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Marine microbiology from space Rafel Simó, Sergio Vallina, Jordi Dachs & Carles Pedrós-Alió

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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Marine microbiology from space Rafel Simó, Sergio Vallina, Jordi Dachs & Carles Pedrós-Alió

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  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. Many microbes Very fewmicrobes Ocean color SeaWiffs web page

  4. The many troubles of a well meaning satellite

  5. 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

  6. 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

  7. 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!

  8. DMSP: dimethylsulphoniopropionate (CH3)2S+-CH2-CH2-COO- is transformed into DMS : dimethyl sulphide (CH3)2S main biological source of S to atmosphere

  9. 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

  10. Earth without clouds

  11. Earth with clouds: albedo is VERY important

  12. 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)

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

  14. 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

  15. DMS conc. (nM) january

  16. DMS conc. (nM) december

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

  18. 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

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

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

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

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

  23. ) ) 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

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