Metadata: Identification_Information: Citation: Citation_Information: Originator: Sean Vitousek Originator: Kilian Vos Originator: Patrick L. Barnard Originator: Andrea C. O’Neill Originator: Amy C. Foxgrover Originator: Maya K. Hayden Publication_Date: 20230315 Title: Projections of shoreline change of current and future (2005-2100) sea-level rise scenarios for the U.S. Atlantic Coast Geospatial_Data_Presentation_Form: Shoreline change projections in Google Earth KMZ formats Series_Information: Series_Name: data release Issue_Identification: DOI:10.5066/10.5066/P9BQQTCI Publication_Information: Publication_Place: Pacific Coastal and Marine Science Center, Santa Cruz, CA Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.5066/P9BQQTCI Larger_Work_Citation: Citation_Information: Originator: Patrick L. Barnard Originator: Kevin M. Befus Originator: Jeffrey J. Danielson Originator: Anita C. Engelstad Originator: Li H. Erikson Originator: Amy C. Foxgrover Originator: Maya K. Hayden Originator: Daniel J. Hoover Originator: Tim Leijnse Originator: Chris Massey Originator: Robert McCall Originator: Norberto C. Nadal-Caraballo Originator: Kees M. Nederhoff Originator: Leonard Ohenhen Originator: Andrea C. O’Neill Originator: Kai A. Parker Originator: Manoocher Shirzaei Originator: Xin Su Originator: Jennifer A. Thomas Originator: Maarten van Ormondt Originator: Sean F. Vitousek Originator: Kilian Vos Originator: Madison C. Yawn Publication_Date: 2023 Title: Future coastal hazards along the U.S. Atlantic coast Series_Information: Series_Name: data release Issue_Identification: DOI:10.5066/P9BQQTCI Publication_Information: Publication_Place: Pacific Coastal and Marine Science Center, Santa Cruz, CA Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.5066/P9BQQTCI Description: Abstract: This dataset contains projections of shoreline change and uncertainty bands for future scenarios of sea-level rise (SLR). Scenarios include 25, 50, 75, 100, 150, 200, and 300 centimeters (cm) of SLR by the year 2100. Output for SLR of 0 cm is also included, reflective of conditions in 2005, in accordance with recent SLR projections and guidance from the National Oceanic and Atmospheric Administration (NOAA; see process steps).Projections were made using the Coastal Storm Modeling System - Coastal One-line Assimilated Simulation Tool (CoSMoS-COAST), a numerical model (described in Vitousek and others, 2017; 2021; 2023) run in an ensemble forced with global-to-local nested wave models and assimilated with satellite-derived shoreline (SDS) observations. Shoreline positions from models are generated at pre-determined cross-shore transects and output includes different cases covering important model behaviors (cases are described in process steps of metadata; see citations listed in the Cross References section for more details on the methodology and supporting information). This model shows change in shoreline positions along transects, considering sea level, wave conditions, along-shore/cross-shore sediment transport, long-term trends due to sediment supply, and estimated variability due to unresolved processes (as described in Vitousek and others, 2021). Variability associated with complex coastal processes (for example, beach cusps/undulations and shore-attached sandbars) are included via a noise parameter in a model, which is tuned using observations of shoreline change at each transect and run in an ensemble of 200 simulations; this approach allows for a representation of statistical variability in a model that is assimilated with sequences of noisy observations. The model synthesizes and improves upon numerous, well-established shoreline models in the scientific literature; processes and methods are described in this metadata (see lineage and process steps), but also described in more detail in Vitousek and others 2017, 2021, and 2023. KMZ data are readily viewable in Google Earth. For best display of results, it is recommended to turn off any 3D features or terrain. For technical users and researchers, shapefile and KMZ data can be ingested into geographic information system (GIS) software such as Global Mapper or QGIS. Purpose: These data provide an estimate of potential shoreline change in response to SLR 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. Supplemental_Information: This data release was funded by the Coastal and Marine Hazards and Resources Program. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Time_Period_of_Content: Time_Period_Information: Single_Date/Time: Calendar_Date: 2023 Currentness_Reference: Year of publication Status: Progress: Complete Maintenance_and_Update_Frequency: As needed Spatial_Domain: Bounding_Coordinates: West_Bounding_Coordinate: -82.11192 East_Bounding_Coordinate: -75.32334 North_Bounding_Coordinate: 38.81563 South_Bounding_Coordinate: 26.06347 Keywords: Theme: Theme_Keyword_Thesaurus: USGS Metadata Identifier Theme_Keyword: USGS:305615c0-6d9d-46b4-95ed-e33be824aba9 Theme: Theme_Keyword_Thesaurus: Global Change Master Directory Theme_Keyword: Hazards Planning Theme_Keyword: Ocean Waves Theme_Keyword: Erosion Theme_Keyword: Sea Level Rise Theme_Keyword: Extreme Weather Theme: Theme_Keyword_Thesaurus: ISO 19115 Topic Category Theme_Keyword: Oceans Theme_Keyword: ClimatologyMeteorologyAtmosphere Theme: Theme_Keyword_Thesaurus: Data Categories for Marine Planning Theme_Keyword: Physical Habitats and Geomorphology Theme: Theme_Keyword_Thesaurus: USGS Thesaurus Theme_Keyword: Climate Change Theme_Keyword: Storms Theme_Keyword: Sea-level Change Theme: Theme_Keyword_Thesaurus: Marine Realms Information Bank (MRIB) keywords Theme_Keyword: sea level change Theme_Keyword: waves Theme_Keyword: coastal erosion Theme: Theme_Keyword_Thesaurus: None Theme_Keyword: U.S. Geological Survey Theme_Keyword: USGS Theme_Keyword: Coastal and Marine Hazards and Resources Program Theme_Keyword: CMHRP Theme_Keyword: Pacific Coastal and Marine Science Center Theme_Keyword: PCMSC Place: Place_Keyword_Thesaurus: Geographic Names Information System (GNIS) Place_Keyword: State of Florida Place_Keyword: State of Georgia Place_Keyword: State of Virginia Place_Keyword: State of Maryland Place_Keyword: State of Delaware 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. Point_of_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey, Pacific Coastal and Marine Science Center Contact_Person: PCMSC Science Data Coordinator Contact_Address: Address_Type: mailing and physical Address: 2885 Mission Street City: Santa Cruz State_or_Province: CA Postal_Code: 95060 Contact_Voice_Telephone: 831-427-4747 Contact_Electronic_Mail_Address: pcmsc_data@usgs.gov Browse_Graphic: Browse_Graphic_File_Name: Shorelineprojections_US_Atlantic.png Browse_Graphic_File_Description: Image map showing study area for shoreline change projections. Browse_Graphic_File_Type: PNG Native_Data_Set_Environment: The datasets were created in a Windows 11 Operating system, using Matlab v2020 and python 3.7. Results were output and saved as KMZs. Cross_Reference: Citation_Information: Originator: Vitousek, S. Originator: Barnard, P.L. Originator: Limber, P. W. Originator: Erikson, L. H. Originator: Cole, B. Publication_Date: 2017 Title: A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change. Other_Citation_Details: Vitousek, S., Barnard, P.L., Limber, P., Erikson, L.H., and Cole, B., 2017, A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change: Journal of Geophysical Research--Earth Surface, v. 122, p. 782-806. Online_Linkage: https://doi.org/10.1002/2016JF004065 Cross_Reference: Citation_Information: Originator: Vitousek, S. Originator: Cagigal, L. Originator: Montaño, J. Originator: Rueda, A. Originator: Mendez, F. Originator: Coco, G. Originator: Barnard, P.L. Publication_Date: 2021 Title: The application of ensemble wave forcing to quantify uncertainty of shoreline change predictions Other_Citation_Details: Vitousek, S., Cagigal, L., Montaño, J., Rueda, A., Mendez, F., Coco, G., and Barnard, P.L., 2021, The application of ensemble wave forcing to quantify uncertainty of shoreline change predictions: Journal of Geophysical Research: Earth Surface, v. 126(7), e2019JF005506. Online_Linkage: https://doi.org/10.1029/2019JF005506 Cross_Reference: Citation_Information: Originator: Vitousek, S. Originator: Vos, K.D. Originator: Splinter, K.D. Originator: Erikson, L.H. Originator: Barnard, P.L. Publication_Date: 2023 Title: A model integrating satellite-derived shoreline observations for predicting fine-scale shoreline response to waves and sea-level rise across large coastal regions Other_Citation_Details: Vitousek, S., Vos, K., Splinter, K.D., Erikson, L. and Barnard, P.L., 2023, A model integrating satellite-derived shoreline observations for predicting fine-resolution shoreline response to waves and sea-level rise applied across large coastal regions: Journal of Geophysical Research: Earth Surface, v. 128(7), e2022JF006936. Online_Linkage: https://doi.org/10.1029/2022JF006936 Cross_Reference: Citation_Information: Originator: Vos, K. Originator: Harley, M.D. Originator: Splinter, K.D. Originator: Simmons, J.A. Originator: Turner, I.L. Publication_Date: 2019 Title: Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery. Other_Citation_Details: Vos, K., Harley, M.D., Splinter, K.D., Simmons, J.A., and Turner, I.L., 2019a, Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery; Coastal Engineering, v. 150, p. 160-174. Cross_Reference: Citation_Information: Originator: Vos, K. Originator: Splinter, K.D. Originator: Harley, M.D. Originator: Simmons, J.A. Originator: Turner, I.L. Publication_Date: 2019 Title: CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery. Other_Citation_Details: Vos, K., Splinter, K.D., Harley, M.D., Simmons, J.A., and Turner, I.L., 2019b, CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery: Environmental Modelling and Software, v. 122, 104528. Cross_Reference: Citation_Information: Originator: Vos, K. Originator: Harley, M.D. Originator: Splinter, K.D. Originator: Walker, A. Originator: Turner, I.L. Publication_Date: 2020 Title: Beach slopes from satellite‐derived shorelines. Other_Citation_Details: Vos, K., Harley, M. D., Splinter, K. D., Walker, A., and Turner, I. L, 2020, Beach slopes from satellite‐derived shorelines: Geophysical Research Letters, v. 47(14), e2020GL088365. Online_Linkage: https://doi.org/10.1029/2020GL088365 Cross_Reference: Citation_Information: Originator: Himmelstoss, E.A. Originator: Farris, A.S. Originator: Henderson, R.E. Originator: Kratzmann, M.G. Originator: Ergul, A. Originator: Zhang, O. Originator: Zichichi, J.L. Originator: Thieler, E.R. Publication_Date: 2021 Title: Digital Shoreline Analysis System (version 5.1) Other_Citation_Details: Himmelstoss, E.A., Farris, A.S., Henderson, R.E., Kratzmann, M.G., Ergul, A., Zhang, O., Zichichi, J.L., and Thieler, E.R., 2021, Digital Shoreline Analysis System (version 5.1): U.S. Geological Survey software release, https://code.usgs.gov/cch/dsas. Online_Linkage: https://code.usgs.gov/cch/dsas Cross_Reference: Citation_Information: Originator: Stockdon, H.F. Originator: Holman, R.A. Originator: Howd, P.A. Originator: Sallenger, A.H.J. Publication_Date: 2006 Title: Empirical parameterization of setup, swash, and runup Other_Citation_Details: Stockdon, H.F., Holman, R.A., Howd, P.A., and Sallenger, A.H.J., 2006, Empirical parameterization of setup, swash, and runup: Coastal Engineering, v. 53, p. 573-588. Online_Linkage: https://doi.org/10.1016/j.coastaleng.2005.12.005 Cross_Reference: Citation_Information: Originator: Wolinsky, M.A. Originator: Murray, A.B. Publication_Date: 2009 Title: A unifying framework for shoreline migration: 2. Application to wave-dominated coasts Other_Citation_Details: Wolinsky, M.A, and Murray, A.B., 2009, A unifying framework for shoreline migration: 2. Application to wave-dominated coasts: Journal of Geophysical Research, v. 114, F01009. Online_Linkage: https://doi.org/10.1029/2007JF000856 Data_Quality_Information: Attribute_Accuracy: Attribute_Accuracy_Report: Attribute values are projections of shoreline position at discrete transect locations due to plausible future sea-level rise scenarios in the future and therefore cannot be cross-checked with observations, because observations do not exist. A formal model accuracy assessment of the projections was conducted for each model output location, and model uncertainty is determined at the 95 percent confidence level. Model positional performance is validated for the period 2015-2020. Unresolved process uncertainty bands based on calculated uncertainty during this model evaluation period are included that also take seasonal variations in the shoreline as derived using the numerical model into account. While several complex coastal processes are explicitly and implicitly accounted for, the model’s estimate of uncertainty does not account for all coastal processes. In dynamic areas including around river mouths, capes, and end of spits, the model’s performance is often poorer and, hence, the uncertainty is often greater. An estimate of unresolved process uncertainty is included to account for the model accuracy (compared with shoreline observations) during a validation period (2015-2020), when such an assessment of accuracy is possible. The unresolved process uncertainty is comparable to the model’s reported uncertainty in most locations. However, in complex locations such as spits, capes, and river inlets, the unresolved process uncertainty is often much larger that the reported model uncertainty. Logical_Consistency_Report: Data have undergone QA/QC and fall within expected/reasonable ranges (Vitousek and others, 2021; 2023; Vos and others, 2019a). Completeness_Report: Dataset is considered complete for the information presented. Users are advised to read the rest of the metadata record carefully for additional details. Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: Data are concurrent with specified transect locations. Vertical_Positional_Accuracy: Vertical_Positional_Accuracy_Report: N/A Lineage: Source_Information: Source_Citation: Citation_Information: Originator: Google Earth Publication_Date: 2020 Title: Aerial imagery for U.S. Atlantic Coast Geospatial_Data_Presentation_Form: image Publication_Information: Publication_Place: online Publisher: Google Earth Online_Linkage: https://earth.google.com/ Type_of_Source_Media: online viewer Source_Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 20161201 Ending_Date: 20200331 Source_Currentness_Reference: dates accessed Source_Citation_Abbreviation: Aerial imagery Source_Contribution: Recent aerial imagery accessed through Google Earth was used to delineate sandy beach areas of focus for the study. This was the most recent cloud-free imagery at the time of access (between December 2016 and March 2020 across the region). Source_Information: Source_Citation: Citation_Information: Originator: Vitousek, S. Originator: Vos, K. Originator: Barnard, P.L. Publication_Date: 2023 Title: Satellite-derived shorelines for the U.S. Atlantic Coast (1984-2021) Geospatial_Data_Presentation_Form: KMZs Publication_Information: Publication_Place: online Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.5066/P9BQQTCI Type_of_Source_Media: online database Source_Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 19840101 Ending_Date: 20211231 Source_Currentness_Reference: valid dates for satellite-derived shorelines Source_Citation_Abbreviation: SDS Source_Contribution: Satellite-derived shorelines were used to calibrate CoSMoS-COAST model parameters at all transects available. Source_Information: Source_Citation: Citation_Information: Originator: Li Erikson Originator: Liv Herdman Originator: Chris Flanary Originator: Anita Engelstad Originator: Prasad Pusuluri Originator: Patrick Barnard Originator: Curt Storlazzi Originator: Mike Beck Originator: Borja Reguero Originator: Kai Parker Publication_Date: 2022 Title: Ocean wave time-series simulated with a global-scale numerical wave model under the influence of projected CMIP6 wind and sea ice fields Geospatial_Data_Presentation_Form: NetCDF Publication_Information: Publication_Place: online Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.5066/P9KR0RFM Type_of_Source_Media: online database Source_Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 20200101 Ending_Date: 20501231 Source_Currentness_Reference: dates accessed Source_Citation_Abbreviation: WW3 Source_Contribution: High-resolution nearshore wave data derived from several global climate models were used to calibrate CoSMoS-COAST models during hindcast period and used in future projections. Source_Information: Source_Citation: Citation_Information: Originator: Sweet, W.V. Originator: Hamlington, B.D. Originator: Kopp, R.E. Originator: Weaver, C.P. Originator: Barnard, P.L. Originator: Bekaert, D. Originator: Brooks, W. Originator: Craghan, M. Originator: Dusek, G. Originator: Frederikse, T. Originator: Garner, G. Originator: Genz, A. S. Originator: Krasting, J.P. Originator: Larour, E. Originator: Marcy, D. Originator: Marra, J.J. Originator: Obeysekera, J. Originator: Osler, M. Originator: Pendleton, M. Originator: Roman, D. Originator: Schmied, L. Originator: Veatch, W. Originator: White, K.D. Originator: Zuzak, C. Publication_Date: 20220215 Title: Global and regional sea level rise scenarios for the United States: updated mean projections and extreme water level probabilities along U.S. coastlines. NOAA Technical Report, SLR and Coastal Flood Hazard Scenarios and Tools: Interagency Task Force Geospatial_Data_Presentation_Form: csv Publication_Information: Publication_Place: online Publisher: National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) Online_Linkage: https://sealevel.nasa.gov/task-force-scenario-tool Online_Linkage: https://oceanservice.noaa.gov/hazards/sealevelrise/sealevelrise-tech-report.html Type_of_Source_Media: online database Source_Time_Period_of_Content: Time_Period_Information: Single_Date/Time: Calendar_Date: 20220215 Source_Currentness_Reference: date accessed Source_Citation_Abbreviation: NOAA SLR projections Source_Contribution: SLR rates were used to create SLR curves for future shoreline change model scenarios. Source_Information: Source_Citation: Citation_Information: Originator: National Oceanic and Atmospheric Administration (NOAA) Publication_Date: 2022 Title: NOAA water level stations Geospatial_Data_Presentation_Form: csv Publication_Information: Publication_Place: online Publisher: NOAA Online_Linkage: https://tidesandcurrents.noaa.gov/stations.html?type=Water+Levels Type_of_Source_Media: online database Source_Time_Period_of_Content: Time_Period_Information: Range_of_Dates/Times: Beginning_Date: 18540701 Ending_Date: 20221130 Source_Currentness_Reference: dates of data accessed Source_Citation_Abbreviation: NOAA tide stations Source_Contribution: adjusting SLR projections for models Source_Information: Source_Citation: Citation_Information: Originator: Mickey, R.C. Originator: Passeri, D.L. Publication_Date: 20220706 Title: Atlantic and Gulf coast sandy coastline topo-bathy profile and characteristic database: U.S. Geological Survey data release Geospatial_Data_Presentation_Form: hd5 Publication_Information: Publication_Place: online Publisher: U.S. Geological Survey Online_Linkage: https://doi.org/10.5066/P9838KPW Type_of_Source_Media: online database Source_Time_Period_of_Content: Time_Period_Information: Single_Date/Time: Calendar_Date: 2022 Source_Currentness_Reference: date downloaded Source_Citation_Abbreviation: topobathy slopes Source_Contribution: beach profile information used to determine transgression slopes Process_Step: Process_Description: Set up model structure as discussed in Vitousek and others (2017, 2021, and 2023) for the U.S. Atlantic Coast. The structure included defining cross-shore transect locations modified from DSAS (Himmelstoss and others, 2021) as locations for the one-dimensional numerical models simulating the shoreline position given changing sea level and wave forcing. Modifications mainly consisted of reduction of excess length to focus on regions of sandy beach. The assimilation scheme outlined in Vitousek and others (2023; 2021, section 2.3), was set up to use an ensemble of 200 members (Nens = 200). Members were differentiated by wave forcing (multiple realizations of future wave conditions), which in this study area was derived from seven WW3 wave model simulations of Global Climate Models (GCMs). The model was set up to assimilate SDS observations and calibrate itself for a majority portion of the historical data period (1990-2015), reserving 5 years of SDS observations (2015-2020) for validation of the model. Although the uncertainty in the SDS positions (with RMS error of 10 m) is generally larger than traditional surveys (RMS error of centimeters to meters), the larger observational uncertainty is handled within the context of the Kalman filter. A representation of the landward boundary of the beach was hand-digitized from aerial imagery in Google Earth. This boundary was used in models at individual transects to classify the landward end of the sandy beach. This sandy beach limit separates the beach from other landscapes, such as vegetated or urban landscapes, in model simulations (representing a coarse categorization of sandy versus not-sandy beach). This limit was digitized from the most recent, cloud-free imagery available at the time of digitization (between December 2016 and March 2020 across the region). Imagery was viewed in Google Earth at a minimum 1:300 scale, and digitized at an average horizontal vertex spacing of 10-20 m. The landward edge or boundary of the sandy beach was visually identified in the imagery using several criteria, dependent on the landscape, by the presence of infrastructure or buildings; changes in vegetation; or established dune systems. If multiple criteria were present, the feature encountered first (as the landward boundary of the beach) was generally used. Source_Used_Citation_Abbreviation: Aerial imagery, SDS, WW3 Process_Date: 20210209 Process_Step: Process_Description: Obtained SDS observations from all available Landsat satellite imagery in the study area using the CoastSat toolbox (Vos and others,2019a; 2019b), at model transect locations. Transects were included along sections of beach adjacent to river mouths and inlets, and these locations should be understood to be highly dynamic and include more uncertainty. SDS observations used in model assimilation and validation are derived from low-cloud-cover (less than 50 percent cloud cover) Landsat imagery from 1990 to 2020, where images with large georectification errors were removed. Imagery had horizontal resolution of 30 m, which was pan-sharpened to 15 m. See the SDS dataset for more details. See Vitousek and others (2021; 2023) for more information. Source_Used_Citation_Abbreviation: SDS Process_Date: 20210720 Process_Step: Process_Description: Shoreline change models were run within Matlab to correct SDS observations for synoptic wave setup as predicted with empirical runup equations as described in Vitousek and others (2021; 2023). The model was run sequentially for three periods: a hindcast/calibration period (1990-2015), a validation period (2015-2020), and projection period (2020-2100). The hindcast period serves as the calibration period, assimilating available data including SDS observations, to automatically-tune and optimize parameters at every transect. The model was started on 01 Jan 1990, using a SDS for the initial condition. This shoreline can appear ‘spikey’, as it is only derived and shown at discrete transect locations. In rare circumstances, the initial shoreline comes from observations at two different instances in time on neighboring transects, which can also lead to spikiness. Any uncertainty in both modeled and observed shoreline position is accounted for and adjusted in the Kalman filter for subsequent time steps, while refining model parameters (see Vitousek and others, 2021; 2023). Depending on location and availability of SDS data, transects were run in 3 configurations: “full model” configuration included all model parameters; “cross-shore only” configuration excluded longshore transport in locations where this was applicable (for example, when the beach was short or enclosed, or if there was too much curvature on the shoreline for the long-shore transport term to be resolved); and a “rate only” configuration shows where only historical rates of shoreline change are used (usually due to limited SDS data). As the models are run in an ensemble, uncertainty was defined as 95 percent confidence intervals determined by the band that enclosed the middle 95 percent of model trajectories in the ensemble illustrating impacts from variable wave conditions from seven different GCMs. This uncertainty encapsulates long-term changes as well as episodic changes and reflects decades of data (Vitousek and others, 2023). However, shoreline changes and erosion from extreme storms can lie outside this band of trajectories, and so to illustrate the potential impact of extreme storms, the maximum landward ensemble trajectory for wave heights of certain intensities (return periods of 1-year, 20-year and 100-years, representative of extreme coastal storm impacts) are also provided. For locations where “rate only” model configurations were used, episodic changes are not projected, and potential storm erosion uncertainty is not available. The impact of large historical events may affect the model output in certain locations; in highly dynamic regions that have experienced large episodic shoreline change (such as near headlands or river mouths), SDS may have higher uncertainty as well as model projections. Data were assimilated during the validation period (2015-2020). While several processes are implicitly included with each location, the model does not explicitly account for all coastal processes. In dynamic areas including around river mouths, capes, inlets, and at the end of spits, uncertainty is greater. An estimate of this potential uncertainty due to unresolved processes was derived from comparing shoreline predictions for this period to observations. This comparison showed an RMS error of less than 15 m most of the study area (on the order of SDS positional error), with higher values in the dynamic areas mentioned above (Vitousek and others, 2023). The confidence bands of the unresolved process uncertainty are based on 2x the root-mean-square error of the un-assimilated model versus observations during this validation period. This unresolved process uncertainty is separate from and not mathematically additive to model uncertainty. Unresolved process uncertainty is not available at locations that do not have enough data for validation (for example, “rate only” and some “cross-shore only” transects). To run any shoreline model, as a simplified representation of shoreline evolution, certain assumptions about the behavior of the model need to be made, since the effect of these assumptions over long projection periods can lead to different outcomes (Vitousek and others, 2017; 2021; 2023). To explore the importance and impact of certain key model assumptions, the model was run for different cases and transgression slopes, representing end-members of model behavior bracketing a spectrum of possible solutions. The first key model parameter affecting shoreline change is a slope factor. The effective slope of the beach (called the equilibrium beach profile slope) is connected to the transgression slope (defined as the relationship between future sea-level rise and beach recession; Wolinsky and Murray, 2009). The equilibrium beach slope is typically derived geometrically from the beach shape, whereas the transgression slope is also affected by physical/hydrodynamic/geologic processes that can vary across landscapes. As these can be defined quite differently for varying needs and landscapes, three different slope scenarios that span a potential range of shoreline changes associated with different equilibrium beach profile slopes and transgression slopes are presented: A) steep, B) intermediate, and C) gentle. For slope A (steep), the transgression slope is defined by a steep equilibrium beach profile slope, derived geometrically from alongshore-smoothed topobathy slopes (between MSL and dune toe) and is more reflective of passive flooding of the beach and in locations with limited space to accommodate active beach changes (such as urban beaches); it is also applicable at shorter time-scales. Slope B (intermediate) has the transgression slope set to be an average of the steeper beach-face slope (between MSL and the dune toe) and the gently sloping offshore beach slope (between the depth of closure and the back of the dune or beach). This case is typical driven by a combination of active beach change and passive flooding of the beach, applicable at intermediate time-scales or at partially developed/partially natural beaches with moderate space to accommodate beach retreat. For slope C (gentle), the transgression slope is set as the offshore beach slope (derived from alongshore-smoothed slope between depth of closure at approximately 10 m water depth to the back of the dune or beach), and typically yields the largest changes in shoreline position. It is applicable for longer time-scales (or larger SLR scenarios) and for low-lying, natural beach and barrier systems with ample space to accommodate active beach changes. Additional key aspects of model behavioral assumptions were investigated in combination: the extent or boundary of the beach (that is, where parameters derived from observed shoreline movement may or may not remain valid over long periods of time), and parameters accounting for shoreline accretion. For the first aspect, the shoreline model does not differentiate different landscapes in terms of shoreline evolution and erodibility. In natural settings, derived parameters from assimilated historical records may arguably hold (or be modified) for areas landward of the beach to include dunes and vegetated areas. But it is similarly arguable that parameters would not hold when encountering hardened infrastructure. Therefore, the model was run for two different cases to show solutions bracketing this behavioral assumption: 1) allowing the shoreline to evolve/erode without impediment/constraint as determined by its historical behavior or 2) limiting the shoreline erosion to the landward end of the modern-day beach. Similarly, modern-day, long-term, cross-shore shoreline change rates (particularly for developed, accreting beaches) may be reflective of human intervention/nourishments, and it is exceedingly difficult to project how interventions/nourishments may progress and/or persist in the future. Therefore, the model was run for two different cases to show end-member solutions of cross-shore accretion (and possibly reflective of generalized coastal management options) in the future: 1) retaining the model-derived residual long-term shoreline change rate (Vitousek and others, 2017; 2021; 2023) for future projections and 2) suppressing the residual shoreline trend by setting this parameter to 0 when it is estimated to be positive (accretionary). The latter case only suppresses the residual trend of the process; it does not affect accretion or erosion due to longshore transport: accretion (and erosion) due to alongshore sediment transport are still reflected in the modeling results. These different end-member solutions are combined for four different model cases. In model cases where a landward model boundary is imposed, model shoreline uncertainty is not shown landward of the boundary; however, potential storm erosion uncertainty is still projected landward. Also note that in these cases when a model boundary is imposed, there are rare locations where the initial shoreline was located landward of the model boundary (occurred in dynamic areas, as landward boundary was digitized from imagery dated 2017 or later); in these locations, when the historical or modeled shoreline is landward of boundary, beach width was then 0 m, long-short transport was neglected, and the resultant projected shoreline was held at imposed model boundary. When historical or modeled shoreline was oceanward of model boundary, all model parameters (as defined per transect) were used and resultant projections are displayed normally. It is important to note that historical impacts of nourishment are captured in the SDS observations, and so impacts are implicitly included in the calibration and shoreline projections. However, as mentioned above, we provided no assumptions about the persistence or policy of this practice. Model parameters derived during the calibration period and projection periods are preserved and used without adjustment in those model cases. Projected SLR curves from NOAA SLR projections through 2100 (relative to 2005; Vitousek and others, 2023) for locations on the U.S. East Coast are used in model scenarios for this study’s SLR scenarios. The SLR projections provide unique conditions for each tide station, and here we apply spatially variable sea-level conditions based on a nearest neighbor approach. For SLR scenarios of 100 cm and less, the NOAA SLR curve showing 114 cm at 2100 is used. For SLRs 150 cm and 200 cm, NOAA’s projection of 150 cm and 209 cm are used, respectively, representing those values of SLR by 2100. A 300 cm sea-level scenario is not reported in the NOAA projection dataset; however, this sea-level scenario is constructed by extrapolating the difference between the 200 cm and 150 cm curve to a 300 cm curve. Final shoreline positions are taken at the corresponding dates along the NOAA SLR projection curve corresponding to the target SLR scenario. For the hindcast period (1990-2015), SLR is extrapolated linearly backwards from 2005 to the beginning of the model (January 1990) based on a historical rate. Source_Used_Citation_Abbreviation: NOAA SLR projections, NOAA tide stations, WW3, SDS, topobathy slopes Process_Date: 20221130 Process_Step: Process_Description: Checked all output to ensure quality results. Process_Date: 20221207 Process_Step: Process_Description: Organized model projections into KMZ files grouped by state. Output is further grouped by model case, numbered thusly: In model case 1 shorelines are not allowed to evolve and erode past current boundaries and recent historical accretion rates are set to 0; case 2 shorelines are not allowed to evolve and erode past current boundaries and recent historical accretion rates are preserved; case 3 shorelines are allowed to erode without limitation and recent historical accretion rates are set to 0; and case 4 shorelines are allowed to erode without limitation and recent historical accretion rates are preserved. KMZs include the initial shoreline, final shoreline projections for SLR scenarios, model uncertainty (representing 95 percent of the ensemble model spread and robust model uncertainty) and transect information including all model parameters calibrated at each respective site. Files also include unresolved process uncertainty, as an estimate of uncertainty for unresolved processes and other sources of error not explicitly included in the model. Null projection and model parameter values are listed as NaN. Data are only shown for transect locations where models were run. File names indicate state and model parameters; for example, ShorelineChange_projctn_NC_Case1_TrgSlopeA.kmz contains shoreline projections in North Carolina for case 1 (landward boundary limitation is imposed to shoreline evolution, and recent historical accretion rates do not continue) and transgression slope A (using a steep equilibrium beach profile slope as the transgression slope). For best display of results, it is recommended to turn off any 3D viewing. Process_Date: 20221230 Process_Step: Process_Description: Edits were made to correct spelling in authors names. No data were changed. The metadata available from a harvester may supersede metadata bundled within a download file. Users are advised to compare the metadata date of this file to any similar file to ensure they are using the most recent version. (scochran@usgs.gov) Process_Date: 20230516 Process_Step: Process_Description: Edits were made to to include final citation information for a Cross_Reference. No data were changed. The metadata available from a harvester may supersede metadata bundled within a download file. Users are advised to compare the metadata date of this file to any similar file to ensure they are using the most recent version. (aoneill@usgs.gov) Process_Date: 20230808 Process_Step: Process_Description: Edits to metadata were made to reflect corrected model case number identifiers in the process step explaining organization of the files. No data were changed. The metadata available from a harvester may supersede metadata bundled within a download file. Users are advised to compare the metadata date of this file to any similar file to ensure they are using the most recent version. (aoneill@usgs.gov) Process_Date: 20240509 Spatial_Data_Organization_Information: Direct_Spatial_Reference_Method: Vector Point_and_Vector_Object_Information: SDTS_Terms_Description: SDTS_Point_and_Vector_Object_Type: GT-polygon composed of chains Point_and_Vector_Object_Count: 14726880 Spatial_Reference_Information: Horizontal_Coordinate_System_Definition: Geographic: Latitude_Resolution: 0.000001 Longitude_Resolution: 0.000001 Geographic_Coordinate_Units: Decimal Degrees Geodetic_Model: Horizontal_Datum_Name: North American Datum 1983 Ellipsoid_Name: Geodetic Reference System 80 Semi-major_Axis: 6378137.000000 Denominator_of_Flattening_Ratio: 298.257222 Vertical_Coordinate_System_Definition: Depth_System_Definition: Depth_Datum_Name: NAVD88 Depth_Resolution: 2.0 Depth_Distance_Units: meters Depth_Encoding_Method: Implicit coordinate Entity_and_Attribute_Information: Detailed_Description: Entity_Type: Entity_Type_Label: Projections of shoreline change position for hindcast period (1990-2021) and for future 21st Century (2021-2100) due to sea-level rise Entity_Type_Definition: KMZs include projected shoreline position changes caused by wave impacts in different named sea-level rise scenarios and different model-case scenarios. Initial shorelines (from automatically detected shorelines at the start of the model run) are included to show trends in shoreline change. Model parameters for each transect model are listed with the respective transect. Shoreline model uncertainty (determined from the rigorous 200-member ensemble) and unresolved process uncertainty are also included. Entity_Type_Definition_Source: Producer Defined Attribute: Attribute_Label: initial shoreline Attribute_Definition: Part of model initial conditions. Position of initial shoreline used at start of simulation. Determined from source satellite-derived shoreline data on 02 January 1995. The position was automatically detected from imagery and should not be used in place of definitive historical shoreline records but is meant to provide comparisons for projected trends in shoreline change. Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Unrepresentable_Domain: geographic position of the initial shoreline condition used in the models, selected from a single shoreline observation circa the model start time (Jan 1st, 1995). Attribute: Attribute_Label: modeled shoreline Attribute_Definition: Position of shoreline, defined as the land-water boundary at Mean Sea Level (MSL) for the indicated SLR scenario. This represents the median trajectory of a 200-member ensemble using multiple realizations of future wave conditions. As the models use the change in sea level over time during computation, final shoreline positions for SLR scenarios are identified for the date indicated. Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Unrepresentable_Domain: modeled shoreline position for the SLR indicated Attribute: Attribute_Label: modeled shoreline uncertainty Attribute_Definition: Modeled uncertainty for projected shoreline position for the given SLR scenario, defined as the upper and lower bounds of a 95 percent confidence interval for the projected 200-member ensemble trajectories. The uncertainty is representative of long-term, seasonal, and daily shoreline change. In model cases where a landward model boundary was imposed (cases 1 and 2), uncertainty does not extend past the model boundary. Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Unrepresentable_Domain: modeled uncertainty of shoreline change determined at 95 percent confidence interval for SLR indicated Attribute: Attribute_Label: potential storm erosion uncertainty Attribute_Definition: Illustrates the potential additional impact of extreme storms on episodic shoreline change for full model and cross-shore transects. It is defined from an extreme value analysis of modeled shoreline positions from the 200-member ensemble based on the return-period/intensity indicated. Thus, it captures extreme potential erosion events from the model ensemble. For other model configurations (for example, “rate only”), see process steps for more info. Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Unrepresentable_Domain: uncertainty in modeled shoreline position considering potential storm erosion for SLR and storm intensity for given return period indicated Attribute: Attribute_Label: unresolved process uncertainty Attribute_Definition: Uncertainty considering unresolved processes and other sources of error not explicitly included in the model, which captures the larger uncertainty in model projections for dynamic and complex areas such as river mouths, capes, inlets, and the ends of spits. Estimates of the so-called unresolved process uncertainty are derived from comparing model output with Satellite-Derived Shoreline (SDS) observations during the validation period (2015-2020). Unresolved process uncertainty is shown for SLR scenarios 25 cm and greater and where validation data were present. For model configurations other than “full” (for example, “rate only”), see process steps and citations for more information. Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Unrepresentable_Domain: Uncertainty of shoreline change projection considering unresolved processes and other sources of error. Attribute: Attribute_Label: Trans_ID Attribute_Definition: Identification of individual transects for each model location, unique across study area Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 1 Range_Domain_Maximum: 34067 Attribute_Units_of_Measure: NA Attribute_Measurement_Resolution: 1 Attribute: Attribute_Label: ShrType Attribute_Definition: Shoreline Type used in the transect model, defined as “full model”, “cross-shore only” (longshore transport is excluded in locations where applicable, such as when the beach was very short or enclosed as a “pocket beach”, or there was curvature in the shoreline), or “rate only” (only historical rates of shoreline change are used because the model’s governing equations would not be appropriately descriptive for response of the beach’s sediment type, for example with cobbled beaches) Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Codeset_Domain: Codeset_Name: full model, cross-shore only, or rate only Codeset_Source: Producer Defined Attribute: Attribute_Label: ChgRate Attribute_Definition: Shoreline change rate determined from a linear regression fit to all available shoreline data Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: -29.82 Range_Domain_Maximum: 18.42 Attribute_Units_of_Measure: meters per year Attribute_Measurement_Resolution: 0.01 Attribute: Attribute_Label: v_lt_assim Attribute_Definition: Long-term shoreline change rate, which is assimilated during the model hindcast period (1990-2015) Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: -3.97 Range_Domain_Maximum: 3.77 Attribute_Units_of_Measure: meters per year Attribute_Measurement_Resolution: 0.01 Attribute: Attribute_Label: v_lt_proj Attribute_Definition: Long-term shoreline change rate for projection period (2020-2100). Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: -5.0 Range_Domain_Maximum: 5.0 Attribute_Units_of_Measure: meters per year Attribute_Measurement_Resolution: 0.01 Attribute: Attribute_Label: DT Attribute_Definition: The equilibrium time scale parameter, as defined in Vitousek and others (2021; 2023), assimilated during the model hindcast period (1990-2015) Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 10.0 Range_Domain_Maximum: 120.0 Attribute_Units_of_Measure: days Attribute_Measurement_Resolution: 0.01 Attribute: Attribute_Label: DY Attribute_Definition: The equilibrium shoreline excursion scale parameter, as defined in Vitousek and others (2021; 2023), which is assimilated during the model hindcast period (1990-2015) Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 2.01 Range_Domain_Maximum: 30.0 Attribute_Units_of_Measure: meters Attribute_Measurement_Resolution: 0.01 Attribute: Attribute_Label: Hsb Attribute_Definition: The background wave height parameter, as defined in Vitousek and others (2021; 2023) Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0.01 Range_Domain_Maximum: 4.0 Attribute_Units_of_Measure: m Attribute_Measurement_Resolution: 0.01 Attribute: Attribute_Label: c_BrunnCo Attribute_Definition: Bruun coefficient, assimilated during model hindcast period (1990-2015) Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0.01 Range_Domain_Maximum: 2.0 Attribute_Units_of_Measure: N/A Attribute_Measurement_Resolution: 0.01 Attribute: Attribute_Label: K_LongShrT Attribute_Definition: longshore transport coefficient determined from model hindcast period (1990-2015) Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0.01 Range_Domain_Maximum: 700.0 Attribute_Units_of_Measure: N/A Attribute_Measurement_Resolution: 0.01 Attribute: Attribute_Label: sigma Attribute_Definition: Gaussian noise parameter (see Vitousek and others, 2017; 2021) determined from model hindcast period (1990-2015) Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0.0001 Range_Domain_Maximum: 2.0 Attribute_Units_of_Measure: m Attribute_Measurement_Resolution: 0.0001 Attribute: Attribute_Label: SLRcm Attribute_Definition: SLR in centimeters referenced for the projection Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0 Range_Domain_Maximum: 300 Attribute_Units_of_Measure: cm Attribute_Measurement_Resolution: 25 Attribute: Attribute_Label: TrgSlope Attribute_Definition: transgression slope used at location Attribute_Definition_Source: Producer Defined Attribute_Domain_Values: Range_Domain: Range_Domain_Minimum: 0.0024 Range_Domain_Maximum: 0.1060 Attribute_Units_of_Measure: N/A Attribute_Measurement_Resolution: 0.0001 Overview_Description: Entity_and_Attribute_Overview: KMZ files include projections of shoreline position changes caused by wave impacts in different named sea-level rise scenarios and different model-case scenarios. For each SLR scenario, shoreline projections illustrate shoreline position changes, model uncertainty bands, modeled uncertainty with potential storm erosion, and unresolved process uncertainty. Transect/model locations and model parameters at each location are also displayed. Initial shorelines (from automatically detected shorelines at the start of the model run) are included to show trends in shoreline change. Entity_and_Attribute_Detail_Citation: Shoreline projections and model uncertainty are determined at transects for U.S. Atlantic Coast; transects are spaced approximately 50 m apart alongshore and identified in whole sequential numbers, increasing to the north. Free parameters and coefficients for numerical models are tuned at each transect location to fit historical data; see Vitousek and others (2021; 2023) for details and mathematical definitions. Coefficients and data used to tune individual transect models are listed at each transect location. Distribution_Information: Distributor: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey - CMGDS Contact_Address: Address_Type: mailing and physical Address: 2885 Mission Street City: Santa Cruz State_or_Province: CA Postal_Code: 95060 Contact_Voice_Telephone: 831-427-4747 Contact_Electronic_Mail_Address: pcmsc_data@usgs.gov Resource_Description: These data are available in KMZ format grouped by state and model case (for example, ShorelineChange_projctn_FL.zip contains all model case KMZs for Florida). Distribution_Liability: 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. Standard_Order_Process: Digital_Form: Digital_Transfer_Information: Format_Name: KMZ Format_Version_Number: Google Earth Pro (version 7.3, Google, 2017) Format_Specification: Features are in KMZ format and are projected in UTM Zone 17 and 18 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Format_Information_Content: The .zip file contains KMZ files for Florida File_Decompression_Technique: WinZip Transfer_Size: 258.5 Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/10.5066/P9BQQTCI Access_Instructions: Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section. Digital_Form: Digital_Transfer_Information: Format_Name: KMZ Format_Version_Number: Google Earth Pro (version 7.3, Google, 2017) Format_Specification: Features are in KMZ format and are projected in UTM Zone 17 and 18 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Format_Information_Content: The .zip file contains KMZ files for Georgia File_Decompression_Technique: WinZip Transfer_Size: 58.4 Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/10.5066/P9BQQTCI Access_Instructions: Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section. Digital_Form: Digital_Transfer_Information: Format_Name: KMZ Format_Version_Number: Google Earth Pro (version 7.3, Google, 2017) Format_Specification: Features are in KMZ format and are projected in UTM Zone 17 and 18 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Format_Information_Content: The .zip file contains KMZ files for Virginia File_Decompression_Technique: WinZip Transfer_Size: 68.1 Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/10.5066/P9BQQTCI Access_Instructions: Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section. Digital_Form: Digital_Transfer_Information: Format_Name: KMZ Format_Version_Number: Google Earth Pro (version 7.3, Google, 2017) Format_Specification: Features are in KMZ format and are projected in UTM Zone 17 and 18 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Format_Information_Content: The .zip file contains KMZ files for Maryland File_Decompression_Technique: WinZip Transfer_Size: 22.8 Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/10.5066/P9BQQTCI Access_Instructions: Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section. Digital_Form: Digital_Transfer_Information: Format_Name: KMZ Format_Version_Number: Google Earth Pro (version 7.3, Google, 2017) Format_Specification: Features are in KMZ format and are projected in UTM Zone 17 and 18 coordinates, with horizontal datum NAD83 and vertical datum NAVD88. Format_Information_Content: The .zip file contains KMZ files for Delaware File_Decompression_Technique: WinZip Transfer_Size: 17.9 Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: https://doi.org/10.5066/10.5066/P9BQQTCI Access_Instructions: Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section. Fees: None. Technical_Prerequisites: These data can be viewed with Google Earth software and other compatible GIS software, such as Global Mapper and QGIS, and can be translated to ESRI formats. Metadata_Reference_Information: Metadata_Date: 20240510 Metadata_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: U.S. Geological Survey, Pacific Coastal and Marine Science Center Contact_Person: PCMSC Science Data Coordinator Contact_Address: Address_Type: mailing and physical Address: 2885 Mission Street City: Santa Cruz State_or_Province: CA Postal_Code: 95060 Contact_Voice_Telephone: 831-427-4747 Contact_Electronic_Mail_Address: pcmsc_data@usgs.gov Metadata_Standard_Name: Content Standard for Digital Geospatial Metadata Metadata_Standard_Version: FGDC-STD-001-1998