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Sea Level Rise

This dataset represents the sea level rise metric based on a model developed by Rob Theiler and associates at USGS Woods Hole, which is a measure of the probability of a focal cell being unable to adapt to predicted inundation by sea level rise. Specifically, whether a site gets inundated by salt water permanently due to sea level rise or intermittently via storm surges associated with sea level rise clearly determines whether an ecosystem can persist at a site and thus its ability to support a characteristic plant and animal community. USGS examined future sea-level rise impacts on the coastal landscape from Maine to Virginia by producing spatially-explicit, probabilistic predictions using sea-level projections (based on an average of two climate change scenarios: RCP 4.5 and 8.5), vertical land movement (due to glacial isostacy) rates, elevation, and land cover data. The data span the coastal zone from an elevation of 5 m inland to -10 m offshore, and are provided for the forecast year 2080.In the layer provided here, the raw coastal response metric produced by USGS is scaled and inverted so that a cell with high probability of exhibiting a dynamic (or adaptive) response to sea level rise gets a zero (low stress) and a cell with low probability of exhibiting a dynamic response gets a value approaching 1 (high stress). In addition, we set all cells classified as sub-tidal to nodata for consistency with other products.

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Metadata XML
Data Info
Content Date 2080
Publication Date 2015
Data Type Raster
Resolution 30 meter
Status Complete
Creator Organization USGS Woods Hole, University of Massachusetts
Additional Docs
Sea Level Rise