CDOM in the Deep Sea: CDOM in the Deep Sea: Distribution and Dynamics from Distribution and Dynamics from

Trans-ocean SectionsTrans-ocean Sections

CDOM in the Deep Sea: CDOM in the Deep Sea: Distribution and Dynamics from Distribution and Dynamics from

Trans-ocean SectionsTrans-ocean Sections

Norm Nelson, Dave Siegel, Craig CarlsonChantal Swan, Stu Goldberg

UC Santa BarbaraSpecial thanks to: Bill Smethie and Samar Khatiwala, LDEO

Dennis Hansell, University of Miami

Norm Nelson, Dave Siegel, Craig CarlsonChantal Swan, Stu Goldberg

UC Santa BarbaraSpecial thanks to: Bill Smethie and Samar Khatiwala, LDEO

Dennis Hansell, University of Miami

Ocean Sciences Meeting 2008

OutlineOutline

• 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

What we already know (Bermuda)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)

Global Surface CDOM Distribution

(From SeaWiFS)

Global Surface CDOM Distribution

(From SeaWiFS)

Siegel et al. [2005] JGR

UCSB Global CDOM Project GoalsUCSB 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

Global CDOM Project SectionsGlobal CDOM Project Sections

EUCFe 2006

EqBOX2005 2006

AMMA 2006

UCSB Global CDOM Project Measurements & MethodsCDOM Analysis At Sea

UCSB Global CDOM Project Measurements & MethodsCDOM Analysis At Sea

• 200 cm Liquid Waveguide Absorption Cell (UltraPath, WPI Inc)

• Single-beam spectrophotometer with D2 & 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 D2 & 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

UltraPathPrecisionUltraPathPrecision

• Duplicate sampleanalysis (same Niskin)

• RMS differenceat 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 sampleanalysis (same Niskin)

• RMS differenceat 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

UltraPath Example CDOM ProfilesUltraPath Example CDOM Profiles

CDOM Dynamics and HydrographyCDOM 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

Selected CDOM sectionsSelected CDOM sections

(Global CDOM map from SeaWiFS/GSM, mission mean)

acd

om (443 nm

, m-1)

Atlantic A22 CDOM / AOU (Apparent Oxygen Utilization)Atlantic A22 CDOM / AOU (Apparent Oxygen Utilization)

STMW

DeepCaribbean

AAIW

NAD

W

GS

STMW

DeepCaribbean

AAIW

NAD

W

GS

Pacific P16 CDOM / AOUPacific P16 CDOM / AOU

Indian I8S/I9N CDOM / AOU Indian I8S/I9N CDOM / AOU

Atlantic vs. Pacific/Indian: what’s different?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

Atlantic A22 CFC-12 Age Atlantic A22 CFC-12 Age

Age calculations by Bill Smethie & Samar Khatiwala [LDEO]

STMW

DeepCaribbean

AAIW

NAD

W

Pacific P16 CFC-12 Pacific P16 CFC-12

AAIW

AABWVery Old Water

P < 0.025 P < 0.025

P < 0.025

P < 0.025

T ~ 10y

T ~ 50y

T > 200 y

Age

vs.

CD

OM

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CDOM DynamicsCDOM 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

CDOM Atlantic / Pacific sectionsCDOM Atlantic / Pacific sectionsTop: (A16N, A20, AMMA, A16S) Bottom: P16N/STop: (A16N, A20, AMMA, A16S) Bottom: P16N/S

CDOM Dynamics: Atlantic

North Atlantic EQSubtropics Subtropics

Mode Water Mode Water

South Atlantic

Rapid meridional overturning allows little CDOM accumulationAdvection + bleaching balances net production

CDOM Dynamics: Pacific / Indian

North Pacific EQSubtropics Subtropics

Mode Water

South PacificSouthern O.

North: Long residence time allows CDOM accumulation

South: Production limited (iron?) Low surface signal carried to depth by advection / water mass formation

CDOM DynamicsCDOM 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

Transformations of CDOM & DOM in the oceanTransformations 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)

a*cdom(325)a*cdom(325)

aa**cdom cdom = CDOM / DOC= CDOM / DOC

(units m(units m22gg-1-1))

Upper layers bleaching Upper layers bleaching & production signals& production signals

aa**cdomcdom increases w/ increases w/

depth & agedepth & age

CDOM “abundance” CDOM “abundance” changes less than the changes less than the DOC decline -- CDOM is DOC decline -- CDOM is refractory DOMrefractory DOM

Aging

NewNew

Ble

ach

ing

Nelson et al. [2007] DSR-I

DOM Quality: Carbohydrates and DOC, A20DOM Quality: Carbohydrates and DOC, A20

STMW

STMW

LTCL

LTCL

uAAIW

Sugars decreaseas CDOM increases

Neutral sugar content of DOC also decreases

AOU increases

Spectral Slope Parameter 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)

Trends in CDOM spectral characteristics - N. Atl. Trends in CDOM spectral characteristics - N. Atl.

P < 0.025P < 0.025 P < 0.025

P < 0.025P < 0.025

P < 0.025 P < 0.025

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Spectral Slope to Age?Spectral Slope to Age?

Handwaving age estimate:Handwaving age estimate:

SSnlfnlf of ≈ 0.014 nm of ≈ 0.014 nm-1-1 … >50 years mean ventilation age … >50 years mean ventilation age

Summary / ConclusionsSummary / 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.

Ongoing and future workOngoing 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

AcknowledgmentsAcknowledgments

• NASA Ocean Biology and Biogeochemistry • NSF Chemical Oceanography

• U.S. CLIVAR/CO2 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/CO2 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