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  • 1
    UID:
    edoccha_BV046633932
    Format: 1 Online-Ressource : , Illustrationen.
    Edition: Living reference work, continuously updated edition
    ISBN: 978-3-642-40457-3
    Language: English
    Subjects: Physics
    RVK:
    RVK:
    Keywords: Numerische Wettervorhersage ; Hydrometeorologie
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    almahu_BV045448487
    Format: 1 Online-Ressource (xxxvi, 1528 Seiten) : , Illustrationen, Diagramme, Karten (überwiegend farbig).
    ISBN: 978-3-642-39925-1
    Series Statement: Springer reference
    Note: Online-Ressource einer mehrteiligen Monografie, die Print-Ausgabe ist in 2 Bänden erschienen
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-642-39924-4
    Language: English
    Subjects: Physics
    RVK:
    Keywords: Numerische Wettervorhersage ; Hydrometeorologie
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 3
    UID:
    almahu_9948126390902882
    Format: 1200 p. 200 illus., 100 illus. in color. , online resource.
    ISBN: 9783642404573
    Content: Hydrometeorological prediction involves the forecasting of the state and variation of hydrometeorological elements -- including precipitation, temperature, humidity, soil moisture, river discharge, groundwater, etc.-- at different space and time scales. Such forecasts form an important scientific basis for informing public of natural hazards such as cyclones, heat waves, frosts, droughts and floods. Traditionally, and at most currently operational centers, hydrometeorological forecasts are deterministic, “single-valued” outlooks: i.e., the weather and hydrological models provide a single best guess of the magnitude and timing of the impending events. These forecasts suffer the obvious drawback of lacking uncertainty information that would help decision-makers assess the risks of forecast use. Recently, hydrometeorological ensemble forecast approaches have begun to be developed and used by operational collection of hydrometeorological services. In contrast to deterministic forecasts, ensemble forecasts are a multiple forecasts of the same events. The ensemble forecasts are generated by perturbing uncertain factors such as model forcings, initial conditions, and/or model physics. Ensemble techniques are attractive because they not only offer an estimate of the most probable future state of the hydrometeorological system, but also quantify the predictive uncertainty of a catastrophic hydrometeorological event occurring. The Hydrological Ensemble Prediction Experiment (HEPEX), initiated in 2004, has signaled a new era of collaboration toward the development of hydrometeorological ensemble forecasts. By bringing meteorologists, hydrologists and hydrometeorological forecast users together, HEPEX aims to improve operational hydrometeorological forecast approaches to a standard that can be used with confidence by emergencies and water resources managers. HEPEX advocates a hydrometeorological ensemble prediction system (HEPS) framework that consists of several basic building blocks. These components include:(a) an approach (typically statistical) for addressing uncertainty in meteorological inputs and generating statistically consistent space/time meteorological inputs for hydrological applications; (b) a land data assimilation approach for leveraging observation to reduce uncertainties in the initial and boundary conditions of the hydrological system; (c) approaches that address uncertainty in model parameters (also called ‘calibration’); (d) a hydrologic model or other approach for converting meteorological inputs into hydrological outputs; and finally (e) approaches for characterizing hydrological model output uncertainty. Also integral to HEPS is a verification system that can be used to evaluate the performance of all of its components. HEPS frameworks are being increasingly adopted by operational hydrometeorological agencies around the world to support risk management related to flash flooding, river and coastal flooding, drought, and water management. Real benefits of ensemble forecasts have been demonstrated in water emergence management decision making, optimization of reservoir operation, and other applications.
    Note: Introduction -- Generation and calibration of meteorological ensemble forecast -- Hydrometeorological observations and data assimilation techniques -- Model parametric uncertainty analysis techniques -- Hydrological models for converting meteorological inputs into hydrological outputs -- Post-processing of hydrological model outputs and generation of ensemble hydrological forecast products -- Verification systems -- Communication and Decision making -- Application showcases -- Mathematical basics and statistical methods. Please find the attachment for more details.
    In: Springer Nature Living Reference
    Language: English
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  • 4
    UID:
    almafu_BV046633932
    Format: 1 Online-Ressource : , Illustrationen.
    Edition: Living reference work, continuously updated edition
    ISBN: 978-3-642-40457-3
    Language: English
    Subjects: Physics
    RVK:
    RVK:
    Keywords: Numerische Wettervorhersage ; Hydrometeorologie
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    UID:
    edocfu_BV046633932
    Format: 1 Online-Ressource : , Illustrationen.
    Edition: Living reference work, continuously updated edition
    ISBN: 978-3-642-40457-3
    Language: English
    Subjects: Physics
    RVK:
    RVK:
    Keywords: Numerische Wettervorhersage ; Hydrometeorologie
    Library Location Call Number Volume/Issue/Year Availability
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  • 6
    UID:
    kobvindex_ZLB34355248
    In: Aus Politik und Zeitgeschichte : APuZ, Bonn, [25. November 1953]-, 69 (2019), Heft 52 : Wetter, Seiten 16 - 21
    Language: German
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  • 7
    UID:
    edoccha_9959027261302883
    Format: 1 online resource (439 illus., 345 illus. in color. eReference.)
    Edition: 1st ed. 2019.
    ISBN: 3-642-39925-8
    Series Statement: Springer Reference
    Content: Hydrometeorological prediction involves the forecasting of the state and variation of hydrometeorological elements -- including precipitation, temperature, humidity, soil moisture, river discharge, groundwater, etc. at different space and time scales. Such forecasts form an important scientific basis for informing public of natural hazards such as cyclones, heat waves, frosts, droughts and floods. Traditionally, and at most operational centers, hydrometeorological forecasts are deterministic, “single-valued” outlooks: i.e., the weather and hydrological models provide a single best guess of the magnitude and timing of the impending events. These forecasts suffer the obvious drawback of lacking uncertainty information that would help decision-makers make risk-based decisions. Recently, hydrometeorological ensemble forecast approaches have begun to be developed and used by operational hydrometeorological services. In contrast to deterministic forecasts, ensemble forecasts are multiple forecasts of the same events. The ensemble forecasts are generated by perturbing uncertain factors such as model forcings, initial conditions, and/or model physics. Ensemble techniques are attractive because they not only offer an estimate of the most probable future state of the hydrometeorological system, but also quantify the predictive uncertainty of a catastrophic hydrometeorological event occurring. “Handbook of Hydrometeorological Ensemble Forecasting” is mainly contributed by the group of experts from HEPEX as a central reference work from this field. The Hydrological Ensemble Prediction Experiment (HEPEX), initiated in 2004, has signaled a new era of collaboration toward the development of hydrometeorological ensemble forecasts. By bringing meteorologists, hydrologists and hydrometeorological forecast users together, HEPEX aims to improve operational hydrometeorological forecasts that can be used with confidence by emergencies and water resources managers. HEPEX advocates a hydrometeorological ensemble prediction system (HEPS) framework that consists of several basic building blocks. These components include:(a) an approach (typically statistical) for addressing uncertainty in meteorological inputs and generating statistically consistent space/time meteorological inputs for hydrological applications; (b) a land data assimilation approach for leveraging observation to reduce uncertainties in the initial and boundary conditions of the hydrological system; (c) approaches that address uncertainty in model parameters (also called ‘calibration’); (d) a hydrologic model or other approach for converting meteorological inputs into hydrological outputs; and finally (e) approaches for characterizing hydrological model output uncertainty. Also integral to HEPS is a verification system that can be used to evaluate the performance of all of its components. HEPS frameworks are being increasingly adopted by operational hydrometeorological agencies around the world to support risk management related to flash flooding, river and coastal flooding, drought, and water management. Real benefits of ensemble forecasts have been demonstrated in water emergence management decision making, optimization of reservoir operation, and other applications. This book not only covers the theoretical and methodological aspects involved in hydrometeorological ensemble forecasting, but also presents a large number of successful application showcases. It should serves as an excellent reference book for researchers and practitioners in hydrometeorological forecasting.
    Note: Introduction -- Overview of Meteorological Ensemble Forecasting -- Post-processing of Meteorological Ensemble Forecasting for Hydrological Applications -- Hydrological Models -- Model Parameter Estimation and Uncertainty Analysis -- Observation and data assimilation -- Post-processing of Hydrological Ensemble Forecasts -- Verification of Hydrometeorological Ensemble Forecasts -- Communication and Use of Ensemble Forecasts for Decision Making -- Ensemble Forecast Application Showcases -- Mathematical and Statistical Fundamentals for Hydrometeorological Ensemble Forecasting.
    Additional Edition: ISBN 3-642-39926-6
    Additional Edition: ISBN 3-642-39924-X
    Language: English
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  • 8
    UID:
    b3kat_BV046633932
    Format: 1 Online-Ressource , Illustrationen
    Edition: Living reference work, continuously updated edition
    ISBN: 9783642404573
    Language: English
    Subjects: Physics
    RVK:
    RVK:
    Keywords: Numerische Wettervorhersage ; Hydrometeorologie
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  • 9
    UID:
    b3kat_BV046330019
    ISSN: 0479-611X
    In: volume:69
    In: number:52
    In: year:2019
    In: pages:16-21
    In: Aus Politik und Zeitgeschichte / hrsg. von der Bundeszentrale für Politische Bildung, Bonn, 2019, 69, 52 (2019), 16-21, 0479-611X
    Language: German
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  • 10
    UID:
    gbv_1746654422
    Format: 5 Illustrationen, 2 Tabellen
    ISSN: 1743-2774
    Note: Published online: 20 Feb 2019 Keywords: Cartogram ; data visualization ; weather forecasts ; early warning ; natural hazards , Engl.
    In: The cartographic journal, London : Taylor and Francis, 1964, 56(2019), 2, Seite 134-145, 1743-2774
    In: volume:56
    In: year:2019
    In: number:2
    In: pages:134-145
    Language: English
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