Funding
ARC (Action de recherche concertée), 2024-2029, UCLouvain/UNamur
EXtreme weather Attribution at mid- and high-Latitudes using advanced statistical Techniques (EXALT)
An interdisciplinary effort involving the Earth and Climate Center (part of ELI) and the Institute of Statistics, Biostatistics and Actuarial Sciences (part of LIDAM) of the UCLouvain. Supported by the Wallonia-Brussels Federation.
The overall objective of EXALT is to introduce a novel comprehensive framework for extreme event attribution and to apply it to heatwaves and compound drought-heat events over Europe, floods in southern and northern Europe, and sea ice extent over the Antarctic. Four PhD students are currently working under the supervision of Francesco Ragone (University of Leicester), François Massonnet (UCLouvain), Hugues Goosse (UCLouvain), Johan Segers (KULeuven and UCLouvain) and myself. For more information, see our website.
MIS (Mandat d’impulsion scientifique), 2024-2028, UCLouvain/UNamur
Flexible statistical models for compound climate events
Funding instrument of the F.R.S-FNRS to support young permanent researchers who seek to develop a scientific unit focusing on a future-oriented area within their university.
The objectives of this project are to (i) propose flexible multivariate dependence models that are capable of a realistic representation of both center and tail(s) of a random vector, to (ii) propose estimators of the parameters of such models with the goal of inferring failure probabilities for multivariate extreme events and improve their precision via data augmentation and (iii) project climate-induced risks of some major compound events in terms of global warming.
FED-tWIN, 2025-2034, UNamur/RMI
attributioN of EXtreme climaTe events based on advanced STATistical and dynamical theories (NEXT-STAT)
Interdisciplinary project involving the UNamur Institute for complex systems (NaXys) and the Royal Meteorological Institute of Belgium (RMI), funded by the Belgian Science Policy (BELSPO). Co-supervised by Stéphane Vannitsem (RMI) and Timoteo Carletti (UNamur).