Constraining Earth Fluid Motion Models with Satellite Images

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Project Description

Developing exact mathematical models to stimulate and predict oceanic and atmospheric motions is a difficult process because of the complex multi-physical intereactions. Satellite images provide a powerful tool to extract in detail some information at various scales that could be used to reduce the uncertainies in the numerical models. Constraining the models with those images requires introducing some physical knowledge about the studied motion. The goal of this project is to study approaches that would allow to directly contraining and calibrating numerical models with structures extracted from images.​​​​​​
Program - Applied Mathematics and Computer Science
Division - Physical Sciences and Engineering
Field of Study - ​​Applied Mathematics, Earth Sciences and Engineering, Electric Engineering or any related field.

About the
Researcher

Ibrahim Hoteit

Professor, Earth Science and Engineering

Ibrahim Hoteit

My research involves the effective use and integration of dynamical models and observations to simulate, study and predict realistic geophysical fluid systems. This involves developing and implementing numerical models and data inversion, assimilation, and uncertainty quantification techniques suitable for large scale applications. I am currently focusing on developing an integrated data-driven modeling system to simulate and predict the circulation and the climate of the Saudi marginal seas: the Red Sea and the Arabian Gulf.

Desired Project Deliverables

​Literature review of images assimilation methods. Explore and study the efficiency of ensemble Kalman flitering methods for images assimilation. Implement and assess performance with numberical test models (e.g. Shallow water)​​