Physical Sciences and Mathematics Commons^™

Southern Maine, New Hampshire, And Northern Massachusetts Continental Shelf Geophysical Database: 2022 Field Campaign – Grain Size Data, Station Summaries, And Seafloor Photographs, Larry G. Ward, Rachel C. Morrison, Michael Bogonko

Data Catalog

Presented in this data report are the geophysical data collected during a major field campaign in 2022, with the purpose of obtaining ground truth for the expansion and improvement of high-resolution surficial geology maps of the western Gulf of Maine (WGOM) and for the description of reference sites developed for future evaluations of acoustic systems (Ward et al., 2021a; 2021b). Data from the UNH Ocean Engineering 972 Hydrographic Field Course classes in 2021 and 2022 are also included. This expansion of the geophysical database is being used to verify seafloor classifications in previously mapped areas that lack sufficient data, and …

Gis Data: Prince George’S County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Harford County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Cecil County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Caroline County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Dataset: Baywide Distribution Of Benthic Ecological Functions In The Past Decades In The Chesapeake Bay, Philip Ignatoff, Xun Cai, Kara Gadeken

Data

We undertook the collection and analysis of long-term benthos data from the Chesapeake Bay Benthic Monitoring Plan. Multiple ecological function traits related to feeding and disturbance were assigned to each observed benthic species based on a thorough literature review. The spatial distributions of the ecological function groups will be utilized in a 3D hydrodynamic biogeochemistry model simulation. This approach aids in estimating the contributions of benthos to estuarine hypoxia and nutrient dynamics. Furthermore, it fosters a connection between ecologists and modelers, promoting collaborative efforts in understanding and modeling the ecosystem.

Gis Data: Kent County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Baltimore County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Queen Anne’S County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Baltimore City, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Gis Data: Wicomico County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …

Sediment Characteristics Of The Chesapeake Bay And Its Tributaries, Virginia Province: Data Files, Gary F. Anderson

Data

During the 1990’s, Dr. Maynard Nichols and colleagues at the Virginia Institute of Marine Science compiled digital databases of sediment observations in the Chesapeake Bay and other coastal bays and rivers. These projects were performed under several cooperative agreements with NOAA, EPA and USGS. This particular dataset covers the Chesapeake Bay for bulk properties and contaminants. Additional references are provided below. The original files and filenames are provided without edit. See the readme.txt file for overall explanation of the datasets and individual .DOC files for the data dictionary and further data processing information for each waterbody.

New Hampshire Continental Shelf Geospatial Database: Surficial Geology Maps And Sediment Grain Size Data, Larry G. Ward, Zachary S. Mcavoy, Rachel C. Morrison

Data Catalog

The “New Hampshire Continental Shelf Geospatial Database: Surficial Geology Maps and Sediment Grain Size Data” consists of high-resolution surficial geology maps of the continental shelf off New Hampshire to Jeffreys Ledge in the Western Guff of Maine (WGOM) and supporting sediment grain size information. The surficial geology maps cover ~3,250 km² (Figure 1). The maps depict three different classifications based on the Coastal and Marine Ecological Classification Standards (CMECS; FGDC, 2012): Geoforms (major morphologic or physiographic features; Figure 2; Table 1), Geologic Substrate Subclass (Figure 3; Table 2), and Geologic Substrate Group (Figure 4; Table 2). The maps are …

Storm Surge Simulation From The 2009 Nor’Easter On The Virginia Shoreline, Karinna Nunez, Yinglong J. Zhang, Evan Hill, Catherine Riscassi Duning

Data

The November 2009 nor’easter formed from the remnants of Hurricane Ida and generated strong winds, heavy rain, and storm surge across the east coast of the United States. The height of the storm surge generated by the nor’easter was modelled throughout Virginia using SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model). SCHISM outputs were translated to GIS and processed to be overlaid upon the LUBC (land use and bank cover) shoreline of coastal Virginia.

A Data Repository For Clarifying Water Clarity: A Call To Use Metrics Best Suited To Corresponding Research And Management Goals In Aquatic Ecosystems (York River Estuary Case Study Dataset), Jessica S. Turner, Kelsey A. Fall, Carl T. Friedrichs

Data

This data repository is a permanent archive of the results presented in the associated publication (Turner et al. 2022, Limnology & Oceanography Letters, doi.xxxx). The objective of this study was to illustrate a water clarity phenomenon in the lower York River Estuary of the Chesapeake Bay. The data include light attenuation, Secchi depth, turbidity, and salinity from the lower York River Estuary in western Chesapeake Bay, Virginia, USA from the years 2014-2016.

Storm Surge Simulation From Hurricane Isabel (2003) On The Virginia Shoreline, Karinna Nunez, Yinglong J. Zhang, Evan Hill, Catherine Riscassi Duning

Data

Hurricane Isabel made landfall in the Outer Banks of North Carolina on September 16, 2003 as a category 2 hurricane. The storm continued northwest after making landfall and significantly impacted Virginia with strong winds, storm surge, and heavy rainfall. The height of the storm surge generated by Hurricane Isabel was modelled throughout Virginia using SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model). SCHISM outputs were translated to GIS and processed to be overlaid upon the LUBC (land use and bank cover) shoreline of coastal Virginia.

New Hampshire Continental Shelf Geophysical Database: 2002-2005 Jeffreys Ledge Field Campaign – Seafloor Photographs And Sediment Data, Larry G. Ward, Raymond E. Grizzle, Rachel C. Morrison

Data Catalog

Jeffreys Ledge is a major physiographic feature in the western Gulf of Maine (WGOM) located ~50 km off the coast of New Hampshire, although coming within ~10 km of shore by Cape Ann, Massachusetts. Jeffreys Ledge rises up as much as ~150 m from the seafloor of the adjacent basins (i.e., Scantum Basin or Wilkinson Basin) to depths less than 50 m on the ridge surface. The ridge extends over 100 km along its north-northeast to south-southwest axes while generally only being 5 to 10 km in width (~20 km maximum). Jeffreys Ledge and the surrounding region, like many features …

New Hampshire Continental Shelf Geophysical Database: 2012-2013 Newbex Field Campaign – Seafloor Photographs And Sediment Data, Larry G. Ward, Zachary S. Mcavoy, Rachel C. Morrison

Data Catalog

An approximately 4.5 km transect running from lower Portsmouth Harbor seaward onto the inner continental shelf was established to serve as the field site for the Newcastle Backscatter Experiment (NEWBEX). Acoustic backscatter measurements were made along the transect to examine relationships between backscatter and seafloor properties. This transect takes advantage of the diversity and heterogeneity of bottom types in lower Portsmouth Harbor and approach. In support of NEWBEX, a field campaign was undertaken to describe the sedimentologic characteristics of the seafloor along the transect. A total of five cruises were carried out approximately seasonally on November 26, 2012 and June …

Nitrogen Reductions Have Decreased Hypoxia In The Chesapeake Bay: Evidence From Empirical And Numerical Modeling : Data Repository, Luke T. Frankel, Marjorie A.M. Friedrichs

Data

This data repository is a permanent archive of the results presented in the associated publication: Frankel et al., 2022, Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling, Science of the Total Environment, accepted for publication in December 2021.

Acoustic Doppler Current Profiler (Adcp) Data 2017: Ayeyarwady Delta, Myanmar, Courtney K. Harris, Jacob T. Wacht

Data

During December 2017, a 2-week research cruise was conducted on the vessel the Sea Princess by scientists from the Virginia Institute of Marine Science, North Carolina State University, Mawlamyine University, and University of Yangon. Kuehl et al. (2019) and Liu et al. (2020) present some of the sediment core, and seabed mapping data from that cruise. The cruise also provided a unique opportunity to obtain Acoustic Doppler Current Profiler (ADCP) data along several transects from the Gulf of Martaban and adjacent continental shelf offshore of Myanmar. During the cruise, an ADCP was mounted from the boat facing vertically downward toward …

Escolar (Lepidocybium Flavobrunneum) Neurocranium, Meredith M. Pratt, Katerina D. Sawickij, David W. Kerstetter

All Scans: Kerstetter Fisheries and Avian Ecology 3D Scan Series

Neurocranium prep of escolar Lepidocybium flavobrunneum obtained from longlining vessel.

North Atlantic Observed Climatological Mean Absolute Geostrophic Velocity Profiles, Tiago Carrilho Biló

Supplementary Data and Tools

North Atlantic observed climatological mean absolute geostrophic velocity components in meters per second from near the surface (pressure = 2.5 dbar) to near ocean bottom (pressure = 5562.0 dbar). The absolute velocity fields in the upper 2000 dbar of the water column were obtained by referencing an ARGO based mean geostrophic shear with mean velocity estimates at 1000 dbar between 2004-2016. The shear was derived using the so-called Roemmich-Gilson Argo climatology (Roemmich & Gilson, 2009). The referencing procedure was conducted using Argo displacement data referred to as YoMaHa'07 (Lebedev et al., 2007). For regions deeper than 2000 dbar, the velocity …

Temporal And Spatial Scaling Of Dissipation Under Non-Breaking Surface Waves, Mingming Shao, Brian K. Haus, Darek Bogucki, Mohammad Barzegar

Supplementary Data and Tools

This dataset is associated to the NSF OCE/Physical Oceanography funded project “Laboratory Investigation of Turbulence Generation by Surface Waves”. There are three papers in preparation that will refer to data contained within this archive. The overarching goal of this project was to address a significant knowledge gap regarding the turbulent dissipation of non-breaking surface waves. To accomplish this, a comprehensive study in the SUrge-STructure-Atmosphere-INteraction (SUSTAIN) wind-wave laboratory at the University of Miami was conducted. A combination of established measurement approaches (Particle Image Velocimetry (PIV) and Vertical Microstructure Profiler (VMP)) and new technologies (Optical Turbulence Sensor (OTS)) have been used carry …

Spray Concentration Measurements From Asist For Freshwater And Seawater, Sanchit Mehta, David G. Ortiz-Suslow, Andrew W. Smith, Brian K. Haus

Supplementary Data and Tools

The size-dependent vertical distribution of spume particles in high wind conditions is necessary to understand their effect on air-sea fluxes of heat and momentum. The predominant focus of previous studies of spray dynamics has been on the marine environment. Spray dynamics in non-seawater bodies have not been extensively studied, and any significant differences between sea and freshwater remain unquantified. To address this gap, we have conducted the first laboratory experiment directly comparing spume concentrations above fresh and real seawater for 10-m equivalent wind speeds of 36-54 m/s. Droplets in the air above the intensely breaking wind-waves were directly observed and …

Simulating Storm Surge And Compound Flooding Events With A Creek-To-Ocean Model: Importance Of Baroclinic Effects : Model Files, Fei Ye, Yinglong J. Zhang, Haocheng Yu, Weiling Sun, Saeed Moghimi, Edward Myers, Karinna Nunez, Ruoyin Zhang, Harry V. Wang, Aron Roland, Kevin Martins, Xavier Bertin, Jiabi Du, Zhou Liu

Data

The supplemental material contains the input files for setting up a 3D baroclinic model based on the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), supplementing the description of model setup in Ye et al. (2019; associated publication).

The SCHISM version used for the simulation was r5082 in the SCHISM svn repository. A compressed file (setup.tar.gz) is provided, which can be extracted with common zip/unzip software on Unix/Windows/Mac (such as gzip, winzip, 7-zip, etc.). Since the dataset is intended for conducting a SCHISM simulation, readers/users should familiarize themselves with the SCHISM model system first.

The SCHISM manual is at: http://ccrm.vims.edu/schismweb/schism_manual.html; …

A Model Archive For Sediment Transport Model Including Short-Lived Radioisotopes: Model Description And Idealized Test Cases, Justin J. Birchler, Courtney K. Harris, Tara A. Kniskern

Data

This dataset includes model input, code, and output used in the publication Birchler et al. (2018, Journal of Marine Science and Engineering), which used a coupled hydrodynamic-sediment transport-biogeochemical model to investigate the roles of resuspension, deposition, on biodiffusion on the behavior of short-lived radioisotopes in an idealized one-dimensional model setting. Model development for this project focused on incorporating radioisotope tracers into the sediment transport module in the Regional Ocean Modeling System (ROMS). As described in Birchler et al. (2018, Journal of Marine Science and Engineering), the model can account for supply and sorption of radioisotope tracers in the …

Presence/Absence And Density Data For Epipelagic Tows Collected During R/V Blazing Seven Cruises Lf2016a And Lf2016b, Northern Gulf Of Mexico From 2016-06-09 To 2016-07-28, Jay R. Rooker, David Wells

DEEPEND Datasets

This dataset reports presence/absence and density data for epipelagic tows collected in the northern Gulf of Mexico during R/V Blazing Seven cruises LF2016A and LF2016B (2016-06-09 to 2016-07-28). Larval fishes were sampled from 48 stations and cruise data were collected at each site including latitude/longitude, date, time, environmental data (temperature, salinity, dissolved oxygen) and Sargassum dry weight. Larval catch data before and after the oil spill will be compared to improve our understanding of the causes of temporal variability as it relates to the Deep-Water Horizon oil spill (DWHOS). Habitat associations of selected taxa (billfishes, tunas, dolphinfishes, flyingfishes) will be …

Conductivity, Temperature, And Depth (Ctd) Data For Deepend Stations, Cruise Dp05, May 2017, David English, Chuanmin Hu, April Cook, Tracey Sutton

DEEPEND Datasets

Conductivity, temperature, and depth data from the ship's CTD, which was deployed at each of the DEEPEND stations. Depth of cast was variable, but extended from near-surface waters to below the euphotic zone. This data also includes measurements from a red light transmissometer, a chlorophyll fluorometer, and a dissolved oxygen sensor. The data is used in the assessment of the water column's vertical structure, and for comparison with physical models. Data were collected in the northern Gulf of Mexico from May 2-12, 2017.

Conductivity, Temperature And Depth (Ctd) Data For Deepend Stations, Cruise Dp03, May 2016, David English, Chuanmin Hu, April Cook, Tracey Sutton

DEEPEND Datasets

Conductivity, temperature and depth data from the ship's CTD, which is deployed at each of the DEEPEND stations. Depth of cast is variable, but extends from near-surface waters to below the euphotic zone. This data is used in the assessment of the water column's vertical structure, and for comparison with physical models. Data were collected during cruise DP03 in the northern Gulf of Mexico, May 2016.

Habitat Classification Of The Gulf Of Mexico (Gom) Using The Hybrid Coordinate Ocean Model (Hycom) And Salinity/Temperature Profiles, Cruises Dp01-Dp04, May 2015 To August 2016, Matt Johnston, Rosanna Milligan, Cole Easson, Sergio Derada, Brad Penta, Tracey Sutton

DEEPEND Datasets

Deep pelagic habitat from the entire Gulf of Mexico (GOM) was classified using the deviation of sea surface height (SSH) from mean SSH for the entire GOM and water temperature at 300 m water depth, founded on ocean condition data from the 1/25° GOM HYbrid Coordinate Ocean Model (HYCOM). Pelagic habitats were segregated into anticyclonic, mixed boundaries, and common water units – all of which likely produce varying levels of forage for deep-sea fauna and may be trophic drivers. Model classifications were compared to classifications based on water column temperature and salinity at depth, as measured by CTD casts during …