Eddy-Driven Jet Object data from ERA5 winters 1979-2020
Author: Jacob Perez Contact: scjp@leeds.ac.uk Paper title: A new characterization of the North Atlantic eddy-driven jet using 2-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 contain...
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ftzenodo:oai:zenodo.org:10053895 2024-09-15T18:23:07+00:00 Eddy-Driven Jet Object data from ERA5 winters 1979-2020 Perez, Jacob 2024-02-01 https://doi.org/10.5281/zenodo.10053895 unknown Zenodo https://doi.org/10.5281/zenodo.10053894 https://doi.org/10.5281/zenodo.10053895 oai:zenodo.org:10053895 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/other 2024 ftzenodo https://doi.org/10.5281/zenodo.1005389510.5281/zenodo.10053894 2024-07-25T19:37:12Z Author: Jacob Perez Contact: scjp@leeds.ac.uk Paper title: A new characterization of the North Atlantic eddy-driven jet using 2-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'])) Other/Unknown Material North Atlantic Zenodo |
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Author: Jacob Perez Contact: scjp@leeds.ac.uk Paper title: A new characterization of the North Atlantic eddy-driven jet using 2-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 |
Other/Unknown Material |
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://doi.org/10.5281/zenodo.10053895 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
https://doi.org/10.5281/zenodo.10053894 https://doi.org/10.5281/zenodo.10053895 oai:zenodo.org:10053895 |
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.1005389510.5281/zenodo.10053894 |
_version_ |
1810463253046755328 |