Success Stories – Making a Difference Optimizing HF Radar for SAR using USCG Surface Drifters Art Allen U.S. Coast Guard Josh Kohut, Scott Glenn Rutgers.

Slides:



Advertisements
Similar presentations
GPS-Cellular Drifter Technology for Coastal Ocean Observing Systems
Advertisements

The Evolution of the 2007 Mid-Atlantic Cold Pool W. S. Brown University of Massachusetts at Dartmouth O. Schofield, S. Glenn, & J. Kohut Rutgers University.
The Search and Rescue Problem MARACOOS Fisheries Workshop 26 September 2011 Arthur Allen U.S. Coast Guard Office of Search and Rescue
Ocean Connections: Mapping potential pathways between the spill in the Gulf of Mexico and the Jersey Shore Dr. Josh Kohut Rutgers University School of.
What happens when the ship hits the fan. By Laura Harrison June 12 th, 2006 Geography 163.
Phased Deployment and Operation of the Mid-Atlantic Regional Coastal Ocean Observing System (MARCOOS) Project Duration: 3 years; currently starting year.
MARCOOS Data Initialization Technique GSMR GOMFM Shelf Operational Modeling using HOPS Next steps – Validation and Assimilation.
-101 MACOORA Annual Meeting October 22-23, 2008 Dartmouth, Massachusetts Presenters: Scott Glenn & Josh Kohut.
Search and Rescue Optimal Planning System
Success Stories – Making a Difference Optimizing HF Radar for SAR using USCG Surface Drifters Art Allen U.S. Coast Guard Josh Kohut, Scott Glenn Rutgers.
National Science Foundation Ocean Observing Initiative Cyber Infrastructure Implementing Organization Observing System Simulation Experiment NSF OOI CI.
Cape Cod to Cape Hatteras: ~1000 km Coastline Results from the Mid Atlantic High Frequency Radar Network Hugh Roarty, Ethan Handel, Erick Rivera, Josh.
InvestigatorAffiliationInvestigatorAffiliation A. AllenU.S. Coast GuardL. AtkinsonOld Dominion University A. F. BlumbergStevens Institute of Technology.
Welcome MACOORA Annual Meeting October 22-23, 2008 Fall River, Massachusetts Carolyn Thoroughgood.
User Needs for data Oil Spills Search & Rescue IOOS Demo Project Eoin (Owen) Howlett ASA Inc. Narragansett, RI SECOORA/SEACOOS Workshop.
Search and Rescue Optimal Planning System
Coastal Ocean Observation Lab John Wilkin, Hernan Arango, John Evans Naomi Fleming, Gregg Foti, Julia Levin, Javier Zavala-Garay,
Development of a Dual-Use Over-The Horizon Radar Network for Monitoring Ocean Currents and Ship Traffic in the Exclusive Economic Zone Scott M. Glenn Coastal.
National Center for Secure and Resilient Maritime Commerce and Coastal Environments (CSR) CSR Scott Glenn, Hugh Roarty Rutgers University Washington DC.
The Gulf of Maine Ocean Observing System. Technical Program Real time monitoring and forecasts of: Weather - surface ocean winds, air temperature, visibility.
Canadian Coast Guard Automated Search Planning B. F. Stone.
Using Ocean Observing Systems & Real Time Data to monitor and clean up Oil Spills.
Cape Cod Cape Hatteras NJ MA CT VA DE NY NC RI MD PA M ID - A TLANTIC R EGIONAL A SSOCIATION C OASTAL O CEAN O BSERVING S YSTEM 1000 km Cape to Cape RAISING.
The goal is to access the right information, in the right format, at the right time, for the right people, to make the right decisions. WHY WE CARE about.
National High Frequency Radar Network Jack Harlan, Ph. D. NOAA IOOS Program Office Project Manager: HF Radar DHS Training 21 Apr 2010 Washington, DC.
The Big I in LIS I COS : A Brief History of the Development of a Coastal Observing System and Some Interesting Products James O’Donnell University of Connecticut.
. Tracking Uncertainty in Search and Rescue Planning Art Allen U.S. Coast Guard Office of Search and Rescue
Ligurian Sea Mid-Atlantic Bight Results from the Mid Atlantic High Frequency Radar Network Radar Network Hugh Roarty, Scott Glenn, Josh Kohut, Erick Rivera,
. SAROPS EDS Environmental Data Server Art Allen United States Coast Guard – Office of Search & Rescue Eoin (Owen) Howlett ASA.
CODAR Ben Kravitz September 29, Outline What is CODAR? Doppler shift Bragg scatter How CODAR works What CODAR can tell us.
Super-Regional Modeling Testbed to Improve Forecasts of Environmental Processes for the U.S. Atlantic and Gulf of Mexico Coasts Super-Regional Modeling.
U.S. IOOS ® HF Radar Network 10 Years of Experience Measuring Ocean Surface Currents Jack Harlan, Ph.D. U.S. Integrated Ocean Observing System (IOOS ®
A Survey of Existing Mid-Atlantic Regional Association Coastal Ocean Observing System MARACOOS Assets Wendell Brown UMass Dartmouth School for Marine Science.
Using A Fleet of Slocum Battery Gliders in a Regional Scale Coastal Ocean Observatory Elizabeth L. Creed, Chhaya Mudgal, Scott M. Glenn and Oscar M. Schofield.
MACOORA The Mid-Atlantic Coastal Ocean Observing Regional Association Annual Membership Meeting and Luncheon Address October 28, 2010 Carolyn.
SCCOOS Goals and Efforts Within COCMP, SCCOOS aims to develop products and procedures—based on observational data—that effectively evaluate and improve.
InvestigatorAffiliationInvestigatorAffiliation A. AllenU.S. Coast GuardL. AtkinsonOld Dominion University A. F. BlumbergStevens Institute of Technology.
Surface Current Mapping in the Lower Chesapeake Bay INTRODUCTION High frequency RADAR antennas are used to observe the surface circulation patterns in.
Potential impact of HF radar and gliders on ocean forecast system Peter Oke June 2009 CSIRO Marine and Atmospheric Research.
Application of Radial and Elliptical Surface Current Measurements to Better Resolve Coastal Features  Robert K. Forney, Hugh Roarty, Scott Glenn 
Ocean Surface Current Observations in PWS Carter Ohlmann Institute for Computational Earth System Science, University of California, Santa Barbara, CA.
Mr. Robert Forney Dr. Hugh Roarty Dr. Scott Glenn Measuring Waves with a Compact HF Radar MTS/IEEE OCEANS15 October 2015 Washington DC.
ASSIMILATION OF HIGH-FREQUENCY RADAR SURFACE CURRENTS INTO A COASTAL OCEAN MODEL OF THE MIDDLE ATLANTIC BIGHT Alan F. Blumberg George Meade Bond Professor.
1 A multi-scale three-dimensional variational data assimilation scheme Zhijin Li,, Yi Chao (JPL) James C. McWilliams (UCLA), Kayo Ide (UMD) The 8th International.
Maracoos DMAC and Asset Map June Maracoos DMAC Principles Data is served and integrated using open, interoperable data standards recommended by.
CODAR Surface Current Maps Improve Coast Guard Search And Rescue Nearest Coastal Site CODAR Currents SLDMB Drifter SAROPS NowSAROPS w/ HFR Surface Currents.
From Regional and National to Global 1. Ocean observations for societal benefit Climate, operational ocean services, ocean health USA Committee for the.
Surface Current Mapping in the Lower Chesapeake Bay INTRODUCTION High frequency RADAR antennas are used to observe the surface circulation patterns in.
User Needs for data Oil Spills Search & Rescue IOOS Demo Project Eoin (Owen) Howlett ASA Inc. Narragansett, RI SECOORA/SEACOOS Workshop.
CASE #3: Floating Away The Situation: While entering New York Harbor, several boxes of rubber ducks fell off their cargo ship. Using the data provided,
Real-Time Beyond the Horizon Vessel Detection
Results from the Mid Atlantic High Frequency Radar Network
National High Frequency Radar Network
Forecasting Drifting Objects
Mid-Atlantic Blue Ocean Economy 2030
MARACOOS High Frequency Radar Network Operations
Bistatic Systems: Preparing for Multistatic
Hugh Roarty, Michael Smith, Ethan Handel and Scott Glenn
Robert K. Forney, Hugh Roarty, Scott Glenn March 5th, 2015
Colin Evans, Hugh Roarty, Scott Glenn, Josh Kohut
Quality Assurance Measures for High Frequency Radar Systems
Analysis of the Wind Resource off New Jersey for Offshore Wind Energy Development Hugh Roarty, Joe Riscica, Laura Palamara, Louis Bowers, Greg Seroka,
Recognizing First and Second Order Features
October 27, 2011 New Brunswick, NJ
Priorities for Next Steps in the ASAP Research program
An Ocean Current Monitoring System for Coastal New Jersey
Offshore Atmospheric and Ocean Monitoring to Support DEEPWATERwind’s Offshore Wind Energy Project Development and Operations Rich Dunk, Ph.D.,
A Multi-static HF Radar Network for the
Observing the Ocean from the Rutgers University “COOL Room”
Coastal Ocean Dynamics Radar (CODAR) Mapping of
Presentation transcript:

Success Stories – Making a Difference Optimizing HF Radar for SAR using USCG Surface Drifters Art Allen U.S. Coast Guard Josh Kohut, Scott Glenn Rutgers University and the Mid-Atlantic Regional Coastal Ocean Observing System

USCG Area of Responsibility

Mid-Atlantic is the Most Urbanized Coast in the Unites States Puerto Rico has many similarities

CG Wide 1) 3 searches / day = ~ 1000 / yr 2) 3 persons lost / day = ~ 1000 / yr 3) Costs $10k/hr to search $10k/hr x ~1000 x ~ 3 hr = ~ $30M 4) Value of Statistical Life = $3M 1000 x $3M = ~ $3B

CG Wide 1) Assume 100 persons involved / yr with sub-optimal search areas 2) Assume 22% POS now “typical” 3) 22 save/100 vs. 48/100 vs. 67/100 4) Save 26 to 45 additional persons / yr ($ 78M – $135M VSL)

Search & Rescue Problem Create a SAR case when alerted Gather data, estimate uncertainties Use model to determine search area Estimate resource availability and capability Plan the next search Promulgate the search plan Perform the search plan Evaluate the completed search Repeat above until survivors are found and rescued

Compact CODAR HF Radars Receive Antenna Transmit Antenna 25 MHz and 13 MHz 5 MHz

MARCOOS

Arthur Allen, Chris Turner, Marion Lewandowski, Paul Hall, Eoin Howlett, Dave Ullman, Jim O’Donnell, Todd Fake, Josh Kohut, Hugh Roarty, Scott Glenn Integration of CODAR and UConn Statistical Forecasts with SAROPS 2002 – Tidally Dominated – Long Island Sound Winds & Tides - Full Continental Shelf

US Coast Guard Self Locating Data Marker Buoy (SLDMB) Drifters are Tossed Overboard Expand and Drift with the Surface currents Positions transmitted to Shore via satellite

Nearest Coastal Site CODAR Currents SLDMB Drifter Long Island Sound (2002) New Jersey Shelf (2004) Comparison of Actual Drifter Tracks with CODAR Data

Nearest Coastal Site CODAR Currents SLDMB Drifter Long Island Sound (2002) New Jersey Shelf (2004) Comparison of Actual Drifter Tracks with CODAR Data

Lost Found 10 days later Search Plane Communication Plane Civil Air Patrol Glider ru02 as seen from Search Plane Lost Glider Recovery: Rutgers, USCG, Civil Air Patrol

Statistical Model STPS – U. Connecticut Dynamical Models NYHOPS – Stevens Institute of Technology ROMS – Rutgers University HOPS – U. Massachusetts, Dartmouth All 4 forecasts will be evaluated for inclusion in the USCG search planning tool, SAROPS MARCOOS Forecast Models HF Radar Data Assimilation