Eddy-Driven Jet Object data from ERA5 winters 1979-2020 ...
Author: Jacob PerezContact: scjp@leeds.ac.uk Paper title: A new characterization of the North Atlantic eddy-driven jet using2-dimensional moment analysis Code used to generate this data can be found at https://github.com/scjpleeds/EDJO-identification. Information about data: Each .npy file contains...
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Online Access: | https://dx.doi.org/10.5281/zenodo.10053894 https://zenodo.org/doi/10.5281/zenodo.10053894 |
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ftdatacite:10.5281/zenodo.10053894 2024-03-31T07:54:16+00:00 Eddy-Driven Jet Object data from ERA5 winters 1979-2020 ... Perez, Jacob 2024 https://dx.doi.org/10.5281/zenodo.10053894 https://zenodo.org/doi/10.5281/zenodo.10053894 unknown Zenodo https://dx.doi.org/10.5281/zenodo.10053895 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 dataset Dataset 2024 ftdatacite https://doi.org/10.5281/zenodo.1005389410.5281/zenodo.10053895 2024-03-04T11:25:53Z Author: Jacob PerezContact: scjp@leeds.ac.uk Paper title: A new characterization of the North Atlantic eddy-driven jet using2-dimensional moment analysis Code used to generate this data can be found at https://github.com/scjpleeds/EDJO-identification. Information about data: Each .npy file contains the variable data for the winters (December, January and February) between 1979/80-2019/2020, in a daily format. File names containing *_lm.npz contain data defined by the largest mass EDJO on each day. File names containing *_full.npz contain EDJO data for days with two objects or more. Array lengths are 3701. Loading and Accessing the data: Accessing data from the largest mass can be done by, data = np.load(filename). To list all variables in a file, print(data.files). Once the data is loaded you can access the relevant variable by, phibar = np.squeeze(np.vstack(data['phibar'])) ... Dataset North Atlantic DataCite Metadata Store (German National Library of Science and Technology) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
description |
Author: Jacob PerezContact: scjp@leeds.ac.uk Paper title: A new characterization of the North Atlantic eddy-driven jet using2-dimensional moment analysis Code used to generate this data can be found at https://github.com/scjpleeds/EDJO-identification. Information about data: Each .npy file contains the variable data for the winters (December, January and February) between 1979/80-2019/2020, in a daily format. File names containing *_lm.npz contain data defined by the largest mass EDJO on each day. File names containing *_full.npz contain EDJO data for days with two objects or more. Array lengths are 3701. Loading and Accessing the data: Accessing data from the largest mass can be done by, data = np.load(filename). To list all variables in a file, print(data.files). Once the data is loaded you can access the relevant variable by, phibar = np.squeeze(np.vstack(data['phibar'])) ... |
format |
Dataset |
author |
Perez, Jacob |
spellingShingle |
Perez, Jacob Eddy-Driven Jet Object data from ERA5 winters 1979-2020 ... |
author_facet |
Perez, Jacob |
author_sort |
Perez, Jacob |
title |
Eddy-Driven Jet Object data from ERA5 winters 1979-2020 ... |
title_short |
Eddy-Driven Jet Object data from ERA5 winters 1979-2020 ... |
title_full |
Eddy-Driven Jet Object data from ERA5 winters 1979-2020 ... |
title_fullStr |
Eddy-Driven Jet Object data from ERA5 winters 1979-2020 ... |
title_full_unstemmed |
Eddy-Driven Jet Object data from ERA5 winters 1979-2020 ... |
title_sort |
eddy-driven jet object data from era5 winters 1979-2020 ... |
publisher |
Zenodo |
publishDate |
2024 |
url |
https://dx.doi.org/10.5281/zenodo.10053894 https://zenodo.org/doi/10.5281/zenodo.10053894 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
https://dx.doi.org/10.5281/zenodo.10053895 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.5281/zenodo.1005389410.5281/zenodo.10053895 |
_version_ |
1795035022843969536 |