PacIOOS Ocean Gliders: SeaGlider 523: Mission 6

Summary:
As a part of PacIOOS, ocean gliders provide very detailed information about the physical and chemical condition of the waters around the Hawaiian Islands. Additionally, these data get used in computer models to make predictions about ocean conditions. Ocean gliders are small, free-swimming, unmanned vehicles that can cruise the ocean for several months gathering information about the temperature, salinity, and other water properties between the surface and 1000 m depth. A pressure sensor on the glider is able to record the depth throughout the dive. Because gliders are unmanned, they communicate with scientists on land when they are at the surface using an antenna on the end of the glider. The SeaGlider autonomous underwater vehicle (AUV) was designed at the University of Washington (UW) Applied Physics Laboratory (APL). These data are taken from Mission 6 of SeaGlider 523.

cdm_data_type = Trajectory
VARIABLES:
trajectory
glider (seaglider)
time (seconds since 1970-01-01T00:00:00Z)
altitude (m)
latitude (degrees_north)
longitude (degrees_east)
temperature (water temperature, Celsius)
conductivity (S m-1)
salinity (salinity PSU, 1e-3)
density (kg m-3)
pressure (dbar)
dive_number (1)


PacIOOS Water Quality Buoy 04: Hilo Bay, Big Island, Hawaii

Summary:
The water quality buoys are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed points. wqb_04 is located in Hilo Bay on the east side of the Big Island. Continuous sampling of this area provides a record of baseline conditions of the chemical and biological environment for comparison when there are pollution events such as storm runoff or a sewage spill.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (Distance below mean sea level, m)
station_name (station)
temperature (water temperature (processed), Celsius)
salinity (salinity PSU (processed), 1)
turbidity (turbidity FNU (processed), 1)
chlorophyll (chlorophyll (processed), ug/L)
oxygen (dissolved oxygen concentration (processed), mg/L)
oxygen_saturation (dissolved oxygen saturation (processed), %)
ph (pH (processed), 1)
temperature_raw (water temperature (raw), Celsius)
temperature_dm_qd (water temperature delayed-mode quality descriptor, 1)
temperature_qc_agg (QARTOD Aggregate/Rollup Test (processed), 1)
temperature_qc_gap (QARTOD Gap Test (processed), 1)
temperature_qc_syn (QARTOD Syntax Test (processed), 1)
temperature_qc_loc (QARTOD Location Test (processed), 1)
temperature_qc_rng (QARTOD Gross Range Test (processed), 1)
temperature_qc_clm (QARTOD Climatology Test (processed), 1)
temperature_qc_spk (QARTOD Spike Test (processed), 1)
temperature_qc_rtc (QARTOD Rate of Change Test (processed), 1)
temperature_qc_flt (QARTOD Flat Line Test (processed), 1)
... (94 more variables)


PacIOOS Water Quality Buoy 05: Pelekane Bay, Big Island, Hawaii

Summary:
The water quality buoys are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed points. wqb_05 is located in Pelekane Bay near Kawaihae Harbor on the west side of the Big Island. Continuous sampling of this area provides a record of baseline conditions of the chemical and biological environment for comparison when there are pollution events such as storm runoff or a sewage spill.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (Distance below mean sea level, m)
station_name (station)
temperature (water temperature (processed), Celsius)
salinity (salinity PSU (processed), 1)
turbidity (turbidity FNU (processed), 1)
chlorophyll (chlorophyll (processed), ug/L)
oxygen (dissolved oxygen concentration (processed), mg/L)
oxygen_saturation (dissolved oxygen saturation (processed), %)
ph (pH (processed), 1)
temperature_raw (water temperature (raw), Celsius)
temperature_dm_qd (water temperature delayed-mode quality descriptor, 1)
temperature_qc_agg (QARTOD Aggregate/Rollup Test (processed), 1)
temperature_qc_gap (QARTOD Gap Test (processed), 1)
temperature_qc_syn (QARTOD Syntax Test (processed), 1)
temperature_qc_loc (QARTOD Location Test (processed), 1)
temperature_qc_rng (QARTOD Gross Range Test (processed), 1)
temperature_qc_clm (QARTOD Climatology Test (processed), 1)
temperature_qc_spk (QARTOD Spike Test (processed), 1)
temperature_qc_rtc (QARTOD Rate of Change Test (processed), 1)
temperature_qc_flt (QARTOD Flat Line Test (processed), 1)
... (94 more variables)


PacIOOS Water Quality Sensor Partnership Program 002: Kephara, Pohnpei, FSM

Summary:
The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point locations. The PacIOOS Water Quality Sensor Partnership Program (WQSPP) supports scientists and natural resource managers to collect water quality data in order to inform research, conservation, planning, and resource management projects in the U.S. Insular Pacific region. Comprised of a network of "roving" water quality nearshore sensors, the WQSPP provides participating partners with sensors, data management, and technical capacity-building to allow for robust data collection. nss_wqspp_002 was located approximately 1 km north of Kephara Island and 75 meters offshore of the barrier reef along the southwest shore of Pohnpei in the Federated States of Micronesia (FSM). The sensor package was mounted to the sea floor at approximately 40 meters depth. Data were recorded hourly. Dr. Kevin Rhodes of the Micronesia Islands Nature Alliance (MINA) deployed this nearshore sensor within the Kephara Marine Sanctuary near Kephara Island and Black Coral Island to examine environmental parameters in association with grouper (Epinephelidae) spawning aggregations. Water temperature measurements collected by the sensor also served to monitor and reveal triggers for coral bleaching events.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (Distance below mean sea level, m)
station_name (station)
temperature (water temperature (processed), Celsius)
salinity (salinity PSU (processed), 1)
turbidity (turbidity NTU (processed), 1)
chlorophyll (chlorophyll (processed), ug/L)
temperature_raw (water temperature (raw), Celsius)
temperature_dm_qd (water temperature delayed-mode quality descriptor, 1)
salinity_raw (salinity PSU (raw), 1)
salinity_dm_qd (salinity PSU delayed-mode quality descriptor, 1)
... (7 more variables)


PacIOOS Water Quality Sensor Partnership Program 003: Palmyra Atoll

Summary:
The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point locations. The PacIOOS Water Quality Sensor Partnership Program (WQSPP) supports scientists and natural resource managers to collect water quality data in order to inform research, conservation, planning, and resource management projects in the U.S. Insular Pacific region. Comprised of a network of "roving" water quality nearshore sensors, the WQSPP provides participating partners with sensors, data management, and technical capacity-building to allow for robust data collection. nss_wqspp_003 was located approximately 350 meters southwest of Sand Island and 350 meters northwest of Penguin Spit along the western shores of Palmyra Atoll in the equatorial Northern Pacific Ocean. The sensor package was mounted to the sea floor at approximately 4 meters depth. Data were recorded every 7 minutes. The U.S. Fish and Wildlife Service (USFWS), with the help of Dr. Jennifer E. Smith from Scripps Institution of Oceanography of the University of California, San Diego (UCSD), deployed this nearshore sensor at Palmyra Atoll National Wildlife Refuge to support reef recovery efforts. USFWS removed a large shipwreck from Palmyra Atoll in 2013. The shipwreck had devastating impacts on the reef as the wreck's iron fostered the growth of corallimorph, an invasive organism that smothered a large amount of the once healthy reef. Over time, coral diversity diminished and the reef turned into a "black reef", dominated by this single, invasive species. The successful removal of the shipwreck was followed by the removal of invasive species and the restoration of vital coral reef habitat. Post-removal surveys of coral growth, health, and recolonization were conducted, but drastic fluctuations in turbidity due to resuspension and occasional temperature elevations triggered seasonal coral bleaching. Data collected by this sensor helped to increase the understanding of oceanographic conditions and associated impacts for ongoing and future coral reef restoration efforts.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (Distance below mean sea level, m)
station_name (station)
... (18 more variables)


PacIOOS Water Quality Sensor Partnership Program 004: Kewalo Basin, Oahu, Hawaii

Summary:
The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point locations. The PacIOOS Water Quality Sensor Partnership Program (WQSPP) supports scientists and natural resource managers to collect water quality data in order to inform research, conservation, planning, and resource management projects in the U.S. Insular Pacific region. Comprised of a network of "roving" water quality nearshore sensors, the WQSPP provides participating partners with sensors, data management, and technical capacity-building to allow for robust data collection. nss_wqspp_004 was located within the Kewalo Basin Harbor channel entrance approximately 85 meters from Point Panic just offshore of the Kewalo Marine Laboratory of the University of Hawaii at Manoa. Kewalo Basin is located along Oahu's South Shore, situated between Kaka'ako Waterfront Park to its north and popular Ala Moana Beach Park to its south. The sensor package was mounted to the sea floor at approximately 1.5 meters depth. As part of the WQSPP, the Friends of Kewalos (FOK) signed a Memorandum of Understanding (MOU) to receive a PacIOOS nearshore sensor for a limited time. The non-profit organization, whose mission is to protect and preserve Kewalo Basin Park, used the sensor to monitor water quality conditions before and during a construction project in Kewalo Basin Harbor. The Kewalo Basin Pier Repair-Improvement and Boat Slip Addition had the potential to stir up bottom sediments and alter the water quality conditions within the basin and the channel entrance with potential impacts on nearshore and offshore ocean users.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (Distance below mean sea level, m)
station_name (station)
temperature (water temperature (processed), Celsius)
salinity (salinity PSU (processed), 1)
turbidity (turbidity NTU (processed), 1)
chlorophyll (chlorophyll (processed), ug/L)
pressure (water pressure (processed), dbar)
... (13 more variables)


PacIOOS Water Quality Sensor Partnership Program 005: Kahala, Oahu, Hawaii

Summary:
The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point locations. The PacIOOS Water Quality Sensor Partnership Program (WQSPP) supports scientists and natural resource managers to collect water quality data in order to inform research, conservation, planning, and resource management projects in the U.S. Insular Pacific region. Comprised of a network of "roving" water quality nearshore sensors, the WQSPP provides participating partners with sensors, data management, and technical capacity-building to allow for robust data collection. nss_wqspp_005 was located approximately 100 meters offshore of Waialae Beach Park in Kahala along the west side of Maunalua Bay on the South Shore of Oahu in the State of Hawaii. The sensor package was mounted to the sea floor at approximately 1.5 meters depth. As part of the WQSPP, Malama Maunalua was awarded use of this nearshore sensor to enhance water quality monitoring efforts in Maunalua Bay. Malama Maunalua is a community-based, non-profit stewardship organization committed to conserving and restoring a healthy and productive Maunalua Bay. The sensor collected critical parameters at Waialae Stream mouth and stormwater outlet to assess sediment loads and water input. The data helped to inform ongoing work at Paiko Restoration Area, which is adversely impacted by invasive algae. The sensor also complemented the existing PacIOOS sensor on the eastern side of Maunalua Bay (NSS-010) to improve the understanding of bay-wide, land-based inputs.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (Distance below mean sea level, m)
station_name (station)
temperature (water temperature (processed), Celsius)
salinity (salinity PSU (processed), 1)
turbidity (turbidity NTU (processed), 1)
chlorophyll (chlorophyll (processed), ug/L)
pressure (water pressure (processed), dbar)
temperature_raw (water temperature (raw), Celsius)
... (12 more variables)


PacIOOS Water Quality Sensor Partnership Program 006: Ngaremlengui, Babeldoab, Palau

Summary:
The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point locations. The PacIOOS Water Quality Sensor Partnership Program (WQSPP) supports scientists and natural resource managers to collect water quality data in order to inform research, conservation, planning, and resource management projects in the U.S. Insular Pacific region. Comprised of a network of "roving" water quality nearshore sensors, the WQSPP provides participating partners with sensors, data management, and technical capacity-building to allow for robust data collection. nss_wqspp_006 was located at Ngaremlengui dock along the Chometubet River in the village of Ngermetengel on the west coast of the island of Babeldoab in the Republic of Palau. The sensor package was originally mounted to the dock at approximately 1 meter depth but was later redeployed at approximately 2 meters depth on October 8, 2020. Data were recorded every 8 or 10 minutes. The Forest and Watershed Restoration Program of the Ebiil Society of Palau replanted vegetative cover in an upland development area above the dock and adjacent river. As part of the WQSPP, the Ebiil Society deployed this PacIOOS nearshore water quality sensor to monitor sediment run-off in the downstream and reef area and thereby assess the success of the revegetation efforts.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (Distance below mean sea level, m)
station_name (station)
temperature (water temperature (processed), Celsius)
salinity (salinity PSU (processed), 1)
turbidity (turbidity NTU (processed), 1)
chlorophyll (chlorophyll (processed), ug/L)
pressure (water pressure (processed), dbar)
temperature_raw (water temperature (raw), Celsius)
temperature_dm_qd (water temperature delayed-mode quality descriptor, 1)
salinity_raw (salinity PSU (raw), 1)
... (10 more variables)


PacIOOS Water Quality Sensor Partnership Program 007: Dausokele Estuary, Pohnpei, FSM

Summary:
The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point locations. The PacIOOS Water Quality Sensor Partnership Program (WQSPP) supports scientists and natural resource managers to collect water quality data in order to inform research, conservation, planning, and resource management projects in the U.S. Insular Pacific region. Comprised of a network of "roving" water quality nearshore sensors, the WQSPP provides participating partners with sensors, data management, and technical capacity-building to allow for robust data collection. As part of the WQSPP, the Conservation Society of Pohnpei (CSP) deployed a nearshore sensor 170 meters northeast of the Pohnpei International Airport runway within Dausokele Estuary within the lagoon along the northern shores of Pohnpei in the Federated States of Micronesia (FSM). The sensor package was mounted to the sea floor at approximately 9.5 meters depth. Data were recorded every 8 minutes. Land-based sedimentation can have severe impacts on the surrounding watersheds, compromising the water quality and the coastal habitat of coral reefs and fish. Inland development activities have purportedly increased in recent years, prompting the need to monitor sediment run-off from key watersheds. Measuring water quality conditions with an accurate sensor will allow CSP to better understand the variations in water quality during different weather conditions, especially periods of heavy rain.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (Distance below mean sea level, m)
station_name (station)
temperature (water temperature (processed), Celsius)
salinity (salinity PSU (processed), 1)
turbidity (turbidity NTU (processed), 1)
chlorophyll (chlorophyll (processed), ug/L)
pressure (water pressure (processed), dbar)
temperature_raw (water temperature (raw), Celsius)
temperature_dm_qd (water temperature delayed-mode quality descriptor, 1)
... (11 more variables)


PacIOOS Water Quality Sensor Partnership Program 008: Maalaea Harbor, Maui, Hawaii

Summary:
The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point locations. The PacIOOS Water Quality Sensor Partnership Program (WQSPP) supports scientists and natural resource managers to collect water quality data in order to inform research, conservation, planning, and resource management projects in the U.S. Insular Pacific region. Comprised of a network of "roving" water quality nearshore sensors, the WQSPP provides participating partners with sensors, data management, and technical capacity-building to allow for robust data collection. As part of the WQSPP, the Maui Nui Marine Resource Council (MNMRC) deployed a nearshore sensor at Maalaea Harbor, Maui. The non-profit organization is interested to learn more about the effects of tides, wind, and swell on water quality in the harbor, and monitor water quality variability over time. The data will help inform the watershed management plan "Vision for Pohakea", which aims to reduce sediment and pollutants in Maalaea Bay and its harbor. MNMRC is also partnering with Waterkeepers Hawaiian Islands to utilize several thousand oysters in the harbor to help improve water quality. Rotating at approximately monthly intervals to various locations within the harbor, the instrument is a Sea-Bird Scientific SBE 16plus V2 SeaCAT CTD coupled with a Sea-Bird Scientific ECO FLNTU optical sensor.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (Distance below mean sea level, m)
station_name (station)
temperature (water temperature, Celsius)
salinity (salinity PSU, 1)
turbidity (turbidity NTU, 1)
chlorophyll (ug/L)
pressure (water pressure, dbar)
platform1 (platform)
instrument1 (instrument)
crs (coordinate reference system)


PacIOOS Water Quality Sensor Partnership Program 009: Nomilo Fishpond, Kauai, Hawaii

Summary:
The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point locations. The PacIOOS Water Quality Sensor Partnership Program (WQSPP) supports scientists and natural resource managers to collect water quality data in order to inform research, conservation, planning, and resource management projects in the U.S. Insular Pacific region. Comprised of a network of "roving" water quality nearshore sensors, the WQSPP provides participating partners with sensors, data management, and technical capacity-building to allow for robust data collection. As part of the WQSPP, Kauai Sea Farm deployed a nearshore sensor at Nomilo Fishpond along the south shore of Kauai. The fishpond is a naturally-formed resource within an ancient volcanic caldera located in Kalaheo and has a centuries-long history of food production. However, it has been underutilized in the past 100 years and is undergoing a renaissance. To reduce excessive phytoplankton and prevent oxygen depletion events, the seawater channel between the pond and ocean has been restored and shellfish farming has been introduced. A research project is also expected to introduce native sea cucumber aquaculture to better cycle nutrients along the pond bottom. The PacIOOS water quality sensor has been utilized to measure changes in four areas of the pond throughout the 10-month deployment to assist with spatial planning and optimization of aquaculture activities and to determine potential impacts of these activities on the aquatic environment of the fishpond. The instrument is a Sea-Bird Scientific SBE 16plus V2 SeaCAT CTD coupled with a Sea-Bird Scientific ECO FLNTU optical sensor.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (Distance below mean sea level, m)
station_name (station)
temperature (water temperature (processed), Celsius)
salinity (salinity PSU (processed), 1)
turbidity (turbidity NTU (processed), 1)
chlorophyll (chlorophyll (processed), ug/L)
... (4 more variables)


PacIOOS Weather Station: Honolulu Harbor Entrance, Oahu, Hawaii

Summary:
The Pacific Islands Ocean Observing System (PacIOOS) operates a Davis Instruments automatic weather station (AWS) near the entrance to Honolulu Harbor on the leeward (western) coast of Oahu in Hawaii to aid with navigation. The station records measurements every 5 minutes of air temperature, wind speed and direction, precipitation, relative humidity, and air pressure. Sensors are located at Pier 1, installed on a tower at an elevation of 64 feet (19.5 meters) above sea level. The station is owned by the Hawaii Pilots Association (HPA). PacIOOS maintains the station and provides data access.

cdm_data_type = TimeSeries
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
altitude (Distance above mean sea level, m)
station_name (station)
air_temperature (air temperature (processed), Celsius)
wind_speed (wind speed (processed), m/s)
gust_speed (gust speed (processed), m/s)
wind_from_direction (wind direction (processed), degrees)
rainfall_rate (rain rate (processed), mm/h)
relative_humidity (relative humidity (processed), %)
air_pressure (air pressure (processed), millibars)
air_temperature_raw (air temperature (raw), Celsius)
air_temperature_dm_qd (air temperature delayed-mode quality descriptor, 1)
air_temperature_qc_agg (QARTOD Aggregate/Rollup Test (processed), 1)
air_temperature_qc_gap (QARTOD Gap Test (processed), 1)
air_temperature_qc_syn (QARTOD Syntax Test (processed), 1)
air_temperature_qc_loc (QARTOD Location Test (processed), 1)
air_temperature_qc_rng (QARTOD Gross Range Test (processed), 1)
air_temperature_qc_clm (QARTOD Climatology Test (processed), 1)
air_temperature_qc_spk (QARTOD Spike Test (processed), 1)
... (92 more variables)


Regional Ocean Modeling System (ROMS): Guam: 2-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 6-day, 3-hourly forecast for the region surrounding Guam and parts of the Commonwealth of the Northern Mariana Islands (CNMI) at approximately 2-km resolution. Boundary conditions provided by the wider ROMS model for the region surrounding the Western North Pacific (roms_mari) at approximately 4-km resolution. Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding Guam and parts of the Commonwealth of the Northern Mariana Islands (CNMI) (wrf_guam) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Guam: 3-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 6-day, 3-hourly forecast for the region surrounding Guam and parts of the Commonwealth of the Northern Mariana Islands (CNMI) at approximately 2-km resolution. Boundary conditions provided by the wider ROMS model for the region surrounding the Western North Pacific (roms_mari) at approximately 4-km resolution. Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding Guam and parts of the Commonwealth of the Northern Mariana Islands (CNMI) (wrf_guam) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: 2-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 7-day, 3-hourly forecast for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: 3-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 7-day, 3-hourly forecast for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: Data Assimilating: 2-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: Data Assimilating: 3-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: Reanalysis: 2-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 3-hourly data assimilating reanalysis for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: Reanalysis: 3-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 3-hourly data assimilating reanalysis for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Oahu South Shore: 2-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 3-day, 3-hourly forecast for the region surrounding the south shore of the island of Oahu at approximately 200-m resolution. Boundary conditions provided by the wider ROMS model for the region surrounding the island of Oahu (roms_hiog) at approximately 1-km resolution. Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the island of Oahu (wrf_oa) at approximately 1.5-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Oahu South Shore: 3-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 3-day, 3-hourly forecast for the region surrounding the south shore of the island of Oahu at approximately 200-m resolution. Boundary conditions provided by the wider ROMS model for the region surrounding the island of Oahu (roms_hiog) at approximately 1-km resolution. Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the island of Oahu (wrf_oa) at approximately 1.5-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Samoa: 2-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 7-day, 3-hourly forecast for the region surrounding the islands of Samoa at approximately 3-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the islands of Samoa (wrf_samoa) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Samoa: 3-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 7-day, 3-hourly forecast for the region surrounding the islands of Samoa at approximately 3-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the islands of Samoa (wrf_samoa) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Samoa: Data Assimilating: 2-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the islands of Samoa at approximately 3-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the islands of Samoa (wrf_samoa) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Samoa: Data Assimilating: 3-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the islands of Samoa at approximately 3-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the islands of Samoa (wrf_samoa) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Western North Pacific: 2-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 7-day, 3-hourly forecast for the region surrounding the Western North Pacific at approximately 8-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the NOAA/NCEP Global Forecast System (GFS) model for the region surrounding the Western North Pacific at approximately 25-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 5 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations are collected independently of PacIOOS and may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents around Palau from CORDC High Frequency Radars (HFR), Scripps Institute of Oceanography; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Western North Pacific: 3-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 7-day, 3-hourly forecast for the region surrounding the Western North Pacific at approximately 8-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the NOAA/NCEP Global Forecast System (GFS) model for the region surrounding the Western North Pacific at approximately 25-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 5 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations are collected independently of PacIOOS and may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents around Palau from CORDC High Frequency Radars (HFR), Scripps Institute of Oceanography; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Western North Pacific: Data Assimilating: 2-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 5-day, 3-hourly data assimilating hindcast for the region surrounding the Western North Pacific at approximately 8-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the NOAA/NCEP Global Forecast System (GFS) model for the region surrounding the Western North Pacific at approximately 25-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 5 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations are collected independently of PacIOOS and may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents around Palau from CORDC High Frequency Radars (HFR), Scripps Institute of Oceanography; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Western North Pacific: Data Assimilating: 3-D Variables

Summary:
Regional Ocean Modeling System (ROMS) 5-day, 3-hourly data assimilating hindcast for the region surrounding the Western North Pacific at approximately 8-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the NOAA/NCEP Global Forecast System (GFS) model for the region surrounding the Western North Pacific at approximately 25-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 5 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations are collected independently of PacIOOS and may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents around Palau from CORDC High Frequency Radars (HFR), Scripps Institute of Oceanography; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Seatrec infiniTE Float: Deployment 1: CTD: Kona, Hawaii Island, Hawaii

Summary:
The Seatrec infiniTE (Infinite Thermal Energy) float is the first subsurface ocean profiling platform powered by clean, renewable energy to address the power constraints of traditional floats. By combining an autonomous profiling float with a proprietary energy harvesting system, the infiniTE float generates electricity from the ocean's temperature differences to power sensors that are not feasible on existing profiling floats. Its baseline configuration includes a conductivity, temperature, depth (CTD) sensor and can profile three times a day to a depth of approximately 1000 meters.

cdm_data_type = Profile
VARIABLES:
profile_number
time (seconds since 1970-01-01T00:00:00Z)
longitude (degrees_east)
latitude (degrees_north)
depth (m)
temperature (water temperature, Celsius)
salinity (salinity PSU, 1)
energy_used (J)
energy_generated (J)
platform1
instrument1
crs


Shark-Borne Temperature Profiles: Tiger Shark 171406

Summary:
Ocean temperature depth profiles as measured via a tagged tiger shark (Galeocerdo cuvier). Data are transmitted via satellite when the shark's dorsal fin surfaces the water, including ocean temperatures at 15 depths distributed across the most recent ascending profile. The timestamp and spatial coordinates of each surface transmission are assigned to the entire profile.

cdm_data_type = Profile
VARIABLES:
profile_id (profile identifier)
time (surface/transmission time of profile, seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
altitude (m)
temperature (mean temperature, Celsius)
temperature_min (minimum temperature, Celsius)
temperature_max (maximum temperature, Celsius)
location_time (surface/transmission time of latitude/longitude position, seconds since 1970-01-01T00:00:00Z)
location_source (source of latitude/longitude surface position, 1)
location_class (positional accuracy flag, 1)
error_radius (radius in meters of Argos estimated geolocation error, m)
error_semi_major_axis (semi-major axis of Argos estimated geolocation error ellipse, m)
error_semi_minor_axis (semi-minor axis of Argos estimated geolocation error ellipse, m)
error_ellipse_orientation (orientation from true north of Argos estimated geolocation error ellipse, degrees)
fastloc_residual (quality indicator of Fastloc geolocation, 1)
fastloc_time_error (estimated error of observed time of Fastloc geolocation, seconds)
gps_satellites (number of GPS satellites used in Fastloc geolocation, 1)
gps_bad_satellites (number of GPS satellites discarded in Fastloc geolocation, 1)
ptt (Argos PTT tag identifier, 0)
deployment_id (deployment identifier, 0)
species_scientific (species scientific name, 0)
species_common (species common name, 0)
specimen_sex (1)
... (4 more variables)


Shark-Borne Temperature Profiles: Tiger Shark 171409


Shark-Borne Temperature Profiles: Tiger Shark 176025


Shark-Borne Temperature Profiles: Tiger Shark 176027


Shark-Borne Temperature Profiles: Tiger Shark 176028


Shark-Borne Temperature Profiles: Tiger Shark 176029


Shark-Borne Temperature Profiles: Tiger Shark 204412


Shark-Borne Temperature Profiles: Tiger Shark 204413


Shark-Borne Temperature Profiles: Tiger Shark 204414


Shark-Borne Temperature Profiles: Tiger Shark 204416


Shark-Borne Temperature Profiles: Tiger Shark 244397


Shark-Borne Temperature Profiles: Tiger Shark 244399


Shark-Borne Temperature Profiles: Tiger Shark 244400


Shark-Borne Temperature Profiles: Tiger Shark 285442


Simulating WAves Nearshore (SWAN) Regional Wave Model: Big Island

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 7-day output with a 5-day hourly forecast for the Big Island of Hawaii at approximately 500-m resolution. This high-resolution model is utilized to capture shallow water effects and nearshore coastal dynamics such as refracting, shoaling, and smaller scale shadowing. It is run directly after the Hawaii regional WaveWatch III (WW3) wave model (ww3_hawaii) has completed. Please note that some of the nested model setup is still in the testing and validation phase. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, second)
pdir (peak wave direction, degrees)
pper (peak wave period, second)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Big Island, Lon+/-180


Simulating WAves Nearshore (SWAN) Regional Wave Model: Guam

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 7-day output with a 5-day hourly forecast for the island of Guam at approximately 500-m resolution. This high-resolution model is utilized to capture shallow water effects and nearshore coastal dynamics such as refracting, shoaling, and smaller scale shadowing. It is run directly after the Mariana Islands regional WaveWatch III (WW3) wave model (ww3_mariana) has completed. Please note that some of the nested model setup is still in the testing and validation phase. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, second)
pdir (peak wave direction, degrees)
pper (peak wave period, second)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Guam: Apra Harbor

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 7-day output with a 5-day hourly forecast for Apra Harbor on the island of Guam at approximately 50-m resolution. This high-resolution model is utilized to capture shallow water effects and nearshore coastal dynamics such as refracting, shoaling, and smaller scale shadowing. It is run directly after the Mariana Islands regional WaveWatch III (WW3) wave model (ww3_mariana) has completed. Please note that some of the nested model setup is still in the testing and validation phase. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, second)
pdir (peak wave direction, degrees)
pper (peak wave period, second)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Kauai

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 7-day output with a 5-day hourly forecast for the Hawaiian islands of Kauai and Niihau at approximately 500-m resolution. This high-resolution model is utilized to capture shallow water effects and nearshore coastal dynamics such as refracting, shoaling, and smaller scale shadowing. It is run directly after the Hawaii regional WaveWatch III (WW3) wave model (ww3_hawaii) has completed. Please note that some of the nested model setup is still in the testing and validation phase. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, second)
pdir (peak wave direction, degrees)
pper (peak wave period, second)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Kauai, Lon+/-180


Simulating WAves Nearshore (SWAN) Regional Wave Model: Manua, American Samoa

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 7-day output with a 5-day hourly forecast for the Manua Islands (Ofu, Olosega, and Tau) of American Samoa at approximately 275-m resolution. This high-resolution model is utilized to capture shallow water effects and nearshore coastal dynamics such as refracting, shoaling, and smaller scale shadowing. It is run directly after the Samoa regional WaveWatch III (WW3) wave model (ww3_samoa) has completed. Please note that some of the nested model setup is still in the testing and validation phase. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, second)
pdir (peak wave direction, degrees)
pper (peak wave period, second)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Manua, American Samoa, Lon+/-180


Simulating WAves Nearshore (SWAN) Regional Wave Model: Maui

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 7-day output with a 5-day hourly forecast for the Hawaiian islands of Maui County (Maui, Molokai, Lanai, and Kahoolawe) at approximately 500-m resolution. This high-resolution model is utilized to capture shallow water effects and nearshore coastal dynamics such as refracting, shoaling, and smaller scale shadowing. It is run directly after the Hawaii regional WaveWatch III (WW3) wave model (ww3_hawaii) has completed. Please note that some of the nested model setup is still in the testing and validation phase. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, second)
pdir (peak wave direction, degrees)
pper (peak wave period, second)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Maui, Lon+/-180


Simulating WAves Nearshore (SWAN) Regional Wave Model: Oahu

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 7-day output with a 5-day hourly forecast for the Hawaiian island of Oahu at approximately 500-m resolution. This high-resolution model is utilized to capture shallow water effects and nearshore coastal dynamics such as refracting, shoaling, and smaller scale shadowing. It is run directly after the Hawaii regional WaveWatch III (WW3) wave model (ww3_hawaii) has completed. Please note that some of the nested model setup is still in the testing and validation phase. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, second)
pdir (peak wave direction, degrees)
pper (peak wave period, second)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Oahu, Lon+/-180


Simulating WAves Nearshore (SWAN) Regional Wave Model: Palau

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 14-day hourly forecast for the Republic of Palau. The computation utilizes spatial resolution ranging from 3,000 m in the open ocean to 50 m at the shore, with model results interpolated to a 275-m grid for display and archive. This high-resolution model captures key coastal wave processes such as refraction, shoaling, breaking, and shadowing to provide a general indication of the nearshore environment. Boundary conditions are derived from global and regional WaveWatch III models operated by PacIOOS. Global wind forcing and polar ice coverage are provided by NOAA's Global Forecast System (GFS), while astronomical tide levels are defined using the Oregon State University Tidal Prediction Software (OTPS) to modulate wave transmission into reef lagoons. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, various sources of uncertainty and error remain. As such, please use these data with the appropriate caution, especially for activities involving ocean safety or decision-making.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, seconds)
pdir (peak wave direction, degrees)
pper (peak wave period, seconds)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Rota, CNMI

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 7-day output with a 5-day hourly forecast for the island of Rota in the Commonwealth of the Northern Mariana Islands (CNMI) at approximately 550-m resolution. This high-resolution model is utilized to capture shallow water effects and nearshore coastal dynamics such as refracting, shoaling, and smaller scale shadowing. It is run directly after the Mariana Islands regional WaveWatch III (WW3) wave model (ww3_mariana) has completed. Please note that some of the nested model setup is still in the testing and validation phase. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, second)
pdir (peak wave direction, degrees)
pper (peak wave period, second)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Saipan, CNMI

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 7-day output with a 5-day hourly forecast for the islands of Saipan, Tinian, and Aguijan in the Commonwealth of the Northern Mariana Islands (CNMI) at approximately 365-m resolution. This high-resolution model is utilized to capture shallow water effects and nearshore coastal dynamics such as refracting, shoaling, and smaller scale shadowing. It is run directly after the Mariana Islands regional WaveWatch III (WW3) wave model (ww3_mariana) has completed. Please note that some of the nested model setup is still in the testing and validation phase. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, second)
pdir (peak wave direction, degrees)
pper (peak wave period, second)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Tutuila, American Samoa

Summary:
Simulating WAves Nearshore (SWAN) regional wave model 7-day output with a 5-day hourly forecast for the island of Tutuila, American Samoa at approximately 250-m resolution. This high-resolution model is utilized to capture shallow water effects and nearshore coastal dynamics such as refracting, shoaling, and smaller scale shadowing. It is run directly after the Samoa regional WaveWatch III (WW3) wave model (ww3_samoa) has completed. Please note that some of the nested model setup is still in the testing and validation phase. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
mdir (mean wave direction, degrees)
mper (mean wave period, second)
pdir (peak wave direction, degrees)
pper (peak wave period, second)
shgt (significant wave height, meters)


Simulating WAves Nearshore (SWAN) Regional Wave Model: Tutuila, American Samoa, Lon+/-180


SPC/GEM 5-m Bathymetry: RMI: Majuro: Lagoon

Summary:
A 5-m resolution gridded digital elevation model (DEM) for the bathymetry (ocean depth) of the lagoon environment of Majuro Atoll in the Republic of the Marshall Islands (RMI). Compiled from ship-borne multibeam sonar surveys conducted from 2003-2006 by the Pacific Community (SPC) Geoscience, Energy and Maritime (GEM) Division, formerly the South Pacific Applied Geoscience Commission (SOPAC). This work was implemented through the project "Reducing Vulnerability of Pacific States" funded by the European Development Fund. Not to be used for navigational purposes. For a grayscale hillshade image layer of this dataset, see "mh_sopac_maj_bathy_lagoon_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)

SPC Geoscience, Energy and Maritime (GEM) Division


SPC/GEM 50-m Bathymetry: RMI: Majuro: Reef

Summary:
A 50-m resolution gridded digital elevation model (DEM) for the bathymetry (ocean depth) of the eastern reef of Majuro Atoll in the Republic of the Marshall Islands (RMI). Compiled from ship-borne multibeam sonar surveys conducted from 2003-2006 by the Pacific Community (SPC) Geoscience, Energy and Maritime (GEM) Division, formerly the South Pacific Applied Geoscience Commission (SOPAC). This work was implemented through the project "Reducing Vulnerability of Pacific States" funded by the European Development Fund. Not to be used for navigational purposes. For a grayscale hillshade image layer of this dataset, see "mh_sopac_maj_bathy_reef_east_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


SRTM30+ Global 1-km Digital Elevation Model (DEM): Version 11: Bathymetry

Summary:
Global 1-km resolution bathymetry from the 30 arc-second SRTM30+ gridded digital elevation model (DEM). Based on the Smith and Sandwell global 1 arc-minute grid between latitudes +/- 81 degrees. Higher resolution grids have been added from the LDEO Ridge Multibeam Synthesis Project, the JAMSTEC Data Site for Research Cruises, and the NOAA/NCEI Coastal Relief Model. Arctic bathymetry is from the International Bathymetric Chart of the Oceans (IBCAO). For a grayscale hillshade image layer of this dataset, see "world_srtm30plus_bathy1km_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)

Scripps Institution of Oceanography (SIO)


SRTM30+ Global 1-km Digital Elevation Model (DEM): Version 11: Bathymetry, Lon0360


SRTM30+ Global 1-km Digital Elevation Model (DEM): Version 11: Land Surface

Summary:
A global 1-km resolution land surface digital elevation model (DEM) derived from U.S. Geological Survey (USGS) 30 arc-second SRTM30 gridded DEM data created from the NASA Shuttle Radar Topography Mission (SRTM). GTOPO30 data are used for high latitudes where SRTM data are not available. For a grayscale hillshade image layer of this dataset, see "world_srtm30plus_dem1km_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


SRTM30+ Global 1-km Digital Elevation Model (DEM): Version 11: Land Surface, Lon0360


Surface CUrrents from a Diagnostic model (SCUD): Pacific

Summary:
The SCUD data product is an estimate of upper-ocean velocities computed from a diagnostic model (Surface CUrrents from a Diagnostic model). This model makes daily estimates of ocean currents by combining geostrophic and Ekman currents. The estimate is computed through derived coefficients such that the results best match ocean drifting buoys. The currents therefore are a best-estimate of currents at 15 meters (drifting buoys are drogued at 15 meters). The dataset is intended to diagnose trajectories of a tracer floating near the surface such as marine debris, oil spills, etc. The data are provided on a 1/4-degree grid for the Pacific.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
u (sea water velocity: eastward component, meter second-1)
v (sea water velocity: northward component, meter second-1)


Surface CUrrents from a Diagnostic model (SCUD): Pacific, Lon+/-180


Tide Model (Barotropic) for the Pacific Ocean: Tidal Elevation

Summary:
Barotropic tide model for the Pacific Ocean. The model is based on harmonics distributed by Oregon State University (OSU) and assimilates satellite altimetry data from TOPEX/Poseidon. It was generated using OSU Tidal Prediction Software (OTPS), modified locally by J. Potemra, using barotropic inverse tidal solutions from OSU. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
ssh (tidal elevation, meters)


Tide Model (Barotropic) for the Pacific Ocean: Tidal Elevation, Lon+/-180


Tide Model (Barotropic) for the Pacific Ocean: Tidal Velocity

Summary:
Barotropic tide model for the Pacific Ocean. The model is based on harmonics distributed by Oregon State University (OSU) and assimilates satellite altimetry data from TOPEX/Poseidon. It was generated using OSU Tidal Prediction Software (OTPS), modified locally by J. Potemra, using barotropic inverse tidal solutions from OSU. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Tide Model (Barotropic) for the Pacific Ocean: Tidal Velocity, Lon+/-180


Tide Model for the Big Island of Hawaii: Tidal Elevation

Summary:
Tide model for the Big Island of Hawaii. The model is based on climatological stratification, but 64 harmonics are used to model the full-depth baroclinic tides. The model has been run at 1km resolution, hourly, through the end of 2025. Due to computing limitations, the model grid is divided into two pieces, one for the Northwestern main Hawaiian Islands (Kauai, Oahu, Maui) and the other for the Big Island. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
ssh (tidal elevation, meters)


Tide Model for the Big Island of Hawaii: Tidal Velocity

Summary:
Tide model for the Big Island of Hawaii. The model is based on climatological stratification, but 64 harmonics are used to model the full-depth baroclinic tides. The model has been run at 1km resolution, hourly, through the end of 2025. Due to computing limitations, the model grid is divided into two pieces, one for the Northwestern main Hawaiian Islands (Kauai, Oahu, Maui) and the other for the Big Island. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth_percent][latitude][longitude]):
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Tide Model for the Hawaiian Islands: Main NW Islands: Tidal Elevation

Summary:
Tide model for the Hawaiian Islands. The model is based on climatological stratification, but 64 harmonics are used to model the full-depth baroclinic tides. The model has been run at 1km resolution, hourly, through the end of 2025. Due to computing limitations, the model grid is divided into two pieces, one for the Northwestern main Hawaiian Islands (Kauai, Oahu, Maui) and the other for the Big Island. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
ssh (tidal elevation, meters)


Tide Model for the Hawaiian Islands: Main NW Islands: Tidal Velocity

Summary:
Tide model for the Hawaiian Islands. The model is based on climatological stratification, but 64 harmonics are used to model the full-depth baroclinic tides. The model has been run at 1km resolution, hourly, through the end of 2025. Due to computing limitations, the model grid is divided into two pieces, one for the Northwestern main Hawaiian Islands (Kauai, Oahu, Maui) and the other for the Big Island. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth_percent][latitude][longitude]):
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Topography, Smith & Sandwell v11.1, 1/60-degree

Summary:
Global seafloor topography from satellite altimetry and ship depth soundings.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
topo (Topography, meters)


Topography, Smith & Sandwell v11.1, 1/60-degree, Lon0360


UHSLC Fast Delivery Tide Gauge Data (daily)

Summary:
The University of Hawaii Sea Level Center (UHSLC) assembles and distributes the Fast Delivery (FD) dataset of hourly- and daily-averaged tide gauge water-level observations. Tide gauge operators, or data creators, provide FD data to UHSLC after a level 1 quality assessment (see processing_level attribute). The UHSLC provides an independent quality assessment of the time series and makes FD data available within 4-6 weeks of collection. This is a "fast" turnaround time compared to Research Quality (RQ) data, which are available on an annual cycle after a level 2 quality assessment. RQ data replace FD data in the data stream as the former becomes available. This file contains hybrid time series composed of RQ data when available with FD data appended to the end of each RQ series.

cdm_data_type = TimeSeries
VARIABLES:
sea_level (relative sea level, millimeters)
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
station_name
station_country (station country (ISO 3166-1))
station_country_code (station country code (ISO 3166-1 numeric))
record_id (unique identifier for each record (i.e., station and version) in the database)
uhslc_id (unique station ID number used by the University of Hawaii Sea Level Center (UHSLC))
gloss_id (unique station ID number used by the WMO/IOC Global Sea Level Observing System (GLOSS))
ssc_id (unique station ID code in the Sealevel Station Catalog (SSC) produced by the WMO/IOC Sea Level Monitoring Facility (VLIZ))
last_rq_date (date of last Research Quality sea level value, seconds since 1970-01-01T00:00:00Z)


UHSLC Fast Delivery Tide Gauge Data (hourly)


USGS 10-m Digital Elevation Model (DEM): American Samoa: Ofu and Olosega

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the Manua Islands of Ofu and Olosega in American Samoa from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "as_usgs_ofuolo_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): American Samoa: Tau

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the Manua Island of Tau in American Samoa from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "as_usgs_tau_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): American Samoa: Tutuila

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Tutuila in American Samoa from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "as_usgs_tutaun_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): CNMI: Aguijan

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Aguijan in the Commonwealth of the Northern Mariana Islands (CNMI) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "mp_usgs_agu_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): CNMI: Rota

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Rota in the Commonwealth of the Northern Mariana Islands (CNMI) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "mp_usgs_rot_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): CNMI: Saipan

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Saipan in the Commonwealth of the Northern Mariana Islands (CNMI) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "mp_usgs_sai_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): CNMI: Tinian

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Tinian in the Commonwealth of the Northern Mariana Islands (CNMI) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "mp_usgs_tin_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): FSM: Chuuk

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the islands of Chuuk in the Federated States of Micronesia (FSM) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "fm_usgs_chu_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): FSM: Kosrae

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Kosrae in the Federated States of Micronesia (FSM) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "fm_usgs_kos_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): FSM: Pohnpei

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Pohnpei in the Federated States of Micronesia (FSM) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "fm_usgs_poh_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Guam

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Guam from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "gu_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Big Island

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for Big Island in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_bigi_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Kahoolawe

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Kahoolawe in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_kaho_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Kauai

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Kauai in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_kaua_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Lanai

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Lanai in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_lana_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Maui

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Maui in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_maui_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Molokai

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Molokai in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_molo_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Niihau

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Niihau in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_niih_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Oahu

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the island of Oahu in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_oahu_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Palau

Summary:
A 10-meter resolution land surface digital elevation model (DEM) for the islands of Palau from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "pw_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


WaveWatch III (WW3) Global Wave Model

Summary:
Through a collaborative effort with NOAA/NCEP and NWS Honolulu, the University of Hawaii has implemented a global-scale WaveWatch III (WW3) 7-day model with a 5-day hourly forecast at approximately 50-km or 0.5-deg resolution. The global model is forced with NOAA/NCEP's Global Forecast System (GFS) winds. This model is designed to capture the large-scale ocean waves and provide spectral boundary conditions for the Hawaii and other Pacific regional WW3 models. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Tdir (peak wave direction, degrees)
Tper (peak wave period, second)
Thgt (significant wave height, meters)
sdir (swell peak wave direction, degrees)
sper (swell peak wave period, seconds)
shgt (swell significant wave height, meters)
wdir (wind peak wave direction, degrees)
wper (wind peak wave period, seconds)
whgt (wind significant wave height, meters)


WaveWatch III (WW3) Global Wave Model, Lon+/-180


WaveWatch III (WW3) Hawaii Regional Wave Model

Summary:
Through a collaborative effort with NOAA/NCEP and NWS Honolulu, the University of Hawaii has implemented a global-scale WaveWatch III (WW3) model (ww3_global), which in turn provides boundary conditions for this Hawaii regional WW3: a 7-day model with a 5-day hourly forecast at approximately 5-km or 0.05-deg resolution. The primary purpose of this regional model is to capture island effects such as island shadowing, refraction, and accurate modeling of local wind waves. Hawaii WW3 is forced with winds from the University of Hawaii Meteorology Department's operational mesoscale model, which has a more suitable spatial resolution than the global scale wind field. The Hawaii regional WW3 also provides boundary conditions for nearshore island-scale models via Simulating WAves Nearshore (SWAN). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Tdir (peak wave direction, degrees)
Tper (peak wave period, second)
Thgt (significant wave height, meters)
sdir (swell peak wave direction, degrees)
sper (swell peak wave period, seconds)
shgt (swell significant wave height, meters)
wdir (wind peak wave direction, degrees)
wper (wind peak wave period, seconds)
whgt (wind significant wave height, meters)


WaveWatch III (WW3) Hawaii Regional Wave Model, Lon+/-180


WaveWatch III (WW3) Mariana Regional Wave Model

Summary:
Through a collaborative effort with NOAA/NCEP and NWS Honolulu, the University of Hawaii has implemented a global-scale WaveWatch III (WW3) model (ww3_global), which in turn provides boundary conditions for this Mariana Islands regional WW3: a 7-day model with a 5-day hourly forecast at approximately 5-km or 0.05-deg resolution. The primary purpose of this regional model is to capture island effects such as island shadowing, refraction, and accurate modeling of local wind waves. The Mariana regional WW3 also provides boundary conditions for nearshore island-scale models via Simulating WAves Nearshore (SWAN). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Tdir (peak wave direction, degrees)
Tper (peak wave period, second)
Thgt (significant wave height, meters)
sdir (swell peak wave direction, degrees)
sper (swell peak wave period, seconds)
shgt (swell significant wave height, meters)
wdir (wind peak wave direction, degrees)
wper (wind peak wave period, seconds)
whgt (wind significant wave height, meters)


WaveWatch III (WW3) Northwestern Hawaiian Islands (NWHI) Regional Wave Model

Summary:
Through a collaborative effort with NOAA/NCEP and NWS Honolulu, the University of Hawaii has implemented a global-scale WaveWatch III (WW3) model (ww3_global), which in turn provides boundary conditions for this Northwestern Hawaiian Islands (NWHI) regional WW3: a 7-day model with a 5-day hourly forecast at approximately 5-km or 0.05-deg resolution. The primary purpose of this regional model is to capture island effects such as island shadowing, refraction, and accurate modeling of local wind waves. NWHI WW3 is forced with winds from the University of Hawaii Meteorology Department's operational mesoscale model, which has a more suitable spatial resolution than the global scale wind field. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Tdir (peak wave direction, degrees)
Tper (peak wave period, second)
Thgt (significant wave height, meters)
sdir (swell peak wave direction, degrees)
sper (swell peak wave period, seconds)
shgt (swell significant wave height, meters)
wdir (wind peak wave direction, degrees)
wper (wind peak wave period, seconds)
whgt (wind significant wave height, meters)


WaveWatch III (WW3) Northwestern Hawaiian Islands (NWHI) Regional Wave Model, Lon+/-180


WaveWatch III (WW3) Samoa Regional Wave Model

Summary:
Through a collaborative effort with NOAA/NCEP and NWS Honolulu, the University of Hawaii has implemented a global-scale WaveWatch III (WW3) model (ww3_global), which in turn provides boundary conditions for this Samoa regional WW3: a 7-day model with a 5-day hourly forecast at approximately 5-km or 0.05-deg resolution. The primary purpose of this regional model is to capture island effects such as island shadowing, refraction, and accurate modeling of local wind waves. The Samoa regional WW3 also provides boundary conditions for nearshore island-scale models via Simulating WAves Nearshore (SWAN). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Tdir (peak wave direction, degrees)
Tper (peak wave period, second)
Thgt (significant wave height, meters)
sdir (swell peak wave direction, degrees)
sper (swell peak wave period, seconds)
shgt (swell significant wave height, meters)
wdir (wind peak wave direction, degrees)
wper (wind peak wave period, seconds)
whgt (wind significant wave height, meters)


WaveWatch III (WW3) Samoa Regional Wave Model, Lon+/-180