Ice Mass Balance in Liaodong Bay: Modeling and Observations
During the winters of 2009/2010 and 2020/2021, observations were carried out at an eastern port of Liaodong Bay to examine the variations in sea ice thickness and atmospheric conditions. The daily ice thickness (DIT) and the cumulative ice thickness (CIT) are the two main observation items related t...
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ftmdpi:oai:mdpi.com:/2073-4441/15/5/943/ 2023-08-20T04:09:43+02:00 Ice Mass Balance in Liaodong Bay: Modeling and Observations Yuxian Ma Dewen Ding Ning Xu Shuai Yuan Wenqi Shi agris 2023-03-01 application/pdf https://doi.org/10.3390/w15050943 EN eng Multidisciplinary Digital Publishing Institute New Sensors, New Technologies and Machine Learning in Water Sciences https://dx.doi.org/10.3390/w15050943 https://creativecommons.org/licenses/by/4.0/ Water; Volume 15; Issue 5; Pages: 943 Liaodong Bay sea ice thickness Stefan’s law HIGHTSI oceanic heat flux Text 2023 ftmdpi https://doi.org/10.3390/w15050943 2023-08-01T09:03:23Z During the winters of 2009/2010 and 2020/2021, observations were carried out at an eastern port of Liaodong Bay to examine the variations in sea ice thickness and atmospheric conditions. The daily ice thickness (DIT) and the cumulative ice thickness (CIT) are the two main observation items related to the thickness of sea ice. For DIT, the sea ice thickness gradually decreases as the temperature increases, and the freezing rate a is 1.48 cm/(°C·d)1/2. For CIT, when the temperature is −12 °C, the maximum growth rate of ice thickness decreases from 3.5 cm/d to 1.5 cm/d as the ice thickness increases from 0 to 20 cm. The residual method was applied to calculate the oceanic heat flux, which is an important parameter of ice modeling, and both the analytic model (Stefan’s law) and numerical model (high-resolution thermodynamic snow-and-ice model) were utilized in this work. It was found that the accuracy of the simulation results was high when the growth coefficient of the analytic mode was 2.3 cm/(°C·d)1/2. With an oceanic heat flux of 2 W·m−2, the maximum error of the numerical model approached 60% in 2010 and 3.7% in 2021. However, using the oceanic heat flux calculated in this work, the maximum error can be significantly reduced to 4.2% in the winter of 2009/2010 and 1.5% in 2020/2021. Additionally, the oceanic heat flux in Liaodong Bay showed a decreasing trend with the increase in ice thickness and air temperature. Text Sea ice MDPI Open Access Publishing Water 15 5 943 |
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MDPI Open Access Publishing |
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ftmdpi |
language |
English |
topic |
Liaodong Bay sea ice thickness Stefan’s law HIGHTSI oceanic heat flux |
spellingShingle |
Liaodong Bay sea ice thickness Stefan’s law HIGHTSI oceanic heat flux Yuxian Ma Dewen Ding Ning Xu Shuai Yuan Wenqi Shi Ice Mass Balance in Liaodong Bay: Modeling and Observations |
topic_facet |
Liaodong Bay sea ice thickness Stefan’s law HIGHTSI oceanic heat flux |
description |
During the winters of 2009/2010 and 2020/2021, observations were carried out at an eastern port of Liaodong Bay to examine the variations in sea ice thickness and atmospheric conditions. The daily ice thickness (DIT) and the cumulative ice thickness (CIT) are the two main observation items related to the thickness of sea ice. For DIT, the sea ice thickness gradually decreases as the temperature increases, and the freezing rate a is 1.48 cm/(°C·d)1/2. For CIT, when the temperature is −12 °C, the maximum growth rate of ice thickness decreases from 3.5 cm/d to 1.5 cm/d as the ice thickness increases from 0 to 20 cm. The residual method was applied to calculate the oceanic heat flux, which is an important parameter of ice modeling, and both the analytic model (Stefan’s law) and numerical model (high-resolution thermodynamic snow-and-ice model) were utilized in this work. It was found that the accuracy of the simulation results was high when the growth coefficient of the analytic mode was 2.3 cm/(°C·d)1/2. With an oceanic heat flux of 2 W·m−2, the maximum error of the numerical model approached 60% in 2010 and 3.7% in 2021. However, using the oceanic heat flux calculated in this work, the maximum error can be significantly reduced to 4.2% in the winter of 2009/2010 and 1.5% in 2020/2021. Additionally, the oceanic heat flux in Liaodong Bay showed a decreasing trend with the increase in ice thickness and air temperature. |
format |
Text |
author |
Yuxian Ma Dewen Ding Ning Xu Shuai Yuan Wenqi Shi |
author_facet |
Yuxian Ma Dewen Ding Ning Xu Shuai Yuan Wenqi Shi |
author_sort |
Yuxian Ma |
title |
Ice Mass Balance in Liaodong Bay: Modeling and Observations |
title_short |
Ice Mass Balance in Liaodong Bay: Modeling and Observations |
title_full |
Ice Mass Balance in Liaodong Bay: Modeling and Observations |
title_fullStr |
Ice Mass Balance in Liaodong Bay: Modeling and Observations |
title_full_unstemmed |
Ice Mass Balance in Liaodong Bay: Modeling and Observations |
title_sort |
ice mass balance in liaodong bay: modeling and observations |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2023 |
url |
https://doi.org/10.3390/w15050943 |
op_coverage |
agris |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Water; Volume 15; Issue 5; Pages: 943 |
op_relation |
New Sensors, New Technologies and Machine Learning in Water Sciences https://dx.doi.org/10.3390/w15050943 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/w15050943 |
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Water |
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15 |
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5 |
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943 |
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1774723349058945024 |