Articles | Volume 9, issue 7
Geosci. Model Dev., 9, 2391–2406, 2016
https://doi.org/10.5194/gmd-9-2391-2016
Geosci. Model Dev., 9, 2391–2406, 2016
https://doi.org/10.5194/gmd-9-2391-2016

Development and technical paper 12 Jul 2016

Development and technical paper | 12 Jul 2016

Evaluating statistical consistency in the ocean model component of the Community Earth System Model (pyCECT v2.0)

Allison H. Baker et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Allison H. Baker on behalf of the Authors (18 Apr 2016)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (27 Apr 2016) by Julia Hargreaves
RR by Anonymous Referee #1 (16 May 2016)
ED: Publish subject to minor revisions (Editor review) (25 May 2016) by Julia Hargreaves
AR by Allison H. Baker on behalf of the Authors (03 Jun 2016)  Author's response    Manuscript
ED: Publish as is (13 Jun 2016) by Julia Hargreaves
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Short summary
Software quality assurance is critical to detecting errors in large, complex climate simulation codes. We focus on ocean model simulation data in the context of an ensemble-based statistical consistency testing approach developed for atmospheric data. Because ocean and atmosphere models have differing characteristics, we develop a new statistical tool to evaluate ocean model simulation data that provide a simple, subjective, and systematic way to detect errors and instil model confidence.