Naila Raboudi

Postdoctoral Fellow

Postdoctoral Fellow

Current

Social Profile:

Research Interests

​Naila's research focuses on advancing Bayesian data assimilation (DA) techniques to address the complexities of filtering and smoothing in large-dimensional estimation problems. She is investigating innovative variants of the ensemble Kalman filter (EnKF) tailored to handle challenging real-world scenarios such as storm surge forecasting, one-way coupled systems, and ocean circulation predictions. Her research further expands to encompass more general large-dimensional DA problems, including for example systems with time-varying observation errors, for which she developed strategies enabling an efficient incorporation and a real-time estimation of these parameters alongside the system state. She is also actively exploring the practical application of these methodologies to oceanic DA problems, such as generating a long-term high-resolution reanalysis of the Arabian Gulf circulation to provide a comprehensive understanding of the historical 3D spatiotemporal dynamics of the region.

Selected Publications

1- Ensemble kalman filtering with one-step-ahead smoothing/ Naila F. Raboudi, Boujemaa Ait-El-Fquih, and Ibrahim Hoteit/ Monthly Weather Review, 2018/ https://doi.org/10.1175/MWR-D-17-0175.1

2- Combining Hybrid and One-Step-Ahead Smoothing for Efficient Short-Range Storm Surge Forecasting with an Ensemble Kalman Filter/ Naila F. Raboudi, Boujemaa Ait-El-Fquih, Clint Dawson, and Ibrahim Hoteit/ Monthly Weather Review, 2019/ https://doi.org/10.1175/MWR-D-18-0410.1

3- A hybrid ensemble adjustment Kalman filter based high-resolution data assimilation system for the Red Sea: Implementation and evaluation/ Habib Toye, Sivareddy Sanikommu, Naila F. Raboudi and Hoteit, Ibrahim/ Quarterly Journal of the Royal Meteorological Society, 2020/ https://doi.org/10.1002/qj.3894

4- Enhancing ensemble data assimilation into one-way-coupled models with one-step-ahead smoothing/ Naila F. Raboudi, Boujemaa Ait-El-Fquih, Aneesh C. Subramanian, and Ibrahim Hoteit/ Quarterly Journal of the Royal Meteorological Society, 2021/ https://doi.org/10.1002/qj.3916

5- Adaptive ensemble optimal interpolation for efficient data assimilation in the red sea/ Habib Toye, Peng Zhan, Furrukh Sana, Sivareddy Sanikommu, Naila F. Raboudi, and Ibrahim Hoteit/ Journal of Computational Science/ https://doi.org/10.1016/j.jocs.2021.101317

6- Ensemble Kalman filtering with coloured observation noise/ Naila F. Raboudi, Boujemaa Ait-El-Fquih, Hernando Ombao, and Ibrahim Hoteit/ Quarterly Journal of the Royal Meteorological Society/ https://doi.org/10.1002/qj.4186

7- Online Estimation of Colored Observation Noise Parameters within an Ensemble Kalman Filtering Framework/ Naila F. Raboudi, Boujemaa Ait-El-Fquih, and Ibrahim Hoteit/ Quarterly Journal of the Royal Meteorological Society/ https://doi.org/10.1002/qj.4484

8- Insights from very Large Ensemble Data Assimilation Experiments with a High Resolution General circulation model of the Red Sea/ Siva Reddy Sanikommu, Naila F. Raboudi, Mohamad Gharamti, Peng Zhan, Bilel Hadri, and Ibrahim Hoteit/ Quarterly Journal of the Royal Meteorological Society/ 10.22541/essoar.169447442.23388027/v1

9- Data Assimilation in Chaotic Systems Using Deep Reinforcement Learning/ Mohamad Abed El Rahman Hammoud, Naila F. Raboudi, Edriss S. Titi, Omar Knio, and Ibrahim Hoteit/ arXiv preprint arXiv:2401.00916/ https://doi.org/10.48550/arXiv.2401.00916

    Education

    • Engineering diploma: Tunisia Polytechnic School (TPS), 2014
    • M.Sc. Earth Sciences and Engineering, KAUST, Jan 2016 – Nov 2016, An ensemble Kalman filter with one-step-ahead smoothing for storm surge forecasting
    • PhD: King Abdullah University of Science and Technology (KAUST), 2017-2022
    • Postdoctoral Fellow: King Abdullah University of Science and Technology (KAUST), 2022-now, Ensemble ocean data assimilation

    Scientific and Professional Membership

    • ​Asia Oceania Geosciences Society (AOGS)

    Awards

    Dean’s Award (2022) for Outstanding academic and research accomplishments of KAUST ErSE students

    KAUST Affiliations

    Research Interests Keywords

    Data assimilation Ensemble Kalman filtering (EnKF) Ocean forecasting