Physical Oceanography Data Sets
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Browsing Physical Oceanography Data Sets by Subject "Coastal ocean"
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Dataset2017 HF Radar observations off the East Taiwan Coast(Woods Hole Oceanographic Institution, 2021-10-04) Kirincich, Anthony R. ; Hsiao, Yu-hung ; Yang, Y.-J.High-frequency radar-based observations of surface currents along the east coast of Taiwan, obtained over a 50-day period in early 2017, are used to examine the occurrence, generation, and downstream advection of submesoscale eddies in the Kuroshio. Measured at an effective depth of 2 m and radial resolution of 3 km from four land-based HF radar systems spanning an 250-km along-stream distance, the surface current observations reveal the instantaneous position of the Kuroshio on hourly time scales as well as the occurrence of numerous high relative vorticity features. Vortex features with spatial scales of 5-20 km were concentrated in the first 30 km offshore, with many created at the southern tip of Taiwan on tidal timescales. Most features, with relative vorticities approaching zeta/f=1, translated northward along the coast at the speed of the Kuroshio itself and were coherent over the 250-km length of the Taiwanese coastline. Both tides and regional winds appear to influence when long-lived features form, and the offshore advection of surface waters by the vortices are observable in intermittent Satellite images of surface chlorophyll. While most features are advected northward with the current, a submarine ridge acts to impede the flow, scattering northward moving features and causing occasional southward-migrating vortices. Data Description: DESCRIPTION; The surface current observations used here were obtained from four long-range (4 MHz transmit frequency) land-based coastal radar systems, operated by the Taiwan Ocean Research Institute (TORI) and the National Taiwan University (NTU). All systems were Codar Ocean Sensors SeaSondes, with the three southern stations operated by TORI, and the northern-most station by NTU. Collected over the time period spanning February 1st to March 26th, 2017, the hourly observations of Doppler cross-spectra had a radial resolution of 3 km. Horizontal resolution was dependent on both the resolution of the measured antenna patterns (1 degree in azimuth) as well as the inherent azimuthal resolution of the radar returns themselves. DATA_PREPARATION_DESCRIPTION; Observed Doppler cross-spectra were reprocessed following Kirincich et al. (2012) using adjusted measured antenna patterns and advanced quality control metrics to estimate the radial surface currents observed at each site. Measured antenna response patterns were adjusted iteratively to reduce radar-to-radar inconsistencies defined using synthetic radials estimated from adjacent radars as well as systematic biases in mean vorticity and divergence patterns. Vector combinations of the radial surface currents, representative of the average currents over the top 2 m of the water column (StewartJoy, 1974) were estimated using power-weighed least-squares methods (Kirincich et al. 2012, Kaplan et al 2005) with a fixed horizontal averaging length-scale of 3 km, and masked for errors due to the geometric dilution of precision (GDOP) greater than 2 (Barrack, 2002). Acquisition Description: SENSOR_INFORMATION; Radio frequency interference from the ionosphere is a particular problem for the TORI and NTU radars, due to a combination of latitude and transmit frequency, causing elevated background noise during local nighttime. Returns at ranges of 90 km, the distance to the primary scattering layer within the ionosphere, are especially affected. SNR was used as an effective screening tool to isolate and eliminate data contaminated by ionospheric radio noise common in the region, adding further improvements to the radial velocity results. However, data from a 50x50 km region directly offshore of the radar site near 23deg 30' N 121deg 30' E was excised during the hours of 11 to 17 UTC each day during the observational period due to poor data returns during times of high ionospheric reflections and radio noise that resulted in poorly resolved and inaccurate vector current estimates. Using synthetic radials from adjacent HFR sites (Emery et al 2019), surface current uncertainties are estimated to be 5-10 cm/s. the west of the 2018-2019 mooring locations. The surface mooring was located at 41.0706degN 70.8177degW in 40 m of water and sampled surface vector winds, air temperature, air pressure, and relative humidity using a Vaisala WXT520 located at 2 m above mean sea level at 10 min ensemble averages, of 1 Hz data. The 2020 surface mooring also had 5 temperature-conductivity sensors (SBE37s) that sampled the oceanic water column at fixed depths below the surface of 0.6,4,6.5,10, and 20-m at 2 min increments. Finally the 2020 subsurface mooring was deployed at 41.0706degN 70.8177degW and contained a sub-surface float at 8-m below sea level in 40 m of water. The float held an upward looking Nortek Signature 1000 AD2CP that collected 2048 pings @4Hz every 20 min at 0.25 m bin depths.
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DatasetHorizontal Stirring over the Northeast U.S. Continental Shelf: the Spatial and Temporal Evolution of Surface Eddy Kinetic Energy(Woods Hole Oceanographic Institution, 2021-09-30) Kirincich, Anthony R. ; Flament, Pierre J. ; Futch, Victoria ; Hodges, Benjamin A.This data was collected by Kirincich as part of the Submesoscale Dynamics Over The Shelf Study, with field observations in 2018 and 2019, as well as the HFR_winds project with field work in 2020. The analysis products presented were used to examine the space and time scales of eddy kinetic energy over the wide, shallow, NES continental shelf using a novel implementation of HFR to achieve spatial and temporal resolutions sufficient to capture the horizontal scales of velocity variability. The data consists of estimates of the near-surface horizontal (East and North) ocean currents made via High Frequency (HF) radar-based remote sensing of the Ocean backscatter spectrum as well as in situ moored hydrographic, velocity, and surface winds, and mobile surface hydrographic observations collected via autonomous vehicles. Data were collected within three separate measurement periods: July to December 2018, July to December 2019, and October to December 2020.