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Remote Sensing at RSMAS – a new NESDIS connection

Remote Sensing at RSMAS – a new NESDIS connection. Peter J. Minnett Meteorology and Physical Oceanography Rosenstiel School of Marine and Atmospheric Science University of Miami. CIMAS Review February 20, 2003. Background.

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Remote Sensing at RSMAS – a new NESDIS connection

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  1. Remote Sensing at RSMAS – a new NESDIS connection Peter J. Minnett Meteorology and Physical Oceanography Rosenstiel School of Marine and Atmospheric Science University of Miami CIMAS Review February 20, 2003

  2. Background • Dr. Eric Bayler, Chief of Ocean Research and Applications at NESDIS intends to establish a new core funding line through CIMAS to support Ocean Remote Sensing at RSMAS. • Activities to support NESDIS objectives. • To complement new Cooperative Institute for Ocean Remote Sensing to be set up at Oregon State University. • Anticipated initial funding ~$250,000 yr-1

  3. Outline • “Critical mass” at RSMAS in several aspects of ocean remote sensing. • Examples of appropriate research topics: • Innovative optical-acoustic remote sensing in shallow water. • MODIS SST and chlorophyll-a developments. • SST validation. • SST application: hurricane prediction. • High resolution winds and waves from X-Band radar on Explorer of the Seas.

  4. RSMAS – UM – AOML • At RSMAS, at least 25 Faculty members involved in satellite remote sensing. • In the Department of Physics: • Dr. H. Gordon • Dr. K. Voss • At NOAA AOML: • Dr. K. Katsaros • A large group on AOML staff members.

  5. Science Teams • RSMAS Faculty serve on • at least 6 NASA Science Teams. • 2 ESA Envisat Science Advisory Groups. • The GODAE High Resolution SST Pilot Project Science Team • …..

  6. Remote sensing strengths • People – expertise, international recognition. • CSTARS – world-class facility. • Inventory of instruments, including ASIS. • Ships – Walton Smith, Explorer of the Seas. • ASIST (Air-Sea Interaction Salt-Water Tank). • High volume data conduits: Internet-2, DOMSAT. • Links with AOML.

  7. Remote sensing strengths • People – expertise, international recognition. • CSTARS – world-class facility. • Inventory of instruments, including ASIS. • Ships – Walton Smith, Explorer of the Seas. • ASIST (Air-Sea Interaction Salt-Water Tank). • High volume data conduits: Internet-2, DOMSAT. • Links with AOML.

  8. Remote sensing strengths • People – expertise, international recognition. • CSTARS – world-class facility. • Inventory of instruments, including ASIS. • Ships – Walton Smith, Explorer of the Seas. • ASIST (Air-Sea Interaction Salt-Water Tank). • High volume data conduits: Internet-2, DOMSAT. • Links with AOML.

  9. Remote sensing strengths • People – expertise, international recognition. • CSTARS – world-class facility. • Inventory of instruments, including ASIS. • Ships – Walton Smith, Explorer of the Seas. • ASIST (Air-Sea Interaction Salt-Water Tank). • High volume data conduits: Internet-2, DOMSAT. • Links with AOML.

  10. Remote sensing strengths • People – expertise, international recognition. • CSTARS – world-class facility. • Inventory of instruments, including ASIS. • Ships – Walton Smith, Explorer of the Seas. • ASIST (Air-Sea Interaction Salt-Water Tank). • High volume data conduits: Internet-2, DOMSAT. • Links with AOML.

  11. Remote sensing strengths • People – expertise, international recognition. • CSTARS – world-class facility. • Inventory of instruments, including ASIS. • Ships – Walton Smith, Explorer of the Seas. • ASIST (Air-Sea Interaction Salt-Water Tank). • High volume data conduits: Internet-2, DOMSAT. • Links with AOML.

  12. Remote sensing strengths • People – expertise, international recognition. • CSTARS – world-class facility. • Inventory of instruments, including ASIS. • Ships – Walton Smith, Explorer of the Seas. • ASIST (Air-Sea Interaction Salt-Water Tank). • High volume data conduits: Internet-2, DOMSAT. • Links with AOML.

  13. NESDIS - CIMAS • Candidate priority areas: • Visible hyperspectral imagery in coastal areas • Atmospheric corrections for ocean color and SST • Validation of SST, for the climate record • Improved coastal forecasting using satellite data • Applications of ocean color data to fisheries • Assimilation of satellite data in ocean models • High resolution wind speeds from SAR and radar scatterometry • Air-sea interaction in the tropical oceans, including absorption of insolation in the water column

  14. Examples of relevant RSMAS research • Hyperspectral measurements in the coastal ocean • SST from MODIS • Chlorophyll from MODIS • Accurate validation of SSTs • Improved coastal forecasting using satellite data • High resolution winds and waves from X-Band Radar

  15. Water column correction Original measured spectrum at surface, water depth of 2 m. Modeled bottom reflectance spectrum.

  16. Acoustic Classification • Can acoustics augment hyperspectral classification in optically shallow water? • Can acoustics substitute for hyperspectral classification in optically deep water? Gleason et al.

  17. Field Studies WAAS GPS TSRB Transducer & Video Echo Sounder & Data Acquisition (QTCView System V)

  18. Examples of relevant RSMAS research • Hyperspectral measurements in the coastal ocean • SST from MODIS • Chlorophyll from MODIS • Accurate validation of SSTs • Improved coastal forecasting using satellite data • High resolution winds and waves from X-Band Radar

  19. MODIS images on RSMAS web pages – SST 4µm SST – Night. December 5, 2002 http://www.rsmas.miami.edu/groups/rrsl/modis/

  20. Terra/Aqua Global DAY SST - Sept 29, 2002 Terra-day Aqua-day

  21. Composite Aqua, Terra SSTAqua, Terra combined orbits nearly eliminate swath gaps Night, Sept 29, 2002

  22. Nearly Complete Single Day CoverageComposite Night (MODIS-T, MODIS-A) Day, Night - (AMSR, TMI) Sept 29, 2002, 0.25o spatial resolution

  23. Examples of relevant RSMAS research • Hyperspectral measurements in the coastal ocean • SST from MODIS • Chlorophyll from MODIS • Accurate validation of SSTs • Improved coastal forecasting using satellite data • High resolution winds and waves from X-Band Radar

  24. MODIS images on RSMAS web pages – Chl-a December 1, 2002

  25. Global Chlorophyll from MODIS September 2001

  26. Examples of relevant RSMAS research • Hyperspectral measurements in the coastal ocean • SST from MODIS • Chlorophyll from MODIS • Accurate validation of SSTs • Improved coastal forecasting using satellite data • High resolution winds and waves from X-Band Radar

  27. In Situ Validation Data • Explorer cruise tracks that provide bias reference • Drifting buoys, used to compute SST equation retrieval coefficients • M-AERI cruise tracks, final validation suite Drifting Buoys

  28. Examples of relevant RSMAS research • Hyperspectral measurements in the coastal ocean • SST from MODIS • Chlorophyll from MODIS • Accurate validation of SSTs • Improved coastal forecasting using satellite data • High resolution winds and waves from X-Band Radar

  29. Hurricane Isidore’s Cold WakeCombined IR, Microwave SST provides daily 0.25 deg resolution SST field and the ability to better forecast hurricane intensification Reynolds Objectively Interpolated SST week prior to hurricane passage Sept 26, 2002 MODIS AQUA, Terra, AMSR, TMI Composite Isidore Cold Wake

  30. Ocean Upper Heat ContentReduction of heat content reduces energy available to support hurricane intensification.Use of low resolution, prior week interpolated data field does not adequately capture reduction of heat content, combined IR/MW SST provides more accurate assessment leading to improved hurricane forecast, using SHIPS. This research is in collaboration with the National Hurricane Center. Reynolds’ SST based heat content Combined IR, µw SST based heat content From Nick Shay, RSMAS- MPO & Sean White, AOML

  31. Examples of relevant RSMAS research • Hyperspectral measurements in the coastal ocean • SST from MODIS • Chlorophyll from MODIS • Accurate validation of SSTs • Improved coastal forecasting using satellite data • High resolution winds and waves from X-Band Radar

  32. Summary We look forward to a new, strong and beneficial link to NESDIS through CIMAS to support research in Satellite Oceanography, to enhance current projects and support new ones.

  33. Peter Minnett – 305 361 4104 pminnett@rsmas.miami.edu

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