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

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 ...

Full description

Bibliographic Details
Main Authors: K. Förster, F. Hanzer, E. Stoll, A. A. Scaife, C. MacLachlan, J. Schöber, M. Huttenlau, S. Achleitner, U. Strasser
Format: Article
Language:English
Published: Copernicus Publications 2018-02-01
Series:Hydrology and Earth System Sciences
Online Access:https://www.hydrol-earth-syst-sci.net/22/1157/2018/hess-22-1157-2018.pdf
id doaj-def15a5e3e824e9ea1d9dd5d05e19712
record_format Article
spelling doaj-def15a5e3e824e9ea1d9dd5d05e197122020-11-24T21:20:10ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382018-02-01221157117310.5194/hess-22-1157-2018Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)K. Förster0K. Förster1K. Förster2F. Hanzer3F. Hanzer4E. Stoll5A. A. Scaife6A. A. Scaife7C. MacLachlan8J. Schöber9M. Huttenlau10S. Achleitner11U. Strasser12Leibniz Universität Hannover, Institute of Hydrology and Water Resources Management, Hanover, GermanyalpS – Centre for Climate Change Adaptation, Innsbruck, AustriaInstitute of Geography, University of Innsbruck, Innsbruck, AustriaInstitute of Geography, University of Innsbruck, Innsbruck, AustriaWegener Center for Climate and Global Change, University of Graz, Graz, AustriaalpS – Centre for Climate Change Adaptation, Innsbruck, AustriaMet Office Hadley Centre, Exeter, Devon, UKCollege of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UKMet Office Hadley Centre, Exeter, Devon, UKTIWAG, Tiroler Wasserkraft AG, Innsbruck, AustriaalpS – Centre for Climate Change Adaptation, Innsbruck, AustriaUnit of Hydraulic Engineering, Institute of Infrastructure, University of Innsbruck, Innsbruck, AustriaInstitute of Geography, University of Innsbruck, Innsbruck, AustriaThis article presents analyses of retrospective seasonal forecasts of snow accumulation. Re-forecasts with 4 months' lead time from two coupled atmosphere&ndash;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 <i>r</i>  =  0.57. 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 <i>r</i>  =  0.28 and 7 of 13 years. The results suggest that some seasonal prediction of hydrological model storage tendencies in parts of Europe is possible.https://www.hydrol-earth-syst-sci.net/22/1157/2018/hess-22-1157-2018.pdf
collection DOAJ
language English
format Article
sources DOAJ
author K. Förster
K. Förster
K. Förster
F. Hanzer
F. Hanzer
E. Stoll
A. A. Scaife
A. A. Scaife
C. MacLachlan
J. Schöber
M. Huttenlau
S. Achleitner
U. Strasser
spellingShingle K. Förster
K. Förster
K. Förster
F. Hanzer
F. Hanzer
E. Stoll
A. A. Scaife
A. A. Scaife
C. MacLachlan
J. Schöber
M. Huttenlau
S. Achleitner
U. Strasser
Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)
Hydrology and Earth System Sciences
author_facet K. Förster
K. Förster
K. Förster
F. Hanzer
F. Hanzer
E. Stoll
A. A. Scaife
A. A. Scaife
C. MacLachlan
J. Schöber
M. Huttenlau
S. Achleitner
U. Strasser
author_sort K. Förster
title Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)
title_short Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)
title_full Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)
title_fullStr Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)
title_full_unstemmed Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)
title_sort retrospective forecasts of the upcoming winter season snow accumulation in the inn headwaters (european alps)
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2018-02-01
description This article presents analyses of retrospective seasonal forecasts of snow accumulation. Re-forecasts with 4 months' lead time from two coupled atmosphere&ndash;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 <i>r</i>  =  0.57. 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 <i>r</i>  =  0.28 and 7 of 13 years. The results suggest that some seasonal prediction of hydrological model storage tendencies in parts of Europe is possible.
url https://www.hydrol-earth-syst-sci.net/22/1157/2018/hess-22-1157-2018.pdf
work_keys_str_mv AT kforster retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT kforster retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT kforster retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT fhanzer retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT fhanzer retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT estoll retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT aascaife retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT aascaife retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT cmaclachlan retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT jschober retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT mhuttenlau retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT sachleitner retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
AT ustrasser retrospectiveforecastsoftheupcomingwinterseasonsnowaccumulationintheinnheadwaterseuropeanalps
_version_ 1726003674208010240