GCM-Filters: A Python Package for Diffusion-based Spatial Filtering of Gridded Data

Python Submitted 05 November 2021 • Published 11 February 2022
Software repository Paper review Download paper Software archive
Review

Editor: @elbeejay (all papers)
Reviewers: @callumrollo (all reviews), @AleksiNummelin (all reviews), @isgiddy (all reviews)

Authors

Nora Loose (0000-0002-3684-9634), Ryan Abernathey (0000-0001-5999-4917), Ian Grooms (0000-0002-4678-7203), Julius Busecke (0000-0001-8571-865X), Arthur Guillaumin (0000-0003-1571-4228), Elizabeth Yankovsky (0000-0003-3612-549X), Gustavo Marques (0000-0001-7238-0290), Jacob Steinberg (0000-0002-2609-6405), Andrew Slavin Ross (0000-0002-2368-6979), Hemant Khatri (0000-0001-6559-9059), Scott Bachman (0000-0002-6479-4300), Laure Zanna (0000-0002-8472-4828), Paige Martin (0000-0003-3538-633X)

Citation

Loose et al., (2022). GCM-Filters: A Python Package for Diffusion-based Spatial Filtering of Gridded Data. Journal of Open Source Software, 7(70), 3947, https://doi.org/10.21105/joss.03947

Copy citation string · Copy BibTeX  
Tags

ocean modeling climate modeling fluid dynamics

Altmetrics
Markdown badge

 

License

Authors of JOSS papers retain copyright.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License

Journal of Open Source Software is an affiliate of the Open Source Inititative.

Journal of Open Source Software is part of Open Journals, which is a NumFOCUS-sponsored project.

Public user content licensed CC BY 4.0 unless otherwise specified.
ISSN 2475-9066