Northern California 3.2 projections of coastal cliff retreat due to 21st century sea-level

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Frequently anticipated questions:

What does this data set describe?

Title:
Northern California 3.2 projections of coastal cliff retreat due to 21st century sea-level
Abstract:
This dataset contains projections of coastal cliff retreat and associated uncertainty across Northern California for future scenarios of sea-level rise (SLR) to include 25, 50, 75, 100, 125, 150, 175, 200, 250, 300, and 500 centimeters (cm) of SLR by the year 2100 and cover coastline from the Golden Gate Bridge to the California-Oregon state border. Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical models and field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power, as part of Coastal Storm Modeling System (CoSMoS). See cited references and methods for more detail.
Supplemental_Information:
This work is one portion of ongoing modeling efforts for California and the western United States. For more information on CoSMoS implementation, see https://walrus.wr.usgs.gov/coastal_processes/cosmos/. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  1. How might this data set be cited?
    Limber, Patrick W., Barnard, Patrick L., O'Neill, Andrea C., and Foxgrover, Amy C., 20221205, Northern California 3.2 projections of coastal cliff retreat due to 21st century sea-level: data release DOI:10.5066/P9048D1S, U.S. Geological Survey, Pacific Coastal and Marine Science Center Santa Cruz, California.

    Online Links:

    This is part of the following larger work.

    Barnard, Patrick L., Erikson, Li H., Foxgrover, Amy C., Limber, Patrick W., O'Neill, Andrea C., Thomas, Jennifer A., and Vitousek, Sean F., 2022, Coastal Storm Modeling System (CoSMoS) for northern California 3.2: data release DOI:10.5066/P9048D1S, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -124.4448
    East_Bounding_Coordinate: -122.4774
    North_Bounding_Coordinate: 41.9985
    South_Bounding_Coordinate: 37.8921
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2022
    Currentness_Reference:
    year of publication
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: Coastal cliff retreat projections in shapefiles
  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):
      • GT-polygon composed of chains (28000)
    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 0.001. Longitudes are given to the nearest 0.001. Latitude and longitude values are specified in Decimal degrees. The horizontal datum used is World Geodetic System 1984 (WGS84).
      The ellipsoid used is WGS84.
      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?
    Northern California projections of cliff retreat for 21st century (2021-2100) due to sea-level rise
    Shapefiles consist of cliff retreat projections (Cliff_ProjectionLines) caused by wave impacts in different named sea-level rise (SLR) scenarios and different management options. Model case or management-case options illustrate projected retreat at impeded locations with existing armoring (HoldTheLine), or showing unimpeded retreat (LetItGo). Positions for SLRs of 25, 50, 75, 92, 100, 125, 150, 175, 200, 250, 300, and 500 cm are included. (Source: originators at United States Geological Survey, Pacific Coastal and Marine Science Center)
    SLR_cm
    amount of sea-level rise (SLR) for projected cliff retreat (25 cm or greater) (Source: producer defined)
    Range of values
    Minimum:25
    Maximum:500
    Units:cm
    Resolution:25
    Northern California cliff retreat uncertainty
    Shapefiles consists of uncertainty range polygons (Cliff_Uncertainty) for corresponding projections of cliff retreat caused by wave impacts in different named sea-level rise (SLR) scenarios and different management options. Model case or management-case options illustrate projected retreat at impeded locations with existing armoring (HoldTheLine), or showing unimpeded retreat (LetItGo). Positions for SLRs of 25, 50, 75, 92, 100, 125, 150, 175, 200, 250, 300, and 500 cm are included. (Source: originators at United States Geological Survey, Pacific Coastal and Marine Science Center)
    SLR_cm
    amount of SLR for given cliff retreat uncertainty (25 cm or greater) (Source: producer defined)
    Range of values
    Minimum:25
    Maximum:500
    Units:cm
    Resolution:25
    Northern California cliff baseline positions
    Shapefile consists of points showing baseline cliff positions (Cliff_0SLR_Baseline_pts) for model transects (Source: originators at United States Geological Survey, Pacific Coastal and Marine Science Center)
    Ln_ID
    transect ID number for each model output location (Source: producer defined)
    Range of values
    Minimum:8071
    Maximum:11589
    Units:NA
    Resolution:1
    SLR_cm
    SLR for baseline points, 0 cm (Source: producer defined)
    Range of values
    Minimum:0
    Maximum:0
    Units:cm
    Resolution:25
    Entity_and_Attribute_Overview:
    Projections of coastal cliff retreat for 21st century sea-level rise. The shapefiles files consist of shoreline positions changes (displayed as lines, with vertices at defined transects) caused by wave impacts in different named sea-level rise scenarios and model case/management options. Baseline cliff locations (points at each transect, for SLR 0 cm) are included for comparison. Projection files include uncertainty bands as a polygon around each projection line.
    Entity_and_Attribute_Detail_Citation:
    Cliff retreat projections and uncertainty are generated and shown at transects (spaced approximately 100m-300m apart alongshore, identified in whole numbers) for Northern California.

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Patrick W. Limber
    • Patrick L. Barnard
    • Andrea C. O'Neill
    • Amy C. Foxgrover
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    Attn: PCMSC Science Data Coordinator
    2885 Mission Street
    Santa Cruz, California
    USA

    831-427-4747 (voice)
    pcmsc_data@usgs.gov

Why was the data set created?

These data provide an estimate of potential coastal cliff retreat and erosion in response to sea-level rise during the 21st century, to help identify and assess possible areas of vulnerability. Uncertainty should be included in any assessment or analysis. Data are intended for policy makers, resource managers, science researchers, and students. These data can be used with geographic information systems or other software to help identify and assess possible areas of vulnerability. These data are not intended to be used for navigation.

How was the data set created?

  1. From what previous works were the data drawn?
    Lidar (source 1 of 7)
    U.S. Geological Survey, 2017, 2016 USGS west coast lidar DEM (WA, OR, CA): NOAA Digital Coast, online.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    A continuous sea cliff edge was digitized from the 2002, 2010, and 2016 lidar DEM. The cliff edge was then used 1) to calculate long-term cliff retreat rates and 2) as the baseline from which future projections of cliff retreat were made.
    TSHEET (source 2 of 7)
    Hapke, C., Reid, D., and Borelli, M., 2007, The National Assessment of Shoreline Change; a GIS compilation of vector cliff edges and associated cliff erosion data for the California coast: U.S. Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    Cliff edges were used to calculate historical long-term rates of cliff retreat
    DEM (source 3 of 7)
    U.S. Geological Survey, 2020, Coastal National Elevation Database (CoNED) Project - Topobathymetric Digital Elevation Model (TBDEM) for Northern California: U.S. Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    Topobathymetric Digital Elevation Model (TBDEM) for Northern California
    Armor database (source 4 of 7)
    Commission, California Coastal, 2005, California Coastal Armoring Database: California Coastal Commission, online.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution: Database of coastal armoring locations across California
    aerial imagery (source 5 of 7)
    Earth, Google, 2021, Aerial imagery for Northern California: Google Earth, online.

    Online Links:

    Type_of_Source_Media: online viewer
    Source_Contribution: Recent aerial imagery to verify armoring locations
    CSTs (source 6 of 7)
    Foxgrover, A.C., Erikson, L.H., and O'Neill, A.C., 2022, Northern California cross-shore transects for CoSMoS 3.2: U.S. Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online dataset
    Source_Contribution:
    cross-short transects (CSTs) used throughout study region for model setup locations
    nearshore wave forcing (source 7 of 7)
    O'Neill, A.C., Erikson, L.H., and Barnard, P.L., 2022, Nearshore total water level (TWL) proxies (2018-2100) for Northern California: U.S. Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online dataset
    Source_Contribution: time series of nearshore wave impacts for projections
  2. How were the data generated, processed, and modified?
    Date: 01-Nov-2020 (process 1 of 5)
    All process steps match those outlined in Limber and others (2018); specific details for implementation in Northern California are included here. Historical sea cliff retreat rates were established using cliff edge positions from TSHEETS and Lidar datasets. In areas where sufficient data were present, all cliff edge data were used to calculate a linear regression rate. Where linear regression was not possible, end-point rates between TSHEET and the most recent lidar were used. In locations without reliable TSHEET data, end-point rates were determined between lidar datasets. Finally, for locations where no cliff edge data were available, rates from nearby transects or the nearest location with similar lithology were spatially averaged and assigned. In addition to the paucity of available data for many transects, the active cliff edge was obscured by vegetation or topographically indistinct in many locations, leading to generally higher uncertainty of cliff-top locations throughout the region. Data sources used in this process:
    • TSHEETS
    • Lidar
    • CSTs
    Data sources produced in this process:
    • Historical rates
    Date: 05-Apr-2021 (process 2 of 5)
    Extracted cross-shore profiles, cliff toe elevations, and beach slopes from Lidar and DEM data. Verified armoring locations with current imagery. Data sources used in this process:
    • Lidar
    • DEM
    • Armoring database
    • aerial imagery
    Data sources produced in this process:
    • cliff profile information
    Date: 30-Aug-2021 (process 3 of 5)
    Ran multi-model ensemble with nearshore wave forcing and various SLR scenarios to project future cliff positions. As described by Limber and others (2018), four ensemble members were used (Hackney, Trenhaile version 1, Trenhaile version 2, TWL models; see manuscript for more details); the Bruun model was not included for this region. Historical retreat rates, cliff toe elevation, beach slopes, and cliff height discussed above were used as inputs to the model ensemble. In much of Northern California, due to the limitations in existing data ensemble projections showed more spread compared to other locations with more observations; therefore, the weighted average used in much of Northern California was more tolerant of spread from individual ensemble members to provide better projection consistency. At headland and peninsula locations with significant projected retreat, projection lines may cross over each other. As this model does not make any assumption or statement on effectiveness of armoring or other structures, it was run in two scenarios providing end-member cases: 1) imposing projection limits where armoring features exist ("Hold the Line") and 2) letting projections proceed past armoring features ("Let it go"). Data sources used in this process:
    • Historical rates
    • cliff profile information
    • nearshore wave forcing
    Data sources produced in this process:
    • model output
    Date: 15-Aug-2022 (process 4 of 5)
    As described in Limber and others (2018), model output and uncertainty were mapped. Visual and statistical QA/QC was performed to identify and correct data that did not meet quality control standards. Data was packaged for dissemination. Baseline cliff points used in the analysis are included for comparison (Cliff_0SLR_Baseline_pts). Projections of cliff retreat for given SLR (Cliff_ProjectionLines) and associated uncertainty (Cliff_Uncertainty) are available for both model cases (limiting projections in locations of existing coastal armoring/"Hold the Line", and letting projection proceed unhindered by armoring/"Let it Go"). All output files are zipped together. Data sources used in this process:
    • model output
    Date: 09-Feb-2023 (process 5 of 5)
    Internal USGS PID registered with PIR tool and updated the metdate for harvesting purposes. No data or metadata were changed. (scochran@usgs.gov)
  3. What similar or related data should the user be aware of?
    Limber, P.W., Barnard, P.L., Vitousek, S., and Erikson, L.H., 2018, A model ensemble for projecting multi-decadal coastal cliff retreat during the 21st century.

    Online Links:

    Other_Citation_Details:
    Limber, P.W., Barnard, P.L., Vitousek, S., and Erikson, L.H, 2018, A model ensemble for projecting multi-decadal coastal cliff retreat during the 21st century: Journal of Geophysical Research--Earth Surface, v. 123, p.1566-1589, https://doi.org/10.1029/2017JF004401.

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

  1. How well have the observations been checked?
    Attribute values are estimates of cliff retreat and uncertainty due to plausible future sea-level rise scenarios in the future and therefore cannot be cross-checked with observations, because observations do not exist. The projections were generated using established numerical methods and are in line with previous work by researchers. While the latest cliff edge data was used in the modeling, the general lack of extensive historical data and difficulty in identifying active cliff edges in many locations (for example, obscured by vegetation, or topographic slope showing no inflection) led to high uncertainty in some areas. Uncertainty bands derived from the ensemble numerical models take into account the positional accuracy of the geospatial data used to calibrate the numerical models, statistical agreement between different models used to generate the projections, and variations of the projections caused by varying initial conditions (a sensitivity analysis). Including uncertainty is recommended for use in any analysis.
  2. How accurate are the geographic locations?
    A formal accuracy assessment of the projections was conducted for each model output location. The horizontal model accuracy (or uncertainty) for each model output point is included within this geospatial dataset and was determined at the 95 percent confidence level.
  3. How accurate are the heights or depths?
    N/A
  4. Where are the gaps in the data? What is missing?
    These geospatial projections are complete. Users are advised to read the rest of the metadata record and references carefully for additional details.
  5. How consistent are the relationships among the observations, including topology?
    Data have undergone QA/QC and fall within expected/reasonable ranges.

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 USGS-authored or produced data and information are in the public domain from the U.S. Government and are freely redistributable with proper metadata and source attribution. Please recognize and acknowledge the U.S. Geological Survey as the originator(s) of the dataset and in products derived from these data.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - ScienceBase
    Denver Federal Center, Building 810, Mail Stop 302
    Denver, CO
    USA

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? These data are available in shapefile formats, packaged in one zip file.
  3. What legal disclaimers am I supposed to read?
    Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (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. 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?

Who wrote the metadata?

Dates:
Last modified: 09-Feb-2023
Metadata author:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Attn: PCMSC Science Data Coordinator
2885 Mission Street
Santa Cruz, California
USA

831-427-4747 (voice)
pcmsc_data@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/pcmsc/DataReleases/ScienceBase/DR_P9048D1S/Coastal_Cliff_Retreat_Projections_NorCal_CoSMoS_3-2_metadata.faq.html>
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