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

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dc.identifier.uri http://dx.doi.org/10.15488/3380
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/3410
dc.contributor.author Förster, Kristian
dc.contributor.author Hanzer, Florian
dc.contributor.author Stoll, Elena
dc.contributor.author Scaife, Adam A.
dc.contributor.author MacLachlan, Craig
dc.contributor.author Schöber, Johannes
dc.contributor.author Huttenlau, Matthias
dc.contributor.author Achleitner, Stefan
dc.contributor.author Strasser, Ulrich
dc.date.accessioned 2018-05-23T08:43:23Z
dc.date.available 2018-05-23T08:43:23Z
dc.date.issued 2018
dc.identifier.citation Förster, K.; Hanzer, F.; Stoll, E.; Scaife, A.A.; MacLachlan, C. et al.: Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps). In: Hydrology and Earth System Sciences 22 (2018), Nr. 2, S. 1157-1173. DOI: https://doi.org/10.5194/hess-22-1157-2018
dc.description.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 snowpack 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 to February (NDJF) compare reasonably well with observations. Even though predictions for precipitation may not be significantly more skilful than for temperature, the predictive skill achieved for precipitation 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 D0.57. The tendency of SWE anomalies (i.e. the sign of anomalies) is correctly predicted in 11 of 13 years. For CFSv2-AWARE, the corresponding values are r D0.28 and 7 of 13 years. The results suggest that some seasonal prediction of hydrological model storage tendencies in parts of Europe is possible. eng
dc.language.iso eng
dc.publisher Göttingen : Copernicus GmbH
dc.relation.ispartofseries Hydrology and Earth System Sciences 22 (2018), Nr. 2
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject Forecasting eng
dc.subject Snow eng
dc.subject Coupled atmosphere ocean general circulation model eng
dc.subject Hydrological modeling eng
dc.subject Meteorological fields eng
dc.subject Seasonal forecasts eng
dc.subject Seasonal prediction eng
dc.subject Snow water equivalent eng
dc.subject Water balance simulation eng
dc.subject Winter snow accumulation eng
dc.subject Climate models eng
dc.subject.ddc 550 | Geowissenschaften ger
dc.subject.ddc 551 | Geologie, Hydrologie, Meteorologie ger
dc.title Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps) eng
dc.type Article
dc.type Text
dc.relation.issn 1027-5606
dc.relation.doi https://doi.org/10.5194/hess-22-1157-2018
dc.bibliographicCitation.issue 2
dc.bibliographicCitation.volume 22
dc.bibliographicCitation.firstPage 1157
dc.bibliographicCitation.lastPage 1173
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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