Snow-hydrological validation of undercatch corrected precipitation across alpine regions in Austria

Stationary precipitation measurements are frequently affected by undercatch errors, which are particularly pronounced in cold and alpine regions with strong winds. Since gridded precipitation products used in land surface modelling are often derived from spatial interpolation of meteorological station data, these measurement errors propagate directly into gridded datasets. Hydrological models provide a powerful tool for validating precipitation products through their integration of multiple water balance components. In this study, we develop a monthly undercatch correction product for Austria using Generalized Additive Models (GAMs) trained on station observations with geographical exposure and terrain elevation as predictors (R² > 0.76 in cross-validation), and apply these corrections to existing gridded precipitation datasets.

We validate the undercatch correction using the conceptual rainfall-runoff model COSERO across Austria and in two high-alpine reservoir catchments (Kölnbrein and Schlegeis). Austrian-wide simulations demonstrate elevation-dependent improvements, with reduced runoff biases particularly in catchments above 1500-2000 m elevation. In the alpine case study regions, the corrected precipitation closes the long-term water balance where uncorrected data showed deficits exceeding 20 %. The physically-based snowpack model Alpine3D, validated against stereo-satellite observations, shows substantial improvements in snow depth simulations with median biases decreasing from -0.87 m to +0.15 m. Additionally, the correction improves representation of snow melt-out behaviour during the ablation season and enables more realistic simulation of long-term glacier volume changes. These results highlight the importance of accounting for undercatch errors in high-alpine terrain and demonstrate the value of comprehensive hydrological validation for precipitation products.

Acknowledgements: We thank the Austrian Climate Research Programme (ACRP), and the Verbund Energy4Business GmbH for funding, fruitful discussions and providing us with data.