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...

Full description

Bibliographic Details
Main Author: Perez, Jacob
Format: Other/Unknown Material
Language:unknown
Published: Zenodo 2024
Subjects:
Online Access:https://doi.org/10.5281/zenodo.10053895
id ftzenodo:oai:zenodo.org:10053895
record_format openpolar
spelling 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
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
description 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