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. This article presents analyses of retrospective seasonal forecasts of snowaccumulation. Re-forecasts with 4 months' lead time from two coupledatmosphere–ocean general circulation models (NCEP CFSv2 and MetOfficeGloSea5) drive the Alpine Water balance and Runoff Estimation model (AWARE)in order to predict mid-winter snow accumulation in the Inn headwaters. Assnowpack is 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 toFebruary (NDJF) compare reasonably well with observations. Even thoughpredictions for precipitation may not be significantly more skilful than fortemperature, the predictive skill achieved for precipitation is retained insubsequent water balance simulations when snow water equivalent (SWE) inFebruary is considered. Given the AWARE simulations driven by observedmeteorological fields as a benchmark for SWE analyses, the correlationachieved using GloSea5-AWARE SWE predictions is r =  0.57. The tendency of SWEanomalies (i.e. the sign of anomalies) is correctly predicted in 11 of13 years. For CFSv2-AWARE, the corresponding values are r =  0.28 and 7 of13 years. The results suggest that some seasonal prediction of hydrological model storage tendencies in parts of Europe is possible.

Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)