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Foundational Coastal Models Updated

New version of NCEI’s coastal relief models released

Coverage of NCEI's updated Coastal Relief Models (1 arc-second cell size or approx. 30 m) encompasses the U.S. Eastern Seaboard, Gulf of Mexico, Puerto Rico/U.S. Virgin Islands, and Hawaii.
Courtesy of NCEI's U.S. Coastal Relief Models (Tiled Color Hillshade Visualization) Map Service

Flooding is becoming more common along U.S. coasts. Almost 40 percent of the United States total population lives in coastal counties and are at risk from high tide flooding, storm surge, and tsunamis. Because the U.S. coasts are essential for tourism, recreation, transportation, and fisheries, the entire country is affected when coasts are flooded. It is critical for coastal communities to prepare to be resilient to the impacts of coastal flooding events. 

NCEI recently released updated versions of its regional-scale coastal relief models (CRMs) for the Atlantic Coast, Gulf Coast, Puerto Rico/U.S. Virgin Islands, and Hawaii. Additional coverage for the West Coast and Alaska will be added in the future. The new CRMs were generated at a refined spatial resolution of 1 arc-second (approximately 30 meters) as opposed to the older version which were at a spatial resolution of 3 arc-seconds (approximately 90 meters). The CRMs are key data products to help researchers and decision-makers understand and predict environmental changes that affect coastal regions.

Turning Data into Models

Understanding risk is the first step in resilience, and models can help. No matter what the model, however, the critical starting point is data. NCEI stewards the U.S. national archive for bathymetric data—data about the depth of water bodies—and holds bathymetric surveys from sources worldwide. These bathymetric data are collected for navigation and ocean resource management by NOAA as well as other federal, academia, and nonprofit organizations.
NCEI develops high-resolution coastal digital elevation models (DEMs) by drawing on its vast archive of bathymetric data and integrating the bathymetric data with land surface height data (topographic data) from other federal agencies, academia, and nonprofit organizations. A coastal DEM depicts Earth’s land surface and seafloor in an integrated digital map of a coastal region. 

Coastal relief models are moderate-resolution, regional-scale DEMs that combine a variety of airborne, shipborne, and satellite-derived datasets from U.S. and global sources into seamless gridded topography and bathymetry extending inland from the coast to out beyond the continental shelf. The CRMs provide a key dataset for coastal hazard modelers to accurately simulate and predict hazards originating offshore, especially tsunamis.

A Nested Approach 

NCEI is an international leader in coastal digital elevation model (DEM) development. NCEI generates continuously updated digital elevation models (CUDEMs) that are tiled to enable targeted, rapid updates as new data become available. This CUDEM framework supports a sustainable, seamless depiction of elevation from the near-shore to the Exclusive Economic Zone. The new 1 arc-second CRMs were generated by merging high-resolution DEMs, including NCEI’s suite of CUDEMs, as well as source data from other international, U.S. federal and state agencies. CUDEMS and CRMs can be viewed on the NCEI Bathymetric Viewer
On the global scale, NCEI’s ETOPO 2022 provides accurate topographic and bathymetric data to predict water movement across global ocean surfaces, which is vital for Earth visualization including for modeling the movement of tsunami waves across ocean basins. The updated CRMs provide a regional view of the seafloor in the U.S. Economic Exclusive Zone (EEZ) to more accurately model the movement and height of the waves as depths become shallower near the coastline.

In summary, ETOPO has global coverage, CUDEM tiles cover coastal areas, and CRMs cover the U.S. Exclusive Economic Zone. Together, they are a full suite of nested local, regional, and global elevation models that help predict wave heights and coastal inundation for both forecasting and planning purposes.