Pacific Islands Ocean Observing System… |
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Pacific Islands Ocean Observing System (PacIOOS) GeoServer Web Map Service (WMS)
http://geo.pacioos.hawaii.edu/geoserver/PACIOOS/hi_otp_all_wave_anom_max/ows
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- Interface
- Web Service, OGC Web Map Service 1.3.0
- Keywords
- WMS, PacIOOS, IOOS, ocean observing, Pacific, US Affiliated Territories, GeoServer, GeoWebCache
- Fees
- NONE
- Access constraints
- NONE
- Supported languages
- No INSPIRE Extended Capabilities (including service language support) given. See INSPIRE Technical Guidance - View Services for more information.
- Data provider
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Pacific Islands Ocean Observing System (PacIOOS) (unverified)
Contact information:
Pacific Islands Ocean Observing System (PacIOOS)
Pacific Islands Ocean Observing System (PacIOOS)
Work:
University of Hawaii at Manoa, POST Building, Room 815, 96822 Honolulu, USAEmail:
Phone: +1 (808) 956-6556
- Service metadata
- No INSPIRE Extended Capabilities (including service metadata) given. See INSPIRE Technical Guidance - View Services for more information.
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GIS map layers from the Pacific Islands Ocean Observing System (PacIOOS) of the School of Ocean and Earth Science and Technology (SOEST) at the University of Hawaii at Manoa (UH). PacIOOS is one of eleven regional observing programs in the U.S. supporting the Integrated Ocean Observing System (IOOS). The PacIOOS region includes the U.S. Pacific Region (Hawaii, Guam, American Samoa, Commonwealth of the Northern Mariana Islands), the Pacific nations in Free Association with the U.S. (Republic of the Marshall Islands, Federated States of Micronesia, Republic of Palau), and the U.S. Minor Outlying Islands (Howland, Baker, Johnston, Jarvis, Kingman, Palmyra, Midway, Wake). These data are served via GeoServer in a variety of interoperable data services and output formats: http://geo.pacioos.hawaii.edu/geoserver/. See http://geoserver.org for further documentation; and GeoServer's Web Map Service (WMS) documentation at: http://docs.geoserver.org/latest/en/user/services/wms/. Supported map formats include PNG, JPEG, GIF, PDF, GeoTIFF, TIFF, KML/KMZ, AtomPub, GeoRSS, OpenLayers, SVG, UTFGrid, and others. Supported info formats include GeoJSON, GML, HTML, XML, plain text, and others. Please note that cached versions of some of our larger and more complex map layers exist in our GeoServer via GeoWebCache (GWC) using WMS-C. This would be the preferred method of accessing such data layers for improved access speeds: http://geo.pacioos.hawaii.edu/geoserver/gwc/service/wms?request=GetCapabilities&version=1.1.1&tiled=true. Use of WMS-C is similar to traditional WMS but with the addition of the "tiled=true" URL parameter, which triggers GeoServer to pull map tiles from GWC if they have been previously generated or to generate them for future usage if not.
Available map layers (1)
Wave Power Average Annual Maximum Anomaly, 2000-2013 - Hawaii (hi_otp_all_wave_anom_max)
Wave power is a major environmental forcing mechanism in Hawaii that influences a number of marine ecosystem processes including coral reef community development, structure, and persistence. By driving mixing of the upper water column, wave forcing can also play a role in nutrient availability and ocean temperature reduction during warming events. Wave forcing in Hawaii is highly seasonal, with winter months typically experiencing far greater wave power than that experienced during the summer months. This layer represents the annual average of the maximum anomaly of wave power (kW/m) from 2000-2013. Data were obtained from the University of Hawaii at Manoa (UH) School of Ocean and Earth Science and Technology (SOEST) SWAN model (Simulating WAves Nearshore) following Li et al. (2016). Hourly 500-m SWAN model runs of wave power were converted to maximum daily wave power from 1979-2013 and then averaged over each month from 1979-2013, creating a monthly time series from which monthly climatologies were made. Time series of anomalies were calculated by quantifying the number and magnitude of events from the maximum daily data set that exceeded the maximum climatological monthly mean. Pixels were removed directly adjacent to coastlines owing to the model being too coarse to handle extreme refraction and dissipation. Nearshore map pixels with no data were filled with values from the nearest neighboring valid offshore pixel by using a grid of points and the Near Analysis tool in ArcGIS then converting points to raster. The average annual maximum wave power anomaly was calculated by taking the average of the annual maximum wave power values in exceedance of the maximum monthly climatological wave power from 2000-2013 for each 500-m grid cell.
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