Dynamical Meteorology and Climatology Unit

Jonathan Demaeyer


Research interests

  • Theoretical and applied weather forecasts postprocessing
  • Ocean-atmosphere coupled variability
  • Low-order modelling
  • Data assimilation
  • Subgrid scale parameterizations
  • Bifurcation analysis in climate models

4 recent publications

  • Demaeyer, J., Bhend, J., Lerch, S., Primo, C., Van Schaeybroeck, B., Atencia, A., ... & Vannitsem, S. (2023). The EUPPBench postprocessing benchmark dataset v1. 0. Earth System Science Data, 15(6), 2635-2653. [link]
  • Demaeyer, J., Penny, S. G., & Vannitsem, S. (2022). Identifying efficient ensemble perturbations for initializing subseasonal‐to‐seasonal prediction. Journal of Advances in Modeling Earth Systems, e2021MS002828. [link]
  • Vannitsem, S., Bremnes, J. B., Demaeyer, J., Evans, G. R., Flowerdew, J., Hemri, S., ... & Ylhaisi, J. (2021). Statistical postprocessing for weather forecasts: Review, challenges, and avenues in a big data world. Bulletin of the American Meteorological Society, 102(3), E681-E699. [link]
  • Demaeyer, J., De Cruz, L., & Vannitsem, S. (2020). qgs: A flexible Python framework of reduced-order multiscale climate models. Journal of Open Source Software, 5(56), 2597. [link]

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