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Marine & Aquatic Sensor Arrays Ken Johnson Monterey Bay Aquarium Research Institute
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Sustained, Integrated Ocean Observing Networks Observatories Network Issues Biogeochemical Sensor Systems General Outline:
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Ocean Observatories Initiative Ocean Observatories Initiative Approved by the National Science Board for a Future NSF Budget Includes: Coastal Observatories Plate Scale Observatory Global Mooring Observatory
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Partners University of Washington Woods Hole Oceanographic Institution National Aeronautics & Space AdministrationNational Aeronautics & Space Administration, JPL JPL Monterey Bay Aquarium Research Institute NEPTUNE Canada (IPOST)
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MARS (the Monterey Accelerated Research System). A cabled observatory in Monterey Bay built with NEPTUNE infrastructure as a proof of concept.
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Tropical Atmosphere Ocean project Real-time data from moored ocean buoys for improved detection, understanding and prediction of El Niño and La Niña.
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Issues - Existing ocean observing systems such as TAO & ARGO deal with relatively simple data sets of well known format - e.g. vertical T & Salinity profiles. New sensors cannot be easily fit into the platform or data system. Data transmission from unattended platforms in the middle of the ocean is a problem. ARGO Global Profiling Drifter Array Temp. & Salinity of Ocean Interior
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E.g., the MBARI OASIS System - Now two moorings in Monterey Bay & two in the equatorial Pacific. M2 M1
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MBARI OASIS Moorings The OASIS moorings communicate by ARGOS, microwave or packet radio. Adding new sensors becomes a large software configuration issue, particularly for complicated sensors.
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M1 Mooring Configuration Schedule 07/03 Initial configuration meeting 08/02 Final science list 08/03 Evaluate configuration 08/04 Instruments on hand for testing 08/07 Assemble instruments & configure - 5 days 08/14 Configure software - 15 days 09/04 Software test - 5 days 09/11 Close controller and install - 5 days 09/19 Complete system test - 5 days 09/28 Data download test - 1 day 10/04 Deploy mooring & cross your fingers
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Software Infrastructure for the MBARI Ocean Observing System Tom O’Reilly Duane Edgington
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MOOS software Application software for sensors, user interfaces, databases, etc. Distributed applications are “glued” together by smart network infrastructure
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Smart network Self-organizing; applications are notified by infrastructure when network configuration changes –E.g., database ingest engine always “aware” of available sensors Enables automatic configuration, remote control, and autonomous coordination of sensors
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Network configuration “Just plug the sensor in, and it works!” Easily replace, remove, or add a new kind of sensor Remote update of sensor’s driver software Minimal configuration effort by human operators lower maintenance cost
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Leading technology candidates CORBA Java - JINI LonWorks Universal Plug-n-Play
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What kind of data will we assimilate in global observing systems? Physical, geophysical observations (T, S, seismicity) - generally sensors are mature. Chemical - nutrients (nitrate, phosphate, iron), gases (carbon dioxide, oxygen) - sensors exist but have not gone commercial. Biological - bio-optical systems are mature, but not very specific. DNA based systems are beginning to appear.
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In Situ Ultraviolet Spectrophotometry
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Measurement of pCO 2 from Moorings: Gernot Friederich Peter Walz Mike Burzcynski Francisco Chavez all at MBARI
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El Niño / La Niña Cycle in Monterey Bay PCO2 (sea - air) atm Temperature
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DNA Based Detection of Phytoplankton Species Using the Environmental Sample Processor (ESP) Chris Scholin Roman Marin Gene Massion all at MBARI NOTE: The entire phytoplankton standing stock of the ocean turns over each 4 days on average!
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Sandwich hybridization bioassay of rRNA in phytoplankton
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Iron (nM) Pseudo-nitzschia australis (cells/L) Does iron regulate toxic plankton blooms (e.g., Wells et al., Evaluation of iron as a triggering factor for red tide blooms. MEPS, 69, 93, 1991)?
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MOOS will be operational in 2003 for biogeochemical studies.
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