Abstract

Abstract. The timing and the volume of snow and ice melt in Alpine catchments are crucial for management operations of reservoirs and hydropower generation. Moreover, a sustainable reservoir operation through reservoir storage and flow control as part of flood risk management is important for downstream communities. Forecast systems typically provide predictions for a few days in advance. Reservoir operators would benefit if lead times could be extended in order to optimise the reservoir management. Current seasonal prediction products such as the NCEP (National Centers for Environmental Prediction) Climate Forecast System version 2 (CFSv2) enable seasonal forecasts up to nine months in advance, with of course decreasing accuracy as lead-time increases. We present a coupled seasonal prediction modelling system that runs at monthly time steps for a small catchment in the Austrian Alps (Gepatschalm). Meteorological forecasts are obtained from the CFSv2 model. Subsequently, these data are downscaled to the Alpine Water balance And Runoff Estimation model AWARE running at monthly time step. Initial conditions are obtained using the physically based, hydro-climatological snow model AMUNDSEN that predicts hourly fields of snow water equivalent and snowmelt at a regular grid with 50 m spacing. Reservoir inflow is calculated taking into account various runs of the CFSv2 model. These simulations are compared with observed inflow volumes for the melting and accumulation period 2015.

Highlights

  • Hydropower is a major contributor to carbon-free energy production in the European Alps where ideal conditions for this type of energy production prevail (Schaefli, 2015)

  • Test operation of the water balance model for seasonal prediction using Climate Forecast System version 2 (CFSv2) data has been started in early summer 2015

  • The results obtained by the water balance model, which is forced using CFSv2 data, are promising with respect to future applications of seasonal forecasts in the study area

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Summary

Introduction

Hydropower is a major contributor to carbon-free energy production in the European Alps where ideal conditions for this type of energy production prevail (Schaefli, 2015). Two types of seasonal prediction strategies are available for hydrologic applications (Yuan et al, 2015): On one hand, common methods in hydrology are based on the Ensemble Seasonal Prediction, building upon procedures which resample historical meteorological data. Climate models based on (dynamical) seasonal methodology rely on physical modelling of the coupled atmosphere-ocean system This is important as atmosphere-ocean systems interact at a broad range of scales, influenced by sea surface temperature anomalies as well as associated surface air pressure fields such as El Niño Southern Oscillation (ENSO) or the North Atlantic Oscillation (NAO), and their atmospheric teleconnections strongly affect weather patterns at smaller scales (Doblas-Reyes et al, 2013). First results of the melting season 2015 and the following accumulation season are presented

Study area
The CFSv2 model and linear regression downscaling
The water balance model AWARE and its application
Results and discussion
Conclusions and outlook
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