A global 0.1-degree gridded dataset of single and compound temperature and precipitation extremes from 1950 to 2025

Extreme weather and climate events are increasingly intensified by human-induced global warming, exacerbating risks to ecosystems and society. Yet many global extremes datasets remain coarse and fragmented, limiting local assessments of temperature and precipitation hazards. Here we introduce ERA5-EX, a global 0.1° gridded dataset of single and compound temperature and precipitation extremes from 1950 to 2025 derived from ERA5-Land. ERA5-EX provides 34 annual variables comprising 26 indices from Expert Team on Climate Change Detection and Indices, and eight bivariate metrics that quantify occurrence days for compound wet-hot, wet-cold, dry-hot, dry-cold, warm day-night, cold day-night, warm-heavy rain, and cold-heavy rain events. We also release the ERA5-EX tool, a Python workflow for tiled global or regional processing from daily inputs through index and compound event generation, feature extraction, and map and time series visualization. Technical evaluation is provided through intercomparison with observationally constrained gridded extremes products for single indices and with publicly available compound event datasets where definitions overlap. The ERA5-EX dataset and tool serve to support climate monitoring and risk assessment.