| Data assimilation in the geosciences: An overview of methods, issues, and perspectives A Carrassi, M Bocquet, L Bertino, G Evensen Wiley Interdisciplinary Reviews: Climate Change 9 (5), e535, 2018 | 650 | 2018 |
| Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: A case study with the Lorenz 96 model J Brajard, A Carrassi, M Bocquet, L Bertino Journal of Computational Science 44, 101171, 2020 | 254 | 2020 |
| Scientific challenges of convective-scale numerical weather prediction JI Yano, MZ Ziemiański, M Cullen, P Termonia, J Onvlee, L Bengtsson, ... Bulletin of the American Meteorological Society 99 (4), 699-710, 2018 | 145 | 2018 |
| Combining data assimilation and machine learning to infer unresolved scale parametrization J Brajard, A Carrassi, M Bocquet, L Bertino Philosophical Transactions of the Royal Society A 379 (2194), 20200086, 2021 | 134 | 2021 |
| Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review S Cheng, C Quilodrán-Casas, S Ouala, A Farchi, C Liu, P Tandeo, ... IEEE/CAA Journal of Automatica Sinica 10 (6), 1361-1387, 2023 | 125 | 2023 |
| Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization M Bocquet, J Brajard, A Carrassi, L Bertino Foundations of Data Science 2 (1), 55-80, 2020 | 125 | 2020 |
| Comparison of local ensemble transform Kalman filter, 3DVAR, and 4DVAR in a quasigeostrophic model SC Yang, M Corazza, A Carrassi, E Kalnay, T Miyoshi Monthly weather review 137 (2), 693-709, 2009 | 110* | 2009 |
| A review of innovation-based methods to jointly estimate model and observation error covariance matrices in ensemble data assimilation P Tandeo, P Ailliot, M Bocquet, A Carrassi, T Miyoshi, M Pulido, Y Zhen Monthly Weather Review 148 (10), 3973-3994, 2020 | 107* | 2020 |
| Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models M Bocquet, J Brajard, A Carrassi, L Bertino Nonlinear Processes in Geophysics 26 (3), 143-162, 2019 | 102 | 2019 |
| A study on cut-off low vertical structure and precipitation in the Mediterranean region F Porcù, A Carrassi, CM Medaglia, F Prodi, A Mugnai Meteorology and Atmospheric Physics 96, 121-140, 2007 | 81 | 2007 |
| Four-dimensional ensemble variational data assimilation and the unstable subspace M Bocquet, A Carrassi Tellus A: Dynamic Meteorology and Oceanography 69 (1), 1304504, 2017 | 67 | 2017 |
| Data assimilation as a nonlinear dynamical systems problem: Stability and convergence of the prediction-assimilation system A Carrassi, M Ghil, A Trevisan, F Uboldi Chaos: An Interdisciplinary Journal of Nonlinear Science 18 (2), 2008 | 66 | 2008 |
| Adaptive covariance inflation in the ensemble Kalman filter by Gaussian scale mixtures PN Raanes, M Bocquet, A Carrassi Quarterly Journal of the Royal Meteorological Society 145, 53– 75, 2019 | 64 | 2019 |
| Lyapunov vectors and assimilation in the unstable subspace: theory and applications L Palatella, A Carrassi, A Trevisan Journal of Physics A: Mathematical and Theoretical 46 (25), 254020, 2013 | 60 | 2013 |
| DADA: data assimilation for the detection and attribution of weather and climate-related events A Hannart, A Carrassi, M Bocquet, M Ghil, P Naveau, M Pulido, J Ruiz, ... Climatic Change 136, 155-174, 2016 | 59 | 2016 |
| Accounting for model error in variational data assimilation: A deterministic formulation A Carrassi, S Vannitsem Monthly Weather Review 138 (9), 3369-3386, 2010 | 58 | 2010 |
| Degenerate Kalman filter error covariances and their convergence onto the unstable subspace M Bocquet, KS Gurumoorthy, A Apte, A Carrassi, C Grudzien, ... SIAM/ASA Journal on Uncertainty Quantification 5 (1), 304-333, 2017 | 57 | 2017 |
| State and parameter estimation with the extended Kalman filter: an alternative formulation of the model error dynamics A Carrassi, S Vannitsem Quarterly Journal of the Royal Meteorological Society 137 (655), 435-451, 2011 | 57 | 2011 |
| Stochastic parameterization identification using ensemble Kalman filtering combined with maximum likelihood methods M Pulido, P Tandeo, M Bocquet, A Carrassi, M Lucini Tellus A: Dynamic Meteorology and Oceanography 70 (1), 1-17, 2018 | 55 | 2018 |
| Adaptive observations and assimilation in the unstable subspace by breeding on the data-assimilation system A Carrassi, A Trevisan, F Uboldi Tellus A: Dynamic Meteorology and Oceanography 59 (1), 101-113, 2007 | 51 | 2007 |
Marc BocquetÉcole des Ponts, Institut Polytechnique de Paris, CEREAVerified email at enpc.fr
