Involved in the EUMETNET Postprocessing module.

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

• 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]