Income-based attribution of extrem events

This dataset accompanies the publication "Unequal Emissions, Unequal Impacts: How High-Income Groups Disproportionately Contribute to Climate Extremes Worldwide." In our study, we combine income-based emission inequality data with an emulator-based modeling framework to thoroughly study the link between emissions of individual, wealthy emitter groups and climate extremes worldwide. Specifically, we assess individual contributions to current global temperature levels and systematically attribute changes in regional monthly heat and drought extremes across the globe. We focus on emissions of the top 10/1/0.1 wealthiest individuals globally and in the US, the EU27, India and China. The dataset contains results for 1-in-50/100/10'000 year extremes in grid-cell level and whenever imapcts are aggregated by region we refer to the regionmask AR6 regions. The file contents are the following: Attributed_GMT.csv: attributed global mean temperature levels by emitter group tas_frequency_hot.nc & spei_frequency_hot.nc: attributed changes in the frequency of extreme events for extreme heat (tas) and potential droughts (spei) on grid-cell level tas_frequency_hot.nc & spei_frequency_hot.nc: attributed changes in the intensity of extreme events for extreme heat (tas) and potential droughts (spei) on grid-cell level processed_extremes_frequency.csv: attributed changes in the frequency of extreme events aggregated to ar6 land regions processed_extremes_intensity.csv: attributed changes in the intensity of extreme events aggregated to ar6 land regions