Articles | Volume 9, issue 7
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, Yong Hu, Dorit M. Hammerling, Yu-heng Tseng, Haiying Xu, Xiaomeng Huang, Frank O. Bryan, and Guangwen Yang


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
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.