Subtropical Storm Alberto Assessment of Potential Coastal Change Impacts: NHC Advisory 8, 0800 AM EDT SUN MAY 27 2018

Metadata also available as - [Outline] - [Parseable text] - [XML]

Frequently anticipated questions:

What does this data set describe?

Title:
Subtropical Storm Alberto Assessment of Potential Coastal Change Impacts: NHC Advisory 8, 0800 AM EDT SUN MAY 27 2018
Abstract:
This dataset defines storm-induced coastal erosion hazards for the Louisiana, Mississippi, Alabama and Florida coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Subtropical Storm Alberto in May 2018. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the three types of coastal change: collision (dune erosion), overwash, and inundation. All hydrodynamic and morphologic variables are included in this dataset.
  1. How might this data set be cited?
    Birchler, Justin J., Doran, Kara S., Long, Joseph W., Schreppel, Heather A., and Stockdon, Hilary F., 20190619, Subtropical Storm Alberto Assessment of Potential Coastal Change Impacts: NHC Advisory 8, 0800 AM EDT SUN MAY 27 2018: U.S. Geological Survey Data Release doi:10.5066/P9Z362BC, U.S. Geological Survey, St. Petersburg, FL.

    Online Links:

    This is part of the following larger work.

    U.S. Geological Survey, 2019, USGS Coastal Change Hazards Portal.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -90.962989
    East_Bounding_Coordinate: -84.334191
    North_Bounding_Coordinate: 30.397062
    South_Bounding_Coordinate: 29.045053
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 27-May-2018
    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?
      This is a Vector data set. It contains the following vector data types (SDTS terminology):
      • String (883)
    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 8.9831528411952133e-009. Longitudes are given to the nearest 8.9831528411952133e-009. 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 6378137.0.
      The flattening of the ellipsoid used is 1/298.257223563.
  7. How does the data set describe geographic features?
    Alberto_PCOI_line
    Probabilities of hurricane-induced coastal erosion, dune morphology, and hurricane hydrodynamic data (Source: USGS)
    FID
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Coordinates defining the features.
    DHIGH
    Elevation of dune crest, in meters, using the North American Vertical Datum of 1988 (NAVD88). Extracted from lidar surveys collected from February 2009 to October 2016. (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0.809263
    Maximum:8.993615
    Units:meters NAVD88
    DLOW
    Elevation of the dune toe, in meters NAVD88. Extracted from lidar surveys collected February 2009 to October 2016. (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0.673475
    Maximum:4.341412
    Units:meters NAVD88
    DHIrms
    Root mean squared error of dune crest elevation measurements (square meters). (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0.109599
    Maximum:1.718375
    Units:square meters
    DLOrms
    Root mean square error of dune toe elevation measurements (square meters). (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0
    Maximum:1.115019
    Units:square meters
    SURGE
    Storm surge water level (Source: NOAA)
    Range of values
    Minimum:0
    Maximum:1.227408
    Units:meters NAVD88
    RUNUP
    Wave runup water level (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0.316245
    Maximum:2.026379
    Units:meters NAVD88
    SETUP
    Wave setup water level (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0.007964
    Maximum:0.7767766
    Units:meters NAVD88
    PCOL
    Probability of collision (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0.016232
    Maximum:95.07805
    Units:percent
    POVW
    Probability of overwash (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0
    Maximum:96.611361
    Units:percent
    PIND
    Probability of inundation (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0
    Maximum:76.756885
    Units:percent
    MEAN
    Mean water level (surge + setup) (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0.404473
    Maximum:1.807431
    Units:meters NAVD88
    EXTREME
    Extreme water level (surge + runup). (Source: USGS)
    ValueDefinition
    -999Null value
    Range of values
    Minimum:0.748464
    Maximum:3.028131
    Units:meters NAVD88
    TIDE
    Predicted tide water level (Source: USGS)
    Range of values
    Minimum:0
    Maximum:0
    Units:meters NAVD88

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Justin J. Birchler
    • Kara S. Doran
    • Joseph W. Long
    • Heather A. Schreppel
    • Hilary F. Stockdon
  2. Who also contributed to the data set?
    The predicted elevations of storm surge were extracted from the National Oceanic and Atmospheric Administration’s (NOAA) Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model, which has been employed by NOAA in inundation risk studies and operational storm surge forecasting. Wave runup and setup conditions were generated using NOAA's WaveWatch III model.
  3. To whom should users address questions about the data?
    U.S. Geological Survey
    Attn: Hilary Stockdon
    600 4th Street South
    Saint Petersburg, FL
    UNITED STATES

    727-502-8074 (voice)
    727-502-8182 (FAX)
    hstockdon@usgs.gov

Why was the data set created?

To provide data on the probability of storm-induced coastal erosion hazards for the Louisiana, Mississippi, Alabama and Florida coast post-Subtropical Storm Alberto.

How was the data set created?

  1. From what previous works were the data drawn?
    ESTOFS (source 1 of 8)
    National Weather Service, National Oceanic and Atmospheric Administration, 20180527, Extratropical Surge and Tide Operational Forecast System.

    Online Links:

    Type_of_Source_Media: Online digital data
    Source_Contribution: Data provides anticipated water levels during the next 4 days.
    WW3 (source 2 of 8)
    NOAA National Weather Service Environmental Modeling Center, 20180527, NOAA Wavewatch III.

    Online Links:

    Type_of_Source_Media: Online digital data
    Source_Contribution:
    Model that was used to estimate wave setup and runup conditions for Subtropical Storm Alberto.
    JALBTCX TX/LA 2009 (source 3 of 8)
    Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM), Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX), 20160523, 2009 US Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center for Expertise (JALBTCX) Topographic Lidar: Post Hurricane Gustav and Post Hurricane Ike.

    Online Links:

    Other_Citation_Details: Geographic Coverage: TX, mainland LA
    Type_of_Source_Media: Online digital data
    Source_Contribution:
    A lidar survey that was used to estimate dune morphology variables.
    DS 839 LA 2012 (source 4 of 8)
    Guy, K.K., 20140602, Topographic Lidar Survey of the Alabama, Mississippi, and Southeast Louisiana Barrier Islands, from September 5 to October 11, 2012: U.S. Geological Survey Data Series 839.

    Online Links:

    Other_Citation_Details: Geographic Coverage: LA, MS
    Type_of_Source_Media: Online digital data
    Source_Contribution:
    A lidar survey that was used to estimate dune morphology variables.
    DS 838 LA 2013 (source 5 of 8)
    Guy, K.K., 20140602, Topographic Lidar Survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013: U.S. Geological Survey Data Series 838.

    Online Links:

    Other_Citation_Details: Geographic Coverage: Chandeleur Islands, LA
    Type_of_Source_Media: Online digital data
    Source_Contribution:
    A lidar survey that was used to estimate dune morphology variables.
    USGS MS 2015 (source 6 of 8)
    U.S. Geological Survey, 20161018, USGS Lidar Point Cloud LA SoTerrebonne-GI 2015.

    Online Links:

    Other_Citation_Details: Geographic Coverage: Mississippi Barrier Islands
    Type_of_Source_Media: Online digital data
    Source_Contribution:
    A lidar survey that was used to estimate dune morphology variables.
    USACE AL 2016 (source 7 of 8)
    United States Army Corps of Engineers (USACE), 20180514, 2016 USACE NCMP Topobathy Lidar: Gulf Coast (AL, FL, MS, TX).

    Online Links:

    Other_Citation_Details: Geographic Coverage: Alabama
    Type_of_Source_Media: Online digital data
    Source_Contribution:
    A lidar survey that was used to estimate dune morphology variables.
    USACE FL 2010 (source 8 of 8)
    United States Army Corps of Engineers (USACE), 20150508, 2010 US Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) Topobathy Lidar: Alabama Coast and Florida Gulf Coast.

    Online Links:

    Other_Citation_Details:
    Geographic Coverage: AL (Fort Morgan to AL/FL border), FL (AL/FL border to Bald Point State Park)
    Type_of_Source_Media: Online digital data
    Source_Contribution:
    A lidar survey that was used to estimate dune morphology variables.
  2. How were the data generated, processed, and modified?
    Date: 2018 (process 1 of 4)
    Process_Description: For dune morphology data: Elevation data from lidar surveys were interpolated in MATLAB (version 2017a) to a gridded domain that was rotated parallel to the shoreline and had a resolution of 10 m in the longshore direction and 2.5 m in the cross-shore direction. The interpolation method applied spatial filtering with a Hanning window that was twice as wide as the grid resolution. Dune morphology data were extracted from the elevation grid in MATLAB. Dune morphology data were then summarized to 1 km sections. Sections with greater than 75 percent of data missing were flagged with the invalid number of -999. The 1-km smoothed dune crest (DHIGH), toe (DLOW) and root mean square (RMS) error for each (DHIrms and DLOrms) were written to line shapefiles using MATLAB's shapewrite.m script. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Justin J. Birchler
    600 4th Street South
    Saint Petersburg, FL
    UNITED STATES

    727-502-8019 (voice)
    727-502-8182 (FAX)
    jbirchler@usgs.gov
    Data sources used in this process:
    • JALBTCX TX/LA 2009
    • DS 839 LA 2012
    • DS 838 LA 2013
    • USGS MS 2015
    • USACE AL 2016
    • USACE FL PH 2010
    Data sources produced in this process:
    • Dune morphology (DHIGH, DLOW, DHIrms, DLOrms)
    Date: 27-May-2018 (process 2 of 4)
    For hydrodynamic data: Water level was computed in MATLAB by adding storm surge from NOAA’s Probabilistic Tropical Storm Surge (P- Surge) model (https://slosh.nws.noaa.gov/psurge2.0/) to wave setup and runup. The wave height and period used for calculating wave runup and setup came from the Wavewatch III model. Hydrodynamic parameters were calculated in MATLAB and exported into ArcGIS shapefile format. For details on modeling parameterization, see: Stockdon, H.F., Doran, K.J., Thompson, D.M., Sopkin, K.L., Plant, N.G., and Sallenger, A.H., 2012, National assessment of hurricane-induced coastal erosion hazards: Gulf of Mexico: U.S. Geological Survey Open-File Report 2012-1084, 51 p. https://doi.org/10.3133/ofr20121084 Person who carried out this activity:
    U.S. Geological Survey
    Attn: Justin J. Birchler
    600 4th Street South
    Saint Petersburg, FL
    UNITED STATES

    727-502-8019 (voice)
    727-502-8182 (FAX)
    jbirchler@usgs.gov
    Data sources used in this process:
    • ESTOFS
    • WW3
    Data sources produced in this process:
    • Hydrodynamics (SURGE, SETUP, RUNUP)
    Date: 27-May-2018 (process 3 of 4)
    Probabilities of coastal erosion hazards were based on estimating the likelihood that the beach system would experience erosion and deposition patterns consistent with collision (PCOL), overwash (POVW), or inundation (PIND) regimes. The regimes were calculated by using values of dune morphology and mean and extreme water levels for each 1 km section, such that the probability of collision (PCOL) occurs when extreme water levels reach the dune toe; overwash (POVW) when extreme water levels reach the dune crest; and inundation (PIND) when mean water levels reach the dune crest. Probabilities were calculated in MATLAB and exported using MATLAB's shapewrite.m script. For details on modeling parameterization, see: Stockdon, H.F., Doran, K.J., Thompson, D.M., Sopkin, K.L., Plant, N.G., and Sallenger, A.H., 2012, National assessment of hurricane-induced coastal erosion hazards: Gulf of Mexico: U.S. Geological Survey Open-File Report 2012-1084, 51 p. . https://doi.org/10.3133/ofr20121084 Person who carried out this activity:
    U.S. Geological Survey
    Attn: Justin J. Birchler
    600 4th Street South
    Saint Petersburg, FL
    UNITED STATES

    727-502-8019 (voice)
    727-502-8182 (FAX)
    jbirchler@usgs.gov
    Data sources used in this process:
    • Dune morphology
    • Hydrodynamics
    Data sources produced in this process:
    • Probabilities (PCOL, POVW, PIND)
    Date: 13-Oct-2020 (process 4 of 4)
    Added keywords section with USGS persistent identifier as theme keyword. Person who carried out this activity:
    U.S. Geological Survey
    Attn: VeeAnn A. Cross
    Marine Geologist
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 x2251 (voice)
    508-457-2310 (FAX)
    vatnipp@usgs.gov
  3. What similar or related data should the user be aware of?

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

  1. How well have the observations been checked?
  2. How accurate are the geographic locations?
    Horizontal accuracy was not estimated.
  3. How accurate are the heights or depths?
    Vertical accuracy for hydrodynamic measurements (surge, setup, and runup) is dependent on input data. SLOSH model accuracy is estimated to be +/- 20 percent of the calculated value. No other accuracy checks were performed. Vertical accuracy for dune morphology (dune crest and toe elevation) data is dependent on the positional accuracy of the lidar data. Estimated accuracy of lidar surveys are +/- 15 centimeters. However, vertical accuracies may vary based on the type of terrain (for example, inaccuracies may increase as slope increases or with the presence of extremely dense vegetation), the accuracy of the global positioning system (GPS), and aircraft-attitude measurements.
  4. Where are the gaps in the data? What is missing?
    This dataset includes dune morphology and hurricane hydrodynamic data used to generate probabilities of hurricane-induced erosion, elevation data from lidar surveys are not included. Measurements were collected approximately every 10 meters (m) and summarized to 1-kilometer (km) segments.
  5. How consistent are the relationships among the observations, including topology?
    No additional checks for consistency were performed on this data.

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. The U.S. Geological Survey requests to be acknowledged as originators of the data in future products or derivative research.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey
    Attn: Justin J. Birchler
    600 4th Street South
    Saint Petersburg, FL

    727-502-8019 (voice)
    727-502-8182 (FAX)
    jbirchler@usgs.gov
  2. What's the catalog number I need to order this data set?
  3. What legal disclaimers am I supposed to read?
    Although these data have been processed successfully on a computer system at the USGS, no warranty expressed or implied is made regarding the display or utility of the data on any other system, or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. The USGS shall not be held liable for improper or incorrect use of the data described and/or contained herein. Any use of trade, firm, or product 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?

Who wrote the metadata?

Dates:
Last modified: 13-Oct-2020
Metadata author:
U.S. Geological Survey
Attn: Justin J. Birchler
600 4th Street South
Saint Petersburg, FL
UNITED STATES

727-502-8019 (voice)
727-502-8182 (FAX)
jbirchler@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/spcmsc/Alberto_PCOI_line_metadata.faq.html>
Generated by mp version 2.9.50 on Tue Sep 21 18:18:32 2021