| 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 | 605 | 2018 |
| TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic. P Sakov, F Counillon, L Bertino, KA Lisæter, PR Oke, A Korablev Ocean Science 8 (4), 633-656, 2012 | 440 | 2012 |
| Sequential data assimilation techniques in oceanography L Bertino, G Evensen, H Wackernagel International Statistical Review 71 (2), 223-241, 2003 | 413 | 2003 |
| On the future navigability of Arctic sea routes: High-resolution projections of the Arctic Ocean and sea ice Y Aksenov, EE Popova, A Yool, AJG Nurser, TD Williams, L Bertino, ... Marine Policy 75, 300-317, 2017 | 355 | 2017 |
| Relation between two common localisation methods for the EnKF P Sakov, L Bertino Computational Geosciences 15, 225-237, 2011 | 236 | 2011 |
| Wave–ice interactions in the marginal ice zone. Part 1: Theoretical foundations TD Williams, LG Bennetts, VA Squire, D Dumont, L Bertino Ocean Modelling 71, 81-91, 2013 | 226 | 2013 |
| 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 | 225 | 2020 |
| An iterative EnKF for strongly nonlinear systems P Sakov, DS Oliver, L Bertino Monthly Weather Review 140 (6), 1988-2004, 2012 | 217 | 2012 |
| A wave‐based model for the marginal ice zone including a floe breaking parameterization D Dumont, A Kohout, L Bertino Journal of Geophysical Research: Oceans 116 (C4), 2011 | 197 | 2011 |
| Gaussian anamorphosis extension of the DEnKF for combined state parameter estimation: Application to a 1D ocean ecosystem model E Simon, L Bertino Journal of Marine Systems 89 (1), 1-18, 2012 | 192 | 2012 |
| Asynchronous data assimilation with the EnKF P Sakov, G Evensen, L Bertino Tellus A: Dynamic Meteorology and Oceanography 62 (1), 24-29, 2010 | 184 | 2010 |
| From observation to information and users: The Copernicus Marine Service perspective PY Le Traon, A Reppucci, E Alvarez Fanjul, L Aouf, A Behrens, ... Frontiers in Marine Science 6, 234, 2019 | 176 | 2019 |
| Application of the Gaussian anamorphosis to assimilation in a 3-D coupled physical-ecosystem model of the North Atlantic with the EnKF: a twin experiment E Simon, L Bertino Ocean Science 5 (4), 495-510, 2009 | 164 | 2009 |
| Process identification by principal component analysis of river water-quality data W Petersen, L Bertino, U Callies, E Zorita Ecological Modelling 138 (1-3), 193-213, 2001 | 162 | 2001 |
| GEROS-ISS: GNSS reflectometry, radio occultation, and scatterometry onboard the international space station J Wickert, E Cardellach, M Martín-Neira, J Bandeiras, L Bertino, ... IEEE Journal of selected topics in applied Earth observations and Remote …, 2016 | 153 | 2016 |
| GODAE systems in operation E DOmBrOwSky, L Bertino, GB Brassington, EP Chassignet, F Davidson, ... Oceanography 22 (3), 80-95, 2009 | 153 | 2009 |
| Wave–ice interactions in the marginal ice zone. Part 2: Numerical implementation and sensitivity studies along 1D transects of the ocean surface TD Williams, LG Bennetts, VA Squire, D Dumont, L Bertino Ocean Modelling 71, 92-101, 2013 | 147 | 2013 |
| Measuring currents, ice drift, and waves from space: the Sea surface KInematics Multiscale monitoring (SKIM) concept F Ardhuin, Y Aksenov, A Benetazzo, L Bertino, P Brandt, E Caubet, ... Ocean Science 14 (3), 337-354, 2018 | 144 | 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 | 132 | 2021 |
| Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization M Bocquet, J Brajard, A Carrassi, L Bertino arXiv preprint arXiv:2001.06270, 2020 | 119 | 2020 |
