Data Assimilation and Inversion Developing Stochastic and Deterministic Data Assimilation and Inversion methods for Fluid Earth Analysis and Prediction Red Sea Studies Modeling, Analyzing, and Predicting the Circulation, the climate and the ecology of the Red Sea Coastal Ocean Predictions Prediction and Uncertainty Quantification of Advanced Predictive Models of Extreme Events in the Coastal Ocean Subsurface Flow and Contamination Management Management of Subsurface Flow and Contamination Using Nonlinear Bayesian/Kalman Data Assimilation |
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Our group work at analyzing, predicting, and quantifying the uncertainties of fluid systems with focus on large-scale earth sciences applications. The group members have expertise in data assimilation and inversion methods, ocean physics and modeling, and ground fluid modeling and history matching. Our research activities at KAUST can be summarized in three main fields, which we are working on in close collaboration with several international institutes in the US and Europe:- Development of efficient stochastic and deterministic data assimilation and inversion methods for large-scale nonlinear problems. We are mainly interested in the application of the full Bayesian estimation theory to large dimensional problems and the control of chaotic systems.
- Application of data assimilation, inversion, and uncertainty quantification methods to fluid earth problems. Currently, the group is involved in ocean, atmosphere, groundwater and reservoir applications.
- Modeling, remote sensing and physical oceanography of the Saudi Seas, with focus on the Red Sea circulation and climate.