Climate Impact Assessment Requires Weighting: Introducing the Weighted Climate Dataset (Papers Track)

Marco Gortan (University of Basel); Lorenzo Testa (Carnegie Mellon University); Giorgio Fagiolo (Sant'Anna School of Advanced Studies); Francesco Lamperti (Sant'Anna School of Advanced Studies)

Paper PDF NeurIPS 2024 Recorded Talk Cite
Extreme Weather Public Policy Societal Adaptation & Resilience Uncertainty Quantification & Robustness

Abstract

High-resolution gridded climate data are readily available from multiple sources, yet climate research and decision-making increasingly require country and region-specific climate information weighted by socio-economic factors. Moreover, the current landscape of disparate data sources and inconsistent weighting methodologies exacerbates the reproducibility crisis and undermines scientific integrity. To address these issues, we have developed a globally comprehensive dataset at both country (GADM0) and region (GADM1) levels, encompassing various climate indicators (precipitation, temperature, SPEI, wind gust). Our methodology involves weighting gridded climate data by population density, night-time light intensity, cropland area, and concurrent population count – all proxies for socio-economic activity – before aggregation. We process data from multiple sources, offering daily, monthly, and annual climate variables spanning from 1900 to 2023. A unified framework streamlines our preprocessing steps, and rigorous validation against leading climate impact studies ensures data reliability. The resulting Weighted Climate Dataset is publicly accessible through an online dashboard at https://weightedclimatedata.streamlit.app/.