Construction of net isopleth plots in cross-sections of tidal estuaries

Construction of isopleth plots of net velocity, material concentration, or material flux in cross-sections of tidal estuaries is not a trivial matter. To construct a flux-preserving isopleth plot requires that each instantaneous measure is weighted by the subarea for which the measure is representative. This area-weighted averaging procedure is outlined. Without area-weighting, net isopleth plots typically yield misleading results in tidal estuaries. In our example, net fluxes of total nitrogen are over-estimated without area-weighting

Comparison of Buoy-Mounted and Bottom-Moored ADCP Performance at Gray’s Reef

Simultaneous ADCP profile measurements are compared over a 2-month period in late 2003. One set of measurements comes from a National Data Buoy Center (NDBC) buoy-mounted ADCP, the other from a bottom-mounted, upward-looking ADCP moored roughly 500 m from the buoy. The study was under- taken to evaluate the proficiency of an experimental configuration by NDBC; unfortunately, the ADCP was not optimally configured. The higher temporally and vertically resolved bottom-mounted ADCP data are interpolated in time and depth to match the buoy-mounted ADCP measurements. It is found that the two ADCP measurements are significantly different. The buoy-mounted measurements are affected by high- frequency (10 h period) noise that is vertically coherent throughout the profiles. This noise results in autospectra that are essentially white, unlike the classic red spectra formed from the bottom-mounted ADCP observations. The spectra imply a practical noise floor of 0.045 m s1 for the buoy-mounted system. Contamination by surface waves is the likely cause of this problem. At tidal frequencies the buoy-mounted system underestimates major axis tidal current magnitude by 10%-40%; interference from the buoy chain and/or fish or plankton are considered the most likely cause of the bias. The subtidal velocity field (periods greater than 40 h) is only partially captured; the correlation coefficient for the east-west current is 0.49 and for the north-south current is 0.64

Complex EOF Analysis as a Method to Separate Barotropic and Baroclinic Velocity Structure in Shallow Water

Defining the vertical depth average of measured currents to be barotropic is a widely used method of separating barotropic and baroclinic tidal currents in the ocean. Away from the surface and bottom bound- ary layers, depth-averaging measured velocity is an excellent estimate of barotropic tidal flow, and internal tidal dynamics can be well represented by the difference between the measured currents and their depth average in the vertical. However, in shallow and/or energetic tidal environments such as the shelf of the South Atlantic Bight (SAB), bottom boundary layers can occupy a significant fraction of the water column, and depth averaging through the bottom boundary layer can overestimate the barotropic current by several tens of centimeters per second near bottom. The depth-averaged current fails to capture the bottom boundary layer structure associated with the barotropic tidal signal, and the resultant estimate of baroclinic tidal currents can mimic a bottom-trapped internal tide. Complex empirical orthogonal function (CEOF) analysis is proposed as a method to retain frictional effects in the estimate of the barotropic tidal currents and allow an improved determination of the baroclinic currents. The method is applied to a midshelf region of the SAB dominated by tides and friction to quantify the effectiveness of CEOF analysis to represent internal structure underlying a strong barotropic signal in shallow water. Using examples of synthesized and measured data, EOF estimates of the barotropic and baroclinic modes of motion are compared to those made using depth averaging. The estimates of barotropic tidal motion using depth-averaging and CEOF methods produce conflicting predictions of the frequencies at which there is meaningful baroclinic variability. The CEOF method preserves the frictional boundary layer as part of the barotropic tidal current structure in the gravest mode, providing a more accurate representation of internal structure in higher modes. The application of CEOF techniques to isolate internal structure co-occurring with highly energetic tidal dynamics in shallow water is a significant test of the method. Successful separation of barotropic and baroclinic modes of motion suggests that, by fully capturing the effects of friction associated with the barotropic tide, CEOF analysis is a viable technique to facilitate examination of the internal tide in similar environments

Overview of the Processes driving Exchange At Cape Hatteras Program

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Seim, H., Savidge, D., Andres, M., Bane, J., Edwards, C., Gawarkiewicz, G., He, R., Todd, R., Muglia, M., Zambon, J., Han, L., & Mao, S. Overview of the Processes driving Exchange at Cape Hatteras Program. Oceanography, (2022), https://doi.org/10.5670/oceanog.2022.205.The Processes driving Exchange At Cape Hatteras (PEACH) program seeks to better understand seawater exchanges between the continental shelf and the open ocean near Cape Hatteras, North Carolina. This location is where the Gulf Stream transitions from a boundary-trapped current to a free jet, and where robust along-shelf convergence brings cool, relatively fresh Middle Atlantic Bight and warm, salty South Atlantic Bight shelf waters together, forming an important and dynamic biogeographic boundary. The magnitude of this convergence implies large export of shelf water to the open ocean here. Background on the oceanography of the region provides motivation for the study and gives context for the measurements that were made. Science questions focus on the roles that wind forcing, Gulf Stream forcing, and lateral density gradients play in driving exchange. PEACH observational efforts include a variety of fixed and mobile observing platforms, and PEACH modeling included two different resolutions and data assimilation schemes. Findings to date on mean circulation, the nature of export from the southern Middle Atlantic Bight shelf, Gulf Stream variability, and position variability of the Hatteras Front are summarized, together with a look ahead to forthcoming analyses.We gratefully acknowledge NSF funding (OCE-1558920 to UNC-CH, OCE-1559476 to SkIO, OCE-1558521 to WHOI, OCE-1559178 to NCSU); technical support from Sara Haines, Craig Marquette, Trip Patterson, Nick DeSimone, Erran Sousa, Gabe Matthias, Patrick Deane, Brian Hogue, Frank Bahr, and Ben Hefner; cruise participants Jacob Forsyth, Joleen Heiderich, Chuxuan Li, Marco Valero, Lauren Ball, John McCord, and Kyle Maddux-Lawrence; and the crew of R/V Armstrong for their able support during three PEACH cruises

Cold event in the South Atlantic Bight during summer of 2003 : model simulations and implications

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C05022, doi:10.1029/2006JC003903.A set of model simulations are used to determine the principal forcing mechanisms that resulted in anomalously cold water in the South Atlantic Bight (SAB) in the summer of 2003. Updated mass field and elevation boundary conditions from basin-scale Hybrid Coordinate Ocean Model (HYCOM) simulations are compared to climatological forcing to provide offshore and upstream influences in a one-way nesting sense. Model skill is evaluated by comparing model results with observations of velocity, water level, and surface and bottom temperature. Inclusion of realistic atmospheric forcing, river discharge, and improved model dynamics produced good skill on the inner shelf and midshelf. The intrusion of cold water onto the shelf occurred predominantly along the shelf-break associated with onshore flow in the southern part of the domain north of Cape Canaveral (29° to 31.5°). The atmospheric forcing (anomalously strong and persistent upwelling-favorable winds) was the principal mechanism driving the cold event. Elevated river discharge increased the level of stratification across the inner shelf and midshelf and contributed to additional input of cold water into the shelf. The resulting pool of anomalously cold water constituted more than 50% of the water on the shelf in late July and early August. The excess nutrient flux onto the shelf associated with the upwelling was approximated using published nitrate-temperature proxies, suggesting increased primary production during the summer over most of the SAB shelf.The preparation of this paper was primarily supported by the Southeast Atlantic Coastal Ocean Observing System (SEACOOS) and the South Atlantic Bight Limited Area Model (SABLAM). SEACOOS is a collaborative, regional program sponsored by the Office of Naval Research under award N00014-02-1-0972 and managed by the University of North Carolina-General Administration. SABLAM was sponsored by the National Ocean Partnership Program (award NAG 13-00041). Data from ship surveys were collected and processed with the support from NSF grant OCE-0099167 (J. R. Nelson), NSF grant OCE-9982133 (J. O. Blanton, SkIO), NASA grant NAG-10557 (J. R. Nelson), and SEACOOS. NOAA NDBC buoy data and NOS coastal water level records were obtained through NOAA-supported data archives and web portals. Moored instrument data from the Carolina Coastal Ocean Observation and Prediction System (Caro-COOPS) were acquired from the system’s website (http://www.carocoops.org). Caro-COOPS is sponsored by NOAA grant NA16RP2543

Global perspectives on observing ocean boundary current systems

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Todd, R. E., Chavez, F. P., Clayton, S., Cravatte, S., Goes, M., Greco, M., Ling, X., Sprintall, J., Zilberman, N., V., Archer, M., Aristegui, J., Balmaseda, M., Bane, J. M., Baringer, M. O., Barth, J. A., Beal, L. M., Brandt, P., Calil, P. H. R., Campos, E., Centurioni, L. R., Chidichimo, M. P., Cirano, M., Cronin, M. F., Curchitser, E. N., Davis, R. E., Dengler, M., deYoung, B., Dong, S., Escribano, R., Fassbender, A. J., Fawcett, S. E., Feng, M., Goni, G. J., Gray, A. R., Gutierrez, D., Hebert, D., Hummels, R., Ito, S., Krug, M., Lacan, F., Laurindo, L., Lazar, A., Lee, C. M., Lengaigne, M., Levine, N. M., Middleton, J., Montes, I., Muglia, M., Nagai, T., Palevsky, H., I., Palter, J. B., Phillips, H. E., Piola, A., Plueddemann, A. J., Qiu, B., Rodrigues, R. R., Roughan, M., Rudnick, D. L., Rykaczewski, R. R., Saraceno, M., Seim, H., Sen Gupta, A., Shannon, L., Sloyan, B. M., Sutton, A. J., Thompson, L., van der Plas, A. K., Volkov, D., Wilkin, J., Zhang, D., & Zhang, L. Global perspectives on observing ocean boundary current systems. Frontiers in Marine Science, 6, (2010); 423, doi: 10.3389/fmars.2019.00423.Ocean boundary current systems are key components of the climate system, are home to highly productive ecosystems, and have numerous societal impacts. Establishment of a global network of boundary current observing systems is a critical part of ongoing development of the Global Ocean Observing System. The characteristics of boundary current systems are reviewed, focusing on scientific and societal motivations for sustained observing. Techniques currently used to observe boundary current systems are reviewed, followed by a census of the current state of boundary current observing systems globally. The next steps in the development of boundary current observing systems are considered, leading to several specific recommendations.RT was supported by The Andrew W. Mellon Foundation Endowed Fund for Innovative Research at WHOI. FC was supported by the David and Lucile Packard Foundation. MGo was funded by NSF and NOAA/AOML. XL was funded by China’s National Key Research and Development Projects (2016YFA0601803), the National Natural Science Foundation of China (41490641, 41521091, and U1606402), and the Qingdao National Laboratory for Marine Science and Technology (2017ASKJ01). JS was supported by NOAA’s Global Ocean Monitoring and Observing Program (Award NA15OAR4320071). DZ was partially funded by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063. BS was supported by IMOS and CSIRO’s Decadal Climate Forecasting Project. We gratefully acknowledge the wide range of funding sources from many nations that have enabled the observations and analyses reviewed here

Moored time-series records for chlorophyll and turbidity collected from the LB1 Mooring, LB2 Mooring, LB3 Mooring in the South Atlantic Bight (SAB) continental shelf off Long Bay from 2011-2012 (Long Bay Wintertime Bloom project)

Dataset: LB_2012_Mooring_OpticsTime series of chlorophyll and turbidity measured every second on three moorings located at Long Bay, S. Carolina in the South Atlantic Bight, located at mid-shelf at 30 m, shelf break at 74 m and upper slope at 171 m along a central shelf/slope survey line SE of Myrtle Beach, SC between 33.17/-78.33 and 32.76/-77.91. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/638349NSF Division of Ocean Sciences (NSF OCE) OCE-1032285, NSF Division of Ocean Sciences (NSF OCE) OCE-103227

CTD data from gliders on the R/V Savannah in the South Atlantic Bight (SAB) continental shelf off Long Bay (-79W, 32N; -77W, 34 N) collected from January to April 2012 (Long Bay Wintertime Bloom project)

Dataset: LB_2012_Glider_CTDTwo Webb Slocum gliders were used to measure salinity, temperature, and depth. Glider 'Pelagia' was deployed in Long Bay, S. Carolina, South Atlantic Bight and glider 'Ramses' was deployed along the upper slope of S. Carolina. in 2012. Data were collected in a time series from January to April, 2012. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/544615NSF Division of Ocean Sciences (NSF OCE) OCE-1032285, NSF Division of Ocean Sciences (NSF OCE) OCE-103227