success stories – making a difference
DESCRIPTION
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. - PowerPoint PPT PresentationTRANSCRIPT
Success Stories – Making a Difference
Optimizing HF Radar for SAR using USCG Surface Drifters
Art Allen U.S. Coast Guard
Josh Kohut, Scott GlennRutgers University
and the Mid-Atlantic RegionalCoastal Ocean Observing System
USCG Area of Responsibility
Mid-Atlantic is the Most Urbanized Coast in the Unites States
Puerto Rico has many similarities
.
Coast Guard Wide
FY CasesLives
Saved
Lives Lost
Before CG
After
CG
Total Unaccounted
for
‘03 31,562 5,104 409 246 655 481
’04 32,517 5,555 502 277 779 676
’05 29,780 5,648 521 320 841 606
’06 28,316 5,260 476 310 786 667
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
Maptech
Spatial - A
3D Analyst
GeoStat - A
HAZMAT
C-Map
Other…
SAROPS Extension
-GUI
-Drift & Resouce allocation modules
EDS
WWW NOAA Navy
SAR Tools Extension
- Flares, Patterns, Etc
(CMF)
CJMTK Mapping Framework
TMS
GEBASE
COP
EXT
MORE
EXT’S
Search And Rescue Optimal Planning System – SAROPS
Search And Rescue Optimal Planning System – SAROPS
SAROPS Computer Screen
Compact CODAR HF Radars
Receive Antenna Transmit Antenna
25 MHz and 13 MHz
5 MHz
MARCOOS
Hurricane Floyd Simulation - 1999 Point Measurement vs. Field of MeasurementsUnited States Coast Guard & Rutgers
Conclusions:
1) 1999 data footprint was too small.
2) Operational decision aids could not use the data.
3) A vision for the future was developed.
Factor of 4Reduction
Factor of 25Reduction
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 Sound2004 - Winds & Tides - Full Continental Shelf
US Coast Guard Self Locating Data Marker Buoy (SLDMB)
Drifters are Tossed Overboard
Expand and Drift with theSurface 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
LostFound 10 days later
Search Plane
Communication Plane
Civil Air Patrol
Glider ru02as seen fromSearch Plane
Lost Glider Recovery: Rutgers, USCG, Civil Air Patrol
Existing HF Radar QA/QC/Metadata Working Groups
www.rowg.org/rowgRowg1: February 2005: Points UnknownRowg2: March, 2006: Charleston SCRowg3: September, 2007: San Diego, CA
www.qartod.orgQ2: Spring, 2005: Norfolk VAQ3: Fall, 2005: San Diego CA
US Coast Guard SAROPS Testbed
In Partnership with - USCG R&D Center - USCG Office of SAR - URI (Dave Ullman) - Rutgers
July 26-September 15 2006
February 24 – April 7 2007
April 30 – June 7, 2007
10 Drifters51 Days
2 Drifters45 Days
6 Drifters30 Days… and counting
Coast GuardSLDMB Drifters
Start
Start
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 ModelsHF Radar Data Assimilation