Climate Impact Assessment Requires Weighting: Introducing the Weighted Climate Dataset

TL;DR

This paper introduces a comprehensive, weighted climate dataset that integrates socio-economic factors to improve climate impact assessments, addressing data inconsistency and reproducibility issues in climate research.

Contribution

The authors developed a globally comprehensive weighted climate dataset using socio-economic proxies, unifying data processing and validation for enhanced climate impact analysis.

Findings

Dataset covers 1900-2023 with daily, monthly, annual data

Weighted data improves relevance for impact assessments

Validated against leading climate impact studies

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/.