Journal metrics

Journal metrics

  • IF value: 1.129 IF 1.129
  • IF 5-year value: 1.519 IF 5-year 1.519
  • CiteScore value: 1.54 CiteScore 1.54
  • SNIP value: 0.798 SNIP 0.798
  • SJR value: 0.610 SJR 0.610
  • IPP value: 1.41 IPP 1.41
  • h5-index value: 21 h5-index 21
  • Scimago H index value: 48 Scimago H index 48
Volume 25, issue 3 | Copyright

Special issue: Numerical modeling, predictability and data assimilation in...

Nonlin. Processes Geophys., 25, 605-631, 2018
https://doi.org/10.5194/npg-25-605-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 30 Aug 2018

Research article | 30 Aug 2018

Comparison of stochastic parameterizations in the framework of a coupled ocean–atmosphere model

Jonathan Demaeyer and Stéphane Vannitsem Jonathan Demaeyer and Stéphane Vannitsem
  • Royal Meteorological Institute of Belgium, Avenue Circulaire, 3, 1180 Brussels, Belgium

Abstract. A new framework is proposed for the evaluation of stochastic subgrid-scale parameterizations in the context of the Modular Arbitrary-Order Ocean-Atmosphere Model (MAOOAM), a coupled ocean–atmosphere model of intermediate complexity. Two physically based parameterizations are investigated – the first one based on the singular perturbation of Markov operators, also known as homogenization. The second one is a recently proposed parameterization based on Ruelle's response theory. The two parameterizations are implemented in a rigorous way, assuming however that the unresolved-scale relevant statistics are Gaussian. They are extensively tested for a low-order version known to exhibit low-frequency variability (LFV), and some preliminary results are obtained for an intermediate-order version. Several different configurations of the resolved–unresolved-scale separations are then considered. Both parameterizations show remarkable performances in correcting the impact of model errors, being even able to change the modality of the probability distributions. Their respective limitations are also discussed.

Download & links
Publications Copernicus
Special issue
Download
Short summary
We investigate the modeling of the effects of the unresolved scales on the large scales of the coupled ocean–atmosphere model MAOOAM. Two different physically based stochastic methods are considered and compared, in various configurations of the model. Both methods show remarkable performances and are able to model fundamental changes in the model dynamics. Ways to improve the parameterizations' implementation are also proposed.
We investigate the modeling of the effects of the unresolved scales on the large scales of the...
Citation
Share