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Vannitsem, Stéphane
ORCID

Instituut
Publicaties (32)

Koninklijk Meteorologisch Instituut (KMI), meer

Institutioneel adres:
Ringlaan 3
1180 Brussel
Belgium

A1 publicaties (26) [show]
Docquier, D.; Vannitsem, S.; Bellucci, A. (2023). The rate of information transfer as a measure of ocean–atmosphere interactions. Earth System Dynamics 14(3): 577-591. https://dx.doi.org/10.5194/esd-14-577-2023, meer Hamilton, O.; Demaeyer, J.; Vannitsem, S.; Crucifix, M. (2023). Multistability in a coupled ocean-atmosphere reduced‐order model: nonlinear temperature equations. Q. J. R. Meteorol. Soc. 149(757): 3423-3439. https://dx.doi.org/10.1002/qj.4564, meer Vannitsem, S. (2023). Impact of tropical teleconnections on the long-range predictability of the atmosphere at midlatitudes: a reduced-order multi-scale model perspective. Journal of Physics: Complexity 4(4): 045006. https://dx.doi.org/10.1088/2632-072X/ad04e8, meer Docquier, D.; Vannitsem, S.; Ragone, F.; Wyser, K.; Liang, X.S. (2022). Causal links between Arctic sea ice and its potential drivers based on the rate of information transfer. Geophys. Res. Lett. 49(9): e2021GL095892. https://dx.doi.org/10.1029/2021GL095892, meer Vannitsem, S.; Liang, X.S. (2022). Dynamical dependencies at monthly and interannual time scales in the climate system: study of the North Pacific and Atlantic regions. Tellus, Ser. A, Dyn. meteorol. oceanogr. 74(1): 141-158. https://dx.doi.org/10.16993/tellusa.44, meer Alberti, T.; Donner, R.V.; Vannitsem, S. (2021). Multiscale fractal dimension analysis of a reduced order model of coupled ocean-atmosphere dynamics. Earth System Dynamics 12(3): 837-855. https://dx.doi.org/10.5194/esd-12-837-2021, meer Vannitsem, S.; Demaeyer, J.; Ghil, M. (2021). Extratropical low-frequency variability with ENSO forcing: a reduced-order coupled model study. J. Adv. Model. Earth Syst. 13(6): e2021MS002530. https://dx.doi.org/10.1029/2021MS002530, meer Tao, L.; Duan, W.; Vannitsem, S. (2020). Improving forecasts of El Niño diversity: a nonlinear forcing singular vector approach. Clim. Dyn. 55(3-4): 739-754. https://hdl.handle.net/10.1007/s00382-020-05292-5, meer Tondeur, M.; Carrassi, A.; Vannitsem, S.; Bocquet, M. (2020). On temporal scale separation in coupled data assimilation with the ensemble Kalman filter. Journal of Statistical Physics 179(5-6): 1161-1185. https://hdl.handle.net/10.1007/s10955-020-02525-z, meer Vannitsem, S.; Duan, W. (2020). On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean-atmosphere systems. Clim. Dyn. 55(5-6): 1125-1139. https://hdl.handle.net/10.1007/s00382-020-05313-3, meer Faranda, D.; Messori, G.; Vannitsem, S. (2019). Attractor dimension of time-averaged climate observables: insights from a low-order ocean-atmosphere model. Tellus, Ser. A, Dyn. meteorol. oceanogr. 71(1): 1-11. https://dx.doi.org/10.1080/16000870.2018.1554413, meer Vannitsem, S.; Dalaiden, Q.; Goosse, H. (2019). Testing for dynamical dependence: application to the surface mass balance over Antarctica. Geophys. Res. Lett. 46(21): 12125-12135. https://dx.doi.org/10.1029/2019GL084329, meer Vannitsem, S.; Solé‐Pomies, R.; De Cruz, L. (2019). Routes to long-term atmospheric predictability in reduced-order coupled ocean-atmosphere systems: impact of the ocean basin boundary conditions. Q. J. R. Meteorol. Soc. 145(723): 2791-2805. https://dx.doi.org/10.1002/qj.3594, meer Demaeyer, J.; Vannitsem, S. (2018). Comparison of stochastic parameterizations in the framework of a coupled ocean-atmosphere model. Nonlinear Process Geophys. 25(3): 605-631. https://dx.doi.org/10.5194/npg-25-605-2018, meer Vannitsem, S.; Ekelmans, P. (2018). Causal dependences between the coupled ocean-atmosphere dynamics over the tropical Pacific, the North Pacific and the North Atlantic. Earth System Dynamics 9(3): 1063-1083. https://dx.doi.org/10.5194/esd-9-1063-2018, meer Demaeyer, J.; Vannitsem, S. (2017). Stochastic parametrization of subgrid-scale processes in coupled ocean-atmosphere systems: benefits and limitations of response theory. Q. J. R. Meteorol. Soc. 143(703): 881-896. https://dx.doi.org/10.1002/qj.2973, meer Vannitsem, S.; Ghil, M. (2017). Evidence of coupling in ocean-atmosphere dynamics over the North Atlantic. Geophys. Res. Lett. 44(4): 2016-2026. https://dx.doi.org/10.1002/2016GL072229, meer De Cruz, L.; Demaeyer, J.; Vannitsem, S. (2016). The Modular Arbitrary-Order Ocean-Atmosphere Model: MAOOAM v1.0. Geosci. Model Dev. 9(8): 2793-2808. https://dx.doi.org/10.5194/gmd-9-2793-2016, meer Vannitsem, S.; Lucarini, V. (2016). Statistical and dynamical properties of covariant lyapunov vectors in a coupled atmosphere-ocean model-multiscale effects, geometric degeneracy, and error dynamics. Journal of Physics A-Mathematical and Theoretical 49(22). https://dx.doi.org/10.1088/1751-8113/49/22/224001, meer Barth, A.; Canter, M.; Van Schaeybroeck, B.; Vannitsem, S.; Massonnet, F.; Zunz, V.; Mathiot, P.; Alvera-Azcárate, A.; Beckers, J.-M. (2015). Assimilation of sea surface temperature, sea ice concentration and sea ice drift in a model of the Southern Ocean. Ocean Modelling 93: 22-39. https://dx.doi.org/10.1016/j.ocemod.2015.07.011, meer Vannitsem, S. (2015). The role of the ocean mixed layer on the development of the North Atlantic Oscillation: a dynamical system's perspective. Geophys. Res. Lett. 42(20): 8615-8623. https://dx.doi.org/10.1002/2015GL065974, meer Vannitsem, S.; Demaeyer, J.; De Cruz, L.; Ghil, M. (2015). Low-frequency variability and heat transport in a low-order nonlinear coupled ocean-atmosphere model. Physica. D, Nonlinear phenomena 309: 71-85. https://dx.doi.org/10.1016/j.physd.2015.07.006, meer Vannitsem, S. (2014). Dynamics and predictability of a low-order wind-driven ocean-atmosphere coupled model. Clim. Dyn. 42(7-8): 1981-1998. dx.doi.org/10.1007/s00382-013-1815-8, meer Vannitsem, S. (2014). Stochastic modelling and predictability: analysis of a low-order coupled ocean-atmosphere model. Philos. Trans. - Royal Soc., Math. Phys. Eng. Sci. 372(2018): 20130282. https://dx.doi.org/10.1098/rsta.2013.0282, meer Vannitsem, S.; De Cruz, L. (2014). A 24-variable low-order coupled ocean-atmosphere model: OA-QG-WS v2. Geosci. Model Dev. 7(2): 649-662. https://dx.doi.org/10.5194/gmd-7-649-2014, meer Vannitsem, S. (2008). Dynamical properties of MOS forecasts: analysis of the ECMWE operational forecasting system. Weather and Forecasting 23(5): 1032-1043. https://dx.doi.org/10.1175/2008WAF2222126.1, meer
Boek [show]
Tricot, C.; Vandiepenbeeck, M.; Van de Vyver, H.; Debontridder, L.; Dewitte, S.; De Backer, H.; Van Malderen, R.; Mangold, A.; Hus, J.; Vannitsem, S.; de Troch, R.; Hamdi, R.; Brouyaux, F.; Roulin, E. (2015). Oog voor het klimaat. KMI: Brussel. 87 pp., meer
Boekhoofdstuk [show]
Vannitsem, S.; De Troch, R.; Hamdi, R. (2015). Onderzoek over klimaatvoorspelling en klimaatmodellering, in: Tricot, C. et al. Oog voor het klimaat. pp. 52-75, meer
Abstracts (3) [show]
Hamilton, O.; Demaeyer, J.; Xavier, A.; Vannitsem, S. (2024). The impact of model resolution on variability in a coupled land atmosphere model, in: EGU General Assembly 2024. Vienna, Austria & Online, 14-19 April 2024. pp. EGU24-9253. https://dx.doi.org/10.5194/egusphere-egu24-9253, meer Docquier, D.; Vannitsem, S.; Bellucci, A.; Frankignoul, C. (2023). The rate of information transfer as a measure of ocean-atmosphere interactions, in: EGU General Assembly 2023. Vienna, Austria & Online, 23–28 April 2023. pp. EGU23-4940. https://dx.doi.org/10.5194/egusphere-egu23-4940, meer Hamilton, O.; Demaeyer, J.; Vannitsem, S.; Crucifix, M. (2023). Multistability in a coupled ocean-atmosphere reduced order model: non-linear temperature equations, in: EGU General Assembly 2023. Vienna, Austria & Online, 23–28 April 2023. pp. EGU23-5496. https://dx.doi.org/10.5194/egusphere-egu23-5496, meer
Rapport [show]
Termonia, P.; Willems, P.; van Lipzig, N.; van Ypersele, J.P.; Fettweis, X.; De Ridder, K.; Gobin, A.; Stavrakou, T.; Ponsar, S.; Pottiaux, E.; Van Schaeybroeck, B.; De Cruz, L.; De Troch, R.; Giot, O.; Hamdi, R.; Vannitsem, S.; Duchêne, F.; Bertrand, C.; Tabari, H.; van Uytven, E.; Hosseinzadehtalaei, P.; Wouters, H.; Vanden Broucke, S.; Demuzere, M.; Marbaix, P.; Villanueva-Birriel, C.; Wyard, C.; Scholzen, C.; Doutreloup, S.; Lauwaet, D.; Bauwens, M.; Müller, J.-F.; Van den Eynde, D. (2018). Combining regional downscaling expertise in Belgium: CORDEX and beyond: Final Report. (BRAIN-be - (Belgian Research Action through Interdisciplinary Networks)). Belgian Science Policy: Brussels. 122 pp., meer