Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 3
Articles | Volume 17, issue 3
https://doi.org/10.5194/gmd-17-1229-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-1229-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 3
Model evaluation paper
 | 
14 Feb 2024
Model evaluation paper |  | 14 Feb 2024

jsmetrics v0.2.0: a Python package for metrics and algorithms used to identify or characterise atmospheric jet streams

Tom Keel, Chris Brierley, and Tamsin Edwards

Viewed

Total article views: 1,201 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
882 262 57 1,201 49 44
  • HTML: 882
  • PDF: 262
  • XML: 57
  • Total: 1,201
  • BibTeX: 49
  • EndNote: 44
Views and downloads (calculated since 12 Jun 2023)
Cumulative views and downloads (calculated since 12 Jun 2023)

Viewed (geographical distribution)

Total article views: 1,201 (including HTML, PDF, and XML) Thereof 1,181 with geography defined and 20 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 26 Jul 2024
Download
Short summary
Jet streams are an important control on surface weather as their speed and shape can modify the properties of weather systems. Establishing trends in the operation of jet streams may provide some indication of the future of weather in a warming world. Despite this, it has not been easy to establish trends, as many methods have been used to characterise them in data. We introduce a tool containing various implementations of jet stream statistics and algorithms that works in a standardised manner.
Read more