Articles | Volume 14, issue 8
https://doi.org/10.5194/gmd-14-5023-2021
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, Colin M. Zarzycki, Elizabeth E. McClenny, Marielle C. Pinheiro, Alyssa M. Stansfield, and Kevin A. Reed

Download

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 | EF: Editorial file upload
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 
Download
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.