18.3
A Global View of Non-Gaussian SST Variability
Philip Sura, NOAA/CIRES, Boulder, CO; and P. D. Sardeshmukh
The skewness and kurtosis of daily sea surface temperature (SST) variations are found to be strongly linked at most locations around the globe in a new high-resolution observational dataset, and are analyzed in terms of a simple stochastically forced mixed-layer ocean model. The analytic theory yields results in remarkable good agreement with observations, strongly suggesting that a univariate linear model of daily SST variations with a mixture of SST-independent (additive) and SST-dependent (multiplicative) noise forcing is sufficient to account for the skewness-kurtosis link. Such a model of non-Gaussian SST dynamics should be useful in predicting extreme events in climate, as many important weather and climate phenomena, such as hurricanes, ENSO, and the NAO depend on a detailed knowledge of the underlying local SSTs. .
Session 18, Dynamics of the Coupled Ocean-Atmosphere System
Friday, 29 June 2007, 1:30 PM-3:00 PM, Ballroom South
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