The Impact of Stochastic Heat Fluxes on Sea Surface Temperature Variability and Atmosphere-Ocean Coupling

Philip Sura

In this talk we study the impact of rapidly-varying (effectively stochastic) sea surface heat fluxes on sea surface temperature (SST) variability and atmosphere-ocean coupling. As stressed by many previous investigators, the clear separation between the dynamical timescales of the ocean and atmosphere allows a simple paradigm for much air-sea interaction in which the rapidly varying component of surface heat fluxes is approximated by a stochastic term. In many previous studies this stochastic heat flux term is approximated by Gaussian white-noise with fixed variance (that is, additive noise). However, as shown from first principles, this stochastic heat flux term depends upon not only the fast atmosphere but also upon the slow ocean. Such state-dependent (multiplicative) noise can alter the dynamics of SST variability and atmosphere-ocean coupling because it induces an additional heat flux term (the noise-induced drift).

As a test of this hypothesis, daily observations at several Ocean Weather Stations are examined in a novel stochastic framework. The classical stochastic view with additive noise implies that SST (and air temperature; TAIR) anomalies obey a Gaussian distribution. However, the observations from Ocean Weather Stations reveal that probability distribution functions (PDFs) of daily averaged SST and TAIR anomalies are actually significantly non-Gaussian. It is shown that it is the state-dependent character of the rapidly-varying boundary-layer heat fluxes that appear to be responsible for the observed non-Gaussianity of SST and TAIR anomalies. It is concluded that the effect of state-dependent noise is crucial to understand and model SST variability and atmosphere-ocean coupling.

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