Extreme Value Analysis (EVA) in Python

Acclimate - an agent-based model for economic loss propagation

Identification of compounding drivers of river floods

A repo for "Extreme Precipitation-Temperature Scaling in California: The Role of Atmospheric Rivers"

🌊 MEANDRE présente de manière guidée un regard d'expert sur les résultats des projections hydrologiques réalisées sur la France. La mise à jour de ces projections a été réalisé entre 2022 et 2024 dans le cadre du projet national Explore2. Ces résultats sont un aperçu de quelques futures possibles pour la ressource en eau.

An RShiny web application for visualizing high frequency meteorological data and identifying extreme climate events in the McMurdo Dry Valleys of Antarctica.

Website for showing the all codes and methodology to analyze compound extreme events and their socio-economic impacts.

R code and example data to determine temporal shifts in intervals between extreme total annual rainfall

[NeurIPS'24] Identifying Spatio-Temporal Drivers of Extreme Events

This repository provides a Python implementation of the Gaussian Mixture Model (GMM) algorithm for detecting extreme events in CMIP6 data.

Trends and variability of precipitation extremes in the Peruvian Altiplano (1971–2013)

Implementation of classical and recurrence-free quantum reservoir computing for predicting chaotic dynamics

This repo is the complete workflow for this publication: Tail associations in ecological variables and their impact on extinction risk, Ghosh et al., Ecosphere 11(5):e03132. For details and citation see here:

[NeurIPS'24] Identifying Spatio-Temporal Drivers of Extreme Events

An explorative interface for spatial extreme events data

A Non-stationary Dependence Model for Extreme European Windstorms

A learn module on exposure of land and population to extreme events