TerraClimate is a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015, providing spatially and temporally consistent climate data for ecological and hydrological studies. It combines high-resolution climatological normals from WorldClim with coarser resolution time-varying data from other sources to produce monthly datasets of precipitation, temperature, wind speed, vapor pressure, and solar radiation. The dataset also includes monthly surface water balance data using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. The data were validated using station data and streamflow gauges, showing improved accuracy compared to coarser resolution datasets. The dataset was developed using climatically aided interpolation, combining Climate Research Unit (CRU) Ts4.0 and Japanese 55-year Reanalysis (JRA-55) data with high-resolution climatological fields from WorldClim. The water balance model was used to calculate monthly water balance, including reference evapotranspiration and runoff. The dataset includes monthly total runoff, climatic water deficit, actual evapotranspiration, snow water equivalent, and soil moisture. TerraClimate is available through an unrestricted data repository hosted by the University of Idaho's Northwest Knowledge Network. The dataset includes monthly and time-varying data for 1958–2015 at a 1/24° spatial resolution. Validation against station data showed high correlation and low mean absolute error, with improvements in accuracy compared to CRU Ts4.0. The dataset has potential applications in climate studies, ecology, agriculture, and water resource management. It provides high-resolution climate and water balance data for regions with limited station-based data, improving the accuracy of climate models and ecological studies. The dataset is available for public use and includes ancillary data to help users understand the robustness of the data for specific geographic locations.TerraClimate is a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015, providing spatially and temporally consistent climate data for ecological and hydrological studies. It combines high-resolution climatological normals from WorldClim with coarser resolution time-varying data from other sources to produce monthly datasets of precipitation, temperature, wind speed, vapor pressure, and solar radiation. The dataset also includes monthly surface water balance data using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. The data were validated using station data and streamflow gauges, showing improved accuracy compared to coarser resolution datasets. The dataset was developed using climatically aided interpolation, combining Climate Research Unit (CRU) Ts4.0 and Japanese 55-year Reanalysis (JRA-55) data with high-resolution climatological fields from WorldClim. The water balance model was used to calculate monthly water balance, including reference evapotranspiration and runoff. The dataset includes monthly total runoff, climatic water deficit, actual evapotranspiration, snow water equivalent, and soil moisture. TerraClimate is available through an unrestricted data repository hosted by the University of Idaho's Northwest Knowledge Network. The dataset includes monthly and time-varying data for 1958–2015 at a 1/24° spatial resolution. Validation against station data showed high correlation and low mean absolute error, with improvements in accuracy compared to CRU Ts4.0. The dataset has potential applications in climate studies, ecology, agriculture, and water resource management. It provides high-resolution climate and water balance data for regions with limited station-based data, improving the accuracy of climate models and ecological studies. The dataset is available for public use and includes ancillary data to help users understand the robustness of the data for specific geographic locations.