This portfolio includes three sets of data, used and explained in Lazarus, Williams & Goldstein (2022, https://doi.org/10.1029/2022GL100098): washover morphometry measured from lidar-derived topographic change along the coastline of New Jersey, USA, following Hurricane Sandy (2012) ('NJ_Sandy_metrics.csv'); the geospatial data layers used to generate those measurements ('WashoverGIS.zip'); and a compilation of washover morphometry reported in the literature ('washover_LAV_literature_examples.csv'). Washover morphometry datasets NJ_Sandy_metrics.csv – The lidar-derived washover morphometry dataset includes: deposit width (m), intrusion length (m), deposit area (m2), deposit volume (m3), deposit perimeter (m), built fraction, the storm event (Sandy 2012), and a general location note. washover_LAV_literature_examples.csv – Also included here are 35 measurements of washover morphometry reported in the literature by six different studies, sampling different storm events in different coastal barrier settings (Carruthers et al., 2013; Williams, 2015; Jamison-Todd et al., 2020; Rodriguez et al. 2020; Hansen et al., 2021; Williams & Rains, 2022). The literature-based dataset includes: intrusion length (m), deposit area (m2), deposit volume (m3), the reference (dataset) in which the measurements were reported, and additional notes. Geospatial data layers ('WashoverGIS' [zipped]) The lidar data underpinning the geospatial data layers here are available from the NOAA Digital Coast Data Viewer (https://coast.noaa.gov/dataviewer/#/): "2012 USGS EAARL-B Lidar: Pre-Sandy" (pre-storm), and "2012 USGS EAARL-B Lidar: Post-Sandy" (post-storm). Geospatial analysis was done in QGIS version 3.22.5. We masked both the pre- and post-storm surfaces to isolate only positive elevations, and subtracted the pre-storm surface from the post-storm surface to calculated the difference between them; we then retained only the positive differences in the resulting surface to isolate sites of sediment deposition. We manually digitized the perimeters of depositional forms we interpreted as washover, corroborated by aerial imagery (https://storms.ngs.noaa.gov/). Basic geometric characteristics (perimeter, area) were taken directly from the washover polygons; washover length and width were taken from oriented minimum bounding boxes around each polygon. Volume for each washover polygon was measured using the Volume Calculation Tool (version 0.4) plugin for QGIS (https://github.com/REDcatch/Volume_calculation_for_QGIS3). In built settings, each washover deposit was associated with a locally estimated built fraction (Lazarus et al., 2021). Elements of the built environment (i.e., buildings) were isolated by creating a binary mask of the pre-storm surface, such that all elevations ³5 m were set to a value = 1, and all elevations <5 m set to zero. Minimum enclosing circles were drawn around each washover polygon, and the total built area (masked value = 1) within each circle summed using the QGIS Zonal Statistics tool. Here, local built fraction is the total built area within a minimum enclosing circle divided by the area of that circle. Geospatial files here include: NJ_north_wash_metrics.shp // NJ_south_wash_metrics.shp – shapefiles of the digitized washover deposits, with morphometric characteristics compiled in their attribute tables NJ_north_BBs.shp // NJ_south_BBs.shp – oriented bounding boxes to determine deposit intrusion length & width NJ_north_MECs.shp // NJ_south_MECs.shp – minimum enclosing circles, used for calculating local built fraction NJ_north_dSandy_POS.tif // NJ_south_dSandy_POS.tif – positive [post-storm - pre-storm] elevation differences NJ_north_rooftops_th05.tif // NJ_south_rooftops_th05.tif – binary mask based on the pre-storm lidar layer ("2012 USGS EAARL-B Lidar: Pre-Sandy") used for calculating built fraction, in which all topographic elements >= 5 m are set = 1, and all < 5 m are set = 0

{"references": ["Carruthers, E. A., Lane, D. P., Evans, R. L., Donnelly, J. P., & Ashton, A. D. (2013). Quantifying overwash flux in barrier systems: An example from Martha's Vineyard, Massachusetts, USA. Marine Geology, 343, 15\u201328. https://doi.org/10.1016/j.margeo.2013.05.013", "Hansen, L. \u00d8., Ernstsen, V. B., Clemmensen, L. B., Al\u2010Hamdani, Z., & Kroon, A. (2021). A method for estimating sediment budgets of washover deposits using digital terrain models. Earth Surface Processes and Landforms, 46(4), 804\u2013821. https://doi.org/10.1002/esp.5066", "Jamison-Todd, S., Stein, N., Overeem, I., Khalid, A., & Trower, E. J. (2020). Hurricane deposits on carbonate platforms: A case study of Hurricane Irma deposits on Little Ambergris Cay, Turks and Caicos Islands. Journal of Geophysical Research: Earth Surface, 125, e2020JF005597. https://doi.org/10.1029/2020JF005597", "Lazarus, E. D., Goldstein, E. B., Taylor, L. A., & Williams, H. E. (2021). Comparing patterns of hurricane washover into built and unbuilt environments. Earth's Future, 9(3), e2020EF001818. https://doi.org/10.1029/2020EF001818", "Rodriguez, A. B., Theuerkauf, E. J., Ridge, J. T. et al. (2020). Long-term washover fan accretion on a transgressive barrier island challenges the assumption that paleotempestites represent individual tropical cyclones. Scientific Reports, 10, 19755. https://doi.org/10.1038/s41598-020-76521-4", "Williams, H. F. L. (2015). Contrasting styles of hurricane Irene washover sedimentation on three east coast barrier islands: cape lookout, North Carolina; Assateague Island, Virginia; and Fire Island, New York. Geomorphology, 231, 182\u2013192. https://doi.org/10.1016/j.geomorph.2014.11.027", "Williams, H. F. L., & Rains, B. J. (2022). Effect of Barrier Height on Magnitude and Character of Hurricane Harvey Washover Fans, Matagorda Peninsula, Texas, USA. Journal of Coastal Research, 38(1), 133\u2013139. https://doi.org/10.2112/JCOASTRES-D-21-00043.1"]}

Funded by The Leverhulme Trust (RPG-2018-282, to EDL and EBG), and an Early-Career Research Fellowship from the Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine (to EBG). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine.