Research

PhD thesis

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


Multi-accuracy in Optimisation and Numerical Linear Algebra

  • S. Gratton, E. Simon, D. Titley-Peloquin, Ph. Toint. Exploiting variable precision in GMRES, arXiv.org/abs/1907.10550 , 2019.
  • S. Gratton, E. Simon, D. Titley-Peloquin, Ph. Toint. Minimizing convex quadratics with variable precision conjugate gradients. arXiv.org/abs/1807.07476 , 2018.
  • 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., 2020. (doi) , Preprint (pdf)

Data Assimilation: Algorithmic developments

  • A. Bernigaud, S. Gratton, F. Lenti, E. Simon, O. Sohab. p-norm regularization in variational data assimilation, submitted, 2020.
  • S. Gratton, E. Simon, D. Titley-Peloquin. Computing optimal empirical covariance matrices from multi-ensembles with application to ensemble-based Kalman filters, submitted, 2019.
  • 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.
  • S. Gratton, S. Guröl, E. Simon, Ph. 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.
  • 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.
  • S. Gratton, S. Guröl, E. Simon, Ph. 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, P. Toint. Observation Thinning in Data Assimilation Computations. EURO J. Comput. Optim. , 3, 31-51, 2015. Preprint (pdf)
  • 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.
  • 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. (pdf)
  • 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. Preprint (pdf)
  • 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)

Operational Oceanography and Industrial Applications

  • 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.
  • 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. Proceedings of ESA Living Planet Symposium, Bergen, 2010. (pdf)
Thème : Overlay par Kaira. Texte supplémentaire
Le Cap, Afrique du sud