Extreme Value Analysis (EVA) in Python
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Updated
Feb 22, 2024 - Python
Extreme Value Analysis (EVA) in Python
Acclimate - an agent-based model for economic loss propagation
A repo for "Extreme Precipitation-Temperature Scaling in California: The Role of Atmospheric Rivers"
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
Trends and variability of precipitation extremes in the Peruvian Altiplano (1971–2013)
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:
Identification of compounding drivers of river floods
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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