A NOAA (AOML) in situ CO2 concentration sensor, attached to a Coral Reef Early Warning System station, utilized in conducting ocean acidification studies near coral reef areas

Effective ecosystem management depends on increasing the speed and accuracy of detecting changes in the distributions of key variables and on reducing the uncertainty of predictions that such changes will occur. This requires both improved models of ecosystem dynamics, and more rapid detection of changes in the variables needed to parameterize and initialize those models. The emergence of integrated ocean and coastal observing systems will help fulfill these needs through delivering near-real time observations of physical, biological, and chemical parameters.

Ocean observing experts identified 20 ocean observing core variables “required to detect and/or predict changes in a maximum number of phenomena of interest to user groups.” Core variables represent the key properties and processes that the U.S. IOOS determined should be measured on a national scale. Subsequent efforts identified six additional core variables. The 26 US IOOS core variables:

Acidity, Bathymetry, Bottom Character, Colored Dissolved Organic Matter, Contaminants, Dissolved Nutrients, Dissolved Oxygen, Fish Abundance, Fish Species, Heat Flux, Ice Distribution, Ocean Color, Optical Properties, Partial Pressure of CO2, Pathogens, Phytoplankton Species, Salinity, Sea Level, Stream Flow, Surface Currents, Surface Waves, Temperature, Total Suspended Matter, Wind Speed and Direction, Zooplankton Abundance, and Zooplankton Species.

However, to fully realize the value of IOOS, there is a need to integrate variables from both federal and non-federal data sources, and identify candidate decision-support tools and models that can be developed or improved through access to integrated data.

Future Developments

  • Need to aggregate a set of standard attributes (e.g., space-time resolution, accuracy, forecast horizons, and timeliness) for operational ocean prediction core variables that can be traced back to user requirements;
  • Summarize attributes of standard observational data (e.g., variables, including topographic, hydrological, meteorological, ecological, etc. data; space-time resolution; and accuracy) needed for multi-disciplinary model forcing, verification, validation, and data assimilation;
  • Identify the data variables and associated requirements (such as temporal, spatial, and quality) needed to improve performance of selected data products and other decision-support tools;
  • Prioritize IOOS core variables for integration based on NOAA’s model and data product requirements.
  • Identify sources, conditions, formats, and transfer protocols of IOOS variables across NOAA and establish functional and

Ultimately full capability for IOOS is the point at which all designated data providers are integrated and making accessible all appropriate, non-classified ocean observing core variables in a U.S. IOOS-compliant manner to end users/customers. U.S. IOOS is a user-driven system linking user needs to required measurements. User needs determine the variables to be measured; the approach to managing, sharing, and analyzing data; and the speed and quality with which data, data products, and services are to be made available to users. This calls for a two-way flow of data and information

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