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

2. Marine microbes through the microscope: small but many

3. Ocean color SeaWiffs web page Many microbes Very few microbes

4. The many troubles of a well meaning satellite

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

6. 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

7. 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!

8. 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

9. 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

10. Earth without clouds

11. Earth with clouds: albedo is VERY important

12. Mixed Layer Depth (m) DMS yield (%) 010203040506070 100 80 60 40 20 0 Simó & Pedrós-Alió, Nature 402: 396-399 (1999) The % of DMSP converted to DMS depends on Mixed Layer Depth

13. CHL : SeaWiFS 1997-2000 W. Gregg (GSFC, NASA) monthly MLD : Samuels & Cox (Levitus)  t = 0.125 kg m -3 monthly monthly

14. R 2 = 0.8255 0 2 4 6 8 10 0246810 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

15. DMS conc. (nM)january

16. december DMS conc. (nM)

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

18. 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 ) 051015202530

19. ANNUAL OCEAN-TO-ATMOSPHERE EMISSION OF DMS 23 - 32 Tg S y -1 anthropogenic ~ 67 volcanic ~ 7

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

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

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

24. 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