The impact of assimilating along-track SLA data on simulated Eddy characteristics in the Agulhas system

• Main Author: De Vos, Marc
• Other Authors: Backeberg, Björn, Counillon, François
• Format: Master Thesis
• Language: English
• Published: University of Cape Town 2016
• Subjects: Ocean and Climate Science; Indian; South Atlantic Ocean
• Online Access: http://hdl.handle.net/11427/20503; https://open.uct.ac.za/bitstream/11427/20503/1/thesis_sci_2016_de_vos_marc.pdf

The Agulhas Current System is a vital element of the global ocean-climate system by virtue of its role in the transfer of energy, nutrients and organic material. In the context of working towards better climate change projections, it is necessary to develop a robust understanding of the complex dynamical mechanisms which facilitate this transfer. Mesoscale cyclonic and anticyclonic eddies transport heat, salt, organic matter and nutrients from the Indian Ocean into the South Atlantic Ocean. In so doing, they are key drivers of the Atlantic Meridional Overturning Circulation (AMOC). As such, it is important that they are adequately simulated by numerical models in order to advance the accuracy of climate prediction. In the absence of spatially and temporally coherent observing systems, numerical models provide the capacity to describe the oceanographic conditions of the region. Given the complexity of the regional dynamics, and the challenges it presents to free-running numerical models, data assimilation is a valuable tool in improving simulation quality. An important step in this continuing process is the objective, quantitative evaluation of model configurations, such that they can be continuously refined. In this study, the impact of assimilating along-track sea level anomaly (SLA) data is investigated with regard to the simulation of mesoscale eddies in the Agulhas System. Two configurations of a Hybrid Coordinate Ocean Model (HYCOM) configuration are analysed; one free run (hereafter 'Free') and one with along-track SLA data from satellite altimetry assimilated (hereafter 'Assim.') via an Ensemble Optimal Interpolation (EnOI) data assimilation scheme. The results of these two configurations are compared with each other, and against a set of corresponding observational data from satellite altimetry (hereafter 'Aviso'). To this end, an automatic eddy detection and tracking algorithm is implemented, in order to quantify eddy characteristics in a coherent and consistent manner.