sympl (v. 0.4.0) and climt (v. 0.15.3) – towards a flexible framework for building model hierarchies in Python

Monteiro, Joy Merwin; McGibbon, Jeremy; Caballero, Rodrigo

doi:https://doi.org/10.5194/gmd-11-3781-2018

Articles | Volume 11, issue 9

https://doi.org/10.5194/gmd-11-3781-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-11-3781-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 11, issue 9

Model description paper

| Highlight paper

|

18 Sep 2018

Model description paper | Highlight paper |

| 18 Sep 2018

sympl (v. 0.4.0) and climt (v. 0.15.3) – towards a flexible framework for building model hierarchies in Python

Joy Merwin Monteiro, Jeremy McGibbon, and Rodrigo Caballero

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Final revised paper (published on 18 Sep 2018)
Supplement to the final revised paper
Preprint (discussion started on 26 Apr 2018)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

SC1: 'Code Availability', Lutz Gross, 04 May 2018
RC1: 'Formal review', Spencer Hill, 25 May 2018
RC2: 'Formal Review', Anonymous Referee #2, 26 May 2018
AC1: 'Response to Formal Reviews and the Short Comment', Joy Monteiro, 20 Jul 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Joy Monteiro on behalf of the Authors (20 Aug 2018) Author's response Manuscript

ED: Publish as is (23 Aug 2018) by Carlos Sierra

AR by Joy Monteiro on behalf of the Authors (31 Aug 2018)

Short summary

In the same way that the fruit fly or the yeast cell serve as model systems in biology, climate scientists use a range of computer models to gain a fundamental understanding of our climate system. These models range from extremely simple models that can run on your phone to those that require supercomputers. Sympl and climt are packages that make it easy for climate scientists to build a hierarchy of such models using Python, which facilitates easy to read and self-documenting models.