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Marine microbiology from space Rafel Simó, Sergio Vallina, Jordi Dachs & Carles Pedrós-Alió Institut de Ciències del Mar CMIMA, CSIC Barcelona. Marine microbes through the microscope: small but many. Many microbes. Very few microbes. Ocean color. SeaWiffs web page.

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slide1

Marine microbiology from space

Rafel Simó, Sergio Vallina, Jordi Dachs &Carles Pedrós-Alió

Institut de Ciències del Mar

CMIMA, CSIC

Barcelona

slide3

Many

microbes

Very fewmicrobes

Ocean color

SeaWiffs web page

slide5

Raw Data

Electronic signal in each pixel

Level 3

Data in bins

Sensor calibration

Each pixel with position and time

Level 0

Radiance at the stellite per pixel

Level 1

Atmospheric correction

with masks and flags

Radiance at Earth’s surface

Level 2

Algorithms

Level 2

Biogeophysical data

From sensor to image

Http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/OCDST/classic_scenes

slide6

Phototrophic microbes visible thanks to Chlorophyll a

A ship would take

10 years of continuous sampling to get the same amount of data points

CZCS 27/11/81

slide7

Marine phytoplankton produce DMSP for

its role in:

-osmoregulation

-cryoprotection

-anti-oxidant

-methyl donor

-overflow of excess S and reducing power

-chemosensory and chemotactic behaviour

DMSP

ubiquitous in the oceans!

slide8

DMSP: dimethylsulphoniopropionate

(CH3)2S+-CH2-CH2-COO-

is transformed into

DMS : dimethyl sulphide

(CH3)2S

main biological source of S to atmosphere

slide9

Albedo

Solar Radiation

Particles

Temperature

DMS

Microbes contribute to climate regulation through DMS production

Atmosphere

Ocean

Microbial community

(plankton)

Charlson, Lovelock, Andreae & Warren (1987) Nature 326:655

slide12

100

80

60

40

20

0

0

10

20

30

40

50

60

70

The % of DMSP converted to DMS depends on Mixed Layer Depth

DMS yield (%)

Mixed Layer Depth (m)

Simó & Pedrós-Alió, Nature 402: 396-399 (1999)

slide13

CHL : SeaWiFS 1997-2000

W. Gregg (GSFC, NASA)

monthly

MLD : Samuels & Cox (Levitus)

t = 0.125 kg m-3

monthly

slide14

2

R

=

0

.

8

2

5

5

Validation of the algorythm: average values from world’s oceans

North Atlantic

1

0

Gulf of Mexico

East China Sea

8

East Mediterranean

West Mediterranean

6

Sargasso Sea

Predicted DMS (nM)

Southern ocean (SOIREE)

4

Equatorial Pacific (IRONEX II)

Equatorial Pacific

2

0

0

2

4

6

8

1

0

Observed DMS (nM)

Simó & Dachs, Global Biogeochem. Cycles, 2002

slide17

SST : ATSR-2

monthly

WIND SPEED : NOAA SSM/I

monthly, Weibull correction

Sea-to-air flux:

F = k ·  [DMS]

slide18

90 N

60 N

30 N

0

30 S

60 S

90 S

90 N

60 N

30 N

0

30 S

60 S

90 S

0

5

10

15

20

25

30

DMS Flux (M m-2 d-1)

January

February

March

April

May

June

July

August

September

October

November

December

180W 90W 0 90E 180EW

90W 0 90E 180EW

90W 0 90E 180E

slide19

ANNUAL OCEAN-TO-ATMOSPHERE EMISSION OF DMS

23 - 32 Tg S y-1

anthropogenic ~ 67

volcanic ~ 7

slide21

MODIS

AEROSOL OPTICAL

DEPTH

(AOD)

POTENTIAL CLOUD CONDENSATION NUCLEI (CCN)

slide22

COEFF. CORRELATION

CCN vs DMS conc

annual series, 7x7º

slide23

ATMOSPHERIC SAMPLING STATIONS (Univ. Miami)

+ Cape Grim + Amsterdam Island

DMS predicted

CCN MODIS

MSA measured

slide24

)

)

DMS vs CCN

KOREA

MACE HEAD

SPEARMAN'S

standardized

standardized

CORREL. COEFF. :

-0,5385

MSA (

MSA (

CCN

blue: DMS

CCN

blue: DMS

DMS

black: CCN

black: CCN

CCN

green: MSA

MSA

DMS

green: MSA

DMS

J F M A M J J A S O N

D

J F M A M J J A S O N

D

)

)

AMSTERDAM IS.

HAWAII

standardized

standardized

MSA (

MSA (

CCN

CCN

blue: DMS

blue: DMS

DMS

black: CCN

black: CCN

CCN

green: MSA

green: MSA

MSA

DMS

DMS

J F M A M J J A S O N

D

J F M A M J J A S O N

D