Research

ORCID : https://orcid.org/0000-0003-3205-1649

PhD students

  • N. Ernout (LEGOS, IRIT)
    • Co-advisors R. Benshila (CNRS, LEGOS), L. Renault (IRD, LEGOS), S. Zhang (INPT, IRIT), since Oct. 2023;
    • Machine learning, oceanography.
  • S. Mauran (IRIT)
    • Co-advisor S. Mouysset (UT3, IRIT), L. Bertino (NERSC), since Oct. 2021;
    • Data assimilation.
  • J. Briant (CECI, IRIT)
    • Co-advisors P. Mycek (CERFACS, CECI), S. Gratton (INPT, IRIT), S. Gürol (CERFACS, CECI), A. Weaver (CERFACS, CECI), since Oct. 2020;
    • Data assimilation.
  • A. Rouvière (ONERA)
    • Co-advisors F. Méry (ONERA), L. Pascal (ONERA), S. Gratton (INPT, IRIT), defended on Apr. 3, 2023;
    • Title: Amélioration des modèles de tolérance de surface pour les couches limites en s’appuyant sur des outils d’intelligence artificielle.
  • A. Bernigaud (IRIT)
    • Co-advisor S. Gratton (INPT, IRIT), defended on Dec. 16, 2022;
    • Title: Introduction de la régularisation en norme Lp, avec 1<p<2, pour la prise en compte de la parcimonie en assimilation de données.
  • D. Mottet (EDF)
    • Co-advisors J.-P. Argaud (EDF), S. Gratton (INPT, IRIT), defended on Jan. 12, 2021;
    • Title: Raffinement adaptatif du processus d’assimilation de données par méthodes de Kalman d’ensemble pour des problèmes non-linéaires.

HDR

Quelques contributions à l’assimilation de données : des moindres carrés non-linéaires pondérés en grande dimension, applications en océanographie
HDR, Toulouse INP, 2023.
Oral presentation slides

PhD thesis

Assimilation variationnelle de données pour des modèles emboîtées
Ph.D thesis, Université Joseph Fourier – Grenoble I, 2007.
Oral presentation slides

Optimisation and Numerical Linear Algebra

  • J. Briant, P. Mycek, M. Destouches, O. Goux, S. Gratton, S. Gürol, E. Simon, A. Weaver: A filtered multilevel Monte Carlo method for estimating the expectation of discretized random fields, submitted. (arXiv)
  • A. Bernigaud, S. Gratton, E. Simon. A nonlinear conjugate gradient in dual space for Lp-norm regularized nonlinear least squares with application in data assimilation, Numer. Algor., 95, 471-497, 2024. (doi)
  • S. Gratton, E. Simon, D. Titley-Peloquin, Ph. L. Toint. A note on inexact inner products in GMRES, SIAM J. Matrix Anal. Appl. , 43, 1406-1422, 2022. (doi), (older version, arXiv).
  • S. Gratton, E. Simon, Ph. Toint. An algorithm for the minimization of nonsmooth and nonconvex functions using inexact evaluations and its worst-case complexity, Math. Program., 187, 1-24, 2021. (doi) , (arXiv).
  • S. Gratton, E. Simon, D. Titley-Peloquin, Ph. L. Toint. Minimizing convex quadratics with variable precision conjugate gradients, Numer. Linear Algebra Appl., 28:e2337, 2021. (doi) , (arXiv) .

Data Assimilation: Algorithmic developments

  • S. Gratton, E. Simon, D. Titley-Peloquin. Computing optimal empirical covariance matrices from multi-ensembles with application to ensemble-based Kalman filters, Math. Geosci., 55, 1147-1168, 2023. (doi)
  • S. Mauran, S. Mouysset, E. Simon, L. Bertino. A kernel extension of the Ensemble Transform Kalman Filter, In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. L. N. C. S., 10476, 438–452, 2023. (doi) (pdf)
  • A. Bernigaud, S. Gratton, F. Lenti, E. Simon, O. Sohab. Lp-norm regularization in variational data assimilation, Q. J. R. Meteorol. Soc., 147, 2067-2081, 2021. (doi)
  • S. Gratton, S. Guröl, E. Simon, Ph. Toint. Guaranteeing the convergence of the saddle formulation for weakly-constrained 4D-VAR data assimilation. Q. J. R. Meteorol. Soc., 144, 2592-2602, 2018. (doi) (arXiv)
  • S. Gratton, S. Guröl, E. Simon, Ph. L. Toint. A note on preconditioning weighted linear squares, with consequences for weakly-constrained variational data assimilation. Q. J. R. Meteorol. Soc., 144, 934-940, 2018. (doi) (arXiv)
  • S. Gratton, S. Guröl, E. Simon, Ph. L. Toint. Les algorithmes et la puissance de calcul dans les techniques de prévision pour les géosciences en grande dimension vus sous l’angle de l’optimisation mathématiques. Colloque Modélisation : succès et limites, CNRS & Académie des Technologies, Paris, 37-47, 2018. (doi)
  • L. Debreu, E. Neveu, E. Simon, F.-X. Le Dimet, A. Vidard. Multigrid solvers and multigrid preconditioners for the solution of variational data assimilation problems. Q. J. R. Meteorol. Soc., 142, 515-528, 2016. (doi)
  • S. Gratton, S. Guröl, E. Simon, Ph. L. Toint. Issues in making the weakly-constrained 4DVar formulation computationally efficient. Oberwolfach Reports, 13, 2726-2731, 2016. (doi)
  • S. Gratton, M. Rincon-Camacho, E. Simon, Ph. L. Toint. Observation Thinning in Data Assimilation Computations. EURO J. Comput. Optim. , 3, 31-51, 2015. (doi)
  • L. Debreu, E. Neveu, E. Simon, F.-X. Le Dimet. Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation. In: E. Blayo et al. (eds): Advanced Data Assimilation for Geosciences. Lecture notes of Les Houches summer school 2012. Oxford University Press, 395-412, 2014. (doi)
  • E. Simon, A. Samuelsen, L. Bertino, D. Dumont. Estimation of positive sum-to-one constrained zooplankton grazing preferences with the DEnKF: a twin experiment. Ocean Sci. , 8, 587-602, 2012. (pdf)
  • J.S. Pelc, E. Simon, L. Bertino, G. El Serafy, A. Heemink. Application of model reduced 4D-Var to a 1D ecosystem model. Ocean Model., 57-58, 43-58, 2012. (pdf)
  • E. Simon, L. Bertino. Gaussian anamorphosis extension of the DEnKF for combined state parameter estimation: application to a 1D ocean ecosystem model. J. Mar. Sys., 89, 1-18, 2012. (doi)
  • E. Simon, L. Debreu, E. Blayo. 4D Variational Data Assimilation for Locally Nested Models : complementary theoretical aspects and application to a 2D shallow water model. Int. J. Numer. Meth. Fluids, 66, 135-161, 2011. (doi)
  • L. Debreu, E. Simon, E. Blayo. 4D Variational Data Assimilation for Locally Nested Models : optimality system and preliminary numerical experiments. INRIA research report, 2011. (pdf)
  • E. Simon, L. Bertino. Application of the Gaussian anamorphosis to assimilation in a 3D coupled physical-ecosystem model of the North Atlantic with the EnKF : a twin experiment. Ocean Sci., 5, 495-510, 2009. (pdf)

Oceanography and Applications

  • T.H. Nguyen, S. Ricci, A. Piacentini, E. Simon, R. Rodriguez-Suquet, S. Pena-Luque. Gaussian anamorphosis for ensemble Kalman filter analysis of SAR-derived wet surface ratio observations, IEEE Trans. Geosci. Remote Sens., 62, 1-21, 2024. (doi) (pdf)
  • A. Rouvière, L. Pascal, F. Méry, E. Simon, S. Gratton. Neural prediction model for transition onset of a boundary-layer in presence of 2D surface defects, Flow, 3, E20, 2023. (doi)
  • T.H. Nguyen, S. Ricci, A. Piacentini, E. Simon, R. Rodriguez-Suquet, S. Pena-Luque. Dealing with non-Gaussianity of SAR-derived wet surface ratio for flood extent representation improvement. IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, 1595-1598, 2023. (arXiv) (doi)
  • A. Rouvière, L. Pascal, F. Méry, E. Simon, S. Gratton. Neural prediction model for transition onset of a boundary-layer in presence of 2D surface defects. AIAA 2022-1073 – AIAA SCITECH 2022 Forum , San Diego, 2022. (doi)
  • R. Benshila, G. Thoumyre, M. Al Najar, G. Abessolo, R. Almar, E. Bergsma, G. Hugonnard, L. Labracherie, B. Lavie, T. Ragonneau, E. Simon, B. Vieuble, D. Wilson. A deep learning approach for estimation of the nearshore bathymetry. J. Coastal Research, 95 (sp1), 1011-1015, 2020. (doi)
  • M.E. Gharamti, A. Samuelsen, L. Bertino, E. Simon, A. Korosov, U. Daewel. Online Tuning of Ocean Biogeochemical Parameters using Ensemble Estimation Techniques: Application to a one-dimensional Model in the North Atlantic. J. Mar. Sys., 168, 1-16, 2017. (doi)
  • E. Simon, A. Samuelsen, L. Bertino, S. Mouysset. Experiences in multiyear combined state-parameter estimation with an ecosystem model of the North Atlantic and Arctic Oceans using the Ensemble Kalman Filter. J. Mar. Sys., 152, 1-17, 2015. (pdf)
  • M. Gehlen, R. Barciela, L. Bertino, P. Brasseur, M. Butenschöon, F. Chai, A. Crise, Y. Drillet, D. Ford, D. Lavoie, P. Lehodey, C. Perruche, A. Samuelsen, E. Simon. Building the capacity for forecasting marine biogeochemistry and ecosystems: recent advances and future developments. J. Operat. Oceanogr., 8 (S1), s168-s187, 2015. (pdf)
  • E. Simon, L. Bertino. Joint state-parameter estimation in a 3D coupled physical-ecosystem model of the North Atlantic: assimilation of SeaWiFS data with a non-Gaussian extension of an ESRF. ESA Living Planet Symposium, Bergen, 2010. (pdf)
Thème : Overlay par Kaira. Texte supplémentaire
Le Cap, Afrique du sud