Particle tracking and Lagrangian statistics related to: "Significant interannual variability and potential predictability of Arctic surface drift pathways"
These files are related to a study of surface drift in the Arctic ocean. See the accompanying journal paper for more info or contact Chris Wilson (cwi@noc.ac.uk). More details are given in README.txt. Acknowledgements This work resulted from the Advective Pathways of nutrients and key Ecological sub...
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ftzenodo:oai:zenodo.org:1118998 2024-09-15T17:53:25+00:00 Particle tracking and Lagrangian statistics related to: "Significant interannual variability and potential predictability of Arctic surface drift pathways" Wilson, Chris Aksenov, Yevgeny Rynders, Stefanie Kelly, Stephen Krumpen, Thomas Coward, Andrew C. 2020-08-25 https://doi.org/10.5281/zenodo.1118998 eng eng Zenodo https://doi.org/10.5281/zenodo.1118997 https://doi.org/10.5281/zenodo.1118998 oai:zenodo.org:1118998 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode Arctic ice ocean surface drift particle Lagrangian flow coherent structure predictability dispersion pollution polar NEMO ARIANE IceTrack MOSAiC APEAR CAO info:eu-repo/semantics/other 2020 ftzenodo https://doi.org/10.5281/zenodo.111899810.5281/zenodo.1118997 2024-07-27T07:00:18Z These files are related to a study of surface drift in the Arctic ocean. See the accompanying journal paper for more info or contact Chris Wilson (cwi@noc.ac.uk). More details are given in README.txt. Acknowledgements This work resulted from the Advective Pathways of nutrients and key Ecological substances in the Arctic (APEAR) project (NE/R012865/1, NE/R012865/2), part of the Changing Arctic Ocean programme, jointly funded by the UKRI Natural Environment Research Council (NERC) and the German Federal Ministry of Education and Research (BMBF). This work also used the ARCHER UK National Supercomputing Service and JASMIN, the UK collaborative data analysis facility. Satellite-based sea ice tracking was carried out as part of the Russian-German Research Cooperation QUARCCS funded by the German Ministry for Education and Research (BMBF) under grant 03F0777A. This study was carried out as part of the international Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) with the tag MOSAiC20192020 (AWI_PS122_1 and AF-MOSAiC-1_00). Other/Unknown Material Arctic Ocean Sea ice Zenodo |
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English |
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Arctic ice ocean surface drift particle Lagrangian flow coherent structure predictability dispersion pollution polar NEMO ARIANE IceTrack MOSAiC APEAR CAO |
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Arctic ice ocean surface drift particle Lagrangian flow coherent structure predictability dispersion pollution polar NEMO ARIANE IceTrack MOSAiC APEAR CAO Wilson, Chris Aksenov, Yevgeny Rynders, Stefanie Kelly, Stephen Krumpen, Thomas Coward, Andrew C. Particle tracking and Lagrangian statistics related to: "Significant interannual variability and potential predictability of Arctic surface drift pathways" |
topic_facet |
Arctic ice ocean surface drift particle Lagrangian flow coherent structure predictability dispersion pollution polar NEMO ARIANE IceTrack MOSAiC APEAR CAO |
description |
These files are related to a study of surface drift in the Arctic ocean. See the accompanying journal paper for more info or contact Chris Wilson (cwi@noc.ac.uk). More details are given in README.txt. Acknowledgements This work resulted from the Advective Pathways of nutrients and key Ecological substances in the Arctic (APEAR) project (NE/R012865/1, NE/R012865/2), part of the Changing Arctic Ocean programme, jointly funded by the UKRI Natural Environment Research Council (NERC) and the German Federal Ministry of Education and Research (BMBF). This work also used the ARCHER UK National Supercomputing Service and JASMIN, the UK collaborative data analysis facility. Satellite-based sea ice tracking was carried out as part of the Russian-German Research Cooperation QUARCCS funded by the German Ministry for Education and Research (BMBF) under grant 03F0777A. This study was carried out as part of the international Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) with the tag MOSAiC20192020 (AWI_PS122_1 and AF-MOSAiC-1_00). |
format |
Other/Unknown Material |
author |
Wilson, Chris Aksenov, Yevgeny Rynders, Stefanie Kelly, Stephen Krumpen, Thomas Coward, Andrew C. |
author_facet |
Wilson, Chris Aksenov, Yevgeny Rynders, Stefanie Kelly, Stephen Krumpen, Thomas Coward, Andrew C. |
author_sort |
Wilson, Chris |
title |
Particle tracking and Lagrangian statistics related to: "Significant interannual variability and potential predictability of Arctic surface drift pathways" |
title_short |
Particle tracking and Lagrangian statistics related to: "Significant interannual variability and potential predictability of Arctic surface drift pathways" |
title_full |
Particle tracking and Lagrangian statistics related to: "Significant interannual variability and potential predictability of Arctic surface drift pathways" |
title_fullStr |
Particle tracking and Lagrangian statistics related to: "Significant interannual variability and potential predictability of Arctic surface drift pathways" |
title_full_unstemmed |
Particle tracking and Lagrangian statistics related to: "Significant interannual variability and potential predictability of Arctic surface drift pathways" |
title_sort |
particle tracking and lagrangian statistics related to: "significant interannual variability and potential predictability of arctic surface drift pathways" |
publisher |
Zenodo |
publishDate |
2020 |
url |
https://doi.org/10.5281/zenodo.1118998 |
genre |
Arctic Ocean Sea ice |
genre_facet |
Arctic Ocean Sea ice |
op_relation |
https://doi.org/10.5281/zenodo.1118997 https://doi.org/10.5281/zenodo.1118998 oai:zenodo.org:1118998 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.111899810.5281/zenodo.1118997 |
_version_ |
1810295512066162688 |