Data, Products, and Services

 


NOAA IOOS Data Integration Framework


The NOAA IOOS program initiated development of a Data Integration Framework (DIF) to improve management and delivery of an initial subset of ocean observations. The DIF will establish the technical infrastructure, standards, and protocols needed to improve delivery of five of 20 IOOS core oceanographic variables defined in the U.S. IOOS Development Plan.

 

NOAA will complete initial delivery of the DIF in 2010, providing five IOOS core variables from multiple observing system data sources in consistent formats expected to achieve improvements in a select set of NOAA's decision-support tools. To achieve an effective system design that results in measurable improvements in these tools, NOAA must first understand the specific data needs associated with the four decision-support tools (discussed in the Enhancing NOAA's Decision Products section below). The NOAA IOOS program asked developers/users of the four data products to define their specific data requirements associated with an initial set of core variables, as well as other IOOS core variables critical to improve to NOAA’s models and predictions. The program will use this information to help design the DIF and to ensure future system enhancements and expansion beyond the initial core variables develop according to the user needs.


IOOS Core Variables

NOAA chose to focus its initial integration efforts on five IOOS "core variables" describing ocean and coastal conditions:


  • Seawater Temperature;
  • Salinity;
  • Water/Sea level;
  • Currents; and
  • Ocean color.

These five core variables were selected to achieve improvements in four of NOAA's decision tools, discussed below.  However, these data are also important for a wide range of scientific applications.  At a very basic level, measurements of how warm or cold the water is or how much salt is in the water can have significant impacts on the organisms that live in our oceans.  For example, coral reefs are highly sensitive to changes in temperature and can become bleached if temperatures become too warm. 

 

To ensure a high level of quality, tide gauge data are compared to visual observations on a tide staff during NOAAís hydrographic surveys.
To ensure a high level of quality, tide gauge data are compared to visual observations on a tide staff during NOAA's hydrographic surveys.

Water-level measurements are used to monitor and predict the expected location and severity of coastal flooding and storm surge impacts. On a day-to-day basis, these data provide timely measurements of local tides, which are of great importance to the shipping industry. 

 

Measurements of the speed and direction of water flows can be used to track the movement of coastal pollutants and oil spills. The U.S. Coast Guard (USCG) is also able to use surface current data in its search and rescue operations, as this information allows the USCG to narrow its search radius by identifying which direction a ship in distress may have drifted. 

 

Finally, ocean color allows scientists to monitor the presence and concentration of phytoplankton in surface waters when a large quantity of these organisms is concentrated in an area. The resulting plankton "bloom" alters the color of the ocean surface and scientists can observe these changes in color from satellite imagery. Most phytoplankton species are not harmful and provide a food source for other marine organisms.  However, some species are quite toxic and can cause beach and shellfish closures. It is important to monitor for these "harmful algal blooms" to mitigate potential public health impacts.
 

Enhancing NOAA's Decision Products

Harmful algal blooms cause red tides, such as in depicted in this photo of the Florida Gulf Coast.
One type of harmful algal bloom causes "red tides", as depicted in this photo of the Florida Gulf Coast. Red tides can cause beach and shellfish closures and negatively impact Florida's tourism industry. Image courtesy of P. Schmidt, Charlotte (FL) Sun.

Decision-support tools and models used to predict hurricane intensity, coastal flooding, and harmful algal blooms, and to develop integrated ecosystem assessments were targeted as the initial areas of emphasis for NOAA’s IOOS efforts. These four decision tools were selected because they represent high-priority NOAA efforts that align well with many of the societal goals described in the U.S. IOOS Development Plan.

  

As an example, the five IOOS "core variables" play key roles in predicting hurricane intensity. When a hurricane is threatening landfall, emergency officials making evacuation decisions rely on predictions from scientists on how quickly an approaching hurricane will increase in intensity.  Because hurricanes tend to strengthen over warmer water, these scientists require access to as much high-quality and compatible sea surface temperature data as possible in the predicted path of the storm.  IOOS provides the connections among national and regional observing systems to deliver these data. 

 

NEXT: Data Integration Framework Documents

 

(top)