Institute for Computational Engineering and Sciences (ICES) | University of Texas at Austin/ USA
The Mean Dynamic Topography (MDT) and its time variable component (DOT) describe ocean dynamics in space and time and support climate modelling and sea level studies. There are two ways to determine them. The geodetic method requires a spectral consistent high-resolution ocean geoid and a geometric description of the sea surface, while the oceanographic approach results from physical ocean circulation models assimilating ocean state parameters.
The project combines both approaches by making intensive use of nowadays available satellite data and by improved modelling techniques including error information. They require advanced computational methods in forward and inverse modelling and to deploy them to problems of high societal relevance (global ocean circulation, sea level change). Objectives: On the geodetic side the ocean geoid shall be computed with resolutions down to 2 km applying parallelized algorithms and tailored filter strate-gies to determine MDT/DOT accompanied by a full error description. On the oceanographic side the impact of geodetic MDT/DOT models including error descriptions in ocean circulation inverse modelling approaches shall be assessed using uncertainty quantification tools. As a result, observation-to-model and variance-error covariance operators as well as methods of optimal experimental design shall be developed in order to directly assimilate geodetic MDT/DOT into ocean circulation models, quantify their complementarity within the global observing system, and assess their impact for reducing uncertainties in key climate metrics of interest.