slide1 l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
What Have We Learned after 5 Years of LEO? Oscar Schofield & Scott Glenn Coastal Ocean Observation Lab (COOL) Rutgers U PowerPoint Presentation
Download Presentation
What Have We Learned after 5 Years of LEO? Oscar Schofield & Scott Glenn Coastal Ocean Observation Lab (COOL) Rutgers U

Loading in 2 Seconds...

play fullscreen
1 / 92

What Have We Learned after 5 Years of LEO? Oscar Schofield & Scott Glenn Coastal Ocean Observation Lab (COOL) Rutgers U - PowerPoint PPT Presentation


  • 253 Views
  • Uploaded on

What Have We Learned after 5 Years of LEO? Oscar Schofield & Scott Glenn Coastal Ocean Observation Lab (COOL) Rutgers University. Science web site http://marine.rutgers.edu/cool. Operational web site http://www.thecoolroom.org.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'What Have We Learned after 5 Years of LEO? Oscar Schofield & Scott Glenn Coastal Ocean Observation Lab (COOL) Rutgers U' - flora


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide1

What Have We Learned after 5 Years of LEO?Oscar Schofield & Scott Glenn Coastal Ocean Observation Lab(COOL)Rutgers University

Science web site

http://marine.rutgers.edu/cool

Operational web site

http://www.thecoolroom.org

slide2

Our Partners: Robert Arnone, Trisha Bergmann, Don Barrick, Buzz Bernstein, Paul Bissett, Emmanuel Boss, Mike Crowley, Gary Fahnenstiel, Clayton Jones, Gary & Barbara Kirkpatrick, John Kerfoot, Dave Kohler, Steve Lohrenz, Alex Kahl, Josh Kohut, Mark Moline, Dave Millie, Chaya Mugdal, Matthew Oliver, Hugh Roharty, Emily Romanna, Doug Webb, Alan Weidemann,

AND John Wilkins

Paul Bissett

Mark Moline

Dale Haidvogel

Scott Glenn

Fred Grassle

Bob Chant

Oscar Schofield

The Jersey Observatory Family

slide3

What is one of oceanography’s Holy Grails?

We need to collect data over decadal scales and over large spatial (10-1000 km) scales so we can define the mean behavior variability and the trends occurring due to natural and anthropogenic changes.

Superimposed on these changes are episodic events,

which impact the physics, chemistry, and biology. Quantifying

the relative importance of these fluctuating properties requires

an adaptive sampling capacity so we can collect

statistics on the importance of the episodic events. This requires

data to be collected for over a decade to assure

that several episodic events are encountered. This will be the key

To define if there is any trended change in response to human

Activity. Until then we will reconciled to debate on AM radio with

Politcal extremists from both sides of the spectrum.

So we need a new to way to observe

the ocean. Ocean observatories

have (hopefully??) evolved to fill this function.

slide4

Gary Kirkpatrick

David Millie

Oscar Schofield

WHY OCEAN OBSERVATORIES?

slide5

NJSOS

Our Observatory Experience

SATELLITES

CODAR

LEO-15

Sustained

LEO-CPSE

Integrated

slide7

LEO-15: A sustained observatory

3km x 3km

1996-Present

slide8

LEO-15: A sustained observatory

Nor’Easter

Upwellng

25

0

Temperature

Depth (m)

15

15

175

210

Julian Day

>6

0

Chlorophyll a

(mg L-1)

Depth (m)

<2

15

175

210

Julian Day

Succeses

High resolution time series during

summer upwelling

High resolution data sets ideal for

validating 1-D models of sediment transport

Variability in coastal optical properties

Goal is to move into preoperational status, where it does not require a science

team for operation, operations being transferred to staff

slide9

30 X 30 km LEO CPSE

An Integrated Observatory

slide10

New Jersey Coastal Upwelling

July 6, ’98 - AVHRR

July 11, ‘98 - SeaWiFS

Chlor-a (mg/m3)

Temperature oC

19 20 21 22 24

.1 .3 .5 1 2 4

40N

40N

Historical

Hypoxia/Anoxia

Field

Station

Field

Station

LEO

LEO

39N

39N

75W

74W

75W

74W

Barnegat

Cape May

slide11

SST

Seasonal temperature

variation is

the primary signal.

Summer

upwelling is 2nd

slide12

Causes of Hypoxia/Anoxia

Surface

bloom

wind

SW upwelling

Stratification

favorable wind

Decay

Bacteria

Depletes Oxygen

slide13

12 m

15 m

20 m

25 m

30 m

35 m

40 m

50 m

100 m

500 m

1000m

2500m

Hypoxia/Anoxia & Bottom Bathymetry

Warsh – NOAA

1989

slide14

Modeled Effect of Bathymetric Variability on Upwelling

1 m/s

current

velocity

Along shore

subsurface deltas

cause upwelling to

be 3d, not 2d.

North

wind

Barnegat delta

LEO delta

Cape May delta

slide15

Courtesy of Hans Graber, Rich Garvine, Bob Chant,

Andreas Munchow, Scott Glenn and Mike Crowley

slide16

15m

6

North

South

slide18

South, offshore flow

North

Fluorometer

slide19

1.0

1

Tidal cycle

Upwelling

Absorption at

440 nm (m-1)

Depth (m)

r2 = .95

r2 = .74

6

0

12

30

60

0

Time (hr)

POC represents potentially

182μmol oxygen/kg

Depleted during an average

upwelling

slide21

A Clear Box

Collaboratory Experiment

Dr. Lisa Covi, Social Psycologist

The COOLroom Operational Collaboratory

COOLroom

Skunk Works

Model

COOLroom

War Room

Model

Evaluate Radical Collocation in

the COOLroom to improve Virtual

Collocation Systems.

Provide guidance for the

Regional Collaboratory

slide22

# of participating

scientists

250

40

40

NOPP & ONR

CPSE

200

30

30

Joint

Sediment Study

150

# of Research Institutions

20

20

Traditional NSF

Ocean Study

100

10

10

50

0

0

0

0

1991

1991

1993

1993

1995

1995

1997

1997

1999

1999

Year

slide24

Atmosphere/Ocean Forecast Models

3-D visualization

Forecast Briefing

Operational

Low-Res COAMPS

Atmospheric

Model

Experimental

High-Res COAMPS

Atmospheric

Model

Air-Sea Interaction

Model

ROMS

Ocean Model

(KPP and MY 2.5

Turbulent Closure)

Bottom Boundary

Layer Model

slide26

Real-Time Ensemble Validation

HR COAMPS / ROMS

2

4

6

8

10

12

KPP

Depth (m)

2

4

6

8

10

12

26

24

22

20

18

16

14

12

10

8

Depth (m)

2

4

6

8

10

12

Depth (m)

MY2.5

18

18

18

19

19

19

20

20

20

21

21

21

July, 2001

July, 2001

July, 2001

Thermistor

  • In an observationally rich
  • environment, ensemble forecasts
  • can be compared to real-time data
  • to assess which model is closer to reality
  • and try to understand why.
slide27

EcoSim

Bio-Optical Model

Physical/Biological Models

Operational

Low-Res COAMPS

Atmospheric

Model

Experimental

High-Res COAMPS

Atmospheric

Model

Air-Sea Interaction

Model

ROMS

Ocean Model

(KPP and MY 2.5

Turbulent Closure)

Bottom Boundary

Layer Model

slide28

EcoSim 2.0 Model Formulation

Air/Sea

CO2

Dust

Physical Mixing and Advection

Light

N2

Iron

CO2

NH4

NO3

PO4

SiO4

Relict

DOM

Cocco-litho-phores

Benthic Flora

Pelagic

Diatoms

Dino-

flagellate

Tricho-desmium

Synecho-

coccus

G. breve

Excreted

DOM

Lysed

DOM

Hetero-

Flagellet

Viruses

Copepod

Ciliates

Bacteria

Sediment

Detritus

Predator

Closure

slide29

+

ESSE Flow

Diagram

ESSE Smoothing via

Statistical Approximation

^

DY0/N

Field

Initialization

Central

Forecast

^

^

Y0

Ycf(-)

Ymp(-)

Shooting

Sample

Probability

Density

Measurement

Model

OA via

ESSE

Measurement

Model

Select

Best

Forecast

Options/

Assumptions

Mean

SVDp

Performance/

Analysis

Modules

Perturbations

Minimum

Error

Variance

Within Error

Subspace

(Sequential

processing of

Observations)

Adaptive

Error

Subspace

Learning

+

Scalable

Parallel

Ensemble

Forecast

Error Subspace

Initialization

Normalization

Peripherals

Analysis

Modules

Convergence

Criterion

Continue/Stop

Iteration

Breeding

DE0/N

+

DP0/N

-

-

+

Most

Probable

Forecast

+

Synoptic

Obs

A Posteriori

Residules

dr (+)

Historical,

Synoptic,

Future in

Situ/Remote

Field/Error

Observations

d0R0

+

-

-

Data

Residuals

Measurement

Error

Covariance

^

d-CY(-)

Ensemble

Mean

+

+

^

eq{Yj(-)}

Gridded

Residules

^

Y(-)

+

-

^

^

j=1

Y(+)

Y(+)

Y1

Yj

Yq

^

-

Y1

Yj

Yq

+

0

+

-

E(-)

P(-)

^

-

+

0

+

+

-

+/-

^

E0

P0

j=q

0

uj(o,Ip)

with physical

constraints

Continuous

Time Model

Errors Q(t)

Key

Ea(+)

Pa(+)

E(+)

P(+)

Field

Operation

Assumption

slide31

Hindcast sensitivity studies

Large diatoms

July 31

SeaWiFS

Chlor-a

3

(mg/m

)

.5

2

39:30N

3

Node A

4

UCSB

5

Small diatoms

39:00N

Measured

Total Chlorophyll Measured

3-5 mg Chl a m-3

Diatom Chlorophyll Modeled

2-3 mg Chl a m-3

slide35

Red Tide Observed at 790 nm on 22 July 2000

With the PHILLS Sensor

100 meters

slide37

Ceratium fusus

c

a

b

Bioluminescence Potential

1e6

4e10

Photons/sec/ml

0

6

12

Depth (m)

18

24

a

0

1.0

2.0

Distance (km)

slide38

Ship Grid Patterns

BL Isosurfaces

1E10 ph/s/35L

0

3E11 ph/s/.35L

Depth (m)

15

Latitude

(~5km)

Longitude

(~2km)

slide41

BL Isosurfaces

5E10ph/s/.35L

1E11ph/s/.35L

Depth (m)

Latitude

(~300m)

Longitude

(~500m)

slide42

Scientists want real-time observational

nowcasts and model forecasts ….

DO REAL PEOPLE CARE?

slide43

Rutgers Web Site Statistics

Data Type

Other

14%

NODES

13%

CODAR

17%

Gulf Stream

10%

MET

17%

LEO

6%

Non-profit (7%)

Rutgers Web Site Statistics

By Hour

SST 53%

Education (6%)

East Coast

19%

8000

June

General Public

69%

7000

Military &

Government(4%)

July

6000

August

NYB

37%

5000

Average Hourly Hits

September

4000

October

3000

November

2000

MAB

28%

December

1000

January

0

Region

0:00

3:00

6:00

9:00

12:00

15:00

18:00

21:00

slide44

Where we do go from here?

“The very few existing time-series stations paint a compelling picture of important oceanic changes in physics, chemistry and biology. Yet these stations capture the time domain at only a single point. New strategies for observing the appropriate spatial correlation are required.”

-- Ocean Sciences at the New Millennium

Ocean Sciences Decadal Committee 2001

slide45

Why do we want the spatial correlation?

Nowcasting & Forecasting

FOR A SINGLE PARTICLE

FOR AN OCEAN OF PARTICLES

Observations

Models

Motivation

  • To get these initial conditions:
  • Modelers like to assimilate maps of coherent array data
  • Modelers do not like to assimilate incoherent time series data
slide46

New Jersey Shelf Observing System (NJ-SOS)

300 X 300 km NJSOS

An Integrated &

Sustained Observatory

Satellites,

RADAR, Gliders

slide47

International Constellation of Ocean Color Satellites

X-Band Earth Observing Satellites

EOS (MODIS) USA 2001

NEMO (COIS) USA 2004

Orbview-2 (SeaWiFS) USA Op.

HY-1 (COCTS/CZI) China 2002

FY1-C (MVISR) China Op.

FY1-D (MVISR) China 2002

IRS-P3 (MOS) India Op.

IRS-P4 (OCM) India Op.

ADEOS-2 Japan 2002

(GLI/POLDER)

ENVISAT(MERIS) Europe 2002

slide48

oC 14 18 22 23 24 25 26 27

FY-1D

Temperature

40N

40N

38N

38N

FY-1D

Chlorophyll-a

.1 .3 1 2 3 4 5 6 7

mg/m3

36N

36N

66W

66W

74W

74W

70W

70W

FY-1D

Sept. 12, 2002

13:38 GMT

slide49

Combining the optics and physical

features for water mass tagging

Here using a mask of temp and

optics marking water masses

From Oliver (former Mote intern)

slide52

Measure IOPs using the

observation network

Hyperspectral

Systems are coming

Satellites algorithms

slide53

phcobilin

Chl b

Chl c

Fig. 3

slide54

PATTERN RECOGNITION (here HABs)

Thanks to Gary Kirkpatrick

slide56

Radial Velocity Map

Brant Beach Site

Brigantine Site

25 km

A

25 cm/s

slide57

1998 1999 2000 2001

Test

slide63

GPS Synchronization : Bistatic

Monostatic HF-Radar

Bistatic HF-Radar

slide64

GPS Synchronization : Bistatic

Ship to Shore

Monostatic

Bistatic

slide66

GPS Synchronization : Bistatic

Buoy to Shore

Monostatic

Bistatic

slide67

GPS Synchronization : Bistatic

Ship to Shore

R/V Endeavor

University of Rhode Island

slide68

R/V Endeavor Cruise Track (12/1/2001 – 12/8/2001)

Standard Bistatic Buoy

Long-range Bistatic

slide70

One applied application given

current health and human safety needs,

commerce needs,

and homeland security needs.

slide74

RF Repeater

RV Endeavor Temperature Cross Section - July 27, 2000

Costs

R/V Endeavor - Rental $13 K/day

Slocum Glider - Purchase $85 K

Long-Duration Glider AUVs

ADCP vs. Glider Drift Comparison

Temperature Cross Section

July 19, 2000

slide76

Ashumet Pond (August 2002)

Glider Mission:

Inital

Blue: glider track

Red: waypoints

Green: calculated water velocity

Black: gps fixes

6

2

Transect 1

5

Optical Backscatter @ 440nm (m-1)

Transect 2

4

3

7

Transect 1

Transect 2

slide77

How do we build a Smart Glider Fleet?

Use Agent Oriented Software

For self-aware & self-controlled robots

Collaborative Society of Glider Software Agents

KNOWLEDGE

REPRESENTATION

SENSORS

DECISION MAKING

KNOWLEDGE BASE

PLANNING

REASONING

COMMUNICATION

COMMUNICATION

SITUATION

PROTOCOLS

MODELLING

Glider Fleet Mission

Status Panel

NASA’s

Deep Space 1

Fly-by of

Comet Borrelly

slide78

Okay, NOPP-congressional earmarks-ONR have

built ocean observatories…

How do we link them???

slide79

NWS Forecast Offices

Seattle, WA

Mount Holly, NJ

  • 121 Offices Nationwide
  • 34 Coastal Offices

Honolulu, HI

Mobile, AL

Are there models for linked regional centers?

slide80

NWS Forecast Office - Mount Holly, NJ

Fort Dix, NJ WSR-88 Doppler Radar

  • NWS Mount Holly Personnel
  • Lead Forecasters : 5
  • General Forecasters: 5
  • Meteorological Interns: 3
  • Hydrometeorological
  • Technicians: 2
  • Electronic Technicians: 4
  • Management: 5

County Warning Area

Marine/Aviation Desk

NWSFO Mount Holly

Radar Desk

slide82

How do you fund this?

Standard Science Budgets

NOPP Partnerships

Senatorial Plus-ups

NSF MREFC

$125K/yr (for 2.9 yrs)

$1-$3 M (for 1-3 yrs)

$3-$8 M (for 3 yrs)

$6-$220 M (for 3-5 yrs)

Advice from Canada, referring to an ocean observation network:

“Purely scientific gains pale into insignificance. Success is measured by the quality of the product supplied, not research papers.”

Howard Freeland (leader of Canadian ARGO effort)

slide83

New York Harbor

Economic Impact $ 30 Billion

NJDOT Maritime Operations Budget $300 Million

Harbor Science Budgets $3 Million

slide84

Technology Partnerships

  • Remote Sensing
  • Coastal ocean algorithms – NRL, U. Maine, NOAA/NESDIS, FERI
  • International constellation of satellites – SeaSpace Inc., NRL
  • HF Radar
  • MultiStatic Network-CODAR
  • NEOS Backbone – GOMOOS, UNC, U. Maryland
  • Ship Tracking/SAR- CODAR, Applied Mathematics Inc.
  • Gliders
  • Autonomous Control – Webb Reserch Inc.
  • Red-Tide Tracking – Mote, Cal-Poly, NRL
  • Modeling
  • Physical/Bio-Optical Modeling – FERI
  • Sediment Transport – USGS, WHOI

Together these components will form the backbone of the

Big American Coastal Ocean Network

BACON

slide85

What will we do with the BACON?

A) National Ecosystem Experimental Demos

NEED

B) Coastal Ocean Observatory Research Studies

COORS

slide86

8

8

8

COORS LITE

Littoral Integrated Transport

Experiment –Hudson

Buoyancy Plumes

COORS DARK

Diver Activated Radiance

Kamakazees –California/

Sea of Japan

COORS LAGER

Large-scale Algal Gulf

Ecosystem Response-

Gulf of Mexico

Ocean.US

Ocean.US

Ocean.US

COORS ALE

Arctic Littoral Experiment

– Norwegian Hydrography &

Algal Blooms

COORS ICE

Integrated Coastal

Experiment – Gulf

of Alaska

COORS MALT??

Mantle Adjustment Long-term

Technologies –NEPTUNE

What kind of COORS should we do?

slide87

So What Have W e Learned after 5 Years of LEO?

  • Make BACON
  • NEED COORS
  • Packaged with that plastic thing - OCEAN.US
slide88

“……I am satisfied that we are

looking at the ocean more

intensely and more deeply

than anyone anywhere else.”

codar range rate measurements of r v endeavor from loveladies nj codar site

10 kt

CODAR Range Rate Measurements of R/V Endeavorfrom Loveladies, NJ CODAR Site

2155

2222

2052

2025

2125

kalman filter solution track shown in red measurement uncertainty ellipses shown in blue

10 kt

Kalman Filter Solution Track Shown in RedMeasurement Uncertainty Ellipses Shown in Blue

2222

2009

slide91

Regional Observation & Forecast Center

  • Startup Costs
  • 1 XBand Satellite Dish $0.5 M
  • 5 CODARs Installed @ $200K $1.0 M
  • 10 Glider AUVs w/sensors @ $100K $1.0 M
  • Chase Boat, Vehicles, Computers, etc. $0.5 M
  • Total: $3.0 M
  • Operational Costs
  • Salary, Fringe, Overhead
  • 24/7 Watch Forecasters 5
  • Satellite Tech 1
  • CODAR Tech 2
  • Glider Tech 2
  • Computer Tech 1
  • Electronics Tech 1
  • Modeler 1
  • Director 1
  • Secretary 1
  • Salary Total 15 @ $150K/year $2.25 M/year
  • Repairs, Maintenance & Training $0.75 M/year
  • Total: $3.0 M/year
  • For 25 National Centers - $75M startup
  • Annual Operating Costs (375people) - $75M
slide92

SAR- 3,300 lives saved $407 Million

1,000 lives lost

$2.5 Billion in Property Saved

Illegal Drugs- $4.4 Billion Intercepted $1445 Million

& EEZ $25 Billion commercial fishing

$10 Billion recreational fishing

Harbor Safety- 95% legal imports by sea $456 Million

75% illegal

90% foreign flag ships

Oil Spills- 8,000 reported/yr $375 Million

Operation Noble Eagle ?,???,???,???

Operational Budget ($3.4 billion before Sept. 11th)

“The Coast Guard cannot possibly continue its current high-security regime

without more vessels, people, and resources.” Sen. John Kerry (MA)