In order to estimate the return period of bivariate CEs, a novel non-parametric approach employing bivariate Generalized Pareto distributions (bi-GPD) is proposed and compared to a copula-based approach. Simulations reveal that this approach is effective in case of positive asymptotic dependence and should be avoided in case of asymptotic independence.
Geostatistics, extreme events and Machine Learning for the climate transition
A project at heart of two transitions
A digital transition
Massive and heterogeneous environmental data, making new geostatistical and Machine Learning methods necessary.
A climate transition
In response to changes affecting air, water, soil and biodiversity, unprecedented in their amplitude, speed and simultaneous nature.
The objectives of the chair in three lines of research
Develop effective methods and tools to process spatialized and temporal data in order to assess the impacts and quantify the risks associated with ongoing climate change.
Predictive methods
Develop predictive methods for spatial and spatio-temporal phenomena, capable of processing large datasets.
A toolbox
Develop innovative simulation methods for extreme events and risk assessment and distribute them freely.
Hybrid approaches
Hybridize the ability of geostatistics to interpolate in space and time and that of Machine Learning to extract links and knowledge.
Publications
In mountainous areas orographic effects create strong horizontal gradients of various rainfall statistics such as the frequency of occurrence, the distribution of intensity and the structure of spatial correlation. To account for these non-stationary statistics this paper presents a non-stationary trans-Gaussian model tailored for daily rainfall over complex topography.
Events
Conference on stochastic weather generators
The Geolearning Chair is contributing to the organization of the conference on Stochastic Weather Generators, which will be held in Grenoble from December 2nd to 4th, 2025. This international workshop aims to explore cutting-edge methods and emerging challenges for simulating weather variables: precipitation, temperatures, etc.
Two presentations of the Geolearning chair at JDS 2025
Mike Pereira and Thomas Romary presented their work at the last Statistics Days, organized by the SFDS.