Organizing committee
Bias Correction in Climate Studies 3rd worshop is organised by the following committee:
- Mathieu Vrac (LSCE-IPSL, France)
- Thomas Romary (Mines Paris PSL, France)
- Denis Allard (INRAE, France)
- Grégoire Mariéthoz (UNIL, Switzerland)
- Jose Manuel Gutierrez (Universidad de Cantabria, Spain)
- Henning Rust (Freie Universität Berlin, Germany)
- Bastien François (KNMI, Netherlands)
- Yoann Robin (LSCE-IPSL, France)
Supporting partners
PEPR Climat - TRACCS: EXTENDING project & LOCALISING project
The TRACCS research program (Transforming Climate Modeling for Climate Services), brings together the French climate modeling community. Its activities cover the fundamental understanding of climate change and its impacts, extending to the development of prototypes of climate services co-constructed by stakeholders and climate modeling experts.
The EXTENDING project (Extreme events under climate changes) and the LOCALISING project are two of the 10 TRACCS core projects.
The overall objective of EXTENDING is to provide refined hazard projections for a much wider range of extreme events and hazards than currently, including heat and cold waves, intense precipitation, droughts and storms, as well as more unusual types of extremes. To do so, EXTENDING explores various avenues, such as developments of statistical methods, postprocessing (bias correction) of climate simulations focusing on extreme climate events, detection & attribution of climate change, and investigation of diverse high-impact events and hazards including compound events.
The LOCALISING project aims to develop fully coupled, multi-component local climate system models allowing representation of climate at kilometer and hourly scales, and combining dynamic models and statistical/machine learning approaches to characterize climate uncertainty at the local scale.
More information about TRACCS can be found here
GeoLearning chair
The GeoLearning chair (2022-2027) aims to develop and apply methods stemming from the recent data science revolution to the challenges created by the climate transition. More specifically, the Chair will develop models and methods in geostatistics, in the theory of extreme events, and in machine learning, with applications to environmental science, to climate, and more generally to natural hazards (floods, storms, etc.).
The chair is co-financed by the SCOR Corporate Foundation for Science, alongside with BNP-Paribas, CCR (Caisse centrale de réassurance), ANDRA (Agence nationale pour la gestion des déchets radioactifs), the MINES ParisTech and INRAE (French National Institute for Agriculture, Food and Environment).
More information about the chair can be found here
SAMA (Statistics for Analysis, Modelling and Assimilation) working group - Institut Pierre Simon Laplace (IPSL)
The SAMA theme at IPSL aims to make better joint use of observations and modelling techniques to better represent climate, geophysical fluids and their constituents, and to improve their forecasting. This objective can be achieved through new mathematical and methodological developments. SAMA is historically grouped around three sub-themes: neural networks (which evolved into “Artificial Intelligence”), data assimilation, and statistics for climate and environmental sciences.
More information about SAMA can be found here
University of Lausanne – GAIA lab (Geostatistical Algorithms and Image Analysis) – COMBINE project
The GAIA lab hosts the COMBINE project which aims at improving multi-model climate projection using statistical and machine learning approaches. The goal of this project is in particular to consider the location-specific character of model biases, and to use model selection and weighting approaches to improve ensemble estimates. While COMBINE is funded by the Swiss National Science Foundation, it is an international effort that comprises researchers from institutions in both Switzerland and France: the University of Lausanne, INRAe and IPSL.
More information about the GAIA lab can be found here.
Mines Paris – PSL - Geostatistics Team
The Geostatistics Team at Mines Paris PSL, founded by Professor Georges Matheron, is a leader in spatial statistics. Specializing in fields like geology, environmental science, climatology, we develop and apply advanced techniques such as kriging, simulations, and modern innovations like SPDEs and deep generative learning. Our team offers training programs ranging from initial education to doctoral studies and hosts the biennial “Les Journées de Géostatistique” in Fontainebleau, showcasing the latest advancements in geostatistics.
More information about the Geostatistics Team can be found here.
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