James D. Dykes

Dynamics of the circulation in the Sea of Marmara: numerical modeling experiments and observations from the Turkish straits system experiment

During September 2008 and February 2009, the NR/V Alliance extensively sampled the waters of the Sea of Marmara within the framework of the Turkish Straits System (TSS) experiment coordinated by the NATO Undersea Research Centre. The observational effort provided an opportunity to set up realistic numerical experiments for modeling the observed variability of the Marmara Sea upper layer circulation at mesoscale resolution over the entire basin during the trial period, complementing relevant features and forcing factors revealed by numerical model results with information acquired from in situ and remote sensing datasets. Numerical model solutions from realistic runs using the Regional Ocean Modeling System (ROMS) produce a general circulation in the Sea of Marmara that is consistent with previous knowledge of the circulation drawn from past hydrographic measurements, with a westward meandering current associated with a recurrent large anticyclone. Additional idealized numerical experiments illuminate the role various dynamics play in determining the Sea of Marmara circulation and pycnocline structure. Both the wind curl and the strait flows are found to strongly influence the strength and location of the main mesoscale features. Large displacements of the pycnocline depth were observed during the sea trials. These displacements can be interpreted as storm-driven upwelling/downwelling dynamics associated with northeasterly winds; however, lateral advection associated with flow from the Straits also played a role in some displacements.

Spatial Error Metrics for Oceanographic Model Verification

AbstractA common problem with modern numerical oceanographic models is spatial displacement, including misplacement and misshapenness of ocean circulation features. Traditional error metrics, such as least squares methods, are ineffective in many such cases; for example, only small errors in the location of a frontal pattern are translated to large differences in least squares of intensities. Such problems are common in meteorological forecast verification as well, so the application of spatial error metrics have been a recently popular topic there. Spatial error metrics separate model error into a displacement component and an intensity component, providing a more reliable assessment of model biases and a more descriptive portrayal of numerical model prediction skill. The application of spatial error metrics to oceanographic models has been sparse, and further advances for both meteorology and oceanography exist in the medical imaging field. These advances are presented, along with modifications necessar...