remote sensing at rsmas – a new nesdis connection

Remote Sensing at RSMAS Remote Sensing at RSMAS – a new NESDIS connection– a new NESDIS connection

Peter J. MinnettMeteorology and Physical Oceanography

Rosenstiel School of Marine and Atmospheric ScienceUniversity of Miami

CIMAS ReviewFebruary 20, 2003

BackgroundBackground

• 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

OutlineOutline• “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 – AOMLRSMAS – UM – AOML

• At RSMAS, at least 25 Faculty members At RSMAS, at least 25 Faculty members involved in satellite remote sensing.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 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 strengthsRemote 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 strengthsRemote 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 strengthsRemote 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 strengthsRemote 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 strengthsRemote 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 strengthsRemote 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 strengthsRemote 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 - CIMASNESDIS - 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 Examples of relevant RSMAS researchS 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 measuredspectrum at surface, water depth of 2 m.

Modeledbottom reflectancespectrum.

Water column correctionWater column correction

•Can acoustics augment hyperspectral classification in optically shallow water?

•Can acoustics substitute for hyperspectral classification in optically deep water?

Acoustic ClassificationAcoustic Classification

Gleason et al.

Field StudiesField Studies

TSRB

Echo Sounder& Data Acquisition(QTCView System V)

Transducer& Video

WAASGPS

Examples of relevant Examples of relevant RSMAS researchS 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 – SSTMODIS images on RSMAS web pages – SST

4µm SST – Night.

December 5, 2002

http://www.rsmas.miami.edu/groups/rrsl/modis/

Aqua-day

Terra-day

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

Composite Aqua, Terra SSTComposite Aqua, Terra SST

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

Nearly Complete Single Day CoverageNearly Complete Single Day CoverageComposite Night (MODIS-T, MODIS-A)

Day, Night - (AMSR, TMI) Sept 29, 2002, 0.25o spatial resolution

Examples of relevant Examples of relevant RSMAS researchS 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-aMODIS images on RSMAS web pages – Chl-a

December 1, 2002

Global Chlorophyll from MODISGlobal Chlorophyll from MODIS

September 2001

Examples of relevant Examples of relevant RSMAS researchS 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 DataIn 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 Examples of relevant RSMAS researchS 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 WakeHurricane Isidore’s Cold WakeCombined IR, Microwave SST provides daily 0.25 deg resolution Combined IR, Microwave SST provides daily 0.25 deg resolution

SST field and the ability to better forecast hurricane intensificationSST 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

ColdWake

Ocean Upper Heat ContentOcean Upper Heat Content

Reduction of heat content reduces energy available to support hurricane intensification.Reduction of heat content reduces energy available to support hurricane intensification.Use of low resolution, prior week interpolated data field does not adequately capture 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 reduction of heat content, combined IR/MW SST provides more accurate assessment leading to improved hurricane forecast, using SHIPS. This research is in collaboration leading to improved hurricane forecast, using SHIPS. This research is in collaboration

with the National Hurricane Center.with the National Hurricane Center.

100 W 95 W

90 W 85 W 80 W

20 N

25 N

30 N

0 20 40 60 80 100 120 140 160

OHC (KJ cm-2)

Reynolds’ SST based heat content Combined IR, µw SST based heat content

FromNick Shay,

RSMAS-MPO &

Sean White, AOML

Examples of relevant Examples of relevant RSMAS researchS 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

SummarySummary

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