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  • 1
    Online Resource
    Online Resource
    Cham :Springer International Publishing AG,
    Keywords: Water vapor, Atmospheric. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (284 pages)
    Edition: 1st ed.
    ISBN: 9783030289065
    DDC: 551.517
    Language: English
    Note: Intro -- Foreword -- Preface -- Acknowledgements -- Contents -- List of Figures -- List of Tables -- Contributors -- 1: Introduction to Atmospheric Rivers -- 1.1 A Brief History of AR Science -- 1.1.1 The 1970s -- 1.1.2 The 1980s -- 1.1.3 The 1990s -- 1.1.4 The 2000s -- AR Impacts: Precipitation, Flooding, and Water Supply -- 1.1.5 2010 and Beyond -- The California AR Observation Network -- The Forecasting Challenge -- AR Duration Found to Help Modulate AR Impacts -- 1.1.6 ARs and Global Climate Change -- 1.2 Structure of This Book -- References -- 2: Structure, Process, and Mechanism -- 2.1 Introduction -- 2.2 Structure of ARs -- 2.2.1 Definition of the Term "Atmospheric River" -- 2.2.2 Water Vapor Transport and the Vertical and Horizontal Structure of ARs -- Direct Observations of Water Vapor Transport -- Observations of Vertical and Horizontal Structure -- Representativeness of Airborne Observations and Typical Range of Key Characteristics -- 2.3 WCBs and TMEs and Their Relationship to ARs -- 2.3.1 Concepts of TMEs, ARs, and WCBs -- 2.3.2 Climatologies -- 2.3.3 Linkages Among the Three Feature Categories -- 2.3.4 Summary -- 2.4 Water Vapor Transport in ARs -- 2.4.1 Moisture Budget During the AR Life Cycle -- 2.4.2 Horizontal and Vertical Moisture Transport and AR Maintenance -- 2.4.3 Methods for Obtaining an AR Water Budget -- 2.4.4 Conclusions, Implications, and Future Directions -- 2.5 ARs and Extratropical Dynamics -- 2.5.1 Mid-Latitude Storm Track and Cyclogenesis -- 2.5.2 Mid-Latitude Cyclones and ARs -- 2.5.3 Linking Extratropical Dynamics to Hydrometeorological Effects -- 2.5.4 Summary -- 2.6 A Case Study Example -- References -- 3: Observing and Detecting Atmospheric Rivers -- 3.1 Introduction -- 3.2 Satellite Observations of ARs -- 3.2.1 Microwave Radiometry: SSM/I -- 3.2.2 Radio Occultation: COSMIC. , 3.2.3 Satellite-Based Cloud and Precipitation Radars: CloudSat and GPM -- 3.3 AR Observatories -- 3.3.1 AR Characteristics Not Readily Observed Using Traditional Meteorological Methods -- The Low-Level Jet and the "Controlling Layer" -- Temporal and Horizontal Spatial Scales of ARs Relative to the Operational Radiosonde Network -- Summary of the Gaps -- 3.3.2 ARO Instrumentation -- Doppler Wind Profilers -- Surface Meteorology Towers -- Global Positioning System/Meterology (GPS/ MET) -- 3.3.3 The ARO Water Vapor Flux Tool -- 3.3.4 The US West Coast ARO "Picket Fence" -- 3.4 Network Observations: Monitoring ARs over California -- 3.4.1 AR Observatories (AROs) -- 3.4.2 Snow-Level Radar -- 3.4.3 Integrated Water Vapor (GPS/MET) -- 3.4.4 Soil Moisture -- 3.5 Field Campaigns and Experiments -- 3.5.1 CALJET -- 3.5.2 PACJET -- 3.5.3 HMT -- 3.5.4 Ghost Nets -- 3.5.5 CalWater-1 -- 3.5.6 WISPAR -- 3.5.7 CalWater-2 -- 3.5.8 ENRR and SHOUT -- 3.5.9 NAWDEX -- 3.5.10 AR Reconnaissance -- 3.5.11 Synthesis of Airborne Cross-Sections Across ARs into a Composite of AR Structure and TIVT -- 3.6 ARs in Reanalyses -- 3.7 AR Identification -- References -- 4: Global and Regional Perspectives -- 4.1 Introduction -- 4.2 Global Climatology -- 4.2.1 AR Detection Method and Justification -- 4.2.2 AR Frequency and IVT -- 4.2.3 AR Landfall Frequency -- 4.2.4 AR Duration -- 4.2.5 AR Precipitation Fraction -- 4.2.6 Seasonality -- 4.2.7 Summary of Sect. 4.2 -- 4.3 Climate Modulation -- 4.3.1 El Niño-Southern Oscillation -- 4.3.2 Madden-Julian Oscillation -- 4.3.3 Arctic Oscillation -- 4.3.4 Pacific/North American Pattern -- 4.3.5 Summary of Sect. 4.3 -- 4.4 ARs along the North American West Coast -- 4.4.1 Summary of Sect. 4.4 -- 4.5 Inland-Penetrating ARs Over the Western United States -- 4.5.1 Summary of Sect. 4.5. , 4.6 ARs in the Southeastern US -- 4.6.1 Summary of Sect. 4.6 -- 4.7 Europe -- 4.7.1 Summary of Sect. 4.7 -- 4.8 Southern South America -- 4.8.1 Summary of Sect. 4.8 -- 4.9 ARs in the Polar Regions -- 4.9.1 Arctic -- 4.9.2 Antarctic -- 4.9.3 Summary of Sect. 4.9 -- References -- 5: Effects of Atmospheric Rivers -- 5.1 Introduction -- 5.2 ARs and Orographic Precipitation -- 5.2.1 Precipitation Formation -- 5.2.2 Orographic Precipitation Enhancement -- 5.3 ARs, Floods and Water Resources -- 5.3.1 Flooding -- 5.3.2 Water Resources -- 5.4 Other Effects of ARs -- 5.4.1 Aquatic Ecosystems -- Estuarine Effects -- 5.4.2 Terrestrial Landscapes -- 5.4.3 Surface Winds -- 5.4.4 Coastal Sea Level -- 5.5 Regional Perspectives on AR Effects -- 5.5.1 North America -- 5.5.2 Europe -- 5.5.3 South America -- 5.5.4 New Zealand -- 5.5.5 Polar Regions -- Antarctica -- Arctic -- 5.6 Summary and Characteristics that Control AR Effects -- 5.6.1 Meteorological Characteristics -- IVT Rates -- IWV Amounts -- Rates of AR Translation Across the Landscape -- Air Temperature -- Atmospheric Stability -- Elevation of the AR Jet -- Barrier Jets -- 5.6.2 Land Characteristics -- Antecedent Conditions -- Terrain Characteristics -- Drainage Density -- Bedrock and Soil Type -- Land Use -- 5.6.3 Some Examples -- 5.7 Looking Forward -- References -- 6: Atmospheric River Modeling: Forecasts, Climate Simulations, and Climate Projections -- 6.1 Introduction -- 6.2 Forecasting ARs -- 6.2.1 An Ingredient-Based Approach to Forecasting ARs -- 6.2.2 Evaluating Forecasts of Landfalling ARs -- 6.2.3 AR Analysis and Forecasting Tools -- 6.3 Simulating ARs -- 6.3.1 Regional Models -- 6.3.2 Global Models -- Evaluating Model Performance for AR Simulations Based on Payne and Magnusdottir (2015) -- 6.4 Climate Projections of ARs. , 6.5 Summary and Emerging Directions -- References -- 7: Applications of Knowledge and Predictions of Atmospheric Rivers -- 7.1 Introduction -- 7.2 US Army Corps of Engineers: ARs and Flood Risk Management -- 7.2.1 A Case History -- 7.2.2 Real-World AR Issues -- Where Will the AR Strike? Stalls, Shifts, Trajectories, and Drainage Basins -- Forecasts or Observations? -- Drafting Floodwaters -- Flood Risks vs. Water Supply -- AR Seasonality -- Probable Maximum Precipitation (PMP) Estimates -- Forecast Improvements -- Next Steps -- 7.3 Forecast Informed Reservoir Operations, Lake Mendocino Pilot Study -- 7.4 ARs Use in Flood Planning in California -- 7.5 AR Science, Natural Hazards Risk Reduction, and ARkStorm -- 7.6 Scales That Communicate AR Intensity and Impacts -- 7.6.1 ECMWF's Extreme Forecast Index for Water Vapor Transport -- 7.6.2 A Scale for Atmospheric River Strength and Impacts -- References -- 8: The Future of Atmospheric River Research and Applications -- 8.1 Introduction -- 8.1.1 F. Martin Ralph (Western US Weather Science -- Regional Water Applications Development) -- 8.1.2 Duane E. Waliser (Global Atmospheric Science -- Satellite and Reanalysis Applications) -- 8.1.3 Jonathan J. Rutz (Weather Forecast Improvement -- AR Detection) -- 8.1.4 Michael D. Dettinger (Hydrologic Science and Applications -- Climate Change Diagnostics) -- 8.2 Observational Gaps -- 8.2.1 Ground Based -- 8.2.2 Airborne Physical Process Studies -- 8.2.3 A Vision for AR Reconnaissance -- Proof of Concept: Data Collection -- Proof of Concept: Data Assimilation and Modeling -- Anticipated Outcomes of AR Recon Data, Modeling, and Assimilation -- Vision of Potential Operational Implementation of AR Recon -- 8.2.4 Satellite -- 8.2.5 Reanalyses: Evaluations and Gaps to Be Addressed to Support AR Science and Applications. , 8.3 Emerging Directions in AR Physical Processes Research -- 8.3.1 Polar Processes Associated with ARs -- 8.3.2 Atmospheric Water Budget and Moist Processes -- 8.3.3 Terrestrial Hydrology and Water Budget -- 8.4 Communicating and Applying AR Information -- 8.4.1 How AR Science Affects Operations in the US National Weather Service's Western Region -- 8.4.2 Communicating ARs to Broader Technical and Lay Communities -- 8.4.3 Developing New AR Forecast Methods and Displays -- 8.4.4 Intercomparisons of AR Tracking Methods -- 8.4.5 Forecast-Informed Reservoir Operations (FIRO) -- 8.5 Exploring Subseasonal-to-Seasonal (S2S) Prediction of ARs -- 8.5.1 Western Water Management Requests Improved Precipitation Outlooks -- 8.5.2 Large-Scale Processes/Short-Term Climate Variability that Modulate ARs -- 8.5.3 The Promise and Challenge of Creating S2S Precipitation Outlooks for the West -- 8.6 Concluding Remarks -- References -- Index.
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  • 2
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Journal of the American Water Resources Association 41 (2005), S. 0 
    ISSN: 1752-1688
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Notes: : Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa Clara-Calleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate-driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/°C, compared to 0.9 m/°C in observations. This close agreement shows that the GCM-RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM-RGWM combination could be used for planning purposes and — when the GCM forecast skills are adequate — for near term predictions.
    Type of Medium: Electronic Resource
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  • 3
    ISSN: 1573-1480
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract Monthly mean surface-air temperatures at 870 sites in the contiguous United States were analyzed for interannual and interdecadal variability over the time interval 1910-87. The temperatures were analyzed spatially by empirical-orthogonal-function analysis and temporally by singularspectrum analysis (SSA). The dominant modes of spatio-temporal variability are trends and nonperiodic variations with time scales longer than 15 years, decadal-scale oscillations with periods of roughly 7 and 10 years, and interannual oscillations of 2.2 and 3.3 years. Together, these modes contribute about 18% of the slower-than-annual United States temperature variance. Two leading components roughly capture the mean hemispheric temperature trend and represent a long-term warming, largest in the southwest, accompanied by cooling of the domain's southeastern quadrant. The extremes of the 2.2-year interannual oscillation characterize temperature differences between the Northeastern and Southwestern States, whereas the 3.3-year cycle is present mostly in the Western States. The 7- to 10-year oscillations are much less regular and persistent than the interannual oscillations and characterize temperature differences between the western and interior sectors of the United States. These continental- or regional-scale temperature variations may be related to climatic variations with similar periodicities, either global or centered in other regions; such variations include quasi-biennial oscillations over the tropical Pacific or North Atlantic and quasi-triennial oscillations of North Pacific sea-surface temperatures.
    Type of Medium: Electronic Resource
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