Data Assimilation into large dimensional systems


Project Description

Develop and test efficient data assimilation (such as ensemble Kalman and particle filters and smoothers, 4DVAR, etc) schemes for state and parameters estimation of large dimensional systems. Numerical experiments will be conducted with simplified atmospheric, oceanic, or hydrological models.​
Program - Earth Science and Engineering
Division - Physical Sciences and Engineering
Field of Study - ​Applied Mathematics, Electrical Engineering, Mechanical Engineering, or any related field​

About the

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

​Report and presentation