Mesoscale SST–wind stress coupling in the Peru–Chile current system: Which mechanisms drive its seasonal variability?

Vera Oerder, François Colas, Vincent Echevin, Sebastien Masson, Christophe Hourdin, Swen Jullien, Gurvan Madec, Florian Lemarié

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

Satellite observations and a high-resolution regional ocean–atmosphere coupled model are used to study the air/sea interactions at the oceanic mesoscale in the Peru–Chile upwelling current system. Coupling between mesoscale sea surface temperature (SST) and wind stress (WS) intensity is evidenced and characterized by correlations and regression coefficients. Both the model and the observations display similar spatial and seasonal variability of the coupling characteristics that are stronger off Peru than off Northern Chile, in relation with stronger wind mean speed and steadiness. The coupling is also more intense during winter than during summer in both regions. It is shown that WS intensity anomalies due to SST anomalies are mainly forced by mixing coefficient anomalies and partially compensated by wind shear anomalies. A momentum balance analysis shows that wind speed anomalies are created by stress shear anomalies. Near-surface pressure gradient anomalies have a negligible contribution because of the back-pressure effect related to the air temperature inversion. As mixing coefficients are mainly unchanged between summer and winter, the stronger coupling in winter is due to the enhanced large-scale wind shear that enables a more efficient action of the turbulent stress perturbations. This mechanism is robust as it does not depend on the choice of planetary boundary layer parameterization.

Original languageEnglish
Pages (from-to)2309-2330
Number of pages22
JournalClimate Dynamics
Volume47
Issue number7-8
DOIs
StatePublished - 1 Oct 2016
Externally publishedYes

Keywords

  • Eastern Boundary Upwelling System
  • Mesoscale SST–wind stress coupling
  • Ocean–atmosphere interactions
  • Regional coupled modeling

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