Articles | Volume 17, issue 15
https://doi.org/10.5194/gmd-17-6035-2024
https://doi.org/10.5194/gmd-17-6035-2024
Methods for assessment of models
 | 
15 Aug 2024
Methods for assessment of models |  | 15 Aug 2024

TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets

Kelly M. Núñez Ocasio and Zachary L. Moon

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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 egusphere-2024-259', Julia Kukulies, 30 Mar 2024
  • RC2: 'Comment on egusphere-2024-259', Anonymous Referee #2, 01 May 2024
  • EC1: 'Reviewer 3 comments', Peter Caldwell, 15 May 2024
  • AC1: 'AC Response', Kelly Núñez Ocasio, 10 Jun 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Kelly Núñez Ocasio on behalf of the Authors (10 Jun 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (19 Jun 2024) by Peter Caldwell
AR by Kelly Núñez Ocasio on behalf of the Authors (27 Jun 2024)
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Short summary
TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.