An explorative interface for spatial extreme events data
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Updated
Jan 7, 2023 - Vue
An explorative interface for spatial extreme events data
A repo for "Extreme Precipitation-Temperature Scaling in California: The Role of Atmospheric Rivers"
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:
A learn module on exposure of land and population to extreme events
Identification of compounding drivers of river floods
Website for showing the all codes and methodology to analyze compound extreme events and their socio-economic impacts.
A Non-stationary Dependence Model for Extreme European Windstorms
Trends and variability of precipitation extremes in the Peruvian Altiplano (1971–2013)
R code and example data to determine temporal shifts in intervals between extreme total annual rainfall
Acclimate - an agent-based model for economic loss propagation
Extreme Value Analysis (EVA) in Python
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