Estimating a mean transport velocity in the marginal ice zone using ice–ocean prediction systems

Understanding the transport of objects and material in the marginal ice zone (MIZ) is critical for human operations in polar regions. This can be the transport of pollutants, such as spilled oil, or the transport of objects, such as drifting ships and search and rescue operations. For emergency resp...

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Published in:The Cryosphere
Main Authors: G. Sutherland, V. de Aguiar, L.-R. Hole, J. Rabault, M. Dabboor, Ø. Breivik
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2022
Subjects:
Online Access:https://doi.org/10.5194/tc-16-2103-2022
https://doaj.org/article/9bc3649d11da4f4cbe5e24fc55b74207
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spelling ftdoajarticles:oai:doaj.org/article:9bc3649d11da4f4cbe5e24fc55b74207 2023-05-15T18:32:26+02:00 Estimating a mean transport velocity in the marginal ice zone using ice–ocean prediction systems G. Sutherland V. de Aguiar L.-R. Hole J. Rabault M. Dabboor Ø. Breivik 2022-06-01T00:00:00Z https://doi.org/10.5194/tc-16-2103-2022 https://doaj.org/article/9bc3649d11da4f4cbe5e24fc55b74207 EN eng Copernicus Publications https://tc.copernicus.org/articles/16/2103/2022/tc-16-2103-2022.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-16-2103-2022 1994-0416 1994-0424 https://doaj.org/article/9bc3649d11da4f4cbe5e24fc55b74207 The Cryosphere, Vol 16, Pp 2103-2114 (2022) Environmental sciences GE1-350 Geology QE1-996.5 article 2022 ftdoajarticles https://doi.org/10.5194/tc-16-2103-2022 2022-12-30T21:28:02Z Understanding the transport of objects and material in the marginal ice zone (MIZ) is critical for human operations in polar regions. This can be the transport of pollutants, such as spilled oil, or the transport of objects, such as drifting ships and search and rescue operations. For emergency response, the use of environmental prediction systems are required which predict ice and ocean parameters and are run operationally by many centres in the world. As these prediction systems predict both ice and ocean velocities, as well as ice concentration, it must be chosen how to combine these data to best predict the mean transport velocities. In this paper we present a case study of four drifting buoys in the MIZ deployed at four distinct ice concentrations. We compare short-term trajectories, i.e. up to 48 h lead times, with standard transport models using ice and ocean velocities from two operational prediction systems. A new transport model for the MIZ is developed with two key features aimed to help mitigate uncertainties in ice–ocean prediction systems: first, including both ice and ocean velocities and linearly weighting them by ice concentration, and second, allowing for a non-zero leeway to be added to the ice velocity component. This new transport model is found to reduce the error by a factor of 2 to 3 for drifters furthest in the MIZ using ice-based transport models in trajectory location after 48 h. Article in Journal/Newspaper The Cryosphere Directory of Open Access Journals: DOAJ Articles The Cryosphere 16 5 2103 2114
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Environmental sciences
GE1-350
Geology
QE1-996.5
spellingShingle Environmental sciences
GE1-350
Geology
QE1-996.5
G. Sutherland
V. de Aguiar
L.-R. Hole
J. Rabault
M. Dabboor
Ø. Breivik
Estimating a mean transport velocity in the marginal ice zone using ice–ocean prediction systems
topic_facet Environmental sciences
GE1-350
Geology
QE1-996.5
description Understanding the transport of objects and material in the marginal ice zone (MIZ) is critical for human operations in polar regions. This can be the transport of pollutants, such as spilled oil, or the transport of objects, such as drifting ships and search and rescue operations. For emergency response, the use of environmental prediction systems are required which predict ice and ocean parameters and are run operationally by many centres in the world. As these prediction systems predict both ice and ocean velocities, as well as ice concentration, it must be chosen how to combine these data to best predict the mean transport velocities. In this paper we present a case study of four drifting buoys in the MIZ deployed at four distinct ice concentrations. We compare short-term trajectories, i.e. up to 48 h lead times, with standard transport models using ice and ocean velocities from two operational prediction systems. A new transport model for the MIZ is developed with two key features aimed to help mitigate uncertainties in ice–ocean prediction systems: first, including both ice and ocean velocities and linearly weighting them by ice concentration, and second, allowing for a non-zero leeway to be added to the ice velocity component. This new transport model is found to reduce the error by a factor of 2 to 3 for drifters furthest in the MIZ using ice-based transport models in trajectory location after 48 h.
format Article in Journal/Newspaper
author G. Sutherland
V. de Aguiar
L.-R. Hole
J. Rabault
M. Dabboor
Ø. Breivik
author_facet G. Sutherland
V. de Aguiar
L.-R. Hole
J. Rabault
M. Dabboor
Ø. Breivik
author_sort G. Sutherland
title Estimating a mean transport velocity in the marginal ice zone using ice–ocean prediction systems
title_short Estimating a mean transport velocity in the marginal ice zone using ice–ocean prediction systems
title_full Estimating a mean transport velocity in the marginal ice zone using ice–ocean prediction systems
title_fullStr Estimating a mean transport velocity in the marginal ice zone using ice–ocean prediction systems
title_full_unstemmed Estimating a mean transport velocity in the marginal ice zone using ice–ocean prediction systems
title_sort estimating a mean transport velocity in the marginal ice zone using ice–ocean prediction systems
publisher Copernicus Publications
publishDate 2022
url https://doi.org/10.5194/tc-16-2103-2022
https://doaj.org/article/9bc3649d11da4f4cbe5e24fc55b74207
genre The Cryosphere
genre_facet The Cryosphere
op_source The Cryosphere, Vol 16, Pp 2103-2114 (2022)
op_relation https://tc.copernicus.org/articles/16/2103/2022/tc-16-2103-2022.pdf
https://doaj.org/toc/1994-0416
https://doaj.org/toc/1994-0424
doi:10.5194/tc-16-2103-2022
1994-0416
1994-0424
https://doaj.org/article/9bc3649d11da4f4cbe5e24fc55b74207
op_doi https://doi.org/10.5194/tc-16-2103-2022
container_title The Cryosphere
container_volume 16
container_issue 5
container_start_page 2103
op_container_end_page 2114
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