Statistical Modeling in Oceanography

This project develops new statistical approaches for the analysis of ocean circulation data and prediction of the ocean's influence on weather. In the first part of the project, Bayesian hierarchical methods are devised

for assimilating hydrographic data into ocean circulation models. In the second part of the project, Bayesian semiparametric regression models are used to produce improved forecasts of heating-degree day probability density functions.