAccess |
op_doi |
https://doi.org/10.5194/os-18-51-2022 |
_version_ |
1812808834919432192 |