Development of Carbon Data

Products for the Coastal Ocean:

Implications for Advanced Ocean

Color Sensors

Antonio ManninoNASA Goddard Space Flight Center

Greenbelt, Maryland USA

Acknowledgments: Stanford Hooker, Mary Russ, Xiaoju Pan, Randy Kawa

GOCI / IOCCG Working Group Meeting - Nov. 1, 2008 - Korea

• Field Activities & DOC Experiments

• Development of CDOM, DOC, POC, ... algorithms

• Products using MODIS Hi-Res SWIR atmospheric corrections

• NASA GEO-CAPE mission formulation studies

Role of Rivers/Estuaries and Continental Margins in Global Cycles of C and N

Nutrients

Nutrients

0.0

0.5

1.0

1.5

2.0

2.5

0.0 0.5 1.0 1.5 2.0

aCDOM(355)

Rrs

ratio

Rrs490/Rrs551

Rrs412/Rrs551

Rrs340/Rrs551

Exp_fit_Rrs412/551

Exp_fit_Rrs_490/551

Exp_fit_Rrs_340/551

Southern MAB CDOM Algorithm

aCDOM(355) (m-1)

Rrs

rat

io

2005 & 2006 in-water Radiometry Field Data

R2=0.91R2=0.94R2=0.96

aCDOM(355) = ln[(Rrs490/Rrs551 - 0.494)/2.7]/-3.371

Radiometry data from Stan Hooker

• Prefer to use Rrs(412/555) band ratio - but atmospheric correction issues for sensor retrieval of 412 nm band.

• OBPG expects 412nm band improvements after spring reprocessing.

• Algorithm range limited to range of field data.

• UV bands should yield more robust retrievals of CDOM.

Satellite aCDOM(355)

A2005147 A2005217 A2005307

27 May, 2005 5 Aug., 2005 3 Nov., 2005

A2006046

15 Feb, 2006

0

1000

2000

3000

4000

5000

6000

J-05

M-05

M-05

J-05

S-05

N-05

J-06

M-06

M-06

J-06

S-06

N-06

Chesapeake Bay Streamflow (m3 s-1)

S2005095

5 April, 2005

0.050.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1.10

1.20

1.30 (m-1)

S2006132

12 May, 2006S2006181

30 June, 2006

USGS

CDOM Algorithms from UV and VIS bands

0.0

0.5

1.0

1.5

2.0

2.5

0.0 0.5 1.0 1.5 2.0

aCDOM(355) (m-

Rrs

ratio

Rrs490/Rrs551

Rrs412/Rrs551

Rrs340/Rrs551

Exp_fit_Rrs_412/551

Exp_fit_Rrs_490/551

Exp_fit_Rrs_340/551

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0.0 1.0 2.0 3.0

aCDOM(355) (m-

Rrs

(490)/

Rrs

(555)

Gulf of Maine

MAB

0.0

0.5

1.0

1.5

2.0

2.5

0.0 1.0 2.0 3.0

aCDOM(355) (m-

Rrs

(412)/

Rrs

(555)

Gulf of Maine

MAB

0.0

0.5

1.0

1.5

2.0

0.0 1.0 2.0 3.0

aCDOM(355) (m-

Rrs

ratio

Rrs490/Rrs555Rrs412/Rrs555Rrs340/Rrs555Exp_fit_Rrs490/555Exp_fit_Rrs412/555Exp_fit_Rrs340/555

R2=0.91R2=0.94R2=0.96

R2=0.80R2=0.92R2=0.95

aCDOM(355) (m-1) aCDOM(355) (m-1)

aCDOM(355) (m-1)aCDOM(355) (m-1)

southern MAB Gulf of Maine

Radiometry data from Stan Hooker

CDOM Algorithms from in-water VIS bands

Rrs(412)/Rrs(555) band ratio yields very consistent relationship with CDOM abs. for all 3 regions compared to the Rrs(490)/Rrs(555) band ratio.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0.0 1.0 2.0 3.0

aCDOM(355) (m-

Rrs

(490)/

Rrs

(555)

Gulf of MaineMABHudson_May2007Hudson_Nov2007

0.0

0.5

1.0

1.5

2.0

2.5

0.0 1.0 2.0 3.0

aCDOM(355) (m-

Rrs

(412)/

Rrs

(555)

Gulf of Maine

MAB

Hudson_May2007

Hudson_Nov2007

aCDOM(355) (m-1) aCDOM(355) (m-1)

Radiometry data from Stan Hooker

Constituent Absorption in the Coastal Ocean

from Pan et al. 2008

CDOM absorbs a significant portion of PAR which may impact PP and should be accounted for in PP models.

DOC vs CDOM Interannual ConsistencyChesapeake Bay & coastal ocean

y = 94x + 75

R2 = 0.90

y = 54.1x + 63.8

R2 = 0.88

y = 94.9x + 71.4

R2 = 0.91

0

50

100

150

200

250

0.0 0.5 1.0 1.5 2.0

aCDOM(355) (m-

DO

C (

M C

)

July, Aug & Sept 2005Jul 2006DB Plume July 2005 & 2006

aCDOM(355) (m-1)

y = 82.1x + 58.2

R2 = 0.89

y = 88.9x + 48.1

R2 = 0.98

y = 86.6x + 48.1

R2 = 0.92

0

50

100

150

200

250

0.0 0.5 1.0 1.5 2.0aCDOM(355) (m-

DO

C (

M C

)

Oct & Nov 2004, Jan & May 2005

Mar/April & May 2005

May 2006

aCDOM(355) (m-1)

Fall, Winter & Spring Summer

Ches Bay Mouth & Plume

50

100

150

200

250

300

0.0 0.5 1.0 1.5 2.0 2.5

ag(355) (m-

DO

C (_

M)

Oct 15 & Nov 15, 2004Jan 10, 2005March 30-31, 2005May 26-27, 2005Nov. 3, 2005May 11, 2006Nov. 28, 2006Mar 19, 2007Apr 23, 2007

aCDOM(355) (m-1)

DO

C (

M)

50

100

150

200

250

300

0.0 0.5 1.0 1.5 2.0 2.5

July 5, 2004Sep 1, 2004June 21, 2005July 26-27, 2005Aug 19, 2005Sep 23, 2005July 3-4, 2006Sept. 6, 2006July 3, 2007Aug 16, 2007

Fall, Winter & Spring Summer

aCDOM(355) (m-1)

DOC vs CDOM Relationships in MAB

y = 85.81x + 49.8

R2 = 0.9595

y = 94.6x + 72.4

R2 = 0.9036

y = 33.97x + 78.6

R2 = 0.9567

y = 48.9x + 69.9

R2 = 0.875

0

50

100

150

200

250

300

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

aCDOM(355) (m-1)

DO

C

Fall_Winter_Spring

Summer

Hudson May 2007

Del Bay Summer '05-'06

Satellite DOC

15 Feb, 2006

5 April, 2005 27 May, 2005 5 Aug, 2005 3 Nov, 2005

12 May, 200650

60

70

80

90

100

110

120

130

140

150

160

170

30 June, 2006

M C

Net Ecosystem Production of DOC

0

50

100

150

10-20m 20-60m >60m

30 March - 1 April 2005

26-30 July 2005

9-12 May 2006

2-5 July 2006

Bottom Depth

DO

C (

M)

Field Data MODIS-Aqua

0

50

100

150

10-20m 20-60m 60-80m 80-500m

18 March 2005

5 Aug 2005

12 May 2006

30 June 2006

Seasonal DOC increase of 12-30 M C from spring to summer Winter DOC inventory in southern MAB of 1.2 Tg C

southern MAB

POC & PN algorithm development

y = 0.1692x

R2 = 0.8804

0

50

100

150

200

0 200 400 600 800

POC (mg m-3)

PN

(m

g m

-3)

Soon, additional data from Hudson plume & Gulf of Maine.

southern MAB

+/- 8hr Particulate Organic Carbon Validation

202.6

231.3

0

20

40

60

80

100

Clark Stram_1 Stram_2 Stram_3 Stram_4b Mannino Gardner

POC Algorithm

Mean A

PD

(%

)

SeaWiFS

MODIS

n=28 n=13

Satellite versus in situ POC Validation in

southern MAB

APD - Absolute Percent Difference

0

20

40

60

80

100

0 20 40 60 80 100

in situ POC (μM

Sate

llite

PO

C (_

M

MODIS

SeaWiFS

in situ POC (μM C)

Sate

llite

PO

C (μ

M C

)

MODIS: APD = 22.6 ± 17% SeaWiFS: APD = 27 ± 22%

Stramska & Stramski 20054b algorithm

POC Algorithm ComparisonSt

ram

ska

4bM

anni

no

0 100

200

300

400

500

600

700

800

900

1000

1100

1200Aug. 5, 2005 Nov. 3, 2005 Feb. 15, 2006 May 12, 2006

MODIS - High ResolutionStramska lower POC nearshore, but higher POC offshore than Mannino

A2004245 A2004320 A2005010 A2005146 A2005147

A2005208 A2005217 A2005307 A2006046A2005206

A2006129 A2006132 A2006181

0

10

20

30

40

50

60

70

80

90

100

MODIS-Aqua Dissolved Organic Carbon (DOC) as % of Total OC - Simulated at 250m

New Approach to Coastal Ocean AlgorithmsNeural Networks using ALL satellite VIS bands

CDOM

Dissolved Organic Carbon Particulate Organic Carbon

Chlorophyll

A. Mannino & D. Lary (613.3), in prep.

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

Terrigenous DOM from Space

Lignin Phenols: APD = 10 ± 8.8% aCDOM(350): APD = 43 ± 24.5%

Lignin Phenols ( g L-1) May 16, 2000

S2000136

0.0

0.4

0.8

1.2

1.6

0.0 0.4 0.8 1.2 1.6

Lignin

a(350)

Field data

Sate

llite

(m-1)

( g L-1)

a CD

OM(3

50)

(m-1)

0

2

4

6

8

10

0 2 4 6 8 10

Lignin Phenols ( g L-1)

X=(Y+0.346)/1.034r = 0.99

Hernes & Benner 2003Mississippi River Plume

Summary• CDOM - DOC relationships suggest variable source

components for estuaries within the MAB and Gulf of Maine

• Processes that influence CDOM include river discharge, photooxidation in late Spring-Summer, and wind-induced vertical mixing in Autumn-Winter.

• DOC distributions are regulated by river discharge, ecosystem productivity in Spring-Summer, and ocean circulation

• Satellite retrieval of CDOM, DOC, POC, PN & dissolved lignin phenols allows us to quantify seasonal and interannual variability of coastal ocean carbon processes

• Terrestrial/riverine/estuarine export of carbon

• Seasonal net ecosystem production of DOC

• POC and DOC inventories

GEO-CAPE Mission Concept

8ºx8º

Mission is combination of

1) Medium-resolution (5 km) continental scanning instrument - designed for atmospheric chemistry.

2) High-resolution (~300m) regional scanning spectrometer.

- Programmable geosynchronous multi-disciplinary observatory.

NRC Decadal Survey recommended GEO-CAPE as a Tier 2 mission to study Coastal and Atmospheric Pollution Events.

- Projected earliest launch of Tier 2 missions is 2020.

Key Issues: Temporal scale, atmospheric corrections for Ocean Color, and enhanced spatial & spectral resolution.

GEO Sensor Requirements - GSFC

Acknowledgments• NASA New Investigator and

Interdisciplinary Science Programs

• NASA Ocean Biology & Biogeochemistry Program

• NOAA - WaCOOL-BIOME program

• P. Hernes

• KC Filippino, P. Bernhardt, M. Mulholland

• Ocean Biology Processing Group