Thématiques & publications

2025Guillot, J., Ailliot, P., Frénod, E., & Tandeo, P. State and Stochastic Parameters Estimation with Combined Ensemble Kalman and Particle Filters. Monthly Weather Review, 153(7), 1141-1154.

2024Obakrim, S., Ailliot, P., Monbet, V., & Raillard, N. EM algorithm for generalized Ridge regression with spatial covariates. Environmetrics, 35(6), e2871.

2024Platzer, P., Ailliot, P., Chapron, B., & Tandeo, P. Could old tide gauges help estimate past atmospheric variability? Climate of the Past, 20(10), 2267-2286.

2024Le Bras, P., Sévellec, F., Tandeo, P., Ruiz, J., & Ailliot, P. Selecting and weighting dynamical models using data-driven approaches. Nonlinear Processes in Geophysics, 31(3), 303-317.

2023Tandeo, P., Ailliot, P., & Sévellec, F. Data-driven reconstruction of partially observed dynamical systems. Nonlinear Processes in Geophysics, 30(2), 129-137.

2023Obakrim, S., Ailliot, P., Monbet, V., & Raillard, N. Statistical modeling of the space–time relation between wind and significant wave height. Advances in Statistical Climatology, Meteorology and Oceanography, 9(1), 67-81.

2023Boutigny, M., Ailliot, P., Chaubet, A., Naveau, P., & Saussol, B. A meta-Gaussian distribution for sub-hourly rainfall. Stochastic Environmental Research and Risk Assessment, 37(10), 3915-3927.

2023Obakrim, S., Monbet, V., Raillard, N., & Ailliot, P. Learning the spatiotemporal relationship between wind and significant wave height using deep learning. Environmental Data Science, 2, e5.

2023Chau, T. T. T., Ailliot, P., Monbet, V., & Tandeo, P. Comparison of simulation-based algorithms for parameter estimation and state reconstruction in nonlinear state-space models. Discrete and Continuous Dynamical Systems-Series S, 16(2), 240-264.

2023Guillot, J., Frénod, E., & Ailliot, P. Physics informed model error for data assimilation. Discrete and Continuous Dynamical Systems-Series S, 16(2), 265-276.

2023Legrand, J., Ailliot, P., Naveau, P., & Raillard, N. Joint stochastic simulation of extreme coastal and offshore significant wave heights. The Annals of Applied Statistics, 17(4), 3363-3383.

2022Michel, M., Obakrim, S., Raillard, N., Ailliot, P., & Monbet, V. Deep learning for statistical downscaling of sea states. Advances in Statistical Climatology, Meteorology and Oceanography, 8(1), 83-95.

2022Koutroulis, E., Petrakis, G., Agou, V., Malisovas, A., Hristopulos, D., Partsinevelos, P., Ailliot, P., Boutigny, M. et al. Site selection and system sizing of desalination plants powered with renewable energy sources based on a web-GIS platform. International Journal of Energy Sector Management, 16(3), 469-492.

2022Ruiz, J., Ailliot, P., Chau, T. T. T., Le Bras, P., Monbet, V., Sévellec, F., & Tandeo, P. Analog data assimilation for the selection of suitable general circulation models. Geoscientific Model Development Discussions, 2022, 1-30.

2021Chau, T. T. T., Ailliot, P., & Monbet, V. An algorithm for non-parametric estimation in state–space models. Computational Statistics & Data Analysis, 153, 107062.

2021Platzer, P., Yiou, P., Naveau, P., Tandeo, P., Filipot, J. F., Ailliot, P., & Zhen, Y. Using local dynamics to explain analog forecasting of chaotic systems. Journal of the Atmospheric Sciences, 78(7), 2117-2133.

2020Chau, T. T. T., Ailliot, P., & Monbet, V. An algorithm for non-parametric estimation in state–space models. Computational Statistics & Data Analysis, 153, 107062.

2020Tandeo, P., Ailliot, P., Bocquet, M., Carrassi, A., Miyoshi, T., Pulido, M., & Zhen, Y. A review of innovation-based methods to jointly estimate model and observation error covariance matrices in ensemble data assimilation. Monthly Weather Review, 148(10), 3973-3994.

2020Ailliot, P., Boutigny, M., Koutroulis, E., Malisovas, A., & Monbet, V. Stochastic weather generator for the design and reliability evaluation of desalination systems with Renewable Energy Sources. Renewable Energy, 158, 541-553.

2019Ailliot, P., Delyon, B., Monbet, V., & Prevosto, M. Time-change models for asymmetric processes. Scandinavian Journal of Statistics, 46(4), 1072-1091.

2017Lguensat, R., Tandeo, P., Ailliot, P., Pulido, M., & Fablet, R. The analog data assimilation. Monthly Weather Review, 145(10), 4093-4107.

2017Monbet, V., & Ailliot, P. Sparse vector Markov switching autoregressive models. Application to multivariate time series of temperature. Computational Statistics & Data Analysis, 108, 40-51.

2016Bessac, J., Ailliot, P., Cattiaux, J., & Monbet, V. Comparison of hidden and observed regime-switching autoregressive models for (u, v)-components of wind fields in the northeastern Atlantic. Advances in Statistical Climatology, Meteorology and Oceanography, 2, pp. 1-16.

2015Ailliot, P., Allard, D., Monbet, V., & Naveau, P. Stochastic weather generators: an overview of weather type models. Journal de la Société Française de Statistique, 156(1), pp. 101-113.

2015Ailliot, P., Bessac, J., Monbet, V., & Pène, F. Non-homogeneous hidden Markov-switching models for wind time series. Journal of Statistical Planning and Inference, 160, pp. 75-88.

2015Kpogo-Nuwoklo, K. A., Ailliot, P., Olagnon, M., Guédé, Z., & Arnault, S. Improving sea wave spectrum estimation using the temporal structure of wave systems. Coastal Engineering, 96, pp. 81-91.

2015Ailliot, P., & Pène, F. Consistency of the maximum likelihood estimate for Non-homogeneous Markov-switching models. ESAIM: PS, 19, pp. 268-292.

2015Saulquin, B., Fablet, R., Ailliot, P., Mercier, G., Doxaran, D., & Fanton d'Andon, O. Characterization of time-varying regimes in remote sensing time series: application to the forecasting of satellite-derived suspended matter concentrations. IEEE JSTARS, 8(1).

2015Bessac, J., Ailliot, P., & Monbet, V. Gaussian linear state-space model for wind fields in the North-East Atlantic. Environmetrics, 26(1), pp. 29-38.

2015Raillard, N., Prevosto, M., & Ailliot, P. Modeling process asymmetries with Laplace moving average. Computational Statistics & Data Analysis, 81, pp. 24-37.

2014Wright, C. J., Scott, R. B., Ailliot, P., & Furnival, D. Lee wave generation rates in the deep ocean. Geophysical Research Letters, 41(7), pp. 2434-2440.

2014Raillard, N., Ailliot, P., & Yao, J. F. Modelling extreme values of processes observed at irregular time step. Application to significant wave height. The Annals of Applied Statistics, 8(1), pp. 622-647.

2013Ailliot, P., Maisondieu, C., & Monbet, V. Dynamical partitioning of directional ocean wave spectra. Probabilistic Engineering Mechanics, 33, pp. 95-102.

2013Wright, C. J., Scott, R. B., Furnival, D., Ailliot, P., & Vermet, F. Global Observations of Ocean-Bottom Subinertial Current Dissipation. Journal of Physical Oceanography, 43, pp. 402-417.

2012Ailliot, P., & Monbet, V. Markov-switching autoregressive models for wind time series. Environmental Modelling & Software, 30, pp. 92-101.

2011Tandeo, P., Ailliot, P., & Autret, E. Linear Gaussian State-Space Model with Irregular Sampling — Application to Sea Surface Temperature. Stochastic Environmental Research & Risk Assessment, 25, 793-804.

2011Ailliot, P., Thompson, C., & Thomson, P. Mixed methods for fitting the GEV distribution. Water Resources Research, 47, W0551, doi:10.1029/2010WR009417.

2011Ailliot, P., Baxevani, A., Cuzol, A., Monbet, V., & Raillard, N. Space-time models for moving fields. Application to significant wave height. Environmetrics, 22(3), pp. 354-369.

2010Ailliot, P., Frenod, E., & Monbet, V. Modeling the coastal ocean over a time period of several weeks. Journal of Differential Equations, 248, pp. 639-659.

2009Tandeo, P., Autret, E., Piollé, J. F., Tournadre, J., & Ailliot, P. A multivariate regression approach to adjust AATSR Sea Surface Temperature to in-situ measurements. IEEE Geoscience and Remote Sensing Letters, 6(1), pp. 8-12.

2009Ailliot, P., Thompson, C., & Thomson, P. Space time modeling of precipitation using a hidden Markov model and censored Gaussian distributions. Journal of the Royal Statistical Society, Series C (Applied Statistics), 58(3), pp. 405-426.

2008Monbet, V., Ailliot, P., & Marteau, P. F. L1-convergence of smoothing densities in non parametric state space models. Statistical Inference for Stochastic Processes, 11(3), pp. 311-325.

2007Monbet, V., Ailliot, P., & Prevosto, M. Survey of stochastic models for wind and sea-state time series. Probabilistic Engineering Mechanics, 22(2), pp. 113-126.

2006Ailliot, P., Monbet, V., & Prevosto, M. An autoregressive model with time-varying coefficients for wind fields. Environmetrics, 17(2), pp. 107-117.

2006Ailliot, P., Frenod, E., & Monbet, V. Long term object drift forecast in the ocean with tide and wind. Multiscale Modeling and Simulation, 5(2), pp. 514-531.

2006Ailliot, P. Some theoretical results on a Markov-switching autoregressive models with gamma innovations. Comptes Rendus de l'Académie des Sciences de Paris, 343(4), pp. 271-274.

2015Tandeo, P., Ailliot, P., Ruiz, J., Hannart, A., Chapron, B., Cuzol, A., Monbet, V., Easton, R., & Fablet, R. Combining analog method and ensemble data assimilation: application to the Lorenz-63 chaotic system. Machine Learning and Data Mining Approaches to Climate Science (Springer).

2004Ailliot, P. Modèles autorégressifs à changements de régimes markoviens. Applications aux séries temporelles de vent. Thèse de l'université de Rennes 1.