Marine microbiology from space Rafel Simó, Sergio Vallina, Jordi Dachs & Carles Pedrós-Alió Institut de Ciències del Mar CMIMA, CSIC Barcelona.

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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

Ocean color SeaWiffs web page Many microbes Very few microbes

The many troubles of a well meaning satellite

Electronic signal in each pixel Raw Data Level 0 Each pixel with position and time Level 1 Radiance at the stellite per pixel Sensor calibration Radiance at Earth’s surface Level 2 Atmospheric correction with masks and flags Biogeophysical data Level 2 Algorithms Level 3 Data in bins From sensor to image

A ship would take 10 years of continuous sampling to get the same amount of data points Phototrophic microbes visible thanks to Chlorophyll a CZCS 27/11/81

DMSP 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 ubiquitous in the oceans!

DMS : dimethyl sulphide (CH 3 ) 2 S DMSP: dimethylsulphoniopropionate (CH 3 ) 2 S + -CH 2 -CH 2 -COO - (CH 3 ) 2 S + -CH 2 -CH 2 -COO - is transformed into main biological source of S to atmosphere

Microbial community (plankton) Atmosphere Ocean Particles Temperature DMS Solar Radiation Albedo Microbes contribute to climate regulation through DMS production Charlson, Lovelock, Andreae & Warren (1987) Nature 326:655

Earth without clouds

Earth with clouds: albedo is VERY important

Mixed Layer Depth (m) DMS yield (%) Simó & Pedrós-Alió, Nature 402: (1999) The % of DMSP converted to DMS depends on Mixed Layer Depth

CHL : SeaWiFS W. Gregg (GSFC, NASA) monthly MLD : Samuels & Cox (Levitus)  t = kg m -3 monthly monthly

R 2 = Observed DMS (nM) Predicted DMS (nM) North Atlantic Gulf of Mexico East China Sea East Mediterranean West Mediterranean Sargasso Sea Southern ocean (SOIREE) Equatorial Pacific (IRONEX II) Equatorial Pacific Validation of the algorythm: average values from world’s oceans Simó & Dachs, Global Biogeochem. Cycles, 2002

DMS conc. (nM)january

december DMS conc. (nM)

SST : ATSR-2 monthly WIND SPEED : NOAA SSM/I monthly, Weibull correction Sea-to-air flux: F = k ·  [DMS]

JanuaryFebruaryMarch AprilMayJune JulyAugustSeptember OctoberNovemberDecember 180W 90W 0 90E 180EW 90W 0 90E 180EW 90W 0 90E 180E 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 DMS Flux (  M m -2 d -1 )

ANNUAL OCEAN-TO-ATMOSPHERE EMISSION OF DMS Tg S y -1 anthropogenic ~ 67 volcanic ~ 7

AEROSOL OPTICAL DEPTH(AOD) POTENTIAL CLOUD CONDENSATION NUCLEI (CCN) MODIS

COEFF. CORRELATION CCN vs DMS conc annual series, 7x7º

ATMOSPHERIC SAMPLING STATIONS (Univ. Miami) + Cape Grim + Amsterdam Island DMS predicted CCN MODIS MSA measured

blue: DMS black: CCN green: MSA J F M A M J J A S O N D DMS – CCN – MSA ( standardized ) MACE HEAD blue: DMS black: CCN green: MSA J F M A M J J A S O N D DMS – CCN – MSA ( standardized ) AMSTERDAM IS. DMS CCN MSA DMS vs CCN SPEARMAN'S CORREL. COEFF. : -0,5385 blue: DMS black: CCN green: MSA J F M A M J J A S O N D DMS – CCN – MSA ( standardized ) KOREA DMS CCN MSA blue: DMS black: CCN green: MSA J F M A M J J A S O N D DMS – CCN – MSA ( standardized ) HAWAII

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