This dataset contains simulated storm surge results for the northern Gulf of Mexico (Mississippi, Alabama, and the Florida panhandle) using a high-resolution SWAN+ADCIRC model (Bilskie, 2016b). The modeling approach incorporates dynamic processes including salt marsh evolution, shoreline and dune height change, land use land cover, as well as sea level rise, for the year 2100. This modeling effort permits more robust and realistic results than using a static, or ‘bathtub,’ approach (Passeri et al., 2015). The outcome is a better understanding of the storm surge generating mechanisms and interactions among hurricane characteristics and the Northern Gulf of Mexico’s geophysical configuration. There are two broad categories of storm surge model results from the Ecological Effects of Sea Level Rise Northern Gulf of Mexico (EESLR-NGOM) project: 1) Storm Surge by Storm [29 GB total file size, 500 files (unzipped)] and 2) Storm Surge Maximum of Maximums (MOMs) [13 GB total file size, 50 files (unzipped)]. The datasets contain both water surface elevation and inundation depth above ground as model outputs. Each storm surge model output, described below, is provided for the following 5 sea level rise scenarios (Parris et al. 2012): Initial Condition (c. 2000) (no change from c. 2000 mean sea level (MSL)), Low (+0.2m from MSL), Intermediate-Low (+0.5m from MSL), Intermediate-High (+1.2m from MSL), and High (+2.0m from MSL).

This dataset contains salt marsh productivity projections under different sea level rise scenarios for the northern Gulf of Mexico (Florida panhandle, Alabama, and Mississippi) using a coupled hydrodynamic-marsh model called Hydro-MEM (Alizad et al. 2016a and 2016b). The modeled outputs were derived through integrated modeling of tidal hydrodynamics (ADCIRC) and marsh productivity (Marsh Equilibrium Model, or MEM) that incorporates dynamic feedbacks among physical and biological processes. The Hydro-MEM model incorporates biological feedback by including the MEM accretion formulation, while also implementing a friction coefficient effect that varies between subtidal and intertidal states. The Hydro-MEM model is capable of capturing the biophysical feedback that modifies relative salt marsh elevation and the biological feedback on hydrodynamics (Alizad et al. 2016a). There are two types of Hydro-MEM model outputs resulting from the Ecological Effects of Sea Level Rise Northern Gulf of Mexico (EESLR-NGOM) project: 1) Salt Marsh Productivity (Low/Medium/High) [202MB total file size, 919 files (unzipped)] and 2) Mean High Water [431 MB total file size, 137 files (unzipped)]. These outputs were generated for areas surrounding the following National Estuarine Research Reserves: Apalachicola (FL), Weeks Bay (AL), and Grand Bay (MS). Each Hydro-MEM model output, described above, is provided for incremental time steps (5 or 20Y) for the following 5 sea level rise scenarios (Parris et al. 2012): Initial Condition (no change from c. 2000 mean sea level (MSL)), Low (+0.2m from MSL), Intermediate-Low (+0.5m from MSL), Intermediate-High (+1.2m from MSL), and High (+2.0m from MSL). Mean high water data are provided for each SLR scenario for two timesteps (2050 and 2100).

The sand shoals (modeled) polygons represent the hypothesized distribution of sand shoals of the Gulf of Mexico and US Atlantic Coast based on seafloor characteristics and distance to shoreline variables. Defined by Rutecki et al. (2014), a sand shoal is "a natural, underwater ridge, bank, or bar consisting of, or covered by, sand or other unconsolidated material, resulting in shallower water depths than surrounding areas." In the dataset, attributes characterize shoals with a classification scheme developed with a basis in the Coastal and Marine Ecological Classification Standard (CMECS).

These elevation data (in meters) in Apalachee Bay, Florida, have been systematically and variably lowered, mitigating the bias in the lidar DEM and improving its spot elevation accuracy by approximately 69% in Apalachee Bay, Florida. These data span the big bend region of Florida’s gulf coast consisting of Gulf, Franklin, Wakulla, Jefferson, and Taylor counties. The data are in GIS raster format. These adjusted data are now suitable for modeling salt marsh evolution and flood inundation under sea-level rise (SLR) scenarios. Lidar data used in this adjustment were collected on March 01, 2018.

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes along the Florida Reef Tract (FRT) from Miami to Boca Chica Key, Florida. Changes in seafloor elevation were calculated from the 1930s to 2016 using digitized hydrographic sheet sounding data and light detection and ranging (lidar)-derived digital elevation models (DEMs) acquired by the National Oceanic and Atmospheric Administration (NOAA) in 2016 and 2017. Most of the elevation data from the 2016/2017 time period was collected during 2016, and, as an abbreviated naming convention, this time period was referred to as 2016. An elevation change analysis between the 1930s and 2016 data was performed to quantify and map historical impacts to seafloor elevation and to determine elevation-change statistics for 15 habitat types found within the study area along the FRT. Annual elevation-change rates were calculated for each elevation-change data point. Seafloor elevation-change along the FRT was projected 25, 50, 75 and 100 years from 2016 using these historical annual rates of elevation change. Water depth was projected 25, 50, 75 and 100 years from 2016 using historical rates of annual elevation change plus 2016 local sea level rise (SLR) data from NOAA. Data were collected under Florida Keys National Marine Sanctuary permit FKNMS-2016-068.

These elevation data (in meters) in the lower Pascagoula River region in Mississippi have been systematically and variably lowered, mitigating the bias in the lidar DEM and improving its spot elevation accuracy by approximately 90.9%. These data span the eastern area of Jackson County, MS (surrounding Pascagoula, MS), and a small area along the Jackson County, MS-Alabama border. The data are in GIS raster format. These adjusted data are now suitable for modeling salt marsh evolution and flood inundation under sea-level rise (SLR) scenarios. Lidar data used in this adjustment were collected in 2014. Real Time Kinematic Global Navigation Satellite System (RTK-GNSS) field surveys were conducted in March 2019.

This dataset is based on archives from the University of Miami’s high-resolution (1/50 degrees, 1.8km) configuration of the Hybrid Coordinate Ocean Model (HYCOM) in the Gulf of Mexico (GoM-HYCOM 1/50) for the year of 2015. The GoM-HYCOM 1/50 used realistic river forcing parameterization with daily river discharge obtained from the Army Corps of Engineers and the U.S. Geological Survey (USGS). Atmospheric forcing was from the European Center for Medium-Range Weather Forecasts (ECMWF) at 0.125-degree spatial resolution and it is nested within a Global HYCOM. The model assimilated satellite observations of sea surface temperature and sea surface height and in situ observations of temperature and salinity. The GOM-HYCOM 1/50 gives details on the fronts and filaments associated with the Mississippi River plume dynamics, as well as GoM mesoscale processes. The dataset includes the surface model fields of temperature, salinity, currents and sea surface height from the GoM-HYCOM 1/50 at 12Z along with two experimental simulations designed to study the effect of river front; Reference, noMR (without Mississippi River), and noMR_noPcip (without Mississippi River and precipitation).

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.

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes at a subsection of Crocker Reef near Islamorada, Florida (FL), within a 6.1 square-kilometer area following the landfall of Hurricane Irma in September 2017. USGS staff used USGS multibeam data collected between October 10 and December 8, 2017 (Fredericks and others, 2019) and March 8-15, 2018 (Fredericks and others, 2019) to assess changes in seafloor elevation and structure in the months following the passage of Hurricane Irma. An elevation change analysis between the 2017 and 2018 USGS multibeam data was performed to quantify and map impacts to seafloor elevations and to determine elevation and volume change statistics for seven habitat types found within a subsection of Crocker Reef, FL.