Extreme Value Analysis (EVA) in Python
Acclimate - an agent-based model for economic loss propagation
[NeurIPS'25] RiverMamba: A State Space Model for Global River Discharge and Flood Forecasting
[NeurIPS'24] Identifying Spatio-Temporal Drivers of Extreme Events
Identification of compounding drivers of river floods
A repo for "Extreme Precipitation-Temperature Scaling in California: The Role of Atmospheric Rivers"
An RShiny web application for visualizing high frequency meteorological data and identifying climate anomalies in the McMurdo Dry Valleys of Antarctica.
🌊 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 futurs possibles pour la ressource en eau.
[NeurIPS'24] Identifying Spatio-Temporal Drivers of Extreme Events
Implementation of classical and recurrence-free quantum reservoir computing for predicting chaotic dynamics
Physics-informed ensemble for 12-h city-region temperature forecasts. Advection–diffusion prior + ConvLSTM + RAFL + edRVFL-SC for extreme-event warnings.
R code and example data to determine temporal shifts in intervals between extreme total annual rainfall
Evaluating AI-Weather forecasts (Pangu AI) on predicting extreme events like tropical cyclones by comparing it to ERA5. // Master Course at the University of Bern: Seminar in Climatology (2024).
This repository provides a Python implementation of the Gaussian Mixture Model (GMM) algorithm for detecting extreme events in CMIP6 data.
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:
Trends and variability of precipitation extremes in the Peruvian Altiplano (1971–2013)
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
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