Ocean and Climate Prediction on Parallel Super Computers

Abstract

The availability of new powerful super computers has lead to new activities in high resolution ocean prediction and data assimilation. This paper will present results from three application areas within ocean and climate modeling.

First, data assimilation systems developed for operational oceanography will be described where information from satellite remote sensing data are integrated with numerical ocean circulation models using sophisticated assimilation techniques. These systems form a backbone for operational ocean forecasting which will become a growing industry in the years to come.

The second example discusses the use of high resolution ocean circulation models applied in met-ocean studies for supporting offshore oil industry operating in deep waters down to 2000 m. These applications require huge computer resources but provide the offshore industry with environ- mental information leading to optimal design criteria for rig selection and safer operation.

Finally, in climate research, coupled ice, ocean and atmospheric models covering the entire globe are used to hindcast the climate in the past and to predict the evolution of the climate system in the future. Such computations requires the models to be run for long time periods in coupled mode and requires extensive super-computer resources.