A global hourly ISIMIP3 climate forcing dataset for impact modeling

Sub-daily climate data are increasingly important for climate-impact assessments because many processes, such as heat stress, hydrological extremes, land–surface energy balance, and renewable-energy production, respond non-linearly to intra-day variability. Daily data miss short-duration events and obscure sub-daily inter-variable interactions, creating biases in impact estimates. To address these limitations and provide consistent forcing across sectors, we generated a global hourly climate dataset by temporally disaggregating the Inter-Sectoral Impact Model Intercomparison Project Phase 3 (ISIMIP3) daily climate archives using the Temporal Disaggregation Tool (Teddy). The approach uses analogue-based hourly profiles from the bias-corrected WFDE5 (WATCH Forcing Data methodology applied to ERA5) reanalysis, preserves daily mass and energy, and maintains temporal coherence between variables. We illustrate the utility of the hourly data with four applications using the MPI Earth System Model (MPI-ESM) under ScenarioMIP pathway SSP3–7.0: (1) the fraction of wet hours, revealing rainfall intermittency not captured by daily wet-day metrics; (2) the number of hours with dangerous heat-index values, capturing joint diurnal cycles of temperature and humidity; (3) hours with wind speeds suitable for onshore wind-power generation; and (4) photovoltaic power potential calculated from radiation, temperature, and wind speed at hourly resolution. We discuss the benefits of preserving inter-variable timing, along with limitations such as reduced spatial coherence at sub-daily scales and potential constraints under strong climate-change signals. The resulting hourly ISIMIP3 dataset provides a harmonized foundation for more realistic sub-daily climate-impact modeling across sectors. The dataset is openly available through the ISIMIP repository under the following DOIs: https://doi.org/10.48364/ISIMIP.736682 (Bechtold et al., 2026a) and https://doi.org/10.48364/ISIMIP.170328 (Bechtold et al., 2026b).