On the improvement of runoff and glacier mass balance modelling by performing an undercatch correction on gridded precipitation data sets based on independent station data

Abstract

Models like the conceptual hydrological model COSERO and the physically-based mountain surface process model Alpine3D are highly sensitive to meteorological inputs, especially precipitation. Gridded precipitation data sets usually originate from spatially interpolated weather station data, which are not corrected for precipitation undercatch. The term precipitation undercatch describes the deviation of measured precipitation in rain gauges to the actual amount in a given area due to several factors like instrument design or effects of splash, evaporation and especially wind. Specifically solid precipitation is prone to wind drag. Because of these effects, models or model chains fail to simulate observations for discharge, reservoir inflow, snow and ice melt as well as glacier mass balance due to the lack of realistic precipitation input into the system in high-alpine regions. However, correcting the undercatch directly within the gridded data set leads to an overestimation of precipitation, which has two main reasons: First, undercatch correction functions are not derived for alpine temperatures and wind speeds. Second, stations at lower elevations, where the undercatch is comparatively small, are usually over-represented in gridded data sets. Therefore, we composed a method to perform a precipitation undercatch correction in high-alpine areas by using a gridded precipitation data set and quality-controlled, representative station data in the vicinity of snow-dominated and glacierized catchments as well as their altitude and exposure to generate spatial undercatch correction fields for three selected catchments in Austria (Maltatal, Zillertal and Vernagtferner) on a monthly basis. These correction factors are a function of elevation and the month and result from a stepwise linear interpolation with elevation, whereas the highest factors are obtained in the winter months due to low temperatures. Using the topography and averaging over whole catchments, the highest (lowest) correction factors are obtained in February (August), ranging from 2.16 to 1.04, depending on the catchment and season. The meteorological data (with and without the undercatch corrected precipitation) was used as an input for a coupled snow-glacier-discharge simulation with the models COSERO and Alpine3D on the selected catchments. The output was validated against reservoir inflow, observed glacier mass balances and satellite derived snow depth maps. With the undercatch corrected precipitation, the models perform substantially better in simulating observations for glacier mass balance as well as reservoir inflow. Acknowledgements: We thank VERBUND AG for fruitful discussions and providing us with data.