Code and derived data for "Exposure-weighted missed share reveals demand-driven drought detection gaps in global monitoring"

This archive contains the reproducible analysis code and derived outputs supporting the manuscript “Exposure-weighted missed share reveals demand-driven drought detection gaps in global monitoring” submitted to Natural Hazards. The archive includes Python/GDAL scripts for source-data verification, drought-index processing, exposure alignment, exposure-weighted missed share (EWMS) and detection-gap exposure-month (DGEM) calculations, EDDI robustness checks, MCDI hydrological validation, lagged validation, bootstrap skill testing, country and basin aggregation, trend analysis, and table generation. It also includes the generated derived NetCDF, GeoTIFF, CSV, and JSON outputs used to prepare the manuscript tables and results. Raw source datasets are not redistributed here because they are publicly available from their original repositories. The workflow uses GHM_drought, MCDI constituent indices, global Area Equipped for Irrigation, hybrid global cropland, and GlobPOP population datasets, with source DOIs documented in the included data manifest and README. This release is intended to provide a citable, reproducible record of the code and derived data associated with the submitted manuscript.