Remote Sensing at RSMAS – a new NESDIS connection Peter J. Minnett Meteorology and Physical Oceanography Rosenstiel School of Marine and Atmospheric Science.

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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.At RSMAS, at least 25 Faculty members involved in satellite remote sensing. In the Department of Physics:In the Department of Physics: –Dr. H. Gordon –Dr. K. Voss At NOAA AOML: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, D OMSAT. 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, D OMSAT. 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, D OMSAT. 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, D OMSAT. 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 S research 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

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

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

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

Examples of relevant S research 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,

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

Composite Aqua, Terra SST Aqua, Terra combined orbits nearly eliminate swath gaps Night, Sept 29, 2002

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

Examples of relevant S research 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 S research 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 Drifting Buoys Explorer cruise tracks that provide bias reference Drifting buoys, used to compute SST equation retrieval coefficients M-AERI cruise tracks, final validation suite

Examples of relevant S research 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 Sept 26, 2002 MODIS AQUA, Terra, AMSR, TMI Composite Reynolds Objectively Interpolated SST week prior to hurricane passage 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 contentCombined IR, µw SST based heat content From Nick Shay, RSMAS- MPO & Sean White, AOML

Examples of relevant S research 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 –