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  • 1
    Call number: ZSP-625-45
    In: PIK report
    Type of Medium: Monograph available for loan
    Pages: 15 S. : Ill., graph. Darst.
    Series Statement: PIK report 45
    Branch Library: GFZ Library
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  • 2
    Monograph available for loan
    Monograph available for loan
    Hamburg : Max-Planck-Institut für Meteorologie
    Associated volumes
    Call number: ZSP-686-86
    In: Report
    Type of Medium: Monograph available for loan
    Pages: 30 S. : graph. Darst. : 29,5 cm
    ISSN: 0937-1060
    Series Statement: Report / Max-Planck-Institut für Meteorologie 86
    Branch Library: GFZ Library
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  • 3
    Call number: ZS-190(57) ; ZSP-625-57
    In: PIK report
    Type of Medium: Series available for loan
    Pages: 25 S.
    Series Statement: PIK report 57
    Classification: D.5.
    Language: English
    Location: Lower compact magazine
    Location: Lower compact magazine
    Branch Library: GFZ Library
    Branch Library: GFZ Library
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  • 4
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    In:  Journal of Hydrology ; Year: 2012 ; Volume: 414-415 ; Issue: 11 ; Pages: 341-353
    Publication Date: 2014-12-12
    Description: We generated medium-range forecasts of runoff for a 50 km2 headwater catchment upstream of a reservoir using numerical weather predictions (NWPs) of the past as input to an operational hydrological model. NWP data originating from different sources were tested. For a period of 8.5 years, we computed daily forecasts with a lead time of +120 h based on an empirically downscaled version of the ECMWF’s ensemble prediction system. For the last 3.5 years of the test period, we also tried the deterministic COSMO-EU forecast disseminated by the German Weather Service for lead times of up to +72 h. Common measures of skill indicate superiority of the ensemble runoff forecast over single-value forecasts for longer lead times. However, regardless of which NWP data were being used, the probability of event detection (POD) was found to be generally lower than 50%. In many cases, values in the range of 20–30% were obtained. At the same time, the false alarms ratio (FAR) was often found to be considerably high. The observed uncertainties in the hydrological forecasts were shown to originate from both the insufficient quality of precipitation forecasts as well as deficiencies in hydrological modeling and quantitative precipitation estimation. With respect to the anticipatory control of reservoirs in the studied catchment, the value of the tested runoff forecasts appears to be limited. This is due to the unfavorably low POD/FAR ratio in conjunction with a high cost–loss ratio. However, our results indicate that, in many cases, major runoff events related to snow melt can be successfully predicted as early as 4–5 days in advance.
    Keywords: ddc:550
    Language: English
    Type: http://purl.org/escidoc/metadata/ves/publication-types/article
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  • 5
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    In:  Hydrology and Earth System Sciences ; Year: 2009 ; Volume: 13 ; Issue: 9 ; Pages: 1649-1658
    Publication Date: 2014-12-12
    Description: For three small, mountainous catchments in Germany two medium-range forecast systems are compared that predict precipitation for up to 5 days in advance. One system is composed of the global German weather service (DWD) model, GME, which is dynamically downscaled using the COSMO-EU regional model. The other system is an empirical (expanded) downscaling of the ECMWF model IFS. Forecasts are verified against multi-year daily observations, by applying standard skill scores to events of specified intensity. All event classes are skillfully predicted by the empirical system for up to five days lead time. For the available prediction range of one to two days it is superior to the dynamical system.
    Keywords: ddc:550
    Type: http://purl.org/escidoc/metadata/ves/publication-types/article
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  • 6
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    In:  Water Resources Research ; Year: 2009 ; Volume: 45 ; Issue: 10 ; Pages: 1-15
    Publication Date: 2014-12-12
    Description: A prototype early warning system for floods is introduced. For a small headwater catchment, probabilistic streamflow predictions in 24-hourly steps are obtained from downscaling all members of the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System and feeding the resulting precipitation and temperature series into a hydrologic model. We apply “expanded downscaling,” a scheme that was previously used for climate scenarios and that is particularly suited to extreme events and the simulation of flood-triggering heavy rainfall. The entire model chain is thoroughly verified, using daily precipitation and streamflow observations and forecasts from the decade 1997–2006. It turns out that strong meteorologic (precipitation) events are skillfully predicted for at least 5 days lead time by the downscaling. That skill, however, is partly lost by deficiencies in the hydrological modeling as revealed in this study. We discuss ways to overcome these difficulties, along with the prospect of employing the whole system operationally, for example, for reservoir regulations. We close with an outlook for early flash flood warnings.
    Keywords: ddc:550
    Type: http://purl.org/escidoc/metadata/ves/publication-types/article
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  • 7
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    In:  Geophysical Research Abstracts, Vol. 18, EGU2016-7976-1, 2016 ; Year: 2016
    Publication Date: 2016-06-01
    Type: http://purl.org/eprint/type/ConferencePaper
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  • 8
    Publication Date: 2018-08-09
    Type: http://purl.org/escidoc/metadata/ves/publication-types/article
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  • 9
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    In:  Water Resources Research ; Year: 2009 ; Volume: 45 ; Issue: 10 ; Pages: 1-15
    Publication Date: 2014-12-12
    Description: A prototype early warning system for floods is introduced. For a small headwater catchment, probabilistic streamflow predictions in 24-hourly steps are obtained from downscaling all members of the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System and feeding the resulting precipitation and temperature series into a hydrologic model. We apply “expanded downscaling,” a scheme that was previously used for climate scenarios and that is particularly suited to extreme events and the simulation of flood-triggering heavy rainfall. The entire model chain is thoroughly verified, using daily precipitation and streamflow observations and forecasts from the decade 1997–2006. It turns out that strong meteorologic (precipitation) events are skillfully predicted for at least 5 days lead time by the downscaling. That skill, however, is partly lost by deficiencies in the hydrological modeling as revealed in this study. We discuss ways to overcome these difficulties, along with the prospect of employing the whole system operationally, for example, for reservoir regulations. We close with an outlook for early flash flood warnings.
    Type: http://purl.org/escidoc/metadata/ves/publication-types/article
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  • 10
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    In:  Hydrology and Earth System Sciences ; Year: 2009 ; Volume: 13 ; Issue: 9 ; Pages: 1649-1658
    Publication Date: 2014-12-12
    Description: For three small, mountainous catchments in Germany two medium-range forecast systems are compared that predict precipitation for up to 5 days in advance. One system is composed of the global German weather service (DWD) model, GME, which is dynamically downscaled using the COSMO-EU regional model. The other system is an empirical (expanded) downscaling of the ECMWF model IFS. Forecasts are verified against multi-year daily observations, by applying standard skill scores to events of specified intensity. All event classes are skillfully predicted by the empirical system for up to five days lead time. For the available prediction range of one to two days it is superior to the dynamical system.
    Type: http://purl.org/escidoc/metadata/ves/publication-types/article
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