Stochastic superparameterization in a quasigeostrophic model of the Antarctic Circumpolar Current

Research output: Contribution to journalArticle

Abstract

Stochastic superparameterization, a stochastic parameterization framework based on a multiscale formalism, is developed for mesoscale eddy parameterization in coarse-resolution ocean modeling. The framework of stochastic superparameterization is reviewed and several configurations are implemented and tested in a quasigeostrophic channel model - an idealized representation of the Antarctic Circumpolar Current. Five versions of the Gent-McWilliams (GM) parameterization are also implemented and tested for comparison. Skill is measured using the time-mean and temporal variability separately, and in combination using the relative entropy in the single-point statistics. Among all the models, those with the more accurate mean state have the less accurate variability, and vice versa. Stochastic superparameterization results in improved climate fidelity in comparison with GM parameterizations as measured by the relative entropy. In particular, configurations of stochastic superparameterization that include stochastic Reynolds stress terms in the coarse model equations, corresponding to kinetic energy backscatter, perform better than models that only include isopycnal height smoothing.

Original languageEnglish (US)
Pages (from-to)1-15
Number of pages15
JournalOcean Modelling
Volume85
DOIs
StatePublished - Oct 28 2014

Fingerprint

circumpolar current
Parameterization
parameterization
entropy
Entropy
mesoscale eddy
smoothing
Kinetic energy
backscatter
kinetic energy
Statistics
climate
ocean
modeling
comparison

Keywords

  • Mesoscale parameterization
  • Southern ocean
  • Stochastic parameterization
  • Superparameterization

ASJC Scopus subject areas

  • Atmospheric Science
  • Oceanography
  • Geotechnical Engineering and Engineering Geology
  • Computer Science (miscellaneous)

Cite this

Stochastic superparameterization in a quasigeostrophic model of the Antarctic Circumpolar Current. / Grooms, Ian; Majda, Andrew J.; Smith, K. Shafer.

In: Ocean Modelling, Vol. 85, 28.10.2014, p. 1-15.

Research output: Contribution to journalArticle

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