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  • Cham :Springer International Publishing AG,  (1)
  • Frontiers Media  (1)
  • 1
    Online Resource
    Online Resource
    Cham :Springer International Publishing AG,
    Keywords: Oceanography-Research. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (322 pages)
    Edition: 1st ed.
    ISBN: 9783319664934
    Series Statement: Springer Oceanography Series
    Language: English
    Note: Intro -- Foreword -- Preface -- Contents -- About the Editors -- Part I: Introduction -- Recent Trends in Ocean Observations -- 1 Introduction -- 2 Recent Trends in Ocean Observations -- 3 Emerging Trends -- 4 Concluding Remarks -- References -- Part II: Surface Observations -- Observing Surface Meteorology and Air-Sea Fluxes -- 1 Introduction -- 2 The Required Observations and the Challenges -- 3 Sensors and Sensor Modules -- 4 Buoy Installation, Data Logging, and Telemetry -- 5 Accuracies Achieved in Surface Meteorology and Air-Sea Fluxes -- 6 Conclusions and Future Work -- References -- Drifter Technology and Impacts for Sea Surface Temperature, Sea-Level Pressure, and Ocean Circulation Studies -- 1 Lagrangian Drifter Technology -- 1.1 The Velocity-Temperature (SVP) Drifter -- 1.2 The Barometer Drifter (SVPB) -- 1.3 The Salinity Drifter (SVPS) -- 1.4 The Minimet Wind Drifter (SVPW) and the Autonomous Drifting Ocean Station (ADOS) -- 1.5 Coastal Ocean Dynamics Experiment (CODE) Drifter and River Drifter (RD) -- 2 The Global Drifter Program -- 3 Impacts of the Global Drifter Program Data -- 3.1 Sea Surface Temperature -- 3.2 Sea-Level Atmospheric Pressure: Climate Studies -- 3.3 Sea-Level Atmospheric Pressure: Numerical Weather Prediction -- 3.4 Subsurface Temperature, Air Pressure and Wind: The Seasonal Hurricane Array -- 3.5 Ocean Currents -- 4 Conclusions -- References -- Origin, Transformation and Measurement of Waves in Ocean -- 1 Introduction -- 2 Generation of Waves -- 3 Wave Measurement Systems -- 3.1 Principle of Resistance -- 3.2 Pressure Variation -- 3.3 Acoustic Principle -- 3.4 Principle of Acceleration -- 3.5 GPS-Based Measurement -- 3.6 Remote Sensing/Radar Techniques -- 3.7 Pilot Project on Wave Measurement Evaluation and Test (PP-WET) -- 4 Estimation of Wave Climate Using Measurements and Numerical Modelling. , 5 Wave Data Analysis -- 5.1 Wave Characteristics in North Indian Ocean -- 5.2 Design Waves -- 5.3 Extreme Waves -- Reference -- Part III: Subsurface Observations -- Oceanographic Floats: Principles of Operation -- 1 Introduction -- 2 Float Density and Behavior -- 3 Float Drag in a Stratified Ocean -- 4 Float Maneuvers -- 5 A Dynamic Float Control Algorithm -- 6 Control Regimes -- 7 Usage and Performance -- 8 Issues and Future Progress -- References -- Measuring Ocean Turbulence -- 1 Introduction -- 1.1 Turbulence in the Ocean -- 1.1.1 Reynolds Decomposition of Stationary, Homogeneous, and Isotropic Flows -- 1.1.2 Dimensional Analyses and the Length Scales of Turbulence -- 1.2 Theoretical Spectra and Subranges -- 1.3 Early Developments in the Measurement of Ocean Microstructure and Turbulence -- 2 Quantifying Turbulence with Ocean Measurements -- 2.1 Integral Approaches -- 2.2 Finescale Parameterizations -- 2.2.1 Calculation from Vertical Shear -- 2.2.2 Calculation from Strain -- 2.3 Direct Microstructure Measurements -- 2.3.1 Calculating the Turbulent Kinetic Energy Dissipation Rate -- 2.3.2 Calculating the Dissipation of Thermal (Scalar) Variance -- 3 Summary -- References -- Underwater Gliders -- 1 Introduction -- 2 Design and Development History -- 2.1 Challenges and Design Philosophy -- 2.2 Development History -- 3 Applications and Strategies -- 3.1 Boundary Currents -- 3.2 Process Studies -- 3.3 Biology and Biogeochemistry -- 3.4 Polar Regions -- 4 Lessons and Future Directions -- References -- Advances in In-Situ Ocean Measurements -- 1 Introduction -- 2 Conductivity Sensors -- 2.1 Conductivity Sensor Metrology and Calibration -- 2.2 Conductivity Sensor Response Characteristics -- 2.3 Conductivity Sensor Drift and Calibration Stability -- 3 Temperature Sensors -- 3.1 Temperature Sensor Metrology and Calibration. , 3.2 Temperature Sensor Response Characteristics -- 3.3 Temperature Sensor Drift and Calibration Stability -- 4 Pressure Sensors -- 4.1 Pressure Sensor Metrology and Calibration -- 4.2 Pressure Sensor Response Characteristics -- 4.3 Pressure Sensor Drift and Calibration Stability -- 5 Dissolved Oxygen Sensors -- 5.1 Dissolved Oxygen Sensor Metrology and Calibration -- 5.2 Dissolved Oxygen Response Characteristics -- 5.3 Dissolved Oxygen Sensor Drift and Calibration Stability -- 6 pH Sensors -- 6.1 pH Sensor Metrology and Calibration -- 6.2 pH Sensor Response Characteristics -- 6.3 pH Sensor Drift and Calibration Stability -- References -- Part IV: Remote Sensing -- Ocean Remote Sensing: Concept to Realization for Physical Oceanographic Studies -- 1 Introduction -- 2 Remote Sensing of Sea Surface Temperature -- 2.1 Measurement Principle: Thermal IR and Microwave Regime -- 2.2 Retrieval of Geophysical Parameters -- 2.3 Accuracy, Precision, and Sampling -- 2.4 Applications of Sea Surface Temperature -- 2.5 New Frontier in SST Measurements -- 3 Satellite Altimetry: A Versatile Tool for Ocean Applications -- 3.1 History of Satellite Altimetry -- 3.2 Measurement Principles -- 3.3 Retrieval of Geophysical Parameters (Sea Surface Height, Significant Wave Height, and Wind Speed) -- 3.4 Coastal Altimetry: A Challenging Task -- 3.5 Oceanographic Applications of Altimeter-Derived Parameters -- 3.6 GNSS-R and Swath Altimetry -- 4 Satellite Scatteromerty: Measuring the Ocean Surface Winds -- 4.1 Past, Present, and Future Scatterometers -- 4.2 Basic Measurement Techniques: em Interaction with Roughness -- 4.3 Retrieval of Ocean Surface Winds from Backscattering -- 4.4 Accuracy, Swath, and Resolution -- 4.5 Ocean and Ice Applications of Scatterometry -- 4.6 New Concept in Scatterometry -- 5 Synthetic Aperture Radar: Exploring Fine-Scale Processes. , 5.1 Concept and Principles of SAR Technology -- 5.2 Ocean Surface Imaging -- 5.3 Retrieval of Oceanographic Parameters -- 5.4 Oceanographic Applications of SAR -- 5.5 Future Advancements in SAR -- 6 Remote Sensing of Ocean Salinity: Filling the Missing Gap in Ocean Observation -- 6.1 Satellite Instruments for Salinity -- 6.2 Measurement Principles and Challenges for Salinity Retrieval from Space -- 6.3 Accuracy and Spatiotemporal Sampling -- 6.4 Applications of Satellite-Derived Salinity -- 7 End Remarks -- References -- Near Real-Time Underwater Passive Acoustic Monitoring of Natural and Anthropogenic Sounds -- 1 Introduction -- 2 Instruments -- 3 Platforms -- 3.1 Fixed Platforms -- 3.2 Mobile Nonnavigated Platforms -- 3.3 Mobile Navigated Platforms -- 4 Measurements -- 4.1 Biotic -- 4.2 Abiotic Sources - Natural and Anthropogenic -- 5 Experience -- 5.1 Marine Mammal Monitoring in Real Time -- 5.2 Seismic Activity Monitoring -- 5.3 Real-Time Ambient Noise Monitoring -- 5.4 The Future of Real-Time Passive Acoustic Monitoring -- References -- Data Return Aspects of CODAR and WERA High-Frequency Radars in Mapping Currents -- 1 Introduction -- 2 Data -- 2.1 HF Radar Radial Current Data -- 2.2 Ocean Surface Wave Data -- 2.3 Wind Data -- 3 HF Radar Data Return -- 3.1 Spatial Patterns of HF Radar Data Return -- 3.2 Temporal Variation of HF Radar Data Return -- 4 Summary -- References -- Part V: Data -- Sensor Performance and Data Quality Control -- 1 Optimizing Observations -- 1.1 Instrument Selection -- 1.2 Instrument Preparation -- 1.2.1 Calibration -- 1.2.2 Configuration -- 1.3 Instrument Integration -- 1.3.1 Mooring Design -- 1.3.2 Burn-in and Telemetry Testing -- 1.3.3 Deployment Preparations -- 2 Data Quality Assurance -- 2.1 Data Quality Evaluation -- 2.1.1 Telemetry Monitoring -- 2.1.2 Intercomparison -- 2.1.3 Postrecovery Procedures. , 2.2 Data Processing -- 3 Telemetry and Real-Time Data -- 3.1 Limitations and Benefits of Real-Time Data -- 3.2 Telemetry Systems Overview -- 3.3 Monitoring Data Output and Quality -- 3.3.1 Monitoring Techniques -- 3.3.2 Quality of Real-Time Data -- References -- Near Real-Time Data Recovery from Oceanographic Moorings -- 1 Introduction -- 1.1 Deep Ocean Subsurface Moorings -- 1.2 Deep Ocean Surface Moorings -- 1.3 Shallow Water Surface Moorings -- 2 Conclusion -- References -- Managing Meteorological and Oceanographic In Situ Data in the WMO Framework -- 1 Requirements for Marine Meteorological and Oceanographic (Meteo-ocean) Data for WMO Applications -- 1.1 The Role of the WMO -- 1.2 The WMO Application Areas -- 1.3 The Use of Meteo-ocean Data -- 1.4 Documenting the User Requirements -- 1.5 Gap Analysis -- 1.6 Guidance to WMO Member Countries and Territories on the Evolution of Global Observing Systems -- 2 The Role of the WMO in the Making and Collection of Meteo-ocean Data -- 2.1 International Cooperation Between Meteorologists and Oceanographers for the Making of Meteo-ocean Observations -- 2.2 Observing Platforms -- 2.3 Satellite Data Telecommunication -- 3 Meteo-ocean Data Management in the WMO Framework -- 3.1 Real-Time Data Exchange -- 3.2 Delayed Mode Data Exchange -- 3.3 Recent Approaches Regarding Ocean Data Integration -- 3.4 Quality Control and Feedback to the Observing Platform Operators -- 3.5 Instrument and Platform Metadata -- 3.6 Data Discovery Metadata -- 3.7 Data Policies -- 3.8 How to Access Data -- 3.9 Incentive for Sharing the Data -- 4 Conclusion -- Part VI: Societal Applications -- Applications of Ocean In-situ Observations and Its Societal Relevance -- 1 Introduction -- 2 The Current Status of the Ocean Observations Network in the Indian Ocean -- 3 The Importance and Application of the In-Situ Ocean Observation Network. , 3.1 Better Understanding of Weather and Climate.
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  • 2
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Subramanian, A. C., Balmaseda, M. A., Centurioni, L., Chattopadhyay, R., Cornuelle, B. D., DeMott, C., Flatau, M., Fujii, Y., Giglio, D., Gille, S. T., Hamill, T. M., Hendon, H., Hoteit, I., Kumar, A., Lee, J., Lucas, A. J., Mahadevan, A., Matsueda, M., Nam, S., Paturi, S., Penny, S. G., Rydbeck, A., Sun, R., Takaya, Y., Tandon, A., Todd, R. E., Vitart, F., Yuan, D., & Zhang, C. Ocean observations to improve our understanding, modeling, and forecasting of subseasonal-to-seasonal variability. Frontiers in Marine Science, 6, (2019): 427, doi:10.3389/fmars.2019.00427.
    Description: Subseasonal-to-seasonal (S2S) forecasts have the potential to provide advance information about weather and climate events. The high heat capacity of water means that the subsurface ocean stores and re-releases heat (and other properties) and is an important source of information for S2S forecasts. However, the subsurface ocean is challenging to observe, because it cannot be measured by satellite. Subsurface ocean observing systems relevant for understanding, modeling, and forecasting on S2S timescales will continue to evolve with the improvement in technological capabilities. The community must focus on designing and implementing low-cost, high-value surface and subsurface ocean observations, and developing forecasting system capable of extracting their observation potential in forecast applications. S2S forecasts will benefit significantly from higher spatio-temporal resolution data in regions that are sources of predictability on these timescales (coastal, tropical, and polar regions). While ENSO has been a driving force for the design of the current observing system, the subseasonal time scales present new observational requirements. Advanced observation technologies such as autonomous surface and subsurface profiling devices as well as satellites that observe the ocean-atmosphere interface simultaneously can lead to breakthroughs in coupled data assimilation (CDA) and coupled initialization for S2S forecasts. These observational platforms should also be tested and evaluated in ocean observation sensitivity experiments with current and future generation CDA and S2S prediction systems. Investments in the new ocean observations as well as model and DA system developments can lead to substantial returns on cost savings from disaster mitigation as well as socio–economic decisions that use S2S forecast information.
    Description: AS was funded by NOAA Climate Variability and Prediction Program (NA14OAR4310276) and the NSF Earth System Modeling Program (OCE1419306). CD was funded by NA16OAR4310094. SG and DG were funded by NASA awards NNX14AO78G and 80NSSC19K0059. DY was supported by NSFC (91858204, 41720104008, and 41421005).
    Keywords: Subseasonal ; Seasonal ; Predictions ; Air-sea interaction ; Satellite ; Argo ; Gliders ; Drifters
    Repository Name: Woods Hole Open Access Server
    Type: Article
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