Articles | Volume 17, issue 3
https://doi.org/10.5194/gmd-17-1229-2024
https://doi.org/10.5194/gmd-17-1229-2024
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

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Cited articles

Ahrens, C. D. and Henson, R.: Meteorology today : an introduction to weather, climate, and the environment, Brooks/Cole, Belmont, CA, 13th edn., IBSN 0357452070, 2021. a
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Barnes, E. A.: Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes, Geophys. Res. Lett., 40, 4734–4739, https://doi.org/10.1002/grl.50880, 2013. a
Barnes, E. A. and Fiore, A. M.: Surface ozone variability and the jet position: Implications for projecting future air quality, Geophys. Res. Lett., 40, 2839–2844, https://doi.org/10.1002/grl.50411, 2013. a
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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.
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