TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets

Ullrich, Paul A.; Zarzycki, Colin M.; McClenny, Elizabeth E.; Pinheiro, Marielle C.; Stansfield, Alyssa M.; Reed, Kevin A.

doi:https://doi.org/10.5194/gmd-14-5023-2021

Articles | Volume 14, issue 8

https://doi.org/10.5194/gmd-14-5023-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-14-5023-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 8

Methods for assessment of models

|

13 Aug 2021

Methods for assessment of models |

| 13 Aug 2021

TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets

Paul A. Ullrich, Colin M. Zarzycki, Elizabeth E. McClenny, Marielle C. Pinheiro, Alyssa M. Stansfield, and Kevin A. Reed

Model code and software

TempestExtremes v2.1 Archived Code Paul Ullrich, Colin Zarzycki, Elizabeth McClenny, Marielle Pinheiro, Alyssa Stansfield, and Kevin Reed https://doi.org/10.5281/zenodo.4385656

Short summary

TempestExtremes (TE) is a multifaceted framework for feature detection, tracking, and scientific analysis of regional or global Earth system datasets. Version 2.1 of TE now provides extensive support for nodal and areal features. This paper describes the algorithms that have been added to the TE framework since version 1.0 and gives several examples of how these can be combined to produce composite algorithms for evaluating and understanding atmospheric features.