Energy flux into internal lee waves: Sensitivity to future climate changes using linear theory and a climate model

Angélique Melet, Robert Hallberg, Alistair Adcroft, Maxim Nikurashin, Sonya Legg

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Internal lee waves generated by geostrophic flows over rough topography are thought to be a significant energy sink for eddies and energy source for deep ocean mixing. The sensitivity of the energy flux into lee waves from preindustrial, present, and possible future climate conditions is explored in this study using linear theory. The bottom stratification and geostrophic velocity fields needed for the calculation of the energy flux into lee waves are provided by Geophysical Fluid Dynamics Laboratory's global coupled ocean-ice-atmosphere model, CM2G. The unresolved mesoscale eddy energy is parameterized as a function of the large-scale available potential energy. Simulations using historical and representative concentration pathway (RCP) scenarios were performed over the 1861-2200 period. The diagnostics herein suggest a decrease of the global energy flux into lee waves on the order of 20% from preindustrial to future climate conditions under the RCP8.5 scenario. In the Southern Ocean, the energy flux into lee waves exhibits a clear annual cycle with maximum values in austral winter. The long-term decrease of the global energy flux into lee waves and the annual cycle of the energy flux in the Southern Ocean are mostly due to changes in bottom velocity.

Original languageEnglish (US)
Pages (from-to)2365-2384
Number of pages20
JournalJournal of Climate
Volume28
Issue number6
DOIs
StatePublished - 2015

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Keywords

  • Bottom currents
  • Climate models
  • Eddies
  • Mountain waves
  • Ocean dynamics
  • Parameterization

Fingerprint

Dive into the research topics of 'Energy flux into internal lee waves: Sensitivity to future climate changes using linear theory and a climate model'. Together they form a unique fingerprint.

Cite this