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  • American Meteorological Society  (2)
  • Celona, Sean  (2)
  • 1
    Online Resource
    Online Resource
    American Meteorological Society ; 2021
    In:  Bulletin of the American Meteorological Society Vol. 102, No. 5 ( 2021-05), p. E1033-E1063
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 102, No. 5 ( 2021-05), p. E1033-E1063
    Abstract: The inner shelf, the transition zone between the surfzone and the midshelf, is a dynamically complex region with the evolution of circulation and stratification driven by multiple physical processes. Cross-shelf exchange through the inner shelf has important implications for coastal water quality, ecological connectivity, and lateral movement of sediment and heat. The Inner-Shelf Dynamics Experiment (ISDE) was an intensive, coordinated, multi-institution field experiment from September–October 2017, conducted from the midshelf, through the inner shelf, and into the surfzone near Point Sal, California. Satellite, airborne, shore- and ship-based remote sensing, in-water moorings and ship-based sampling, and numerical ocean circulation models forced by winds, waves, and tides were used to investigate the dynamics governing the circulation and transport in the inner shelf and the role of coastline variability on regional circulation dynamics. Here, the following physical processes are highlighted: internal wave dynamics from the midshelf to the inner shelf; flow separation and eddy shedding off Point Sal; offshore ejection of surfzone waters from rip currents; and wind-driven subtidal circulation dynamics. The extensive dataset from ISDE allows for unprecedented investigations into the role of physical processes in creating spatial heterogeneity, and nonlinear interactions between various inner-shelf physical processes. Overall, the highly spatially and temporally resolved oceanographic measurements and numerical simulations of ISDE provide a central framework for studies exploring this complex and fascinating region of the ocean.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    American Meteorological Society ; 2021
    In:  Journal of Atmospheric and Oceanic Technology Vol. 38, No. 4 ( 2021-04), p. 789-803
    In: Journal of Atmospheric and Oceanic Technology, American Meteorological Society, Vol. 38, No. 4 ( 2021-04), p. 789-803
    Abstract: A method based on machine learning and image processing techniques has been developed to track the surface expression of internal waves in near–real time. X-band radar scans are first preprocessed and averaged to suppress surface wave clutter and enhance the signal-to-noise ratio of persistent backscatter features driven by gradients in surface currents. A machine learning algorithm utilizing a support vector machine (SVM) model is then used to classify whether or not the image contains an internal solitary wave (ISW) or internal tide bore (bore). The use of machine learning is found to allow rapid assessment of the large dataset, and provides insight on characterizing optimal environmental conditions to allow for radar illumination and detection of ISWs and bores. Radon transforms and local maxima detections are used to locate these features within images that are determined to contain an ISW or bore. The resulting time series of locations is used to create a map of propagation speed and direction that captures the spatiotemporal variability of the ISW or bore in the coastal environment. This technique is applied to 2 months of data collected near Point Sal, California, and captures ISW and bore propagation speed and direction information that currently cannot be measured with instruments such as moorings and synthetic aperture radar (SAR).
    Type of Medium: Online Resource
    ISSN: 0739-0572 , 1520-0426
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 2021720-1
    detail.hit.zdb_id: 48441-6
    Location Call Number Limitation Availability
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