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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/hess-2017-370
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
03 Jul 2017
Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Hydrology and Earth System Sciences (HESS).
Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)
Kristian Förster1, Florian Hanzer1, Elena Stoll2, Adam A. Scaife3,4, Craig MacLachlan3, Johannes Schöber5, Matthias Huttenlau2, Stefan Achleitner6, and Ulrich Strasser1 1Institute of Geography, University of Innsbruck, Innsbruck, Austria
2alpS – Centre for Climate Change Adaptation, Innsbruck, Austria
3Met Office Hadley Centre, Exeter, Devon, United Kingdom
4College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
5TIWAG, Tiroler Wasserkraft AG, Innsbruck, Austria
6Unit of Hydraulic Engineering, Institute of Infrastructure, University of Innsbruck, Innsbruck, Austria
Abstract. This article presents analyses of retrospective seasonal forecasts of snow accumulation. Re-forecasts with 4 months lead time from two coupled atmosphere–ocean general circulation models (NCEP CFSv2 and MetOffice GloSea5) drive the Alpine Water balance and Runoff Estimation model (AWARE) in order to predict mid-winter snow accumulation in the Inn headwaters. As the snowpack is a hydrological storage that evolves during the winter season, it is strongly dependent on precipitation totals of the previous months. Climate model (CM) predictions of precipitation totals integrated from November to February (NDJF) compare reasonably well with observations. This predictive skill is retained in subsequent water balance simulations when snow water equivalent (SWE) in February is considered. Given the AWARE simulations driven by observed meteorological fields as a benchmark for SWE analyses, the correlation achieved using GloSea5-AWARE SWE predictions is r = 0.57. The tendency of SWE anomalies (i.e. the sign of anomalies) is correctly predicted in 11 of 13 years. For CFSv2, the corresponding values are r = 0.28 and 7 of 13 years. The results suggest that some seasonal predictions may be capable of predicting tendencies of hydrological model storages in parts of Europe.

Citation: Förster, K., Hanzer, F., Stoll, E., Scaife, A. A., MacLachlan, C., Schöber, J., Huttenlau, M., Achleitner, S., and Strasser, U.: Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps), Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-370, in review, 2017.
Kristian Förster et al.
Kristian Förster et al.
Kristian Förster et al.

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Short summary
This article presents predictability analyses of snow accumulation for the upcoming winter season. The results achieved using two coupled atmosphere–ocean general circulation models and a water balance model show that the tendency of snow water equivalent anomalies (i.e. the sign of anomalies) is correctly predicted in up to 11 of 13 years. The results suggest that some seasonal predictions may be capable of predicting tendencies of hydrological model storages in parts of Europe.
This article presents predictability analyses of snow accumulation for the upcoming winter...
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