National IOOS High Frequency Radar Search and Rescue Project

The U. S. Integrated Ocean Observing System (IOOS (R)) partners have begun an effort to extend the use of high frequency (HF) radar for U. S. Coast Guard (USCG) search and rescue operations to all U. S. coastal areas with HF radar coverage. This project builds on the success of an IOOS and USCG-supported regional USCG search and rescue product created by Applied Science Associates (ASA), Rutgers University and University of Connecticut for the mid-Atlantic region. We describe the regional product and the expanded national product's two main components: optimally-interpolated velocity fields and a predicted velocity field. The regional product uses optimally-interpolated fields of HF radar-derived ocean surface current component estimates and then an extrapolation in time using local estimates of the autocorrelation function. The forecast fields are the result of a suite of applications known as the Short Term Prediction System (STPS). STPS, originally developed by the University of Connecticut for the USCG, uses a Gauss-Markov approach to compute forecasts of the surface velocity field. The USCG search and rescue operations center began operational access to the regional product in May 2009. Presently, the IOOS national HF radar network is composed of 128 radars covering most of the coastal waters of the U. S. The data from each radar are ingested by a trio of national servers, providing data redundancy and failover capability. To provide further robustness, these servers are widely separated geographically, being located at Scripps Institution of Oceanography in California, Rutgers University in New Jersey and the NOAA National Data Buoy Center in Mississippi. The current project, extending the optimal interpolation and STPS products to all coastal areas, began in FY2011 with the original partners, mentioned above, as well as Scripps Institution of Oceanography which is implementing nationwide the optimal interpolation code (originally developed at SIO) and providing near-real-time HF radar data to ASA, developers of the USCG's data server system. Rutgers University originally implemented, tested and hardened the optimal interpolation software code for the mid-Atlantic region and will test and validate the new codefor the entire East and Gulf coasts. Testing will involve comparisons of the optimally interpolated HF radar data fields with USCG Self-Locating Data Marker Buoys (SLDMB), similar to the well-known Davis drifters and other conventional current measurement sensor data provided by IOOS regional partners. Meanwhile, STPS will be tested throughout those U. S. coastal waters monitored by HF radars. STPS parameters are optimized to ensure realistic regional coastal ocean dynamics are represented in the forecasts. The optimal interpolation software (also known as an objective mapping technique) is applied to the HF radar surface velocity vector field using both observed and idealized covariance matrices. This mapping results in a smoothed vector field and fills in spatial gaps as well. This is in contrast to the conventional widely-used unweighted least squares technique. A further benefit is that the method provides an improved uncertainty estimate of the velocity vector field. Both the gap-filling and the uncertainty estimates will be beneficial for the ingest of HF radar data into the NOAA Office of Response and Restoration's General NOAA Operational Modeling Environment (GNOME). GNOME provides its own prediction algorithms so would not need to use the the STPS. By providing both the optimally-interpolated HF radar-derived surface current velocity fields and the STPS-derived predictions, we will enhance the information available for both USCG coastal search and rescue operations and NOAA's oil spill response operations.