SDCLIREFv2

The intensity and frequency of hydrometeorological extreme events are expected to increase due to climate change. Accurate analysis of precipitation and temperature, particularly for low-flow assessments, requires high spatial and sub-daily resolution data, which is often insufficient in density and duration. The ClimEx-II project (Climate Change and Hydrological Extreme Events 2nd Phase) focuses on understanding these changes in hydrological extremes. CRCM5-LE, a Single-Model Regional Climate Model Ensemble driven by CanESM2 under RCP8.5 was created to distinguish between clear climate change signals and natural variability. The ensemble covers a European and a North American domain, each comprising 50 members from 1951 to 2100. As a reference data set for correcting the bias in CRCM5, Wood et al. (2017) introduced the SDCLIREF, a sub-daily (3h), high-resolution (500m) data set for the domain of Bavaria and hydrologically important neighbouring catchments for the period from 1980 to 2010. For temporal densification, the Method of Fragments (Sharma and Srikanthan (2006); Westra et al. (2012)) was applied. Findings from ClimEx-I have shown that precipitation in the reference meteorology for the Alpine region is partly underestimated. This underestimation is due to two main factors: wind-related measurement errors (especially with snow) and the non-representative distribution of measurement stations. The ClimEx-I dataset has been extended to cover 2015-2020 to include the dry periods of recent years. The dataset now includes hourly and daily disaggregated data from 1980 to 2020. This extension allows for a better estimation of the current climate and shifts the reference period to 1991-2020. In some northern areas, this results in an increase in annual mean temperatures by up to 0.9°C. Comparing the two reference periods, higher temperatures were observed in almost all months across the regions, except for the Alpine areas in September and October. With the precipitation correction applied for the reference period shift, the dataset now provides a current and realistic depiction of the climatic baseline. This helps represent the dynamics of ongoing climate change and allows for more precise calibration of the hydrological model for low-flow events. The 500m data are upscaled by the method of Bilinear Combine to the 12km resolution used in CRCM5-LE.