| Sensitivity of the AROME ensemble to initial and surface perturbations during HyMeX F Bouttier, L Raynaud, O Nuissier, B Ménétrier Quarterly Journal of the Royal Meteorological Society 142, 390-403, 2016 | 105 | 2016 |
| Linear filtering of sample covariances for ensemble-based data assimilation. Part I: Optimality criteria and application to variance filtering and covariance localization B Ménétrier, T Montmerle, Y Michel, L Berre Monthly Weather Review 143 (5), 1622-1643, 2015 | 105 | 2015 |
| Optimized localization and hybridization to filter ensemble-based covariances B Ménétrier, T Auligné Monthly Weather Review 143 (10), 3931-3947, 2015 | 47 | 2015 |
| Linear filtering of sample covariances for ensemble-based data assimilation. Part II: Application to a convective-scale NWP model B Ménétrier, T Montmerle, Y Michel, L Berre Monthly Weather Review 143 (5), 1644-1664, 2015 | 43 | 2015 |
| A 3D ensemble variational data assimilation scheme for the limited‐area AROME model: Formulation and preliminary results T Montmerle, Y Michel, E Arbogast, B Ménétrier, P Brousseau Quarterly Journal of the Royal Meteorological Society 144 (716), 2196-2215, 2018 | 40 | 2018 |
| Improvement of numerical weather prediction model analysis during fog conditions through the assimilation of ground-based microwave radiometer observations: a 1D-Var study P Martinet, D Cimini, F Burnet, B Ménétrier, Y Michel, V Unger Atmospheric Measurement Techniques 13 (12), 6593-6611, 2020 | 36 | 2020 |
| Estimation and diagnosis of heterogeneous flow‐dependent background‐error covariances at the convective scale using either large or small ensembles B Ménétrier, T Montmerle, L Berre, Y Michel Quarterly Journal of the Royal Meteorological Society 140 (683), 2050-2061, 2014 | 36 | 2014 |
| Heterogeneous background‐error covariances for the analysis and forecast of fog events B Ménétrier, T Montmerle Quarterly Journal of the Royal Meteorological Society 137 (661), 2004-2013, 2011 | 35 | 2011 |
| Ensemble–variational integrated localized data assimilation T Auligné, B Ménétrier, AC Lorenc, M Buehner Monthly Weather Review 144 (10), 3677-3696, 2016 | 31 | 2016 |
| Implicit and explicit cross‐correlations in coupled data assimilation P Laloyaux, S Frolov, B Ménétrier, M Bonavita Quarterly Journal of the Royal Meteorological Society 144 (715), 1851-1863, 2018 | 24 | 2018 |
| Estimating optimal localization for sampled background‐error covariances of hydrometeor variables M Destouches, T Montmerle, Y Michel, B Ménétrier Quarterly Journal of the Royal Meteorological Society 147 (734), 74-93, 2021 | 20 | 2021 |
| An evaluation of methods for normalizing diffusion‐based covariance operators in variational data assimilation AT Weaver, M Chrust, B Ménétrier, A Piacentini Quarterly Journal of the Royal Meteorological Society 147 (734), 289-320, 2021 | 16 | 2021 |
| An overlooked issue of variational data assimilation B Ménétrier, T Auligné Monthly Weather Review 143 (10), 3925-3930, 2015 | 13 | 2015 |
| Sensitivity of the AROME ensemble to initial and surface perturbations during HyMeX, QJ Roy. Meteor. Soc., 142, 390–403 F Bouttier, L Raynaud, O Nuissier, B Ménétrier | 12 | 2016 |
| Data assimilation for the Model for Prediction Across Scales–Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 1.0. 0): EnVar implementation and … Z Liu, C Snyder, JJ Guerrette, BJ Jung, J Ban, S Vahl, Y Wu, Y Trémolet, ... Geoscientific Model Development Discussions 2022, 1-33, 2022 | 11 | 2022 |
| Objective filtering of the local correlation tensor Y Michel, B Ménétrier, T Montmerle Quarterly Journal of the Royal Meteorological Society 142 (699), 2314-2323, 2016 | 10 | 2016 |
| Future benefits of high-density radiance data from MTG-IRS in the AROME fine-scale forecast model Final Report S Guedj, V Guidard, B Ménétrier, JF Mahfouf, F Rabier Météo-France & CNRS/CNRM-GAME, 2014 | 7 | 2014 |
| Modelling of background error covariances for the analysis of clouds and precipitation T Montmerle, Y Michel, B Ménétrier Proceedings of the ECMWF-JCSDA Workshop on Assimilating Satellite …, 2010 | 6 | 2010 |
| Using ensemble-estimated background error variances and correlation scales in the NEMOVAR system AT Weaver, M Chrust, B Ménétrier, A Piacentini, J Tshimanga, Y Yang, ... Report TR/PA/18/15, 39, 2018 | 5 | 2018 |
| Future benefits of high-density radiance data from MTG-IRS in the AROME fine-scale forecast model S Guedj, V Guidard, B Ménétrier, JF Mahfouf, F Rabier Final EUMETSAT report, 2014 | 5 | 2014 |
