IMPROVED PREDICTION OF THE EFFECTS OF ANTHROPOGENIC STRESSORS IN THE GULF OF MEXICO THROUGH REGIONAL-SCALE NUMERICAL MODELING AND DATA ASSIMILATION

Abstract

The Gulf of Mexico (GOM) is of great ecological and socio-economic importance; however, its ecosystems are increasingly stressed by anthropogenic pressures. Two of the most serious are excessive nutrient inputs from land that affect the shelf in the northern GOM and lead to reoccurring extensive hypoxia, and oil exploration and extraction activities that have become more risky by increasingly extending into the deep sea leading to pollution there. Realistic physical-biogeochemical models are invaluable tools for understanding and predicting the resulting effects on the marine system, but a model’s predictive capabilities are limited by various sources of error resulting from imperfect descriptions of physical and biological processes, inaccurate forcing, uncertain initial and boundary conditions, and imprecise parameter values. Data assimilation methods that merge the information contained in observations and dynamical models are crucial for providing the most accurate views of ocean processes. This thesis aims to improve our understanding and our predictive capabilities of shelf hypoxia and movement of deep-water pollutants in the GOM through regional-scale numerical modeling and data assimilation. First, two numerical models of dissolved oxygen with different ecological complexity are applied to investigate the mechanisms controlling the development of seasonal bottom-water hypoxia on the continental shelf in the northern GOM. Next, a multivariate sequential data assimilation method, the deterministic Ensemble Kalman Filter (DEnKF), is tested in an idealized upwelling model to explore the effects of multivariate updates of physical and biogeochemical model states. Finally, the DEnKF technique is implemented in a realistic physical-hydrocarbon model of the GOM to assess the effects of data assimilation on the mesoscale circulation and the movement of a deep-water hydrocarbon plume.