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Bibliography

Publications of the year

Articles in International Peer-Reviewed Journals

  • 1A. Beljaars, E. Dutra, G. Balsamo, F. Lemarié.

    On the numerical stability of surface-atmosphere coupling in weather and climate models, in: Geoscientific Model Development Discussions, 2017, vol. 10, pp. 977-989. [ DOI : 10.5194/gmd-10-977-2017 ]

    https://hal.inria.fr/hal-01406623
  • 2E. Blayo, A. Rousseau, M. Tayachi Pigeonnat.

    Boundary conditions and Schwarz waveform relaxation method for linear viscous Shallow Water equations in hydrodynamics, in: SMAI Journal of Computational Mathematics, 2017, vol. 3, pp. 117-137. [ DOI : 10.5802/smai-jcm.22 ]

    https://hal.inria.fr/hal-01467335
  • 3R. Buizza, S. Brönnimann, L. Haimberger, P. Laloyaux, M. J. Martin, M. Fuentes, M. Alonso-Balmaseda, A. Becker, M. Blaschek, P. Dahlgren, E. de Boisseson, D. Dee, M. Doutriaux-Boucher, F. Xiangbo, V. John, K. Haines, S. Jourdain, Y. Kosaka, D. Lea, F. Lemarié, M. Mayer, P. Messina, C. Perruche, P. Peylin, J. Pullainen, N. Rayner, E. Rustemeier, D. Schepers, R. Saunders, J. Schulz, A. Sterin, S. Stichelberger, A. Storto, C.-E. Testut, M.- A. Valente, A. Vidard, N. Vuichard, A. Weaver, J. While, M. Ziese.

    The EU-FP7 ERA-CLIM2 project contribution to advancing science and production of Earth-system climate reanalyses, in: Bulletin of the American Meteorological Society, November 2017. [ DOI : 10.1175/BAMS-D-17-0199.1 ]

    https://hal.inria.fr/hal-01661240
  • 4T. Capelle, P. Sturm, A. Vidard, B. Morton.

    Calibration of the Tranus Land Use Module: Optimisation-Based Algorithms, their Validation, and Parameter Selection by Statistical Model Selection, in: Computers, Environment and Urban Systems, 2017. [ DOI : 10.1016/j.compenvurbsys.2017.04.009 ]

    https://hal.inria.fr/hal-01519654
  • 5P. Cattiaux, J. R. León, A. Pineda Centeno, C. Prieur.

    An overlook on statistical inference issues for stochastic damping Hamiltonian systems under the fluctuation-dissipation condition, in: Statistics, 2017, vol. 51, no 1, pp. 11-29. [ DOI : 10.1080/02331888.2016.1259807 ]

    https://hal.archives-ouvertes.fr/hal-01405427
  • 6P. Cattiaux, C. Prieur, J. R. Leon.

    Invariant density estimation for a reflected diffusion using an Euler scheme, in: Monte Carlo Methods and Applications, 2017, vol. 23, no 2, pp. 71-88. [ DOI : 10.1515/mcma-2017-0104 ]

    https://hal.inria.fr/hal-01683980
  • 7F. Comte, C. Prieur, A. Samson.

    Adaptive estimation for stochastic damping Hamiltonian systems under partial observation, in: Stochastic Processes and their Applications, November 2017, vol. 127, no 11, pp. 3689 - 3718. [ DOI : 10.1016/j.spa.2017.03.011 ]

    https://hal.archives-ouvertes.fr/hal-01659337
  • 8C. Eldred, D. Le Roux.

    Dispersion analysis of compatible Galerkin schemes for the 1D shallow water model, in: Journal of Computational Physics, 2017, pp. 1-41, forthcoming.

    https://hal.archives-ouvertes.fr/hal-01669048
  • 9L. Gilquin, L. A. Jiménez Rugama, E. Arnaud, F. J. Hickernell, H. Monod, C. Prieur.

    Iterative construction of replicated designs based on Sobol' sequences, in: Comptes Rendus Mathématique, January 2017, vol. 355, no 1, pp. 10-14. [ DOI : 10.1016/j.crma.2016.11.013 ]

    https://hal.inria.fr/hal-01349444
  • 10L. Li, F.-X. Le Dimet, J. Ma, A. Vidard.

    A level-set based image assimilation method: Potential applications for predicting the movement of oil spills, in: IEEE Transactions on Geoscience and Remote Sensing, November 2017, vol. 55, no 11, 14 p. [ DOI : 10.1109/TGRS.2017.2726013 ]

    https://hal.inria.fr/hal-01411878
  • 11S. Nanty, C. Helbert, A. Marrel, N. Pérot, C. Prieur.

    Uncertainty quantification for functional dependent random variables, in: Computational Statistics, June 2017, vol. 32, no 2, pp. 559-583. [ DOI : 10.1007/s00180-016-0676-0 ]

    https://hal.archives-ouvertes.fr/hal-01075840
  • 12V. Oerder, F. Colas, V. Echevin, S. Masson, F. Lemarié.

    Impacts of the Mesoscale Ocean-Atmosphere Coupling on the Peru-Chile Ocean Dynamics: The Current-Induced Wind Stress Modulation, in: Journal of Geophysical Research. Oceans, January 2018. [ DOI : 10.1002/2017JC013294 ]

    https://hal.inria.fr/hal-01661645
  • 13A. B. Owen, C. Prieur.

    On Shapley value for measuring importance of dependent inputs, in: SIAM/ASA Journal on Uncertainty Quantification, 2017, https://arxiv.org/abs/1610.02080.

    https://hal.archives-ouvertes.fr/hal-01379188
  • 14C. Pelletier, F. Lemarié, É. Blayo.

    Sensitivity analysis and metamodels for the bulk parameterization of turbulent air-sea fluxes, in: Quarterly Journal of the Royal Meteorological Society, December 2017, forthcoming. [ DOI : 10.1002/qj.3233 ]

    https://hal.inria.fr/hal-01663668
  • 15V. Shutyaev, I. Gejadze, A. Vidard, F.-X. Le Dimet.

    Optimal solution error quantification in variational data assimilation involving imperfect models, in: International Journal for Numerical Methods in Fluids, January 2017, vol. 83, no 3, pp. 276–290. [ DOI : 10.1002/fld.4266 ]

    https://hal.inria.fr/hal-01411666

Invited Conferences

  • 16E. Blayo.

    Introduction à l'assimilation de données, in: 2017 - Workshop Vers le traitement des données massives: défis et applications en mécanique des fluides et en sciences de l'ingénieur, Orsay, France, November 2017.

    https://hal.inria.fr/hal-01659631
  • 17F. Lemarié.

    Analysis of Ocean-atmosphere Coupling Algorithms: Consistency and Stability, in: third international workshop on “Energy transfers in Atmosphere and Ocean”, Hamburg, Germany, May 2017.

    https://hal.inria.fr/hal-01660700
  • 18C. Pelletier, F. Lemarié, É. Blayo.

    A theoretical study of a simplified air-sea coupling problem including turbulent parameterizations, in: COUPLED PROBLEMS 2017 - VII International Conference on Computational Methods for Coupled Problems in Science and Engineering, Rhodes, Greece, M. Papadrakakis, E. Oñate, B. Schrefler (editors), International Center for Numerical Methods in Engineering (CIMNE) , June 2017, pp. 38-49.

    https://hal.archives-ouvertes.fr/hal-01659443

International Conferences with Proceedings

  • 19M. P. DAOU, O. Bertrand, E. Blayo, A. Rousseau.

    Tridimensional model coupling using Schwarz methodology - Application to a water intake of a hydroelectric plant, in: Simhydro 2017, Sophia-Antipolis, France, June 2017, pp. 14 - 16.

    https://hal.inria.fr/hal-01659455

Conferences without Proceedings

  • 20E. Blayo, F. Lemarié, C. Pelletier.

    Stabilité et consistance des algorithmes de couplage océan-atmosphère, in: AMA 2017 - Ateliers de Modélisation de l'Atmosphère, Toulouse, France, January 2017.

    https://hal.inria.fr/hal-01659487
  • 21F. Lemarié, L. Debreu, J. Demange, É. Blayo, P. Marchesiello.

    Stability analysis of split-explicit oceanic models, in: 2017 - Mathematics of the Weather workshop, Erquy, France, October 2017.

    https://hal.inria.fr/hal-01660775
  • 22F. Lemarié, G. Samson, J.-L. Redelsperger, H. Giordani, G. Madec.

    Toward an improved representation of air-sea interactions in high-resolution global ocean forecasting systems, in: EGU 2017 - European Geosciences Union General Assembly, Vienna, Austria, April 2017, pp. 1-19.

    https://hal.inria.fr/hal-01660799
  • 23F. Lemarié, G. Samson, J.-L. Redelsperger, G. Madec, H. Giordani.

    Toward an improved representation of air-sea interactions in high-resolution global oceanic forecasting systems, in: 2017 - Copernicus Marine week, Brussels, Belgium, September 2017.

    https://hal.inria.fr/hal-01660783
  • 24C. Pelletier, F. Lemarié, É. Blayo.

    Approximation explicite des formules "bulks" en vue du développement d'un couplage océan-atmosphère cohérent, in: AMA 2017 - Ateliers de modélisation de l'atmosphère, Toulouse, France, Météo-France, January 2017, pp. 1-37.

    https://hal.inria.fr/hal-01660572

Internal Reports

  • 25A. Vidard, R. Pellerej, F. Lemarié.

    Report on fully coupled data assimilation in simplified systems with implications for Earth system reanalysis, Inria Grenoble Rhône-Alpes, November 2017.

    https://hal.inria.fr/hal-01667509

Scientific Popularization

Other Publications

  • 27A. Briançon-Marjollet, E. Heidsick, C. Hoffmann, M. Nodet, D. Seyve, S. TÉROUANNE.

    Construire et expérimenter une évaluation par les pairs, June 2017, Atelier présenté au colloque QPES (Question de Pédagogie dans l'Enseignement Supérieur).

    https://hal.inria.fr/hal-01619779
  • 28S. Dewyspelaere, M. Nodet, J. Charton, P. Garat, F. Letue, C. Pès, V. Wales.

    Exemple d'EPI au collège : l'évolution des glaciers, October 2017, working paper or preprint.

    https://hal.inria.fr/hal-01619788
  • 29E. Di Bernardino, C. Prieur.

    Estimation of the Multivariate Conditional-Tail-Expectation for extreme risk levels: illustrations on environmental data-sets, October 2017, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01524536
  • 30L. Gilquin, E. Arnaud, C. Prieur, A. Janon.

    Making best use of permutations to compute sensitivity indices with replicated designs, June 2017, working paper or preprint.

    https://hal.inria.fr/hal-01558915
  • 31B. Iooss, C. Prieur.

    Shapley effects for sensitivity analysis with dependent inputs: comparisons with Sobol' indices, numerical estimation and applications, October 2017, https://arxiv.org/abs/1707.01334 - working paper or preprint.

    https://hal.inria.fr/hal-01556303
  • 32L. A. Jiménez Rugama, L. Gilquin.

    Reliable error estimation for Sobol' indices, January 2017, working paper or preprint.

    https://hal.inria.fr/hal-01358067
  • 33E. Kazantsev.

    Parameterizing subgrid scale eddy effects in a shallow water model, November 2017, working paper or preprint.

    https://hal.inria.fr/hal-01413010
  • 34K. Klingbeil, L. Debreu, F. Lemarié, H. Burchard.

    The numerics of hydrostatic structured-grid coastal ocean models: state of the art and future perspectives, 2017, working paper or preprint.

    https://hal.inria.fr/hal-01443357
  • 35A. Vidard.

    Report on the use of 3D or 4D-Var for the ocean component in the coupled data assimilation context, December 2017, working paper or preprint.

    https://hal.inria.fr/hal-01667507
References in notes
  • 36T. Capelle.

    Development of optimisation methods for land-use and transportation models, Inria, April 2017.

    https://tel.archives-ouvertes.fr/tel-01665395
  • 37P. Cattiaux, J. R. Leon, C. Prieur.

    Estimation for Stochastic Damping Hamiltonian Systems under Partial Observation. I. Invariant density, in: Stochastic Processes and their Applications, March 2014, vol. 124, no 3, pp. 1236-1260. [ DOI : 10.1016/j.spa.2013.10.008 ]

    https://hal.archives-ouvertes.fr/hal-00739136
  • 38P. Cattiaux, J. R. Leon, C. Prieur.

    Estimation for Stochastic Damping Hamiltonian Systems under Partial Observation. II Drift term, in: ALEA (Latin American Journal of Probability and Statistics), 2014, vol. 11, no 1, pp. 359-384.

    https://hal.archives-ouvertes.fr/hal-00877054
  • 39P. Cattiaux, J. R. Leon, C. Prieur.

    Recursive Estimation for Stochastic Damping Hamiltonian Systems, in: Journal of Nonparametric Statistics, 2015, vol. 27, no 3, pp. 401-424.

    https://hal.archives-ouvertes.fr/hal-01071252
  • 40M. Champion, G. Chastaing, S. Gadat, C. Prieur.

    L2 Boosting on generalized Hoeffding decomposition for dependent variables. Application to Sensitivity Analysis, 2013, 48 pages, 7 Figures.
  • 41G. Chastaing.

    Generalized Sobol sensitivity indices for dependent variables, Université de Grenoble, September 2013.

    https://tel.archives-ouvertes.fr/tel-00930229
  • 42G. Chastaing, F. Gamboa, C. Prieur.

    Generalized Hoeffding-Sobol Decomposition for Dependent Variables - Application to Sensitivity Analysis, in: Electronic Journal of Statistics, December 2012, vol. 6, pp. 2420-2448. [ DOI : 10.1214/12-EJS749 ]

    http://hal.archives-ouvertes.fr/hal-00649404
  • 43G. Chastaing, C. Prieur, F. Gamboa.

    Generalized Sobol sensitivity indices for dependent variables: numerical methods, March 2013.

    http://hal.inria.fr/hal-00801628
  • 44A. Cousin, E. Di Bernardino.

    On multivariate extensions of Value-at-Risk, in: J. Multivariate Anal., 2013, vol. 119, pp. 32–46.

    http://dx.doi.org/10.1016/j.jmva.2013.03.016
  • 45C. De Michele, G. Salvadori, R. Vezzoli, S. Pecora.

    Multivariate assessment of droughts: Frequency analysis and dynamic return period, in: Water Resources Research, 2013, vol. 49, no 10, pp. 6985–6994.
  • 46E. Di Bernardino, T. Laloë, V. Maume-Deschamps, C. Prieur.

    Plug-in estimation of level sets in a non-compact setting with applications in multivariate risk theory, in: ESAIM: Probability and Statistics, February 2013, vol. 17, pp. 236-256. [ DOI : 10.1051/ps/2011161 ]

    https://hal.archives-ouvertes.fr/hal-00580624
  • 47E. Di Bernardino, V. Maume-Deschamps, C. Prieur.

    Estimating Bivariate Tail: a copula based approach, in: Journal of Multivariate Analysis, August 2013, vol. 119, pp. 81-100. [ DOI : 10.1016/j.jmva.2013.03.020 ]

    https://hal.archives-ouvertes.fr/hal-00475386
  • 48E. Di Bernardino, C. Prieur.

    Estimation of Multivariate Conditional Tail Expectation using Kendall's Process, in: Journal of Nonparametric Statistics, March 2014, vol. 26, no 2, pp. 241-267. [ DOI : 10.1080/10485252.2014.889137 ]

    https://hal.archives-ouvertes.fr/hal-00740340
  • 49N. Feyeux, M. Nodet, A. Vidard.

    Optimal Transport for Data Assimilation, July 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01342193
  • 50L. Gilquin, E. Arnaud, C. Prieur, H. Monod.

    Recursive estimation procedure of Sobol' indices based on replicated designs, January 2016, working paper or preprint.

    https://hal.inria.fr/hal-01291769
  • 51L. Gilquin.

    Monte Carlo and quasi-Monte Carlo sampling methods for the estimation of Sobol' indices. Application to a LUTI model, Université Grenoble Alpes, October 2016.

    https://hal.inria.fr/tel-01403914
  • 52L. Gilquin, C. Prieur, E. Arnaud.

    Replication procedure for grouped Sobol' indices estimation in dependent uncertainty spaces, in: Information and Inference, August 2015, vol. 4, no 4, pp. 354-379. [ DOI : 10.1093/imaiai/iav010 ]

    https://hal.inria.fr/hal-01045034
  • 53M. Gross, H. Wan, P. J. Rasch, P. M. Caldwell, D. L. Williamson, D. Klocke, C. Jablonowski, D. R. Thatcher, N. Wood, M. Cullen, B. Beare, M. Willett, F. Lemarié, E. Blayo, S. Malardel, P. Termonia, A. Gassmann, P. H. Lauritzen, H. Johansen, C. M. Zarzycki, K. Sakaguchi, R. Leung.

    Recent progress and review of Physics Dynamics Coupling in geophysical models, May 2016, working paper or preprint.

    https://hal.inria.fr/hal-01323768
  • 54W. Hoeffding.

    A class of statistics with asymptotically normal distribution, in: Ann. Math. Statistics, 1948, vol. 19, pp. 293–325.
  • 55A. Janon, T. Klein, A. Lagnoux-Renaudie, M. Nodet, C. Prieur.

    Asymptotic normality and efficiency of two Sobol index estimators, in: ESAIM: Probability and Statistics, October 2014, vol. 18, pp. 342-364. [ DOI : 10.1051/ps/2013040 ]

    https://hal.inria.fr/hal-00665048
  • 56A. Janon, M. Nodet, C. Prieur.

    Goal-oriented error estimation for reduced basis method, with application to certified sensitivity analysis.

    http://hal.archives-ouvertes.fr/hal-00721616
  • 57A. Janon, M. Nodet, C. Prieur.

    Certified reduced-basis solutions of viscous Burgers equation parametrized by initial and boundary values, in: ESAIM: Mathematical Modelling and Numerical Analysis, March 2013, vol. 47, no 2, pp. 317-348. [ DOI : 10.1051/m2an/2012029 ]

    http://hal.inria.fr/inria-00524727
  • 58A. Janon, M. Nodet, C. Prieur.

    Uncertainties assessment in global sensitivity indices estimation from metamodels, in: International Journal for Uncertainty Quantification, 2014, vol. 4, no 1, pp. 21-36. [ DOI : 10.1615/Int.J.UncertaintyQuantification.2012004291 ]

    https://hal.inria.fr/inria-00567977
  • 59A. Janon, M. Nodet, C. Prieur, C. Prieur.

    Global sensitivity analysis for the boundary control of an open channel, in: Mathematics of Control, Signals, and Systems, March 2016, vol. 28, no 1, pp. 6:1-27. [ DOI : 10.1007/s00498-015-0151-4 ]

    https://hal.archives-ouvertes.fr/hal-01065886
  • 60A. Janon, M. Nodet, C. Prieur, C. Prieur.

    Goal-oriented error estimation for fast approximations of nonlinear problems, GIPSA-lab, 2016, Rapport interne de GIPSA-lab.

    https://hal.archives-ouvertes.fr/hal-01290887
  • 61F. Lemarié, E. Blayo, L. Debreu.

    Analysis of ocean-atmosphere coupling algorithms : consistency and stability, in: Procedia Computer Science, 2015, vol. 51, pp. 2066–2075. [ DOI : 10.1016/j.procs.2015.05.473 ]

    https://hal.inria.fr/hal-01174132
  • 62F. Lemarié.

    Numerical modification of atmospheric models to include the feedback of oceanic currents on air-sea fluxes in ocean-atmosphere coupled models, Inria Grenoble - Rhône-Alpes ; Laboratoire Jean Kuntzmann ; Universite de Grenoble I - Joseph Fourier ; Inria, August 2015, no RT-0464.

    https://hal.inria.fr/hal-01184711
  • 63J. R. Leon, A. Samson.

    Hypoelliptic stochastic FitzHugh-Nagumo neuronal model: mixing, up-crossing and estimation of the spike rate, in: Annals of Applied Probability, 2017.

    https://hal.archives-ouvertes.fr/hal-01492590
  • 64S. Nanty, C. Helbert, A. Marrel, N. Pérot, C. Prieur.

    Uncertainy quantification for functional dependent random variables, 2014, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01075840
  • 65S. Nanty, C. Helbert, A. Marrel, N. Pérot, C. Prieur.

    Sampling, metamodelling and sensitivity analysis of numerical simulators with functional stochastic inputs, in: SIAM/ASA Journal on Uncertainty Quantification, May 2016, vol. 4, no 1, pp. 636-659. [ DOI : 10.1137/15M1033319 ]

    https://hal.archives-ouvertes.fr/hal-01187162
  • 66V. Oerder, F. Colas, V. Echevin, S. Masson, C. Hourdin, S. Jullien, G. Madec, F. Lemarié.

    Mesoscale SST – Wind Stress coupling in the Peru–Chile Current System: Which mechanisms drive its seasonal variability?, in: Climate Dynamics, October 2016, vol. 47, no 7, pp. 2309–2330. [ DOI : 10.1007/s00382-015-2965-7 ]

    https://hal.inria.fr/hal-01253181
  • 67A. B. Owen.

    Sobol' indices and Shapley value, in: Journal on Uncertainty Quantification, 2014, vol. 2, pp. 245–251.
  • 68R. Pellerej, A. Vidard, F. Lemarié.

    Toward variational data assimilation for coupled models: first experiments on a diffusion problem, in: CARI 2016, Tunis, Tunisia, October 2016.

    https://hal.archives-ouvertes.fr/hal-01337743
  • 69C. Pelletier, É. Blayo, F. Lemarié, P. Braconnot.

    Études préliminaires en vue d'un couplage océan-atmosphère bien couplé, in: 43e Congrès National d'Analyse Numérique, CANUM 2016, Obernai, France, May 2016.

    https://hal.inria.fr/hal-01660567
  • 70L. Renault, M. J. Molemaker, J. C. Mcwilliams, A. Shchepetkin, F. Lemarié, D. Chelton, S. Illig, A. Hall.

    Modulation of Wind-Work by Oceanic Current Interaction with the Atmosphere, in: Journal of Physical Oceanography, June 2016, vol. 46, no 6, pp. 1685–1704. [ DOI : 10.1175/JPO-D-15-0232.1 ]

    https://hal.inria.fr/hal-01295496
  • 71G. Salvadori, C. De Michele, F. Durante.

    On the return period and design in a multivariate framework, in: Hydrology and Earth System Sciences, 2011, vol. 15, no 11, pp. 3293–3305.
  • 72E. Song, B. L. Nelson, J. Staum.

    Shapley Effects for Global Sensitivity Analysis: Theory and Computation, Northwestern University, 2015.
  • 73P. Tencaliec, A.-C. Favre, C. Prieur, T. Mathevet.

    Reconstruction of missing daily streamflow data using dynamic regression models, in: Water Resources Research, December 2015, vol. 51, no 12, pp. 9447–9463. [ DOI : 10.1002/2015WR017399 ]

    https://hal.inria.fr/hal-01245238