Bias Correction of CRCM5-LE for Hydrological Bavaria

The frequency and intensity of extreme hydrometeorological events are anticipated to rise as a result of climate change. For precise analysis, especially in low-flow assessments, it is crucial to have data on precipitation and temperature with high spatial and sub-daily resolution. However, such data is often lacking in both density and duration. The ClimEx-II project (Climate Change and Hydrological Extreme Events 2nd Phase) is dedicated to enhancing our understanding of these shifts in hydrological extremes.

The Canadian Regional Climate Model version 5 Large Ensemble (CRCM5-LE; Leduc et al. (2019)) under RCP 8.5 builds the climatic boundary conditions for the hydrological modelling. The ensemble covers a European and a North American domain, each comprising 50 members from 1951 to 2100. The SDCLIREF v2 (Lehr- und Forschungseinheit für physische Geographie und komplexe Umweltsysteme 2024),  a sub-daily (3h), high-resolution (500m) data set for the domain of Bavaria and hydrologically important neighbouring catchments marks the reference data set. 

In ClimEx-II, bias correction is a crucial step before downscaling (regional) climate model simulations to higher resolutions as it adjusts local inconsistencies in the climate model. The corrected and downscaled meteorological inputs can be used to drive a hydrological model (Emami and Koch 2018,  Fang et al. 2015). The quality of the corrected data depends on the method used. Therefore, this data set comprises a comparison of the input and output data from three different bias correction methods, UBC (Cannon et al., 2015), MBCn (Cannon 2018) and VBC (Funk et al., 2024) for three diverse climate regions in Bavaria:

Fränkische Saale Salz is a franconian catchment

Iller Kempten is a pre-alpine catchment

Hart an der Ziller is an alpine catchment

Each catchment comprises six to seven grid cells of a 12 km resolution. Five climate variables of hydrological importance are corrected in a 3-hourly temporal resolution per grid cell:

Near-Surface Dewpoint Temperature in °C (dew)

Precipitation in kg/m2 (pr)

Surface Downwelling Shortwave Radiation in W/m2 (rsds)

Near-Surface Wind Speed in m/s (sfcWind)

Near-Surface Air Temperature in °C (tas)

The environment in each file comprises the inputs to the bias correction

mp_dts: CRCM5-LE model data during the projection period (2011-2030) before correction

mc_dts: CRCM5-LE model data during calibration period (1991-2010)

oc_dts: SDCLIREF v2 reference data during calibration period (1991-2010)

,the outputs from the bias correction comparison during the projection period

vbc: CRCM5-LE model data during the projection period (2011-2030) after correction by VBC

mbcn: CRCM5-LE model data during the projection period (2011-2030) after correction by MBCn

ubc: CRCM5-LE model data during the projection period (2011-2030) after correction by UBC

and the held-out reference data for validation

op_dts: SDCLIREF v2 reference data during the projection period (2011-2030).

Each of the above-presented data sets consists of six columns. The five climate variables are indexed by their abbreviations. The sixth column time contains a string marking the respective timestamp. All CRCM5-LE model data contain a seventh column indicating the respective ensemble member. The evaluation results by Wasserstein Distance and Model Correction Inconsistency from Funk et al. (2024) are captured in the three additional files starting with 06_*.