The Teddy-Tool v1.0: temporal disaggregation of daily climate model data for climate impact analysis

Abstract. Climate models provide required input data for global or regional climate impact analysis in aggregated form, often on a daily basis to save space on data servers. Today, many impact models work with daily data, however, sub-daily climate information is getting increasingly important for more and more models from different sectors, such as the agricultural, the water, and the energy sector. Therefore, the open source Teddy-Tool (temporal disaggregation of daily climate model data) has been developed to disaggregate (temporally downscale) daily climate data to sub-daily hourly values for temperature, precipitation, humidity, longwave radiation, shortwave radiation, surface pressure and wind speed. Thereby, mass and energy are strictly preserved by the Teddy-Tool to exactly reproduce the daily values from the climate models. Here, we describe and document the temporal disaggregation, which is based on globally available bias-corrected hourly reanalysis WFDE5 data from 1980–2019 to take specific local and seasonal features of the diurnal course empirically into account. The physical dependency between variables is preserved, since the diurnal profile of all variables is taken from the same, most similar meteorological day of the historical reanalysis dataset. We perform a sensitivity analysis of different time window sizes used for finding the most similar meteorological day in the past. In addition, we perform a cross-validation, autocorrelation and extreme value analysis for 30 globally distributed samples around the world, representing different climate zones. The validation shows that Teddy is able to reproduce historical diurnal courses with high correlations >0.9 for all variables, except for wind speed (>0.75) and precipitation (>0.5). Consequently, sub-daily data provided by the Teddy-Tool could make climate impact assessments more robust and reliable.