1/30 is there a higher c ant storage in the indian ocean? estimating the storage of anthropogenic...

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IS THERE A HIGHER CIS THERE A HIGHER CANTANT STORAGE STORAGE

IN THE INDIAN OCEAN?IN THE INDIAN OCEAN?

Estimating the storage of anthropogenic carbon in the subtropical Indian Ocean: a comparison of five different approaches

M. Álvarez, C. Lo Monaco, T. Tanhua, A. Yool, A. Oschlies, J. L. Bullister, C. Goyet, N. Metzl, F. Touratier, E. McDonagh, and H. L. Bryden, Biogeosciences, 6, 681-703, 2009.

http://www.biogeosciences-discuss.net/6/729/2009/bgd-6-729-2009.html

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CANT ALONG CD139 CRUISE (2002) 32ºS INDIAN OCEAN

44.5 5 Pg 44.8 6 Pg 20.3 3 Pg

Indian Ocean

Pacific Ocean Atlantic Ocean

(Sabine et al, Science 2004)

CCANTANT inventory referred to 1994 = 110 ± 13 Pg C inventory referred to 1994 = 110 ± 13 Pg C

Indian Ocean contains

- 21% of the total CANT inventory

- half of the Atlantic CANT inventory despite having only 20% less area

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Indian Ocean CIndian Ocean CANTANT vertical distribution vertical distribution mol/kg mol/kg

(Sabine et al, Science 2004)

RedSea /Persian Gulf Intermediate Water

Antarctic Intermediate Water (AAIW)

AAIW marks the deepest CANT penetration in the Subtropical gyre

No CANT in deep and bottom waters

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Hypothesis:

CANT penetrates deeper than 1000-1500 m

How to assess this question:

compare different CANT methods -> difficult: every method has high uncertainties

help: relation of CANT with tracers (CFC12, CCl4)

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On board R/V Charles Darwin, CD139 cruise, 1/3 – 15/4/2002, from Durban to Freemantle

P.I.: Harry Bryden (National Oceanographic Centre, Southampton, UK)

Physics: temperature, salinity, ADCP, LADCP

Chemistry: oxygen, salinity, nutrients, CO2 (pH & TA, TIC), CFCs (11, 12, 113), CCl4.

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Salinity (psu)Africa Australia

NADW

AAIW

SAMW

CDW

AABW

AAIW

SAMW

NADW

AAIW

SAMW

AABW

NADW

AAIW

SAMW

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CFC-12 (pmol/kg)

CDW

AABW

NADW

AAIW

SAMW

CDW

Africa Australia

AAIW

SAMW

AABW

AAIW

SAMW

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CANT TECHNIQUES

1. CANT SAB99: method by Sabine et al. (GBC,1999), using their CDis

2. CANT LM05: method by LoMonaco et al. (JGR, 2005)

3. CANT TrOCA: Touratier & Goyet (Tellus, 2007)

4. CANT TTD

5. CANT from OCCAM model

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CANT = C* - CDis = C – AOU/RC – ½(TA + AOU/RN ) + 106/104 · N* - C280 – CDis

C is the current total inorganic carbon

TA = TA - TA0, current alkalinity - preformed alkalinity TA0= 378.1 + 55.22 · Sal + 0.0716 · PO - 1.236 · Tpot

AOU is the Apparent Oxygen Utilization, assuming oxygen saturation

C280 is the inorganic carbon in equilibrium with the preindustrial atmosphere. C280 = f (Tpot, Sal, TA0, pCO2280) from thermodynamic equations pCO2280 = CO2 fugacity at a 100% of water vapor pressure in uatm = f(Tpot, Sal, 280) C280 in GSS96 => constants by Goyet & Poisson (1989) & a constant pCO2280 = 280 uatm linearilized equation: C280 = 2072 - 8.982 · (Tpot - 9) - 4.931 · (Sal - 35) + 0.842 · (TA0- 2320)

N* = (0.87 · (NO3 - 16 · PO4 + 2.9)) term accounting for the denitrification

Back-calculation technique by Sabine et al. (GBC, 1999) to estimate CANT.

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CDis is obtained with own CD139 data using CFC12 ages and limit at 40 years

a) Old deep waters, CANT = 0 => C* = CDis

b) In upper waters, having the age: CDis = C*t|σ=cte

C*t = C - CBio - C t where Ct = f (Tpot, Sal, TA0, pCO2t) pCO2 in the atmosphere at 2002 – age (t)

c) In between => weigthed mean C* and C*t|=cte

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-35

-30

-25

-20

-15

-10

-5

0

5

25.8 26.3 26.8 27.3 27.8q

C di

s um

ol/k

g

SAB99 own Tables

SAB99

Comb

Interpolated

C*t method C* & C*t means C* method


Fig. 4. Air-sea CO2 disequilibrium (mol kg-1) by q density intervals. Blue points correspond to the values taken directly from SAB99 work, light blue and orange points correspond to the values estimated using the CD139 biogeochemical data, following SAB99 (orange) and combined (light blue) methods. Interpolated points are highlighted with black open circles.

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Back-calculation technique by Lo Monaco et al. (JGR, 2005):

CANT = CT – CBio - CT0 obs – (CT– CBio – C0 obs) REF

CT = measured TIC

CBio = 0.73·(O20 – O2) + 0.5·(TA – TA0) => biological activity variation in TIC

TA0 => preformed TA

O20 = O2

sat – ··O2Sat => O2 = 12% undersaturation

K = > mixing ratio of ice-covered water (OMP)

C0 obs => preformed TIC currently observed in the formation area water masses

REF = reference water where no CANT should be detected.

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mixing ratios of southern and northern waters:

k(S) + k(NADW) = 1 determined from OMP analysis

TA0 = k(S) TA0(S) + k(N) TA0(NADW)

C0,obs = k(S) C0,obs(S) + k(N) C0,obs(NADW)

southern relationships:

winter surface data from the Atlantic and Indian oceans (WOCE and OISO cruises)

TA0(S) = 0.0685 PO + 59.787 S - 1.448 q + 217.15 (± 5.5 µmol/kg, r2 = 0.96, n = 243)

C0,obs(S) = -0.0439 PO + 42.79 S - 12.019 q + 739.83 (± 6.3 µmol/kg, r2 = 0.99, n = 428)

northern relationships

subsurface data from the North Atlantic and Nordic Seas (WOCE and KNORR cruises)

TA0(N) = 42.711 S + 1.265 q + 804.6 (± 9.3 µmol/kg, r2 = 0.92, n = 297)

C0,obs(N) = 10.69 S + 0.306 NO + 1631.6 (± 9.2 µmol/kg, r2 = 0.79, n = 364)

Back-calculation technique by Lo Monaco et al. (JGR, 2005)

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OMP analysis modified from Lo Monaco et al. (JGR, 2005)Endmembers: AAIW, NADW-E, NIDW, Indian Water, WDS/CDW, ISW Weddell Variables: Sal, Tpot, SiO2 and NO

34.1 34.2 34.3 34.4 34.5 34.6 34.7 34.8 34.9-2

0

2

4

6

AAIW2 IW

NADW-E NIDW

WDW/CDW

ISW Wed

0 20 40 60 80 100 120 140 160 180-2

0

2

4

6

AAIW2 IW

NADW-E NIDW

WDW/CDW

ISW Wed

450 500 550 600-2

0

2

4

6

AAIW2 IW

NADW-E NIDW

WDW/CDW

ISW Wed

Salinity

SiO2

NO

Tpo

tT

pot

Tpo

t

16/30-2 -1 0 1 2

-5500

-5000

-4500

-4000

-3500

-3000

-2500

-2000

-1500

-1000

Med-Calc weighted & adim.-0.2 -0.1 0 0.1 0.2 0.3

-5500

-5000

-4500

-4000

-3500

-3000

-2500

-2000

-1500

-1000

Med-Calc Real-10 -5 0 5 10 15

-5500

-5000

-4500

-4000

-3500

-3000

-2500

-2000

-1500

-1000

Med-Calc Real

Tpot

Sal

SiO2NO

data5

Tpot

Sal SiO2

NO

CANT ALONG CD139 CRUISE (2002) 32ºS INDIAN OCEANBack-calculation technique by Lo Monaco et al. (JGR, 2005): OMP

Tpot, Sal, SiO2 NO STD Res. 0.0481 0.0051 1.3 3R2 0.9979 0.9967 0.9973 0.9611 (n=1299)

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CANT ALONG CD139 CRUISE (2002) 32ºS INDIAN OCEAN2. Back-calculation technique by Lo Monaco et al. (JGR, 2005): OMP

NADW contribution

Ice-covered SW contribution

Africa AustraliaAfrica Australia

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REF = NADW= reference water where no CANT should be detected.

Applied to samples with more 50% NADW from OMP analysis

(CT – CBio – C0 obs) REF = - 54.4 ± 1.4 umol/kg

(LoMonaco JGR2005 -51 umol/kg)


CANT = CT – CBio - CT0 obs – (CT– CBio – C0 obs) REF

CANT = CT – CBio - CT0 obs – (- 54.4)

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CANT TrOCA, Touratier et al (Tellus B, 2007):

CANT = (O2 + 1.279 · (CT – 0.5 · TA) – exp (7.511-0.01087· θ -781000/TA2))/1.279)

CANT (TrOCA) = (TrOCA – TrOCA280) / a

TrOCA = O2 + a · (CT -1/2 ·TA) a = ψO2 / [ψCO2 + ½ ·( ψ H+ − ψHPO24−)]

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4. CANT TTD (Waugh et al., 2004; 2006; Tanhua et al., 2008):

- each water sample has its own “age”, i.e. time since it was last in contact with the atmosphere. The sum of all these ages makes the TTD of a water sample

- the mean age ( ) and the width of the TTD () are assumed to be of equal magnitude: realistic assumption of the relation between advective and diffusive transport in the Ocean

- CANT is an inert passive tracer where air-sea disequilibrium hasn’t changed over time.

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5. CANT OCCAM

- global, medium-resolution, primitive equation ocean general circulation model (Marsh et al., 2005).

- OCCAM's vertical resolution is 66 levels (5 m thickness at the surface, 200 m at depth), with a horizontal resolution of typically 1 degree.

- Advection is 4th order accurate, and the model is time-integrated using a forward leapfrog scheme with a 1 hour time-step.

- Surface fluxes of heat and freshwater not specified but are calculated empirically using NCEP-derived atmospheric boundary quantities (Large and Yeager, 2004).

- OCCAM incorporates a NPZD plankton ecosystem (Oschlies, 2001; Yool et al., 2007) which drives the biogeochemical cycles of nitrogen, carbon, oxygen and alkalinity.

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CANT vertical distributions

pCFC12 & pCCl4 SAB99 LM05Troca TTD OCCAM

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CANT mean profile differences

-10 0 10 20

-5000

-4000

-3000

-2000

-1000

0The whole section

-10 0 10 20

-5000

-4000

-3000

-2000

-1000

0Western section

-10 0 10 20

-5000

-4000

-3000

-2000

-1000

0Mid section

-10 0 10 20

-5000

-4000

-3000

-2000

-1000

0East section

Troca

LM05

TTDOCCAM

data5

a)

c) d)

b)

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Neutral density layers & salinity

Africa Australia

Bottom

AAIW

SAMW

Deep

Surface

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0

2

4

6

8

10

12

Surface SAMW AAIW Deep Bottom

CA

NT

inve

ntor

y (m

olC

/m2)

Troca

LM05

SAB99

TTD

OCCAM

LMZero

0

5

10

15

20

25

30

35

Total SAMW AAIW Deep Bottom

CA

NT

inve

ntor

y (m

olC

/m2)


CANT mean inventories

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Revelle = 10


Surface, SAMW waters and upper AAIW

Revelle = 13

Fig. 10. Partial pressure of CFC-12 (ppt) and CANT estimates (mmol kg-1) for upper waters with potential temperature higher than 5ºC, pressure higher than 200 dbar and CFC-12 age less than 30 years. Also shown in black is the atmospheric evolution of CFC-12 and CANT using Revelle factors of 10 and 13 (see text for details), some time markers are shown.

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Deep and bottom waters

Fig. 11. a) Partial pressure of CFC-12 (ppt) and b) partial pressure of CCl4 (ppt) versus CANT (mol kg-1) estimates for deep waters with potential temperature lower than 5ºC, pressure higher than 200 dbar and CFC-12 age higher than 40 years. In the case of CCl4, the temperature limit is 3ºC. Also shown in black are the atmospheric evolution of CFC-12, CCl4 and CANT using Revelle factors of 10 and 13 (see text for details), some time markers are shown.

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Table 1. Mean standard deviation CANT specific inventory (molC m-2) by water masses in the

subtropical Indian Ocean for the different methods here evaluated. Mean and standard deviation values were obtained randomly modifying the initially calculated single CANT values by 5

mol kg-1. A set of 100 perturbations were done for the five methods. The standard deviation for each layer is weighted by the layer contribution to the total section area. See text for the acronyms. N/D stands for not determined. Values between brackets correspond to the LM05 method assuming a 100% oxygen saturation in equation (7), =0.

Upper SAMW AAIW Deep Bottom Total*

SAB99 N/D 8.50.5 8.10.4 00.5 0.30.2 23.9 2

LM05 N/D 110.7 110.50.60.4

(0.50.4)1.20.3

(0.00.3)30.82.5

(29.52.5)

TrOCA N/D 8.40.5 9.40.5 1.90.5 1.40.3 28.12.2

TTD 7.2 0.7 9.30.6 9.30.5 20.4 1.30.2 28.92.3

OCCAM 6.91.5 9.30.8 7.60.5 0.50.1 00 24.4 2.8

* The total specific inventory is calculated as the sum of the SAMW, AAIW, Deep and Bottom contributions plus 7 molC m-2, i.e., the TTD and OCCAM mean specific inventory for the upper layer.


Inventories

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This work investigates the CANT penetration and inventory in the subtropical Indian Ocean along 32ºS calculated with data collected in 2002. Five different methods are compared and discussed: three carbon-based methods (C*, LM05 and TrOCA), TTD and a simulation from the OCCAM global model.

Comparatively, the C* method seems to yield too shallow penetration of CANT, with no or very low CANT detected in deep or bottom waters, mainly due to the formulation and assumptions of CTdis.

Our results indicate that SAB99 CTdis values are inconsistent with the current air-sea CO2 disequilibrium found in current Indian Ocean winter CTdis values. Although this could also be misleading taking into account that water masses are usually formed in particular times and areas of the ocean.

Previous estimates of CANT inventory in the subtropical Indian Ocean with the C* method appear to be underestimates.

Considering the CANT estimates derived from those methods consistent with the tracer distributions and the knowledge about water masses, our best estimate for the mean CANT specific inventory is 282 molC m-2 which compares with 242 molC m-2 from C*, 17% higher.


Conclusions

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Hypothesis:

CANT penetrates deeper than 1000 m (Sabine et al 1999)

How to assess this question:

difficult: every method has uncertainties

help: relation of CANT with tracers (CFC12, CCl4)

seems to be hinted by any other method

absolutely true, no method is perfect

questions still arise, saturation, mixing, etc..

community should combine methods and time-evolution studies at specially

sensitive regions

OPEN DISCUSSION: KEY REGION ….. THE SO

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Discusión:

¿Cuáles son las asunciones de cada método?

¿nos creemos el desequilibrio?

¿Qué método os parece el más fiable?

¿Se os ocurre como evaluar los métodos de otra manera?

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