Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: empirical and model results
Large changes in the sea ice regime of the Arctic Ocean have occurred over the last decades justifying the development of models to forecast sea ice physics and biogeochemistry. The main goal of this study is to evaluate the performance of the Los Alamos Sea Ice Model (CICE) to simulate physical and...
Published in: | Journal of Geophysical Research: Biogeosciences |
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Language: | English |
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Wiley-Blackwell Publishing Inc.
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Online Access: | https://eprints.utas.edu.au/26659/ https://eprints.utas.edu.au/26659/1/Duarte%202016.pdf |
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ftunivtasmania:oai:eprints.utas.edu.au:26659 2023-05-15T14:27:37+02:00 Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: empirical and model results Duarte, P Meyer, A Olsen, LM Kauko, HM Assmy, P Rosel, A Itkin, P Hudson, SR Granskog, MA Gerland, S Sundfjord, A Steen, H Hop, H Cohen, L Peterson, AK Jeffrey, N Elliott, SM Hunke, EC Turner, AK 2017 application/pdf https://eprints.utas.edu.au/26659/ https://eprints.utas.edu.au/26659/1/Duarte%202016.pdf en eng Wiley-Blackwell Publishing Inc. https://eprints.utas.edu.au/26659/1/Duarte%202016.pdf Duarte, P, Meyer, A orcid:0000-0003-0447-795X , Olsen, LM, Kauko, HM, Assmy, P, Rosel, A, Itkin, P, Hudson, SR, Granskog, MA, Gerland, S, Sundfjord, A, Steen, H, Hop, H, Cohen, L, Peterson, AK, Jeffrey, N, Elliott, SM, Hunke, EC and Turner, AK 2017 , 'Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: empirical and model results' , Journal of Geophysical Research: Biogeosciences, vol. 122, no. 7 , pp. 1632-1654 , doi:10.1002/2016JG003660 <http://dx.doi.org/10.1002/2016JG003660>. Arctic sea ice ocean model CICE evaluation N-ICE2015 ice thickness nutrient algal bloom ice melt primary production Article PeerReviewed 2017 ftunivtasmania https://doi.org/10.1002/2016JG003660 2021-09-13T22:17:34Z Large changes in the sea ice regime of the Arctic Ocean have occurred over the last decades justifying the development of models to forecast sea ice physics and biogeochemistry. The main goal of this study is to evaluate the performance of the Los Alamos Sea Ice Model (CICE) to simulate physical and biogeochemical properties at time scales of a few weeks and to use the model to analyze ice algal bloom dynamics in different types of ice. Ocean and atmospheric forcing data and observations of the evolution of the sea ice properties collected from 18 April to 4 June 2015, during the Norwegian young sea ICE expedition, were used to test the CICE model. Our results show the following: (i) model performance is reasonable for sea ice thickness and bulk salinity; good for vertically resolved temperature, vertically averaged Chl a concentrations, and standing stocks; and poor for vertically resolved Chl a concentrations. (ii) Improving current knowledge about nutrient exchanges, ice algal recruitment, and motion is critical to improve sea ice biogeochemical modeling. (iii) Ice algae may bloom despite some degree of basal melting. (iv) Ice algal motility driven by gradients in limiting factors is a plausible mechanism to explain their vertical distribution. (v) Different ice algal bloom and net primary production (NPP) patterns were identified in the ice types studied, suggesting that ice algal maximal growth rates will increase, while sea ice vertically integrated NPP and biomass will decrease as a result of the predictable increase in the area covered by refrozen leads in the Arctic Ocean. Article in Journal/Newspaper Arctic Arctic Arctic Ocean ice algae Sea ice University of Tasmania: UTas ePrints Arctic Arctic Ocean Journal of Geophysical Research: Biogeosciences 122 7 1632 1654 |
institution |
Open Polar |
collection |
University of Tasmania: UTas ePrints |
op_collection_id |
ftunivtasmania |
language |
English |
topic |
Arctic sea ice ocean model CICE evaluation N-ICE2015 ice thickness nutrient algal bloom ice melt primary production |
spellingShingle |
Arctic sea ice ocean model CICE evaluation N-ICE2015 ice thickness nutrient algal bloom ice melt primary production Duarte, P Meyer, A Olsen, LM Kauko, HM Assmy, P Rosel, A Itkin, P Hudson, SR Granskog, MA Gerland, S Sundfjord, A Steen, H Hop, H Cohen, L Peterson, AK Jeffrey, N Elliott, SM Hunke, EC Turner, AK Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: empirical and model results |
topic_facet |
Arctic sea ice ocean model CICE evaluation N-ICE2015 ice thickness nutrient algal bloom ice melt primary production |
description |
Large changes in the sea ice regime of the Arctic Ocean have occurred over the last decades justifying the development of models to forecast sea ice physics and biogeochemistry. The main goal of this study is to evaluate the performance of the Los Alamos Sea Ice Model (CICE) to simulate physical and biogeochemical properties at time scales of a few weeks and to use the model to analyze ice algal bloom dynamics in different types of ice. Ocean and atmospheric forcing data and observations of the evolution of the sea ice properties collected from 18 April to 4 June 2015, during the Norwegian young sea ICE expedition, were used to test the CICE model. Our results show the following: (i) model performance is reasonable for sea ice thickness and bulk salinity; good for vertically resolved temperature, vertically averaged Chl a concentrations, and standing stocks; and poor for vertically resolved Chl a concentrations. (ii) Improving current knowledge about nutrient exchanges, ice algal recruitment, and motion is critical to improve sea ice biogeochemical modeling. (iii) Ice algae may bloom despite some degree of basal melting. (iv) Ice algal motility driven by gradients in limiting factors is a plausible mechanism to explain their vertical distribution. (v) Different ice algal bloom and net primary production (NPP) patterns were identified in the ice types studied, suggesting that ice algal maximal growth rates will increase, while sea ice vertically integrated NPP and biomass will decrease as a result of the predictable increase in the area covered by refrozen leads in the Arctic Ocean. |
format |
Article in Journal/Newspaper |
author |
Duarte, P Meyer, A Olsen, LM Kauko, HM Assmy, P Rosel, A Itkin, P Hudson, SR Granskog, MA Gerland, S Sundfjord, A Steen, H Hop, H Cohen, L Peterson, AK Jeffrey, N Elliott, SM Hunke, EC Turner, AK |
author_facet |
Duarte, P Meyer, A Olsen, LM Kauko, HM Assmy, P Rosel, A Itkin, P Hudson, SR Granskog, MA Gerland, S Sundfjord, A Steen, H Hop, H Cohen, L Peterson, AK Jeffrey, N Elliott, SM Hunke, EC Turner, AK |
author_sort |
Duarte, P |
title |
Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: empirical and model results |
title_short |
Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: empirical and model results |
title_full |
Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: empirical and model results |
title_fullStr |
Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: empirical and model results |
title_full_unstemmed |
Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: empirical and model results |
title_sort |
sea ice thermohaline dynamics and biogeochemistry in the arctic ocean: empirical and model results |
publisher |
Wiley-Blackwell Publishing Inc. |
publishDate |
2017 |
url |
https://eprints.utas.edu.au/26659/ https://eprints.utas.edu.au/26659/1/Duarte%202016.pdf |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Arctic Ocean ice algae Sea ice |
genre_facet |
Arctic Arctic Arctic Ocean ice algae Sea ice |
op_relation |
https://eprints.utas.edu.au/26659/1/Duarte%202016.pdf Duarte, P, Meyer, A orcid:0000-0003-0447-795X , Olsen, LM, Kauko, HM, Assmy, P, Rosel, A, Itkin, P, Hudson, SR, Granskog, MA, Gerland, S, Sundfjord, A, Steen, H, Hop, H, Cohen, L, Peterson, AK, Jeffrey, N, Elliott, SM, Hunke, EC and Turner, AK 2017 , 'Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: empirical and model results' , Journal of Geophysical Research: Biogeosciences, vol. 122, no. 7 , pp. 1632-1654 , doi:10.1002/2016JG003660 <http://dx.doi.org/10.1002/2016JG003660>. |
op_doi |
https://doi.org/10.1002/2016JG003660 |
container_title |
Journal of Geophysical Research: Biogeosciences |
container_volume |
122 |
container_issue |
7 |
container_start_page |
1632 |
op_container_end_page |
1654 |
_version_ |
1766301432921718784 |