MAB_hIPR.SHP: Half interpercentile range (half of the difference between the 16th and 84th percentiles) of wave-current bottom shear stress in the Middle Atlantic Bight for May, 2010 - May, 2011

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Frequently-anticipated questions:


What does this data set describe?

Title:
MAB_hIPR.SHP: Half interpercentile range (half of the difference between the 16th and 84th percentiles) of wave-current bottom shear stress in the Middle Atlantic Bight for May, 2010 - May, 2011
Abstract:
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are created using numerical models, and near-bottom output of steady and oscillatory velocities and an estimate of bottom roughness are used to calculate a time-series of bottom shear stress at 1-hour intervals. Statistical descriptions such as the median and 95th percentile, which are the output included with this database, are then calculated to create a two-dimensional picture of the regional patterns in shear stress. In addition, time-series of stress are compared to critical stress values at select points calculated from observed surface sediment texture data to determine estimates of sea floor mobility.
Supplemental_Information:
This data layer is a subset of the U.S. Geological Survey Sea Floor Stress and Sediment Mobility database, and contains the half interpercentile range (half of the difference between the 16th and 84th percentiles, equal to the standard deviation for a normal distribution) of bottom shear stress for the Middle Atlantic Bight.
  1. How should this data set be cited?

    Dalyander, P. Soupy , 2012, MAB_hIPR.SHP: Half interpercentile range (half of the difference between the 16th and 84th percentiles) of wave-current bottom shear stress in the Middle Atlantic Bight for May, 2010 - May, 2011: Database, U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    This is part of the following larger work.

    Dalyander, P.S., Butman, B., Sherwood, C.R., and Signell, R.P., 2012, U.S. Geological Survey Sea Floor Stress and Sediment Mobility Database: Database, U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

  2. What geographic area does the data set cover?

    West_Bounding_Coordinate: -76.819008
    East_Bounding_Coordinate: -68.407028
    North_Bounding_Coordinate: 41.623672
    South_Bounding_Coordinate: 34.102524

  3. What does it look like?

    mobility_website_browse_HiPR.jpg (JPEG)
    Image displaying coverage area of bottom shear stress and the half interpercentile range (half of the difference between the 16th and 84th percentiles) for a 1-year period for the Middle Atlantic Bight.

  4. Does the data set describe conditions during a particular time period?

    Beginning_Date: 01-May-2010
    Ending_Date: 01-May-2011
    Currentness_Reference: ground condition

  5. What is the general form of this data set?

    Geospatial_Data_Presentation_Form: vector digital data

  6. How does the data set represent geographic features?

    1. How are geographic features stored in the data set?

      Indirect_Spatial_Reference: Middle Atlantic Bight
      This is a Vector data set. It contains the following vector data types (SDTS terminology):
      • G-polygon (2888)

    2. What coordinate system is used to represent geographic features?

      Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.000001. Longitudes are given to the nearest 0.000001. Latitude and longitude values are specified in Decimal degrees.

      The horizontal datum used is D_WGS_1984.
      The ellipsoid used is WGS_1984.
      The semi-major axis of the ellipsoid used is 6378137.000000.
      The flattening of the ellipsoid used is 1/298.257224.

  7. How does the data set describe geographic features?

    MAB_hIPR
    Shapefile Attribute Table (Source: ESRI)

    FID
    Internal feature number. (Source: ESRI)

    Sequential unique whole numbers that are automatically generated.

    Shape
    Feature geometry. (Source: ESRI)

    Coordinates defining the features.

    Year
    This value is the half interpercentile range (half of the difference between the 16th and 84th percentiles, equal to the standard deviation for a normal distribution) of bottom shear stress calculated for the one year time period of May 1, 2010 through April 30, 2011. The NODATA value is -9999. (Source: USGS)

    Range of values
    Minimum:0.0107
    Maximum:1.5544
    Units:Pa
    Resolution:0.0001

    Winter
    This value is the half interpercentile range (half of the difference between the 16th and 84th percentiles, equal to the standard deviation for a normal distribution) of bottom shear stress calculated for the period of December 1, 2010 through February 28, 2011. The NODATA value is -9999. (Source: USGS)

    Range of values
    Minimum:0.0066
    Maximum:1.7355
    Units:Pa
    Resolution:0.0001

    Spring
    This value is the half interpercentile range (half of the difference between the 16th and 84th percentiles, equal to the standard deviation for a normal distribution) of bottom shear stress calculated for the period of March 1, 2011, through April 30, 2011, and May, 2010. The NODATA value is -9999. (Source: USGS)

    Range of values
    Minimum:0.0077
    Maximum:1.4690
    Units:Pa
    Resolution:0.0001

    Summer
    This value is the half interpercentile range (half of the difference between the 16th and 84th percentiles, equal to the standard deviation for a normal distribution) of bottom shear stress calculated for the period of June 1, 2010, through August 31, 2010. The NODATA value is -9999. (Source: USGS)

    Range of values
    Minimum:0.0065
    Maximum:1.3537
    Units:Pa
    Resolution:0.0001

    Fall
    This value is the half interpercentile range (half of the difference between the 16th and 84th percentiles, equal to the standard deviation for a normal distribution) of bottom shear stress calculated for the period of September 1, 2010, to November 30, 2010. The NODATA value is -9999. (Source: USGS)

    Range of values
    Minimum:0.0157
    Maximum:1.7370
    Units:Pa
    Resolution:0.0001


Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

  2. Who also contributed to the data set?

  3. To whom should users address questions about the data?

    P. Soupy Dalyander
    U.S. Geological Survey
    Oceanographer
    384 Woods Hole Road
    Woods Hole, MA 02543-1598
    USA

    (508) 548-8700 x2290 (voice)
    (508) 457-2310 (FAX)
    sdalyander@usgs.gov


Why was the data set created?

This GIS layer contains an estimate of the half interpercentile range of bottom shear stress for the Middle Atlantic Bight. The half interpecentile range is calculated as half of the difference between the 16th and 84th percentiles, and for a normal distribution would be equal to the standard deviation. This output is based on statistical characterization of numerical model estimates of wave and circulation patterns over an approximately one year time frame. This data layer is primarily intended to show the overall distribution of the range of stress values on large spatial scales, and should be used qualitatively. Intended users include scientific researchers and the coastal and marine spatial planning community.


How was the data set created?

  1. From what previous works were the data drawn?

    NOAA GFS (source 1 of 4)
    NOAA National Centers for Environmental Prediction (NCEP), 20110601, NOAA/NCEP Global Forecast System (GFS) Atmospheric Model: NOAA National Centers for Environmental Prediction, Camp Springs, MD.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    The NOAA Global Forecast System (GFS) 0.5 degree model was used to provide wind speed data at 10 m above the sea surface to drive the numerical wave model used to generate bottom orbital wave velocities for calculations of a time-series of bottom shear stress.

    NOAA NAM (source 2 of 4)
    NOAA National Centers for Environmental Prediction (NCEP), 20110601, NOAA/NCEP North American Mesoscale (NAM) Atmospheric Model: NOAA National Centers for Environmental Prediction, Camp Springs, MD.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    The NOAA North American Mesoscale (NAM) model was used to provide wind speed data at 10 m above the sea surface to drive the numerical wave model used to generate bottom orbital wave velocities for calculations of a time-series of bottom shear stress.

    RU ESP (source 3 of 4)
    Rutgers Ocean Modeling Group, 20110601, Esperimental System for Predicting Shelf and Slope Optics (ESPreSSO): Rutgers Ocean Modeling Group, New Brunswick, NJ.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    The Rutgers University ESPreSSO model was used to provide estimates of near-bed current velocity used for calculating the time-series of bottom shear stress.

    The ESPreSSO hydrodynamic model (<http://www.myroms.org/espresso/>) has been operated by Rutgers University since October 2009 as a data-assimilative nowcast/forecast system for the Mid-Atlantic Regional Association Coastal Ocean Observing System (MARACOOS, <http://maracoos.org/>), part of the U.S. Integrated Ocean Observing System (<http://www.ioos.gov>). The underlying circulation model is the Regional Ocean Modeling System (ROMS; <http://www.myroms.org>), a finite-difference, hydrostatic, primitive equation ocean model that solves for the free surface elevation and three dimensional flow patterns, temperature, and salinity.

    The ESPreSSO configuration of ROMS has 5 km horizontal resolution and 36 layers in vertical terrain-following coordinates. Bathymetry and land-sea masking is from the National Geophysical Data Center (NGDC) Coastal Relief Model. The vertical turbulence closure is the k-kl option of the Generalized Length Scale (GLS) formulation. Air-sea fluxes of momentum and heat are computed using bulk formulae applied to ROMS ocean surface conditions and meteorological conditions (wind velocity, rain, downward long- and short-wave radiation, and marine boundary layer temperature, pressure, and relative humidity) from the NOAA NAM atmospheric forecast. Ocean open boundary values are from a global forecast that uses the HYbrid Coordinate Ocean Model (HyCOM) with assimilation of satellite and in situ data with the Navy Coupled Ocean Data Assimilation (NCODA) system. ESPreSSO river inflows are from daily U.S. Geological Survey (USGS) stream gauge data, and tidal harmonic boundary variability is determined from a regional tidal model.

    Output from the ESPreSSO forecast system is saved every 2 hours. Access to model results is made practical through the use of Thematic Real-time Environmental Distributed Data Services (THREDDS) technology, which allows subsets of large data sets to be accessed directly via Open-source Project for a Network Data Access Protocol (OPeNDAP) over the Internet from remote locations without transferring the entire multi-gigabyte model output.

    The ESPreSSO data assimilation methodology consists of using the incremental strong constraint 4-dimensional variational (IS4DVar) approach to optimally adjust the model state within a 3-day duration analysis interval that precedes each 72-hour forecast. The assimilation cycle is repeated daily (hence the 3-day analysis windows overlap) and the first 24 hours of each forecast is retained as the "best estimate" of the ocean state for that day. It was these "best estimate" data that were analyzed here.

    The data assimilated include surface currents from the MARACOOS HF-Radar (CODAR) network, sea surface temperature from satellite infrared (AVHRR) and microwave (AMSR-E) radiometers, and sea surface height anomalies from the Jason-2 altimeter satellite. In addition, a regional high-resolution climatology based on a 4-dimensional weighted least squares mapping of historical hydrographic data is assimilated to constrain biases in temperature and salinity introduced by the boundary conditions and/or internal model drift.

    NOAA WW3 (source 4 of 4)
    NOAA National Centers for Environmental Prediction (NCEP, 20110601, NOAA/NWS/NCEP Global Wavewatch III Operational Wave Forecast: NOAA National Centers for Environmental Prediction, Camp Springs, MD.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    Boundary conditions for the wave model were provided by the global NOAA/NWS/NCEP Wavewatch III operational ocean wave forecast.

  2. How were the data generated, processed, and modified?

    Date: 2011 (process 1 of 4)
    The Simulating WAves Nearshore (SWAN) numerical wave model (version 40.81, modified for proper calculation of RMS bottom orbital velocity and for output of bottom wave direction) was used to create a time-series of bottom orbital velocity, bottom representative period, and bottom wave direction over the one year time period of May, 2010 - May, 2011 in each grid cell in the model domain. The wave model SWAN is a 3rd generation phase-averaged numerical wave model which conserves wave energy subject to generation, dissipation, and transformation processes and resolves spectral energy density over a range of user-specified frequencies and directions. Although stress calculations were only performed over the spatial extent of the hydrodynamic model, SWAN was run over a larger spatial scale. This ~5 km resolution grid, which covers the U.S. East Coast, Gulf of Mexico, and much of the western north Atlantic, was originally developed for use with the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) model system forecast and is shown elsewhere (Warner et al., 2010). This domain pushes the boundaries of the grid far from the region of interest to allow the wave spectrum (relatively important in calculations of stress) to evolve away from the boundary. The model was run for April 2010 using the default SWAN initial condition formulation for a non-stationary run, e.g., a JONSWAP spectrum from prescribed initial wind conditions, to develop initial conditions for the one year study period (May 2010 to May 2011).

    Significant wave height, dominant wave period, and wave direction were prescribed as SWAN TPAR format files on the model grid boundary with a spatial resolution of a boundary point every 25 grid cells using results from the NOAA Wavewatch III global multi-grid model, updated every 3 hours. A JONSWAP (JOint NOrth Sea WAve Project) spectral shape was assumed at these boundary points. Wind forcing was provided at 3-hour resolution from the NOAA North American Mesoscale (NAM) model (12 km resolution) over its domain, with forcing at the most offshore portions of the grid (outside the NAM grid) provided by the NOAA Global Forecasting System (GFS) model at 0.5 degree resolution. The SWAN directional resolution was 6 degrees (60 bins), determined via sensitivity analysis as the coarsest (and hence least computationally expensive) resolution that does not result in the "Garden-Sprinkler Effect" (GSE), wherein swell traveling over large distances inaccurately disintegrates into non-continuous wave fields as a result of frequency and directional discretization. The minimum frequency bin should be set to a value less than 0.7 times the lowest expected peak frequency and the maximum frequency bin should be set at least 2.5-3 times the highest expected peak frequency expected. In order to determine appropriate values, the peak periods from 43 NDBC buoys throughout the wave model domain were analyzed (when available) over the one year period of the study, yielding 297,533 hourly observations. The 99th and 1st percentiles of peak period were 15 s and 3 s, corresponding to frequencies of 0.07 Hz and 0.33 Hz, noting that these values may be biased by buoy limits of detection at high and low frequencies. The frequency range was therefore specified as 0.04-1 Hz. SWAN was allowed to internally determine the frequency resolution as one tenth of each frequency bin for best performance of the discrete interaction approximation (DIA) method of nonlinear 4-wave interactions, resulting in 34 frequency bins. Bottom friction calculations used the Madsen formulation with a uniform roughness length scale of 0.05 m. This value was selected for the best comparison of model output and buoy observations within the domain, and does not correspond to physical roughness values or the bottom roughness used in stress calculations. Wind generation and whitecapping parameterizations follow the modified Komen approach prescribed by Rogers et al. (2003), which reduces inaccurate attenuation of swell energy by whitecapping. Wave model outputs of bottom orbital velocity, bottom representative period, and bottom wave direction were output hourly and interpolated onto the ESPreSSO model grid.

    NDBC observations were used for model validation; ten full-spectra wave buoys are within the domain. Due to maintenance problems observations from all buoys were not available over the entire time period and data from Texas Tower Station 44066 for January 2011, when the buoy was adrift but still reporting, were manually removed. Using the GM method and the same bottom roughness of 0.005 m used to process model output, surface and bottom parameters were calculated from buoy spectra and compared to model output at the same locations. The same person that conducted this processing step conducted each subsequent processing step.

    References:

    Rogers, W.E., Hwang, P.A., Wang, D.W., 2003. Investigation of Wave Growth and Decay in the SWAN Model: Three Regional-Scale Applications. J. Phys. Oceanogr. 33, 366-389.

    Warner, J.C., Armstrong, B., He, R., Zambon, J.B., 2010. Development of a Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modeling System. Ocean Modelling 35, 230-244.

    Person who carried out this activity:

    P. Soupy Dalyander
    U.S. Geological Survey
    Oceanographer
    384 Woods Hole Road
    Woods Hole, MA 02543-1598
    USA

    (508) 548-8700 x2290 (voice)
    (508) 457-2310 (FAX)
    sdalyander@usgs.gov

    Data sources used in this process:
    • NOAA GFS
    • NOAA NAM
    • NOAA WW3

    Data sources produced in this process:

    • SWAN WEST ATL

    Date: 2011 (process 2 of 4)
    Use the wave model and current model results to calculate the time series of bottom shear stress within each model grid cell using Mathworks MATLAB software (v2011A). Bottom shear stress estimates are made following Grant-Madsen (GM) (Madsen, 1994), from the estimated bottom orbital velocities and bottom wave periods generated with SWAN, and near-bed current estimates from the ESPreSSO hydrodynamic model. The GM approach relies on an eddy viscosity turbulence closure model and formulates the wave stress, current stress, and combined wave-current bottom stress as functions of a representative bottom wave orbital velocity, representative bottom wave period, current flow at some reference height, the angle between wave and current propagation, and bottom roughness. Full details of the GM formulation may be found elsewhere (Glenn, 1983; Glenn and Grant, 1987; Grant and Madsen, 1979, 1982, 1986; Madsen, 1994; Madsen et al., 1988).

    Wave direction, bottom orbital velocities, and bottom periods are calculated internally by the wave model. Near-bed current magnitude and direction are taken from the hydrodynamic model, with the reference height taken as the distance from the cell vertical midpoint to the seabed. GM requires that the current velocity be taken above the wave boundary layer (WBL) but within the log-profile current velocity layer. If the thickness of the WBL calculated using GM exceeds of one or more of the deepest grid cells, the current estimate and associated reference height are used from the deepest grid cell at each location where the reference height exceeds the width of the WBL. An estimate must be used for the maximum reference height where the log-profile velocity layer assumption is valid. As discussed in Grant and Madsen (1986), the thickness of the log-profile layer based on laboratory experiments is approximately 10% of the current boundary layer thickness (Clauser, 1956). Because tidal currents, storm currents, and mean flow have a boundary layer thickness on the order of magnitude 10's of meters (Goud, 1987), a maximum value for reference height is set as 5 m. The GM bottom boundary layer model also requires a value for bottom roughness; a uniform value of 0.005 m is used throughout the domain.

    References:

    Madsen, O.S., 1994. Spectral wave-current bottom boundary layer flows, Proceedings 24th Conf. Coastal Eng., pp. 384-398.

    Glenn, S.M., 1983. A Continental Shelf Bottom Boundary Layer Model: The Effects of Waves, Currents, and a Moveable Bed. Dissertation, Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, Cambridge, MA, 237 pp.

    Glenn, S.M., Grant, W.D., 1987. A suspended sediment stratification correction for combined wave and current flows. J. Geophys. Res. 92, 8244-8264.

    Goud, M.R., 1987. Prediction of Continental Shelf Sediment Transport Using a Theoretical Model of the Wave-Current Boundary Layer. Dissertation, Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, Cambridge, MA, 211 pp.

    Grant, W.D., Madsen, O.S., 1986. The continental-shelf bottom boundary-layer. Annu. Rev. Fluid Mech. 18, 265-305.

    Grant, W.D., Madsen, O.S., 1982. Movable bed roughness in unsteady oscillatory flow. J. Geophys. Res. 87, 469-481.

    Grant, W.D., Madsen, O.S., 1979. Combined wave and current interaction with a rough bottom J. Geophys. Res. 84, 1797-1808.

    Madsen, O.S., 1994. Spectral wave-current bottom boundary layer flows, Proceedings 24th Conf. Coastal Eng., pp. 384-398.

    Madsen, O.S., Poon, Y., Graber, H.C., 1988. Spectral wave attenuation by bottom friction: theory, Proceedings 21st Int. Conf. Coast. Eng., pp. 492-504.

    Data sources used in this process:

    • SWAN WEST ATL
    • RU ESP

    Data sources produced in this process:

    • MAB STRESS TSERIES

    Date: 2011 (process 3 of 4)
    Calculate the half interpercentile range of bottom shear stress by year and season in Mathworks MATLAB software (v2011A). This value is calculated as half of the difference between the 16th and 84th percentiles of the time series within each grid cell, and would be equal to the standard deviation of the the observations followed a normal distribution. These statistical values are saved in MATLAB .mat format.

    Data sources used in this process:

    • MAB STRESS TSERIES

    Data sources produced in this process:

    • MAB HIPR STATISTIC

    Date: 2011 (process 4 of 4)
    Export the values for each grid cell from MATLAB format into an ArcGIS shapefile using the Mathworks MATLAB Mapping Toolbox (v2011A). Grid cells where the height of the deepest grid cell in the circulation model is always above the maximum accepted reference height for validity of a log-profile assumption (necessary for stress calculations) are excluded and not exported to Arc. In some cases, data may exist during parts of the year and not others; in this case, the statistic is calculated and included for the season where model output exist, and a missing data value of -9999 (replacing the MATLAB native NaN format) is used for seasons where no valid statistic can be calculated. A geographic data structure is created in MATLAB with the following fields: Geometry ('Polygon'), Lon (the five longitude points defining each grid cell, with one of the four grid corner values repeated to close the polygon in Arc), Lat (same as Lon, for the latitude points of the grid), Year (the statistic calculated for the entire year), Winter (the statistic calculated for December, January, and February), Spring (the statistic calculated for March, April, and May), Summer (the statistic calculated for June, July, and August), and Fall (the statistic calculated for September, October, and November). The shapefile is then written with the "shapewrite" command. Because MATLAB does not assign a projection, the projection corresponding to the projection associated with the bathymetry used in the numerical models is added in ArcCatalog 9.3. The file was then quality checked in ArcMap to insure values were properly exported to the shapefile from MATLAB.

    Data sources used in this process:

    • MAB HIPR STATISTIC

  3. What similar or related data should the user be aware of?

    U.S. Geological Survey, 2012, Documentation of the U.S. Geological Survey Sea Floor Stress and Sediment Mobility Database: Open-File Report 2012-1137, U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:


How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?

    Each attribute in this data layer covers a specific time period of interest. The attributes include winter (December - February), spring (March - May), summer (June - August), fall (September - November), and the entire year. Each of these attributes was calculated from model output spanning May, 2010 to May, 2011. Statistical values will vary somewhat if calculated from model parameters covering a different time period, or if a different numerical model is used to estimate the time-series of waves and circulation used in calculating the time-series of bottom shear stress.

  2. How accurate are the geographic locations?

    Numerical models are used in the generation of time-series of bottom shear stress used in creating this data layer. Because the overall horizontal accuracy of the data set depends on the accuracy of the model, the underlying bathymetry, and forcing values used, and so forth, the spatial accuracy of this data layer cannot be meaningfully quantified. These maps are intended to provide a qualitative and relative regional assessment of bottom shear stress at the approximately 5 km resolution displayed; users are advised not to use the data set to estimate shear stress quantitatively at any specific geographic location.

  3. How accurate are the heights or depths?

  4. Where are the gaps in the data? What is missing?

    All model output values were used in the calculation of this statistic. The statistic was calculated for the date range of May, 2010 to May, 2011, and would potentially vary somewhat if performed on a different time period. The underlying time-series of bottom shear stress was calculated from wave and current estimates generated with numerical models, and would vary if different models are used or if different model inputs (such as bathymetry or forcing winds) or parameterizations were chosen.

  5. How consistent are the relationships among the observations, including topology?

    No duplicate features are present. All polygons are closed, and all lines intersect where intended. No undershoots or overshoots are present.


How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Access_Constraints: None
Use_Constraints:
Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey as the originator of the dataset.

  1. Who distributes the data set? (Distributor 1 of 1)

    P. Soupy Dalyander
    U.S. Geological Survey
    Oceanographer
    384 Woods Hole Road
    Woods Hole, MA 02543-1598
    USA

    (508) 548-8700 x2290 (voice)
    (508) 457-2310 (FAX)
    sdalyander@usgs.gov

  2. What's the catalog number I need to order this data set?

    Downloadable Data: Sea Floor Stress and Sediment Mobility Database, half interpercentile range (half of the difference between the 16th and 84th percentiles, equal to the standard deviation for a normal distribution) of bottom shear stress for the Middle Atlantic Bight (MAB_hIPR)

  3. What legal disclaimers am I supposed to read?

    Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the USGS in the use of these data or related materials.

    Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

  4. How can I download or order the data?

  5. What hardware or software do I need in order to use the data set?

    These data are available in Environmental Systems Research Institute (ESRI) shapefile format. The user must have ArcGIS or ArcView 3.0 or greater software to read and process the data file. In lieu of ArcView or ArcGIS, the user may utilize another GIS application package capable of importing the data. A free data viewer, ArcExplorer, capable of displaying the data is available from ESRI at www.esri.com.


Who wrote the metadata?

Dates:
Last modified: 27-Jun-2012
Metadata author:
U.S. Geological Survey
c/o P. Soupy Dalyander
Oceanographer
384 Woods Hole Role
Woods Hole, MA 02543-1598
USA

(508) 548-8700 x2290 (voice)
(508) 457-2310 (FAX)
sdalyander@usgs.gov

Metadata standard:
FGDC Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)
Metadata extensions used:


Generated by mp version 2.8.25 on Wed Jun 27 13:10:22 2012