The Inner-Shelf Dynamics Experiment

17 USC 105 interim-entered record; under review.The article of record as published may be found at http://dx.doi.org/10.1175/BAMS-D-19-0281.1The 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.U.S. Office of Naval Research (ONR)ONR Departmental Research Initiative (DRI)Inner-Shelf Dynamics Experiment (ISDE

Continuous Coastal Monitoring with an Automated Terrestrial Lidar Scanner

This paper details the collection, geo-referencing, and data processing algorithms for a fully-automated, permanently deployed terrestrial lidar system for coastal monitoring. The lidar is fixed on a 4-m structure located on a shore-backing dune in Duck, North Carolina. Each hour, the lidar collects a three-dimensional framescan of the nearshore region along with a 30-min two-dimensional linescan time series oriented directly offshore, with a linescan repetition rate of approximately 7 Hz. The data are geo-referenced each hour using a rigorous co-registration process that fits 11 fixed planes to a baseline scan to account for small platform movements, and the residual errors from the fit are used to assess the accuracy of the rectification. This process decreased the mean error (defined as the magnitude of the offset in three planes) over a two-year period by 24.41 cm relative to using a fixed rectification matrix. The automated data processing algorithm then filters and grids the data to generate a dry-beach digital elevation model (DEM) from the framescan along with hourly wave runup, hydrodynamic, and morphologic statistics from the linescan time series. The lidar has collected data semi-continuously since January 2015 (with gaps occurring while the lidar was malfunctioning or being serviced), resulting in an hourly data set spanning four years as of January 2019. Examples of data products and potential applications spanning a range of spatial and temporal scales relevant to coastal processes are discussed