Articles | Volume 25, issue 2
https://doi.org/10.5194/npg-25-413-2018
https://doi.org/10.5194/npg-25-413-2018
Research article
 | 
19 Jun 2018
Research article |  | 19 Jun 2018

Evaluating a stochastic parametrization for a fast–slow system using the Wasserstein distance

Gabriele Vissio and Valerio Lucarini

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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 Gabriele Vissio on behalf of the Authors (08 May 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (09 May 2018) by Juan Manuel Lopez
RR by Anonymous Referee #2 (24 May 2018)
ED: Publish subject to minor revisions (review by editor) (24 May 2018) by Juan Manuel Lopez
AR by Gabriele Vissio on behalf of the Authors (30 May 2018)  Author's response    Manuscript
ED: Publish as is (04 Jun 2018) by Juan Manuel Lopez
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Short summary
Constructing good parametrizations is key when studying multi-scale systems. We consider a low-order model and derive a parametrization via a recently developed statistical mechanical approach. We show how the method allows for seamlessly treating the case when the unresolved dynamics is both faster and slower than the resolved one. We test the skill of the parametrization by using the formalism of the Wasserstein distance, which allows for measuring how different two probability measures are.