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griddap Subset tabledap Make A Graph wms files Title Summary FGDC ISO 19115 Info Background Info RSS Institution Dataset ID Argo Float Vertical Profiles Argo float vertical profiles from Coriolis Global Data Assembly Centres\n(GDAC). Argo is an international collaboration that collects high-quality\ntemperature and salinity profiles from the upper 2000m of the ice-free\nglobal ocean and currents from intermediate depths. The data come from\nbattery-powered autonomous floats that spend most of their life drifting\nat depth where they are stabilised by being neutrally buoyant at the\n\"parking depth\" pressure by having a density equal to the ambient pressure\nand a compressibility that is less than that of sea water. At present there\nare several models of profiling float used in Argo. All work in a similar\nfashion but differ somewhat in their design characteristics. At typically\n10-day intervals, the floats pump fluid into an external bladder and rise\nto the surface over about 6 hours while measuring temperature and salinity.\nSatellites or GPS determine the position of the floats when they surface,\nand the floats transmit their data to the satellites. The bladder then\ndeflates and the float returns to its original density and sinks to drift\nuntil the cycle is repeated. Floats are designed to make about 150 such\ncycles.\nData Management URL:\n\ncdm_data_type = TrajectoryProfile\nVARIABLES:\nfileNumber (File Number)\ndata_type\nformat_version (File format version)\nhandbook_version (Data handbook version)\nreference_date_time (Date of reference for Julian days, seconds since 1970-01-01T00:00:00Z)\ndate_creation (Date of file creation, seconds since 1970-01-01T00:00:00Z)\ndate_update (Date of update of this file, seconds since 1970-01-01T00:00:00Z)\nplatform_number (Float unique identifier)\nproject_name (Name of the project)\npi_name (Name of the principal investigator)\n... (37 more variables)\n (external link) Argo argoFloats SmartBay Observatory ADCP data The SmartBay Observatory in Galway Bay is an underwater observatory which uses cameras, probes \nand sensors to permit continuous and remote live underwater monitoring. It was installed in 2015 on the seafloor 1.5km off the coast of \nSpiddal, Co. Galway, Ireland at a depth of 20-25m. Underwater observatories allow ocean researchers unique real-time access to monitor \nongoing changes in the marine environment. The Galway Bay Observatory is an important contribution by Ireland to the growing global \nnetwork of real-time data capture systems deployed in the ocean. Data relating to the marine environment at the Galway Observatory site is \ntransferred in real-time through a fibre optic telecommunications cable to the Marine Institute headquarters and then made publically \navailable on the internet. The data includes a live video stream, the depth of the observatory node, the water temperature and salinity, \nand estimates of the chlorophyll and turbidity levels in the water which give an indication of the volume of phytoplankton and other \nparticles, such as sediment, in the water. Maintenance take place on the observatory every 18 to 24 months. A Teledyne RDI Workhorse \nBroadband 600KHz acoustic Doppler current profiler (ADCP ) is mounted on the observatory infrastructure. It is approximately two metres \nabove the seabed, looking up towards the sea surface. Data are collected every minute for 1.0m depth bins from approx. 1 metre above the \ninstrument to the surface. Data are collected in RDI's PD0 binary format (more information is available from the link: \n The .PD0 raw files are processed as they are collected and the real time values for the Near \nSurface and Mid Water Current Speeds and Directions are extracted. The extracted values are displayed in near-real-time on \ The processed data is also provided via an ERDDAP data server allowing the data to be downloaded in a range of open \nformats. The sensor is deployed on the EMSO Smartbay Cable End Equipment Node in Galway Bay in approx. 25m depth of water.\n\ncdm_data_type = Point\nVARIABLES:\ninstrument_id\n... (30 more variables)\n (external link) Marine Institute spiddal_obs_adcp

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