Return to search results
💡 Advanced Search Tip
Search by organization or tag to find related datasets
10-meter rasters of predicted elevation with respect to projected sea-level change for the Northeastern U.S. for the 2030s, 2050s, 2080s and 2100s
This data release presents an update to the Coastal Response Likelihood (CRL) model (Lentz and others 2015); a spatially explicit, probabilistic model that evaluates coastal response for the Northeastern U.S. under various sea-level scenarios. The model considers the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Updated model results provide higher spatial resolution predictions (from 30 meters (m) to 10 m) of adjusted land elevation ranges (AE) with respect to projected relative sea-level scenarios, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR) characterized as either static (inundated) or dynamic (maintaining or changing state). The predictions span the coastal zone vertically from 10 m below to 10 m above mean high water (MHW). Results are produced at a horizontal resolution of 10 meters for four decades (2030, 2050, 2080 and 2100) and two possible sea-level change scenarios (Intermediate Low (IL), Intermediate High (IH)) as defined by Sweet and others 2022. Adjusted elevations and their respective probabilities are generated using regional geospatial datasets of relative sea-level scenarios and current elevation data. Coastal response outcomes are determined by combining adjusted elevation outputs with land cover data and expert judgment (Lentz and others 2015) to assess whether an area is likely to maintain its existing land class, or transition to a new one (dynamic), or become submerged (static). The intended users of these data include scientific researchers, coastal planners, and natural resource managers.
Complete Metadata
| @id | http://datainventory.doi.gov/id/dataset/e08b3bf355494f6d8c60982d6db18286 |
|---|---|
| bureauCode |
[ "010:12" ] |
| identifier | USGS:6811383bd4be0276ecc8495b |
| spatial | -77.5278,36.5437,-66.9432,45.1918 |
| theme |
[ "geospatial" ] |
