| Abstract: Sea surface temperature (SST) and salinity (SSS) time
series from four ocean weather stations and data from an integration of
the GFDL coupled ocean-atmosphere model are analyzed to test the applicability
of local linear stochastic theory to the mixed-layer ocean. According to
this theory, mixed-layer variability away from coasts and fronts can be
explained as a 'red noise' response to the 'white noise' forcing by atmospheric
disturbances. At one weather station, Papa (northeast Pacific), this stochastic
theory can be applied to both salinity and temperature, explaining the
relative redness of the SSS spectrum. Similar results hold for a model
grid point adjacent to Papa, where the relationships between atmospheric
energy and water fluxes and actual changes in SST and SSS are what is expected
from local linear stochastic theory. At the other weather stations, this
theory cannot adequately explain mixed-layer variability. Two oceanic processes
must be taken into account: at Panulirus (near Bermuda), mesoscale eddies
enhance the observed variability at high frequencies. At Mike and India
(North Atlantic), variations in SST and SSS advection, indicated by the
coherence and equal persistence of SST and SSS anomalies, contribute to
much of the low frequency variability in the model and observations. To
achieve a global perspective, TOPEX altimeter data and model results are
used to identify regions of the ocean where these mechanisms of variability
are important. Where mesoscale eddies are as energetic as at Panulirus,
indicated by the TOPEX global distribution of sea level variability, one
would expect enhanced variability on short time scales. In regions exhibiting
signatures of variability similar to Mike and India, variations in SST
and SSS advection should dominate at low frequencies. According to the
model, this mode of variability is found in the circumpolar ocean and the
northern North Atlantic, where it is associated with the irregular oscillations
of the model's thermohaline circulation. |