ONR Sponsored Research at the Long-term Ecosystem Observatory (LEO-15)

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ONR SponsoredResearch at the Long-term
Ecosystem Observatory (LEO-15)
Coastal Ocean Modeling and Observation Program
Real-Time Adaptive Sampling Networks Scott M.
Glenn, Dale B. Haidvogel, Oscar M.E. Schofield
Hyperspectral Remote Sensing of the Coastal
Ocean Adaptive Sampling and Forecasting of
Nearshore in situ Optical Properties Oscar M. E.
Schofield, Scott M. Glenn, Dale B. Haidvogel, J.
Fred Grassle, Mark A. Moline, Paul Bissett
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NOPP ResearchProjects at the Long-term
Ecosystem Observatory (LEO-15)

• 1998 Multi-Scale Model-Driven Sampling with
  Autonomous Systems at a National Littoral
  Laboratory
• J. Frederick Grassle, Scott M. Glenn, Dale B.
  Haidvogel, Christopher J. von Alt, Edward R.
  Levine, Donald E. Barrick, Belinda J. Lipa and
  Joel W. Young
• 1999 Demonstration of a Relocatable Regional
  Ocean/Atmosphere Modeling System with Coastal
  Autonomous Sampling Networks
• Scott M. Glenn, Dale B. Haidvogel, Roni Avissar,
  J. Frederick Grassle, Oscar M. E. Schofield,
  Christopher J. von Alt, Edward R. Levine, Douglas
  C. Webb, Donald E. Barrick, Belinda J. Lipa, Joel
  W. Young, Richard P. Signell

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ONR/NOPP Objectives

• Establish a National Littoral Laboratory
• Deploy a Real-Time Multi-Disciplinary Coastal
  Ocean Observatory
• Develop a Data-Assimilative Coupled
  Ocean-Atmosphere Coastal Forecast Model
• Encourage Community Involvement Through an
  Open-Access Architecture

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ONR/NOPP Objectives

• Operate the System in a Continuing Series of
  Coastal Predictive Skill Experiments
• 1998 - Improve Nowcast Skill
• Assimilation of remote sensing surface data, and
• Shipboard/AUV adaptive sampling subsurface data
• 1999 - Improve Forecast Skill
• Improved surface, bottom and lateral boundary
  conditions
• New turbulent closure schemes
• Physical/bio-optical adaptive sampling with ships
  and AUVs

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Scientific Objectives

• Multi-Disciplinary Studies of Coastal Upwelling
  on a Highly Stratified, Shallow, Wide Shelf
• 3-D Structure, Evolution and Dynamics of the
  Recurrent Upwelling Centers and their
  Interactions with Topography
• Effects on Biological/Chemical Processes
  Including Phytoplankton, Zooplankton and Larval
  Distributions, and Hypoxia
• Effects of Biology and Sediment Transport on
  Ocean Color and Visibility

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The Challenge

• Shelf waters deeper than 3 meters and shallower
  than about 30 meters have often been ignored in
  the past because of the very difficult operating
  conditions and the complex dynamics, where the
  water is filled with turbulent boundary layers.
• Ken H. Brink 12/12/97
• Observational Coastal Oceanography
• National Science Foundation OCE Workshops
• http//www.joss.ucar.edu/joss_psg/project/oce_work
  shop

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AVHRR Met Tower Nodes BASS Towed Vehicle -
Flight Tests REMUS - Flight Tests Optical
Sampling Tests
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SeaWiFS RADARSAT AVIRIS CODAR ADCP/Thermistor REMU
S - Survey REMUS - Docking REMUS - Turbulence
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SODAR Met Buoy Optical Node Optical Vessel Webb
Glider Freewave Communications Thermistor
Strings Underwater Video
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Ocean Color Products
Remote sensing reflectance at wavelength 412,
443, 490, 510, 555 and 670 nm Diffuse attenuation
coefficient at 532 nm by Mueller Surface albedo
measured at 865 nm Chlorophyll a concentration by
Rick Stumpf Absorption at wavelength 412 nm due
to dissolved organics Absorption at wavelength
443 nm due to phytoplankton Absorption at
wavelength 412, 443, 490, 510, 555 and 670 nm by
Robert Arnone Backscatter at 443 and 555 nm by
Robert Arnone Chlorophyll a concentration by
Kendall Carder Absorption at wavelength 412, 443,
490, 510, 555 and 670 nm by Kendall
Carder Absorption at wavelength 412 nm due to
dissolved organics by Kendall Carder Absorption
at wavelength 443 nm due to phytoplankton by
Kendall Carder Backscatter at 443 and 555 nm by
Kendall Carder Attenuation at 670 nm by Kendall
Carder SeaDas Products Upwelling/Nonwelling
radiance at 670 and 865 nm Chlorophyll a
concentration Coastal Zone Color Scanner Diffuse
attenuation at 490 nm Water leaving radiance at
412, 443, 490 510 and 555 nm Normalized
difference vegetation index Optical Depth at 865
nm
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LEO-15 Coastal Area
Field Station
Different bottom types and/or depth?
Great Bay
Little Egg Inlet
Bottom features
Surface, bottom and/or suspended
sediment features?
Brigantine Inlet
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Suspended Sediment and Bottom MaskAlgorithms
Applied to LEO-15 Image
Suspended Sediment Algorithm
Bottom Algorithm
Courtesy of Curtiss Davis at NRL
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FutureOcean Color SatelliteConstellation
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Radarsat Imagery
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Sea Surface Height (m) and Surface Currents
(cm/s) - 20 July, 1998
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NASAFundedBistaticGPS Altimeter
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NASA FundedInstrument Incubator
ProgramDelay-DopplerAltimeter
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Delay-Doppler Altimeter Satellite
Solar Panel
TTC Antenna
GPS Antenna
Propulsion
Altitude Control Component
Star Tracker
Miniaturized IEM
WVR Cold Horns
RA/WVR Antenna Reflector
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WITTEX Concept
Water Inclination Topography and Technology
Experiment Witte (1878)

• Multiple (e.g. 3) altimeters in
• one orbit plane.
• One launch vehicle deploys
• all altimeters.
• Small satellites enabled by
• delay-Doppler altimeter
• technology.
• Less transmit power (1/10)
• Smaller along-track footprint (250 m)
• Near-shore data (1 km)
• Better measurement precision (2x)

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CODAR Ocean Currents
Kilometers
CODAR North
0 5 10
Little Egg Harbor
CODAR Central Site
Great Bay
LEO-15
A T L A N T I C O C E A N
CODAR South
Atlantic City
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Rutgers CODAR System Specifications
Long Range Site
Northern Site
Southern Site
4.80 MHz
25.36 MHz
25.19 MHz
Signal Frequency
62.50 m
11.83 m
11.92 m
Signal Wavelength
5.92 m
31.25 m
5.96 m
Ocean Wavelength
2 Hz
1 Hz
2 Hz
Sweep Repetition
50 KHz
100 KHz
Frequency Sweep
100 KHz
1.5 km
3.0 km
1.5 km
Bin Increment
5
5
1 - 5
Angle Increment
Offshore Range
50 km
50 km
200 km
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Radial Velocity Comparison with ADCP A
CODAR Site
Moored ADCP
25 km
A
25 cm/s
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Raw Velocity Comparison with ADCP C
Northern Site
RMS 7.2 cm/s
ADCP CODAR
Time (year-day)
Southern Site
RMS 9.5 cm/s
Time (year-day)
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Tidal Velocity Comparison with ADCP C
Northern Site
RMS 1.6 cm/s
ADCP CODAR
Time (year-day)
Southern Site
RMS 4.3 cm/s
Time (year-day)
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Raw Velocity Comparison with ADCP A
Northern Site
RMS 19.5 cm/s
ADCP CODAR
A
200 201 202
203 204
205 206
Time (year-day)
Southern Site
RMS 19.6 cm/s
200 201 202
203 204
205 206
Time (year-day)
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Role of Antenna Patterns in Signal Direction
Determination
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Measured vs. Ideal Antenna Patterns
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Measured vs. Ideal Antenna Patterns 4 ft Antenna
Elements
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RMS 8.6 cm/s R2 0.78 NP 61
RMS 17.4 cm/s R2 0.14 NP 456
4 ftIdealPatterns
8 ftIdealPatterns
RMS 8.3 cm/s R2 0.84 NP 114
RMS 7.9 cm/s R2 0.86 NP 278
4 ft InterpolatedPatterns
4 ft MeasuredPatterns
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8 ftIdealAntennaPatterns
4 ft IdealAntennaPatterns
Percent Coverage
4 ftInterpolatedPatterns
4 ftMeasuredPatterns
Percent Coverage
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New Jersey Clam FishingBoat Sinkings
Beth Dee Bob January, 1999
Adriatic January, 1999
22 Open Boat August, 1999
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Bistatic CODAR
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MCC results

• See classified presentation in SCIF

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Cabled Robotic Profilers
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REMUS Navigation / Thermistor Network
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Lagrangian Observations at LEO-15
1996 - Far Horizon air deployable surface
drifters 1998 - Webb multi-trip autonomous
profiling CTD 1999 - Bacteria 2001 - Proposed
dye dump
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REMUS
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REMUS Accomplishments at LEO-15

• 1997

First Sea Trials
Cost REMUS - 160/km R/V Caleta (30ft.) - 40/km
1998
Docking ADCP Data Collection 10 Missions, 261
km 4 Month Data Delay
1999
ADCP Data Collection First Night Bioluminescence
Mission 8 Missions, 377 km Processed Data
Available at End of Mission
2000
ADCP/CTD/Optical Data Collection Undulating
Mode 11 Missions, 440 km Target Processed Data
Available at End of Mission
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Webb Glider Profiles - July 26, 1999
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Rutgers Marine Field Station
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R/V Caleta - Physical Sampling
Towed Survey Systems
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R/V Walford - Bio-Optics
Bio-Optical Profiling Systems
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http//marine.rutgers.edu/cool/
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12 million hits to date
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Regional Ocean Modeling System (ROMS) Development
Initiated by Rutgers/UCLA
1997

• Features
• Free-surface, hydrostatic, primitive equation
  model
• State-of-the-art turbulence closure schemes for
  atmosphere and ocean
• Efficient coarse-grained, shared-memory, parallel
  code
• Enables support of high-resolution real-time
  coastal forecasting applications

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Navy Products
Rutgers
Global Atmospheric Forecasts
NOGAPS
1998
I.C. B.C.
Local Atmospheric Forecasts
NORAPS
Atm. Forcing
Ocean Models
ROMS
SBL
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Navy Products
NOAA Rutgers
Global Atmospheric Forecasts
NOGAPS
NCEP
1999
I.C. B.C.
I.C. B.C.
Local Atmospheric Forecasts
COAMPS 27 km 6 hours
RAMS 4 km 30 min
Atm. Forcing
Atm. Forcing
Ocean Models
ROMS
PBL SBL BBL WBL
MODAS (POM)
I.C. B.C.
Waves
WAM
Wave Models
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Navy Products
NOAA Rutgers
Global Atmospheric Forecasts
NOGAPS
NCEP
1999
I.C. B.C.
I.C. B.C.
COAMPS 27 km 6 hours
Local Atmospheric Forecasts
RAMS 4 km 30 min
Atm. Forcing
Atm. Forcing
Ocean Models
ROMS
PBL SBL BBL WBL
MODAS (POM)
I.C. B.C.
Waves
WAM
Wave Models
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Well sampled ocean
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RAMS Forecast
40.00
1800 19 Jul 99 85 of 145 Monday
WindVectorsandAirTemp
36.67
77.03
71.11
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Boundary Layer Schematic
L o n g w a v e
Shortwave
O
E v a p
H
H
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Model-Model Comparison
The basic response with the two schemes is quite
similar but ....

• More intermediate density water is trapped at
  the coast with the Mellor-Yamada scheme.

• The surface jet is approximately 10 cm/s weaker
  with the Mellor-Yamada scheme.

Across-shore velocity
Density
Along-shore velocity
LMD
M-Y
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BottomBoundaryLayerModel
Sediment Concentration
Bottom Shear Velocity
Ripple Height (m) - July 29, 1999
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July 1999 - Tuckerton Wind Comparison
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Surface Currents and Temperature (oC)
AVHRR/CODAR July 28, 1999 0800 GMT
28 26 24 22 20 18 16 14 12 10
7420W 7410W 7400W 7350W
7420W 7410W 7400W 7350W
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Conclusions

• Constructed a real-time coastal ocean observation
  system for the inner shelf.
• Operated since 1997, with peak observations in
  the summer.
• Extensive use of remote sensing surface data,
  subsurface time series at selected locations, and
  subsurface adaptive sampling data at selected
  times.
• Real-time communications (sensor to shore, shore
  to ship) critical to mission planning.
• World Wide Web based data distribution system.
• New coastal ocean forecast model (ROMS) developed
  and coupled to a high resolution atmospheric
  model (RAMS).
• Ensemble forecasts include sensitivities to
  boundary conditions and internal dynamics.
• Real-time data is available for assimilation and
  to determine which forecast is on track.

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Acknowledgements

• Kristie Andreson
• Hernan Arango
• Trish Bergmann
• Bob Chant
• Jay Cullen
• Liz Creed
• Mike Crowley
• Scott Durski
• John Fracassi
• Joe Gryzmski

Josh Kohut Sage Lichtenwalner Mark Moline Chris
Orrico Hai Pan Rich Styles Sasha Tozzi Jess
Vanisko John Wiggins
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