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Jonathan Demaeyer
Jonathan Demaeyer
Royal Meteorological Institute of Belgium
Verified email at meteo.be
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Cited by
Year
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, 1-44, 2020
1882020
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
432015
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
37*2016
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
362018
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
302017
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
28*2022
The EUPPBench postprocessing benchmark dataset v1. 0
J Demaeyer, J Bhend, S Lerch, C Primo, B Van Schaeybroeck, A Atencia, ...
Earth System Science Data 15 (6), 2635-2653, 2023
172023
Noise-induced escape from bifurcating attractors: Symplectic approach in the weak-noise limit
J Demaeyer, P Gaspard
Physical Review E 80 (3), 031147, 2009
152009
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
142018
Stochastic Parameterization of Subgrid-Scale Processes: A Review of Recent Physically Based Approaches
J Demaeyer, S Vannitsem
Advances in Nonlinear Geosciences, 55-85, 2018
132018
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
122020
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
72021
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
72020
A trace formula for activated escape in noisy maps
J Demaeyer, P Gaspard
Journal of Statistical Mechanics: Theory and Experiment 2013 (10), P10026, 2013
62013
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
52022
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, 2021
22021
Physics of the Eddy Memory Kernel of a Baroclinic Midlatitude Atmosphere
E Vanderborght, J Demaeyer, G Manucharyan, W Moon, HA Dijkstra
Journal of the Atmospheric Sciences, 2024
2024
Variability and Predictability of a reduced-order land atmosphere coupled model
AK Xavier, J Demaeyer, S Vannitsem
arXiv preprint arXiv:2310.04326, 2023
2023
Multistability in a coupled ocean–atmosphere reduced‐order model: Nonlinear temperature equations
O Hamilton, J Demaeyer, S Vannitsem, M Crucifix
Quarterly Journal of the Royal Meteorological Society 149 (757), 3423-3439, 2023
2023
Rare event algorithm study of extremes of summer Arctic sea ice reduction
J Sauer, F Ragone, F Massonnet, G Zappa, J Demaeyer
arXiv preprint arXiv:2308.09984, 2023
2023
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