Applying the fluctuation-dissipation theorem to a two-layer model of quasigeostrophic turbulence

Nicholas J. Lutsko, Isaac M. Held, Pablo Zurita-Gotor

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

The fluctuation-dissipation theorem (FDT) provides a means of calculating the response of a dynamical system to a small force by constructing a linear operator that depends only on data from the internal variability of the unperturbed system. Here the FDT is used to estimate the response of a two-layer quasigeostrophic model to two zonally symmetric torques, both barotropic, with the same sign of the forcing in the two layers, and baroclinic, with opposite sign forcing in the two layers. The supercriticality of the model is also varied to test how the FDT fares, as this parameter is varied. To perform the FDT calculations the data are decomposed onto empirical orthogonal functions (EOFs) and only those EOFs that are well resolved are retained in the FDT calculations. In the barotropic case good qualitative estimates are obtained for all values of the supercriticality, though the FDT consistently overestimates the response, perhaps because of significant non-Gaussian behavior present in the model. Nevertheless, this adds to the evidence that the annular-mode time scale plays an important role in determining the response of the midlatitudes to small perturbations. The baroclinic case is more challenging for the FDT. However, by constructing different bases with which to calculate the EOFs, it is shown that the issue in this case is that the baroclinic variability is poorly sampled, not that the FDT fails. The strategies developed in order to generate these estimates may be applicable to situations in which the FDT is applied to larger systems.

Original languageEnglish (US)
Pages (from-to)3161-3177
Number of pages17
JournalJournal of the Atmospheric Sciences
Volume72
Issue number8
DOIs
StatePublished - 2015

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Keywords

  • Dynamics
  • Empirical orthogonal functions
  • Large-scale motions
  • Nonlinear dynamics
  • Storm tracks

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