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Minnett_remote-sensing

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									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
• 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
                  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.
      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.
          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
  –…..
         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.
         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.
         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.
          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.
          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.
          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.
          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.
             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
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
      Water column correction
Original
measured
spectrum at
surface,
water depth
of 2 m.


Modeled
bottom
reflectance
spectrum.
              Acoustic Classification
•Can acoustics augment hyperspectral classification in
optically shallow water?
•Can acoustics substitute for hyperspectral classification in
optically deep water?




                                                    Gleason et al.
Field Studies
  WAAS
   GPS



                                     TSRB
Transducer
& Video




                Echo Sounder
                & Data Acquisition
                (QTCView System V)
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
MODIS images on RSMAS web pages – SST




                                   4µm SST – Night.
                                   December 5, 2002




                 http://www.rsmas.miami.edu/groups/rrsl/modis/
Terra/Aqua Global DAY SST - Sept 29, 2002

                            Terra-day




                             Aqua-day
        Composite Aqua, Terra SST

Aqua, Terra combined orbits nearly eliminate swath gaps
                Night, Sept 29, 2002
Nearly Complete Single Day Coverage
 Composite Night (MODIS-T, MODIS-A)
       Day, Night - (AMSR, TMI)
  Sept 29, 2002, 0.25o spatial resolution
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
MODIS images on RSMAS web pages – Chl-a




                           December 1, 2002
Global Chlorophyll from MODIS




         September 2001
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
  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
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
              Hurricane Isidore’s Cold Wake
  Combined IR, Microwave SST provides daily 0.25 deg resolution
 SST field and the ability to better forecast hurricane intensification

Reynolds Objectively Interpolated SST   Sept 26, 2002 MODIS AQUA, Terra,
week prior to hurricane passage         AMSR, TMI Composite




                                                Isidore

                                                          Cold
                                                          Wake
                             Ocean Upper Heat Content
Reduction 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
            100 W       95       90 W        85 W         80 W
                        W




         30 N




         25 N




                                                                                                           From
         20 N                                                                                         Nick Shay,
                                                                                                        RSMAS-
                                                                                                         MPO &
                                                                                                     Sean White,
                        0       20      40          60           80
                                                                         -2)
                                                                            100   120   140   160
                                                                                                         AOML
                                                         OHC (KJ      cm
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
             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.
Peter Minnett – 305 361 4104
                  pminnett@rsmas.miami.edu

								
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