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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Chekroun, M. D., Liu, H., and Wang, S.: Approximation of Stochastic Invariant Manifolds, SpringerBriefs in Mathematics, Springer International Publishing, Cham, Switzerland, 2015a.
Chekroun, M. D., Liu, H., and Wang, S.: Stochastic Parameterizing Manifolds and Non-Markovian Reduced Equations, SpringerBriefs in Mathematics, Springer International Publishing, Cham, Switzerland, 2015b.
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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.