1. CDOM in the Deep Sea: Distribution and Dynamics from Trans-ocean Sections Norm Nelson, Dave Siegel, Craig Carlson Chantal Swan, Stu Goldberg UC Santa Barbara Special thanks to: Bill Smethie and Samar Khatiwala, LDEO Dennis Hansell, University of Miami Norm Nelson, Dave Siegel, Craig Carlson Chantal Swan, Stu Goldberg UC Santa Barbara Special thanks to: Bill Smethie and Samar Khatiwala, LDEO Dennis Hansell, University of Miami Ocean Sciences Meeting 2008

2. Outline About the project Distribution and hydrography Global dynamics of CDOM CDOM and DOM diagenesis Ongoing and future activities About the project Distribution and hydrography Global dynamics of CDOM CDOM and DOM diagenesis Ongoing and future activities

3. What we already know (Bermuda) CDOM is produced and destroyed in the top 250m on an annual basis Sources include microbes and zooplankton Sinks include solar bleaching and possibly consumption by microbes Lab experiments show microbes and zooplankton can produce CDOM faster than observed rates of change in water samples Estimated turnover time scales ~100 days. (we can’t measure these rates very well in the lab) CDOM is produced and destroyed in the top 250m on an annual basis Sources include microbes and zooplankton Sinks include solar bleaching and possibly consumption by microbes Lab experiments show microbes and zooplankton can produce CDOM faster than observed rates of change in water samples Estimated turnover time scales ~100 days. (we can’t measure these rates very well in the lab)

4. Global Surface CDOM Distribution (From SeaWiFS) Siegel et al. [2005] JGR

5. UCSB Global CDOM Project Goals Quantify global distribution of CDOM Surface, intermediate, and deep water Determine physical and biological factors controlling CDOM distribution Apply knowledge gained to problems of ocean circulation and DOM characterization and cycling Collect calibration and validation data for ocean color models Quantify global distribution of CDOM Surface, intermediate, and deep water Determine physical and biological factors controlling CDOM distribution Apply knowledge gained to problems of ocean circulation and DOM characterization and cycling Collect calibration and validation data for ocean color models

6. Global CDOM Project Sections EUCFe 2006 EqBOX 2005 2006 AMMA 2006

7. UCSB Global CDOM Project Measurements & Methods CDOM Analysis At Sea 200 cm Liquid Waveguide Absorption Cell (UltraPath, WPI Inc) Single-beam spectrophotometer with D 2 & Tungsten- halogen light sources, diode-array spectrometer detector Fast, low sample volume (2 min/sample, 30-60 ml) Issues with blanks (refractive index correction) 200 cm Liquid Waveguide Absorption Cell (UltraPath, WPI Inc) Single-beam spectrophotometer with D 2 & Tungsten- halogen light sources, diode-array spectrometer detector Fast, low sample volume (2 min/sample, 30-60 ml) Issues with blanks (refractive index correction) Nelson et al. [2007] DSR-I

8. UltraPath Precision Duplicate sample analysis (same Niskin) RMS difference at 325 nm: 0.0034 m -1 This is ~4% of mean RMS/Mean is between 5 and 10% between 300 and 400 nm Longer wavelengths are not as good Overall project: precision not as good, ca. 0.01 m -1 Duplicate sample analysis (same Niskin) RMS difference at 325 nm: 0.0034 m -1 This is ~4% of mean RMS/Mean is between 5 and 10% between 300 and 400 nm Longer wavelengths are not as good Overall project: precision not as good, ca. 0.01 m -1 Nelson et al. [2007] DSR-I

9. UltraPath Example CDOM Profiles

10. CDOM Dynamics and Hydrography Distribution of CDOM in the ocean basins –Are there spatial gradients in the deep sea? Relationship with AOU and age tracers –Is CDOM produced/consumed by microbes at depth? Atlantic vs. Pacific& Indian Distribution of CDOM in the ocean basins –Are there spatial gradients in the deep sea? Relationship with AOU and age tracers –Is CDOM produced/consumed by microbes at depth? Atlantic vs. Pacific& Indian

11. Selected CDOM sections (Global CDOM map from SeaWiFS/GSM, mission mean) a cdom (443 nm, m -1 )

12. Atlantic A22 CDOM / AOU (Apparent Oxygen Utilization) STMW Deep Caribbean AAIW NADW GS STMW Deep Caribbean AAIW NADW GS

13. Pacific P16 CDOM / AOU

14. Indian I8S/I9N CDOM / AOU

16. Atlantic vs. Pacific/Indian: what’s different? Atlantic: Productivity high but meridional overturning time scales much shorter North Pacific / Indian: Most distant part of the global conveyor, longest time since ventilation, considerable remineralization Southern Ocean / S. Pacific: Massive ventilation and deep water formation, productivity limited (iron?) We can look at this more closely using age tracers -- CFC invasion Atlantic: Productivity high but meridional overturning time scales much shorter North Pacific / Indian: Most distant part of the global conveyor, longest time since ventilation, considerable remineralization Southern Ocean / S. Pacific: Massive ventilation and deep water formation, productivity limited (iron?) We can look at this more closely using age tracers -- CFC invasion

17. Atlantic A22 CFC-12 Age Age calculations by Bill Smethie & Samar Khatiwala [LDEO] STMW Deep Caribbean AAIW NADW

18. Pacific P16 CFC-12 AAIW AABW Very Old Water

19. P < 0.025 T ~ 10y T ~ 50y T > 200 y Age vs. CDOM Nelson et al. [2007] DSR-I

20. CDOM Dynamics Pacific / Indian: Overall correlation with AOU, wide CDOM range Atlantic: Correlation with age & AOU in the main thermocline, subtropical mode water, and upper AAIW, narrow CDOM range Advection obscures CDOM production signal in the Atlantic Pacific / Indian: Overall correlation with AOU, wide CDOM range Atlantic: Correlation with age & AOU in the main thermocline, subtropical mode water, and upper AAIW, narrow CDOM range Advection obscures CDOM production signal in the Atlantic

21. CDOM Atlantic / Pacific sections Top: (A16N, A20, AMMA, A16S) Bottom: P16N/S

22. CDOM Dynamics: Atlantic North Atlantic EQSubtropics Mode Water South Atlantic Rapid meridional overturning allows little CDOM accumulation Advection + bleaching balances net production

23. CDOM Dynamics: Pacific / Indian North Pacific EQSubtropics Mode Water South Pacific Southern O. North: Long residence time allows CDOM accumulation South: Production limited (iron?) Low surface signal carried to depth by advection / water mass formation

24. CDOM Dynamics Surface: Rapid turnover, production, consumption, and bleaching balanced, upwelling a minor contributor. Mode waters: Ventilation carries surface signature across wide areas Intermediate + Deep waters: CDOM abundance controlled by advection/net production balance Surface: Rapid turnover, production, consumption, and bleaching balanced, upwelling a minor contributor. Mode waters: Ventilation carries surface signature across wide areas Intermediate + Deep waters: CDOM abundance controlled by advection/net production balance

25. Transformations of CDOM & DOM in the ocean What chemical transformations of CDOM occur in the ocean? –We don’t have many handles to turn on this at the moment, but we have: Changes in the CDOM/DOC relationship (a* cdom ) DOM quality indexes (Neutral sugar and carbohydrate content) Changes in the CDOM spectrum (Spectral slope parameter) What chemical transformations of CDOM occur in the ocean? –We don’t have many handles to turn on this at the moment, but we have: Changes in the CDOM/DOC relationship (a* cdom ) DOM quality indexes (Neutral sugar and carbohydrate content) Changes in the CDOM spectrum (Spectral slope parameter)

26. a * cdom (325) a * cdom = CDOM / DOC (units m 2 g -1 ) Upper layers bleaching & production signals a * cdom increases w/ depth & age CDOM “abundance” changes less than the DOC decline -- CDOM is refractory DOM Aging New Bleaching Nelson et al. [2007] DSR-I

27. DOM Quality: Carbohydrates and DOC, A20 STMW LTCL uAAIW Sugars decrease as CDOM increases Neutral sugar content of DOC also decreases AOU increases

28. Spectral Slope Parameter S (nm -1 ), 280-400 nm, non linear fit Typical Coastal: 0.015 nm -1 Typical Sargasso Surface: > 0.025 nm -1 Newly Produced Sargasso: ~ 0.022 nm -1 (Nelson et al. Mar. Chem 2004) S (nm -1 ), 280-400 nm, non linear fit Typical Coastal: 0.015 nm -1 Typical Sargasso Surface: > 0.025 nm -1 Newly Produced Sargasso: ~ 0.022 nm -1 (Nelson et al. Mar. Chem 2004)

29. Trends in CDOM spectral characteristics - N. Atl. P < 0.025 Nelson et al. [2007] DSR-I

30. Spectral Slope to Age? Handwaving age estimate: S nlf of ≈ 0.014 nm -1 … >50 years mean ventilation age

31. Summary / Conclusions CDOM dynamics worldwide reflect a balance between production and bleaching, moderated by the rate of advection. CDOM is also produced (slowly) at depth as a byproduct of remineralization. The CDOM optical signature is more refractory than the bulk DOC pool. DOM undergoes chemical transformations with age that are reflected in the carbohydrate composition and optical properties. CDOM dynamics worldwide reflect a balance between production and bleaching, moderated by the rate of advection. CDOM is also produced (slowly) at depth as a byproduct of remineralization. The CDOM optical signature is more refractory than the bulk DOC pool. DOM undergoes chemical transformations with age that are reflected in the carbohydrate composition and optical properties.

32. Ongoing and future work What is the nature of CDOM in the deep ocean and what transformations occur? We’re tackling this with fluorescence spectroscopy and hopefully more advanced techniques to try and identify key chromophore groups and how they change over time and space What is the nature of CDOM in the deep ocean and what transformations occur? We’re tackling this with fluorescence spectroscopy and hopefully more advanced techniques to try and identify key chromophore groups and how they change over time and space

33. Acknowledgments NASA Ocean Biology and Biogeochemistry NSF Chemical Oceanography U.S. CLIVAR/CO 2 Repeat Hydrography Project (Jim Swift, Lynne Talley, Dick Feely, Rik Wanninkhof, Rana Fine) UCSB Field Teams: Dave Menzies, Jon Klamberg, Meredith Meyers, Ellie Wallner, Meg Murphy, Natasha McDonald Hansell Group: Charlie Farmer, Wenhao Chen Bill Landing (FSU) and Chris Measures (UHI) (Water samples) Ru Morrison & Mike Lesser, UNH (MAA analysis) Wilf Gardner and Team, TAMU (C-Star transmissometer) Mike Behrenfeld and Team, OSU (Equatorial BOX project) Erica Key and Team, U Miami (AMMA-RB 2006) Jim Murray and Team, UW (EUCFe 2006) R/Vs Brown, Knorr, Revelle, Melville, Thompson, Ka’I, Kilo Moana NASA Ocean Biology and Biogeochemistry NSF Chemical Oceanography U.S. CLIVAR/CO 2 Repeat Hydrography Project (Jim Swift, Lynne Talley, Dick Feely, Rik Wanninkhof, Rana Fine) UCSB Field Teams: Dave Menzies, Jon Klamberg, Meredith Meyers, Ellie Wallner, Meg Murphy, Natasha McDonald Hansell Group: Charlie Farmer, Wenhao Chen Bill Landing (FSU) and Chris Measures (UHI) (Water samples) Ru Morrison & Mike Lesser, UNH (MAA analysis) Wilf Gardner and Team, TAMU (C-Star transmissometer) Mike Behrenfeld and Team, OSU (Equatorial BOX project) Erica Key and Team, U Miami (AMMA-RB 2006) Jim Murray and Team, UW (EUCFe 2006) R/Vs Brown, Knorr, Revelle, Melville, Thompson, Ka’I, Kilo Moana