Articles | Volume 14, issue 8
Geosci. Model Dev., 14, 5023–5048, 2021
https://doi.org/10.5194/gmd-14-5023-2021
Geosci. Model Dev., 14, 5023–5048, 2021
https://doi.org/10.5194/gmd-14-5023-2021

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 et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2020-303', Hristo Chipilski, 07 Feb 2021
    • AC1: 'Reply on RC1', Paul Ullrich, 22 Jun 2021
  • RC2: 'Comment on gmd-2020-303', Anonymous Referee #2, 26 May 2021
    • AC2: 'Reply on RC2', Paul Ullrich, 22 Jun 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Paul Ullrich on behalf of the Authors (22 Jun 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (25 Jun 2021) by Fabien Maussion
RR by Anonymous Referee #2 (11 Jul 2021)
ED: Publish subject to technical corrections (11 Jul 2021) by Fabien Maussion
AR by Paul Ullrich on behalf of the Authors (16 Jul 2021)  Author's response    Manuscript
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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.