Mean wave power density estimates represent naturally available US wave energy, derived from measurements observed during a 51-month study period. Measurements were taken from 42,000 grid points out to a distance of 50 nautical miles from shore. Values represent the average instantaneous power generated by a meter length of wave crest per grid point. In accordance with accepted global practice, wave power density is measured in kilowatts per meter of wave crest aggregated across a unit diameter circle. Data were classified using quantiles. Bathymetric effects are known to have a large effect on wave characteristics at depths shallower than ~20m on the east coast and ~50m on the west coast. Reliable site-specific information in shallow waters can only be produced using results from models with higher spatial resolution that include shallow-water physics. Results may not be accurate in the shallower waters of the inner continental shelf.

Significant wave height is a spectrally derived time-series, which is the average of the highest third of the waves in a random seaway and roughly corresponds to the mean wave height. Values are in meters. Data represent monthly summaries for the time period from January 1980 to December 2009 and include the parameters; significant wave height (ssh), wave energy period (wep), and wave hindcast direction (dfp).

Monthly and annual U and V vectors were summarized for 14 unique depth levels from daily means using the HYCOM and NCODA Global 1/12-degree Reanalysis. The U vector (m/s) is to the East and the V vector (m/s) is to the North. Current magnitude (m/s) was calculated using the daily U and V vectors. Descriptive statistics of mean, variance, standard deviations, minimum, and maximum were calculated for each month from the twenty years of data using the daily means (1992-2012). Mean, variance, and standard deviation was calculated for the annual summary period (1992-2012). The mean direction in degrees (with 0 = North) was calculated from the summarized U and V vector means, and represents the direction that the current is moving toward. The 1/12-degree global HYCOM+NCODA Ocean Reanalysis was funded by the U.S. Navy and the Modeling and Simulation Coordination Office. Computer time was made available by the DoD High Performance Computing Modernization Program. The output is publicly available at http://hycom.org.

This dataset represents US states and equivalent territorial units which have at least one coastal border.

These data show bathymetric contours (isobaths) that help characterize the general physiographic patterns of the seafloor. Contour intervals are every 10 m from zero to -100 m, every 25 m from -100 m to -500 m, and every 100 m from -500 m to full depth. The DEM utilized was the Global Multi-Resolution Topography Synthesis which is a multi-resolution gridded global Digital Elevation Model that includes cleaned processed ship-based multibeam sonar data at their full spatial resolution (approximately 100m in the deep sea).

These data show the location of ocean observing assets within U.S. waters, and the physical parameters generally collected at each platform or gauge.

Wave energy period is a sea state parameter, derived from the zeroth and first negative moments of the frequency spectrum. It is the period corresponding to the weighted average of the wave energy. Wave energy period values in this dataset are represented in seconds. The Wave Energy Resource Assessment project is a joint venture between NREL and Virginia Tech. NREL is the prime contractor and Virginia Tech is responsible for development of the models and estimating the wave resource. NREL also serves as an independent validator and also develops the final GIS-based display of the data. Data represent monthly summaries for the time period from January 1980 to December 2009 (30 years) for the following parameters: significant wave height (ssh), wave energy period (wep), and wave hindcast direction (dfp). For complete details regarding this study please read the full report, available here: https://openei.org/datasets/dataset/mapping-and-assessment-of-the-united-states-ocean-wave-energy-resource. A note about the data: Bathymetric effects are known to have a large effect on wave characteristics at depths shallower than approximately 20m (\~65 ft) on the Atlantic coast and 50 m (\~160 ft) on the Pacific coast. A variance between depths exists due to the feature differences for each continental shelf. The methodology used in this resource assessment precludes providing site-specific information to such developers. Reliable site-specific information in shallow waters can only be produced using results from models with higher spatial resolution that include shallow-water physics. The wave resource assessment group acknowledges that its results will not be accurate in the shallower waters of the inner continental shelf. These shallow water regions are located within the dark gray boundaries on the map.

Wave hindcast direction represents the direction of peak in directionally-resolved wave energy flux. Wave hindcast direction values in this dataset are represented in degrees. The Wave Energy Resource Assessment project is a joint venture between NREL and Virginia Tech. NREL is the prime contractor and Virginia Tech is responsible for development of the models and estimating the wave resource. NREL also serves as an independent validator and also develops the final GIS-based display of the data. Data represent monthly summaries for the time period from January 1980 to December 2009 (30 years) for the following parameters: significant wave height (ssh), wave energy period (wep), and wave hindcast direction (dfp). For complete details regarding this study please read the full report, available here: https://openei.org/datasets/dataset/mapping-and-assessment-of-the-united-states-ocean-wave-energy-resource. A note about the data: Bathymetric effects are known to have a large effect on wave characteristics at depths shallower than approximately 20m (\~65 ft) on the Atlantic coast and 50 m (\~160 ft) on the Pacific coast. A variance between depths exists due to the feature differences for each continental shelf. The methodology used in this resource assessment precludes providing site-specific information to such developers. Reliable site-specific information in shallow waters can only be produced using results from models with higher spatial resolution that include shallow-water physics. The wave resource assessment group acknowledges that its results will not be accurate in the shallower waters of the inner continental shelf. These shallow water regions are located within the dark gray boundaries on the map.

This dataset summarizes 2015 Ocean Economy employment statistics for the U.S. coastal states by breaking down each ocean economic indicator per each ocean sector. The dataset also provides percent employment and percent GDP by sector. This percentage is a percent of the ocean sector compared to the total Ocean Economy for each state. This information was harvested from the Economics: National Ocean Watch (ENOW) time-series data on the ocean and Great Lakes economy, derived from the Bureau of Labor Statistics and the Bureau of Economic Analysis. ENOW data measures four economic indicators: Establishments, Employment, Wages, and Gross Domestic Product (GDP) for six economic sectors that are dependent on the oceans and Great Lakes, including: Marine Construction, Living Resources, Offshore Mineral Extraction, Ship and Boat Building, Tourism and Recreation, and Marine Transportation.

These data represent the boundaries of the U.S. Integrated Ocean Observing System (IOOS) eleven regional associations (RAs). There are thousands of ocean observing tools in use every day-satellites in orbit, gliders, buoys, high-frequency radar, sharks with satellite tags, sensors on the ocean floor, and more operated by different organizations and researchers. IOOS, a national-regional partnership, gathers and integrates many of those data streams and makes those observations compatible and accessible by science, industry, government, and citizens. RAs design regional coastal observing systems to meet the unique needs of the regional environment and stakeholders. The eleven IOOS RAs maintain and operate regional coastal observing systems and develop information products for their users. The RAs provide increased observations, distinctive knowledge, and critical technological abilities, and apply these towards the development of products to meet regional and local needs