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The research conducted in the Section is devoted to the fundamental aspects of the dynamics of the atmosphere and climate, mainly related to the understanding of their variability and predictability, through the development of mathematical models and the use of time series analysis techniques.These problems are tackled by applying, adapting and extending the tools of nonlinear dynamics, chaos theory and stochastic processes. The theoretical results obtained are first tested on simplified models and are subsequently applied to realistic forecasting models.


Most prominent achievements:

  • The development of a theory of the error growth in unstable dynamical systems and its application to low and intermediate order atmospheric models.
  • The modelling of the quaternary glaciations and the discovery of the phenomenon of stochastic resonance, providing a qualitative explanation of the sensitivity of the climatic system to weak external forcings.
  • The discovery of the chaotic nature of the dynamics of the quaternary glaciations and its modelling.
  • The development of statistical prediction models and their use in the classification and prediction of weather and hydrological regimes.
  • The investigation of the dynamics of realistic operational regional models.
  • The development of a theory of recurrent events and extreme values in the context of deterministic systems.
  • The development of new data assimilation shemes taking into account of the deterministic nature of model errors.

Current research activities:

  • Dynamics of model errors, in particular the role of parametric errors, subgrid scale parameterization and errors in the boundary conditions.
  • Development and analysis of control strategies of prediction errors: Modelling of error sources through various types of noises.
  • Dynamical basis of Model Output Statistics (MOS) techniques.
  • Development of a unifed theory describing the dynamics of both initial and model errors.
  • Development of a dynamical theory of the extreme events generated by deterministic processes: Probability distributions, return times, comparison with traditional approaches.Study of the extreme events coming from natural data.
  • Kinetics and thermodynamics of transitions between states: transient effects, nucleation, self-assembly of complex materials (aerosols, pollutants) in the atmosphere.   
  • Development of low-order coupled ocean-atmosphere models; study of their dynamics and predictability.


  • Center for Nonlinear phenomena and complex systems (ULB), Grégoire Nicolis.
  • Catalan Institute of Climate Sciences, Barcelona, Spain, Alberto Carrassi.
  • Université Catholique de Louvain, Belgium, Hugues Goosse, Michel Crucifix.
  • Université de Liège, Belgium, Alexander Barth.
  • University of Hamburg, Germany, Valerio Lucarini.
  • Laboratoire de Météorologie Dynamique, France, Michael Ghil.

Current projects:

  • BRAIN-BE project, Improving the representation and prediction of climate processes through stochastic parameterization schemes (STOCHCLIM), 2013-2017. Coordinateur : Dr S. Vannitsem, Partners: Profs Crucifix (UCL) and P. Termonia (UGent).  

Past projects:

  • Belgian federal Office for Scientific, Technical and Cultural Affairs: Approche nouvelle de l'assimilation de données tenant compte des propriétés statistiques et dynamiques de l'erreur de modélisation. Coordinator: C. Nicolis
  • European Commission project, 'Extreme Events. Causes and Consequences'', E2C2. Coordinator of RMI node: C. Nicolis
  • ESA project:  influence of mass transport and surface growth processes on protein crystal perfection.
  •  Understanding and predicting Antarctic Sea Ice variability at the decadal timescale. Projet SPP: SD/CA/04A. 2011-2014, Coordinator: Prof H Goosse (UCL); partners: Dr. A Barth (ULg), Dr. S. Vannitsem (RMI).