Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System
Sea ice data assimilation can greatly improve forecasts of Arctic sea ice evolution. Many previous sea ice data assimilation studies were conducted without assimilating ocean state variables, even though the sea ice evolution is closely linked to the oceanic conditions, both dynamically and thermody...
Published in: | Journal of Geophysical Research: Oceans |
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Online Access: | https://epic.awi.de/id/eprint/50464/ https://epic.awi.de/id/eprint/50464/1/Liang_etal_JGROceans140_4727_2019.pdf https://hdl.handle.net/10013/epic.daa1133d-ee4b-4ecd-baa9-85c62d3f3d8e https://hdl.handle.net/ |
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ftawi:oai:epic.awi.de:50464 2023-05-15T14:27:44+02:00 Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System Liang, Xi Losch, Martin Nerger, Lars Mu, Longjiang Yang, Qinghua Liu, Chengyan 2019 application/pdf https://epic.awi.de/id/eprint/50464/ https://epic.awi.de/id/eprint/50464/1/Liang_etal_JGROceans140_4727_2019.pdf https://hdl.handle.net/10013/epic.daa1133d-ee4b-4ecd-baa9-85c62d3f3d8e https://hdl.handle.net/ unknown https://epic.awi.de/id/eprint/50464/1/Liang_etal_JGROceans140_4727_2019.pdf https://hdl.handle.net/ Liang, X. , Losch, M. orcid:0000-0002-3824-5244 , Nerger, L. orcid:0000-0002-1908-1010 , Mu, L. orcid:0000-0001-5668-8025 , Yang, Q. and Liu, C. (2019) Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System , Journal of Geophysical Research-Oceans, 124 (7), pp. 4727-4743 . doi:10.1029/2019JC015073 <https://doi.org/10.1029/2019JC015073> , hdl:10013/epic.daa1133d-ee4b-4ecd-baa9-85c62d3f3d8e EPIC3Journal of Geophysical Research-Oceans, 124(7), pp. 4727-4743 Article isiRev 2019 ftawi https://doi.org/10.1029/2019JC015073 2021-12-24T15:45:01Z Sea ice data assimilation can greatly improve forecasts of Arctic sea ice evolution. Many previous sea ice data assimilation studies were conducted without assimilating ocean state variables, even though the sea ice evolution is closely linked to the oceanic conditions, both dynamically and thermodynamically. Based on the method of a localized ensemble error subspace transform Kalman filter, satellite‐retrieved sea ice concentration and sea ice thickness are assimilated into an Arctic sea ice‐ocean model. As a new addition, sea surface temperature (SST) data are also assimilated. The additional assimilation of SST improves not only the simulated ocean temperature in the mixed layer of the ocean substantially but also the accuracy of sea ice edge position, sea ice extent, and sea ice thickness in the marginal sea ice zone. The improvement in the simulated potential temperature in the upper 1,000 m can be attributed to the enhanced vertical convection processes in the regions where the assimilated observational SST is colder than the simulated SST without assimilation. The improvements in the sea ice edge position and sea ice thickness simulations are primarily caused by the SST data assimilation reducing biases in the simulated SST and the associated coupled ocean‐sea ice processes. Our investigation suggests that, due to the complex interaction between the sea ice and ocean, assimilating ocean data should be an indispensable component of numerical polar sea ice forecasting systems. Article in Journal/Newspaper Arctic Arctic Sea ice Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Arctic Journal of Geophysical Research: Oceans 124 7 4727 4743 |
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Open Polar |
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Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
op_collection_id |
ftawi |
language |
unknown |
description |
Sea ice data assimilation can greatly improve forecasts of Arctic sea ice evolution. Many previous sea ice data assimilation studies were conducted without assimilating ocean state variables, even though the sea ice evolution is closely linked to the oceanic conditions, both dynamically and thermodynamically. Based on the method of a localized ensemble error subspace transform Kalman filter, satellite‐retrieved sea ice concentration and sea ice thickness are assimilated into an Arctic sea ice‐ocean model. As a new addition, sea surface temperature (SST) data are also assimilated. The additional assimilation of SST improves not only the simulated ocean temperature in the mixed layer of the ocean substantially but also the accuracy of sea ice edge position, sea ice extent, and sea ice thickness in the marginal sea ice zone. The improvement in the simulated potential temperature in the upper 1,000 m can be attributed to the enhanced vertical convection processes in the regions where the assimilated observational SST is colder than the simulated SST without assimilation. The improvements in the sea ice edge position and sea ice thickness simulations are primarily caused by the SST data assimilation reducing biases in the simulated SST and the associated coupled ocean‐sea ice processes. Our investigation suggests that, due to the complex interaction between the sea ice and ocean, assimilating ocean data should be an indispensable component of numerical polar sea ice forecasting systems. |
format |
Article in Journal/Newspaper |
author |
Liang, Xi Losch, Martin Nerger, Lars Mu, Longjiang Yang, Qinghua Liu, Chengyan |
spellingShingle |
Liang, Xi Losch, Martin Nerger, Lars Mu, Longjiang Yang, Qinghua Liu, Chengyan Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System |
author_facet |
Liang, Xi Losch, Martin Nerger, Lars Mu, Longjiang Yang, Qinghua Liu, Chengyan |
author_sort |
Liang, Xi |
title |
Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System |
title_short |
Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System |
title_full |
Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System |
title_fullStr |
Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System |
title_full_unstemmed |
Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System |
title_sort |
using sea surface temperature observations to constrain upper ocean properties in an arctic sea ice‐ocean data assimilation system |
publishDate |
2019 |
url |
https://epic.awi.de/id/eprint/50464/ https://epic.awi.de/id/eprint/50464/1/Liang_etal_JGROceans140_4727_2019.pdf https://hdl.handle.net/10013/epic.daa1133d-ee4b-4ecd-baa9-85c62d3f3d8e https://hdl.handle.net/ |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Arctic Sea ice |
genre_facet |
Arctic Arctic Sea ice |
op_source |
EPIC3Journal of Geophysical Research-Oceans, 124(7), pp. 4727-4743 |
op_relation |
https://epic.awi.de/id/eprint/50464/1/Liang_etal_JGROceans140_4727_2019.pdf https://hdl.handle.net/ Liang, X. , Losch, M. orcid:0000-0002-3824-5244 , Nerger, L. orcid:0000-0002-1908-1010 , Mu, L. orcid:0000-0001-5668-8025 , Yang, Q. and Liu, C. (2019) Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice‐Ocean Data Assimilation System , Journal of Geophysical Research-Oceans, 124 (7), pp. 4727-4743 . doi:10.1029/2019JC015073 <https://doi.org/10.1029/2019JC015073> , hdl:10013/epic.daa1133d-ee4b-4ecd-baa9-85c62d3f3d8e |
op_doi |
https://doi.org/10.1029/2019JC015073 |
container_title |
Journal of Geophysical Research: Oceans |
container_volume |
124 |
container_issue |
7 |
container_start_page |
4727 |
op_container_end_page |
4743 |
_version_ |
1766301602915811328 |