1 / 35

30 Co-PIs, 20 Institutions

Surface current and wave validation of a nested multi-static regional HF radar network in the Mid-Atlantic Bight. NWS WFOs Std Radar Sites Mesonet Stations LR HF Radar Sites Glider AUV Tracks USCG SLDMB Tracks NDBC Offshore Platforms CODAR Daily Average Currents. Cape Cod to

reina
Télécharger la présentation

30 Co-PIs, 20 Institutions

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Surface current and wave validation of a nested multi-static regional HF radar network in the Mid-Atlantic Bight NWS WFOs Std Radar Sites Mesonet Stations LR HF Radar Sites Glider AUV Tracks USCG SLDMB Tracks NDBC Offshore Platforms CODAR Daily Average Currents Cape Cod to Cape Hatteras: ~1000 km Coastline 30 Co-PIs, 20 Institutions

  2. Regional Theme 1: Maritime Safety – Search And Rescue MARCOOS Regional Observations Before HF Radar Coast Guard SAROPS After HF Radar USCG Weatherflow

  3. USCG Area of SAR Responsibility

  4. SLDMB Deployments1 Jan 2006 – 31 Dec 2007

  5. CG wide SAR Statistics

  6. Search & Rescue Problem • Create a SAR case when alerted

  7. Search & Rescue Problem • Create a SAR case when alerted • Gather information about case

  8. Search & Rescue Problem • Create a SAR case when alerted • Gather information about case • Get environmental data & uncertainties

  9. Search & Rescue Problem • Create a SAR case when alerted • Gather information about case • Get environmental data & uncertainties • Use model to determine search area

  10. Search & Rescue Problem • Create a SAR case when alerted • Gather information about case • Get environmental data & uncertainties • Use model to determine search area • Estimate resource availability and capability

  11. Search & Rescue Problem • Create a SAR case when alerted • Gather information about case • Get environmental data & uncertainties • Use model to determine search area • Estimate resource availability and capability • Plan, promulgate & perform the next search

  12. Search & Rescue Problem • Create a SAR case when alerted • Gather information about case • Get environmental data & uncertainties • Use model to determine search area • Estimate resource availability and capability • Plan, promulgate & perform the next search • Evaluate the completed search

  13. Search & Rescue Problem • Create a SAR case when alerted • Gather information about case • Get environmental data & uncertainties • Use model to determine search area • Estimate resource availability and capability • Plan, promulgate & perform the next search • Evaluate the completed search • Repeat above until survivors are found and rescued

  14. SAROPS Interface

  15. Catalog Server Winds Currents Drifters Weather THREDDS OPeNDAP EDS Catalog DB Web Services Internet SAROPS Client Web Client

  16. Example EDS Data Sources • Winds • FNMOC NOGAPS • FNMOC COAMPS • NOAA NCEP NAM • NOAA NCEP GFS • NOAA NDFD* • NOAA NDBC • Regional Models (e.g GLERL) • Other… commercial • Currents • NAVO Global NCOM • NOAA NCEP HYCOM • NOS Regional • ADCIRC • CODAR • Regional Models • Other… Bluelink, • Satellite Data(AOML), commercial

  17. Example EDS Data Sources • Winds • FNMOC NOGAPS • FNMOC COAMPS • NOAA NCEP NAM • NOAA NCEP GFS • NOAA NDFD* • NOAA NDBC • Regional Models (e.g GLERL) • Other… commercial • Currents • NAVO Global NCOM • NOAA NCEP HYCOM • NOS Regional • ADCIRC • CODAR • Regional Models • Other… Bluelink, • Satellite Data(AOML), commercial

  18. 26 Sites

  19. Regional Theme 1: Maritime Safety Search And Rescue Product Flow Chart MARCOOS QA/QC HF Radar Data STPS, (UConn) SAROPS ROMS (Rutgers) YEAR 1 HOPS (SMAST) YEAR 2 NYHOPS (Stevens)

  20. US Coast Guard SAROPS Testbed Models SAROPS QA/QC Goals: Ensure that data going to Coast Guard is within uncertainty estimates defined in SAROPS Standardize settings among 26 current sites. Continue research on new algorithms/settings

  21. US Coast Guard SAROPS Testbed July 26-September 15 2006 10 Drifters 51 Days February 24 – April 7 2007 2 Drifters 45 Days In Partnership with - USCG R&D Center - USCG Office of SAR - URI (Dave Ullman)

  22. HF radar grid HF radar grid Tuckerton

  23. Drifter to Drifter Comparisons

  24. Abs[Codar-drifter] (cm/s) RMS: 10.24 cm/s R2: 0.62

  25. Total Vector Comparisons East Component RMS: 8.5 cm/s R2: 0.76 NP: 929 North Component RMS: 11.7 cm/s R2: 0.40 NP: 929

  26. Test and Evaluate QA/QC Procedures UNC-CH (Seim and Haines) - First Order Lines - MUSIC Parameters ODU (Garner and Atkinson) - Real-time Diagnostics - Baseline Comparisons Rutgers (Kohut, Roarty, Lichtenwalner) - Merging Algorithm - Antenna Pattern Sensitivity - Nearshore waves and Currents

  27. Test and Evaluate QA/QC Procedures UNC-CH (Seim and Haines) - First Order Lines - MUSIC Parameters ODU (Garner and Atkinson) - Real-time Diagnostics - Baseline Comparisons Rutgers (Kohut, Roarty, Lichtenwalner) - Merging Algorithm - Antenna Pattern Sensitivity - Nearshore waves and Currents

  28. How CODAR Averages… Time Series Cross-spectra Radial Files 11:00 12:00 13:00 RadsSITE_04_04_21_1200

  29. Test and Evaluate QA/QC Procedures Original Algorithm RMS: 11.7 cm/s R2: 0.55 NP: 783 Vector Count Min: 2 Max: 4 Avg: 2.8 New Algorithm RMS: 10.8 cm/s R2: 0.60 NP: 842 Vector Count Min: 3 Max: 12 Avg: 6.8

  30. Test and Evaluate QA/QC Procedures UNC-CH (Seim and Haines) - First Order Lines - MUSIC Parameters ODU (Garner and Atkinson) - Real-time Diagnostics - Baseline Comparisons Rutgers (Kohut, Roarty, Lichtenwalner) - Merging Algorithm - Antenna Pattern Sensitivity - Nearshore waves and Currents

  31. HF Radar derived Wave Evaluation Longterm trends and focused process studies

  32. Transition Through the Storm

  33. Present Algorithm HF Radar derived Wave Evaluation Nearshore bathymetric effects Inversion: deep to shallow (Lipa and Barrick) Linear dispersion vs. depth Refraction: Snell’s Law CODAR In Situ Nearshore Algorithm

  34. Test and Evaluate QA/QC Procedures UNC-CH (Seim and Haines) - First Order Lines - MUSIC Parameters ODU (Garner and Atkinson) - Real-time Diagnostics - Baseline Comparisons Rutgers (Kohut, Roarty, Lichtenwalner) - Merging Algorithm - Antenna Pattern Sensitivity - Nearshore waves and Currents December 2007 – February 2008

  35. Summary MARCOOS is providing regional surface current observations to the Coast Guard through SAROPS MARCOOS will provide regional surface current forecasts to the Coast Guard through SAROPS MARCOOS QA/QC team is continually testing new algorithms to further lower uncertainties of surface current and nearshore wave estimates.

More Related