IGPP Seminar Series

A Global View of Non-Gaussian SST Variability

by Philip Sura, Research Scientist
NOAA's Earth System Research Laboratory in Boulder, CO.

Abstract

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 is 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.
Monday, 02 April 2007
3853 Slichter Hall
Refreshments at 3:45 PM
Lecture at 4:00 PM