| Statistical Postprocessing for Weather Forecasts: Review, Challenges, and Avenues in a Big Data World S Vannitsem, JB Bremnes, J Demaeyer, GR Evans, J Flowerdew, S Hemri, ... Bulletin of the American Meteorological Society 102 (3), E681-E699, 2021 | 95 | 2021 |
| Low-frequency variability and heat transport in a low-order nonlinear coupled ocean–atmosphere model S Vannitsem, J Demaeyer, L De Cruz, M Ghil Physica D: Nonlinear Phenomena 309, 71-85, 2015 | 38 | 2015 |
| Exploring the Lyapunov instability properties of high-dimensional atmospheric and climate models L De Cruz, S Schubert, J Demaeyer, V Lucarini, S Vannitsem Nonlinear Processes in Geophysics 25 (2), 387-412, 2018 | 30 | 2018 |
| The modular arbitrary-order ocean-atmosphere model: MAOOAM v1. 0 L De Cruz, J Demaeyer, S Vannitsem Geoscientific Model Development 9 (8), 2793-2808, 2016 | 30* | 2016 |
| Stochastic parametrization of subgrid‐scale processes in coupled ocean–atmosphere systems: benefits and limitations of response theory J Demaeyer, S Vannitsem Quarterly Journal of the Royal Meteorological Society 143 (703), 881-896, 2017 | 27 | 2017 |
| Data assimilation for chaotic dynamics A Carrassi, M Bocquet, J Demaeyer, C Grudzien, P Raanes, S Vannitsem Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol …, 2022 | 14* | 2022 |
| Noise-induced escape from bifurcating attractors: Symplectic approach in the weak-noise limit J Demaeyer, P Gaspard Physical Review E 80 (3), 031147, 2009 | 14 | 2009 |
| Stochastic Parameterization of Subgrid-Scale Processes: A Review of Recent Physically Based Approaches J Demaeyer, S Vannitsem Advances in Nonlinear Geosciences, 55-85, 2018 | 12 | 2018 |
| Comparison of stochastic parameterizations in the framework of a coupled ocean–atmosphere model J Demaeyer, S Vannitsem Nonlinear Processes in Geophysics 25 (3), 605-631, 2018 | 11 | 2018 |
| qgs: A flexible Python framework of reduced-order multiscale climate models J Demaeyer, L De Cruz, S Vannitsem Journal of Open Source Software 5 (56), 2597, 2020 | 7 | 2020 |
| Correcting for model changes in statistical postprocessing–an approach based on response theory J Demaeyer, S Vannitsem Nonlinear Processes in Geophysics 27 (2), 307-327, 2020 | 6 | 2020 |
| A trace formula for activated escape in noisy maps J Demaeyer, P Gaspard Journal of Statistical Mechanics: Theory and Experiment 2013 (10), P10026, 2013 | 6 | 2013 |
| Extratropical Low‐Frequency Variability With ENSO Forcing: A Reduced‐Order Coupled Model Study S Vannitsem, J Demaeyer, M Ghil Journal of Advances in Modeling Earth Systems 13 (6), e2021MS002530, 2021 | 5 | 2021 |
| Identifying Efficient Ensemble Perturbations for Initializing Subseasonal‐To‐Seasonal Prediction J Demaeyer, SG Penny, S Vannitsem Journal of Advances in Modeling Earth Systems 14 (5), e2021MS002828, 2022 | 2 | 2022 |
| The EUPPBench postprocessing benchmark dataset v1. 0 J Demaeyer, S Lerch, C Primo, B Van Schaeybroeck, A Atencia, ... Earth System Science Data Discussions, 1-25, 2023 | | 2023 |
| Multistability in a Coupled Ocean-Atmosphere Reduced Order Model: Non-linear Temperature Equations O Hamilton, J Demaeyer, S Vannitsem, M Crucifix arXiv preprint arXiv:2301.04990, 2023 | | 2023 |
| Statistical post-processing of ensemble forecasts at the Belgian met service J Demaeyer, S Vannitsem, B Van Schaeybroeck European Centre For Medium-Range Weather Forecasts, 2022 | | 2022 |
| Extratropical Low-Frequency Variability With ENSO Forcing: A Reduced-Order Coupled Model Investigation S Vannitsem, J Demaeyer, M Ghil AGU Fall Meeting Abstracts 2021, A15M-1829, 2021 | | 2021 |
| Correcting for Model Changes in Statistical Postprocessing an Approach Based on Response Theory S Vannitsem, J Demaeyer AGU Fall Meeting Abstracts 2021, NG15B-0429, 2021 | | 2021 |
| qgs: A flexible Python framework of reduced-order multiscale climate models L De Cruz, J Demaeyer, S Vannitsem EGU General Assembly Conference Abstracts, EGU21-1091, 2021 | | 2021 |
Stéphane VannitsemResearcher, Royal Meteorological Institute of BelgiumVerified email at meteo.be
