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Impact of oceanic processes on the carbon cycle during the last termination Article

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Bouttes, N., Paillard, D., Roche, D.M., Waelbroeck, C., Kageyama, M., Lourantou, A., Michel, E. and Bopp, L. (2012) Impact of oceanic processes on the carbon cycle during the last termination. Climate of the Past, 8 (1). pp. 149170. ISSN 18149324 doi: https://doi.org/10.5194/cp81492012 Available at http://centaur.reading.ac.uk/34189/

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Climateof the Past

Impact of oceanic processes on the carbon cycleduring the last termination

N. Bouttes1,2, D. Paillard1, D. M. Roche1,3, C. Waelbroeck1, M. Kageyama1, A. Lourantou4, E. Michel1, and L. Bopp1

1Laboratoire des Sciences du Climat et de l’Environnement, UMR8212, IPSL-CEA-CNRS-UVSQ, Centre d’Etudes deSaclay, Orme des Merisiers bat. 701, 91191 Gif Sur Yvette, France2NCAS-Climate, Meteorology Department, University of Reading, Reading, RG66BB, UK3Faculty of Earth and Life Sciences, Section Climate Change and Landscape dynamics, Vrije Universiteit Amsterdam,De Boelelaan, 1085, 1081 HV Amsterdam, The Netherlands4LOCEAN, University Paris VI, Paris, France

Correspondence to:N. Bouttes ([email protected])

Received: 31 May 2011 – Published in Clim. Past Discuss.: 14 June 2011Revised: 10 December 2011 – Accepted: 12 December 2011 – Published: 20 January 2012

Abstract. During the last termination (from∼18 000 yearsago to∼9000 years ago), the climate significantly warmedand the ice sheets melted. Simultaneously, atmospheric CO2increased from∼190 ppm to∼260 ppm. Although this CO2rise plays an important role in the deglacial warming, thereasons for its evolution are difficult to explain. Only boxmodels have been used to run transient simulations of thiscarbon cycle transition, but by forcing the model with dataconstrained scenarios of the evolution of temperature, sealevel, sea ice, NADW formation, Southern Ocean verticalmixing and biological carbon pump. More complex models(including GCMs) have investigated some of these mecha-nisms but they have only been used to try and explain LGMversus present day steady-state climates.

In this study we use a coupled climate-carbon model ofintermediate complexity to explore the role of three oceanicprocesses in transient simulations: the sinking of brines,stratification-dependent diffusion and iron fertilization. Car-bonate compensation is accounted for in these simulations.We show that neither iron fertilization nor the sinking ofbrines alone can account for the evolution of CO2, and thatonly the combination of the sinking of brines and interactivediffusion can simultaneously simulate the increase in deepSouthern Oceanδ13C. The scenario that agrees best with thedata takes into account all mechanisms and favours a rapidcessation of the sinking of brines around 18 000 years ago,when the Antarctic ice sheet extent was at its maximum. Inthis scenario, we make the hypothesis that sea ice forma-tion was then shifted to the open ocean where the salty wa-ter is quickly mixed with fresher water, which prevents deep

sinking of salty water and therefore breaks down the deepstratification and releases carbon from the abyss. Based onthis scenario, it is possible to simulate both the amplitudeand timing of the long-term CO2 increase during the last ter-mination in agreement with ice core data. The atmosphericδ13C appears to be highly sensitive to changes in the terres-trial biosphere, underlining the need to better constrain thevegetation evolution during the termination.

1 Introduction

The last termination, which took place between∼18 000and ∼9000 years ago, is characterized by a global warm-ing (Visser et al., 2003; North Greenland Ice Core Projectmembers, 2004; EPICA community members, 2004; Barkeret al., 2009) associated to a shrinking of the ice sheets(Peltier, 1994, 2004; Svendsen et al., 2004). The climateevolved from a cold glacial state (sea surface temperatureof −2 to −6◦ C cooler relative to today in the SouthernOcean;MARGO Project Members, 2009) associated withlarge Northern Hemisphere ice sheets covering large partsof Europe and North America (Peltier, 2004) to a warmer in-terglacial state with reduced ice sheets, similar to the modernones.

The warming in Antarctica is tightly linked to an atmo-spheric CO2 increase from∼190 ppm at the Last GlacialMaximum (LGM, ∼21 000 years ago) to∼260 ppm at thebeginning of the Holocene (∼9000 years ago) (Monnin et al.,2001; Lourantou et al., 2010). The CO2 rise is crucial to

Published by Copernicus Publications on behalf of the European Geosciences Union.

150 N. Bouttes et al.: Ocean processes during the last termination

explain the warming and shrinking of ice sheets (Bergeret al., 1998; Charbit et al., 2005; Ganopolski et al., 2010),in association with the change of insolation. Yet explainingsuch an increase remains a challenge.

Moreover, the isotopic composition of carbon (δ13C) bothin the atmosphere and ocean also evolves during the tran-sition, providing clues and constraints on the evolution ofthe carbon cycle. The atmosphericδ13C (δ13Catm) presents aW-shape with two negative excursions of 0.5 % during Hein-rich event 1 (H1) and the Younger Dryas (YD) (Lourantouet al., 2010). In the ocean the vertical gradient ofδ13Cocean(the gradient between the upper,−2000 m to 0 m, and thedeep,−5000 m to−3000 m, ocean1δ13Cocean= δ13Cupper−

δ13Cbottom) decreases both in the South and North Atlantic.In particular, the deep South Atlantic values increase fromaround−0.8 ‰ at the LGM to around 0.4 ‰ in the modernocean (Hodell et al., 2003; Curry and Oppo, 2005), and morelocally from around−1 ‰ to around 0 ‰ at the location ofcore MD07-3076Q (44◦ S, 14◦ W, −3770 m) (Skinner et al.,2010; Waelbroeck et al., 2011).

Furthermore, during the deglaciation the carbon content ofthe terrestrial biosphere globally increases as the vegetationexpands on previously glaciated areas, although it decreaseson areas of the continental shelf that become flooded (Mon-tenegro et al., 2006). The general warming generates a mi-gration of ecosystems towards the poles while the rise of CO2favours the uptake of carbon by plants (Kaplan et al., 2002;Kohler and Fischer, 2004). Carbon storage by the terrestrialbiosphere from the LGM to the preindustrial is estimatedby vegetation models to be between 600 GtC and 821 GtC(Kaplan et al., 2002; Brovkin et al., 2002b; Kohler and Fis-cher, 2004). Reconstructions based on proxy data estimatethe range of possible terrestrial carbon change to be 270–720 GtC from marine records (Bird et al., 1994), and 750–1050 GtC from pollen based estimations (Crowley, 1995).

Since both the atmosphere and the terrestrial biospherecarbon contents increase during the termination, it is gen-erally concluded that the ocean, the largest of the three reser-voirs, must be the one that looses carbon. Various hypothe-ses have been proposed to explain the atmospheric CO2 in-crease based on modifications of the oceanic carbon content.Most of them focus either on changes in the dynamics ofthe ocean or on modifications of the marine biology (Archeret al., 2000; Sigman and Boyle, 2000; Fischer et al., 2010;Sigman et al., 2010). Yet the tight link between Antarc-tic temperature and CO2 (Cuffey and Vimeux, 2001) sug-gests a simple mechanism instead of a complex associationof numerous independent processes. Besides, many of themhave been discarded or only account for a small CO2 changesuch as the coral reef hypothesis (Berger, 1982; Broeckerand Peng, 1982; Opdyke and Walker, 1992; Kohler et al.,2005a), modification of winds (Toggweiler et al., 2006; Men-viel et al., 2008a), or sea ice extension (Stephens and Keel-ing, 2000; Archer et al., 2003), as they required unrealisticchanges to account for most of the glacial-interglacial CO2

change. Other mechanisms have been confirmed. Enhancedmarine biology by iron fertilization during the glacial period,which would then decrease during the deglaciation, is as-sumed to play a role (Martin, 1990), although of relativelysmall importance as it could account for a 15–20 ppm change(i.e. approximately 20 % of the∼90 ppm total CO2 change)(Bopp et al., 2003; Tagliabue et al., 2009). Carbonate com-pensation is a recognized process that amplifies the uptakeor loss of carbon by the ocean (Broecker and Peng, 1987;Archer et al., 2000; Brovkin et al., 2007). Finally, changesin the oceanic circulation and mixing can have a signifi-cant impact on glacial CO2 (Toggweiler, 1999; Paillard andParrenin, 2004; Kohler et al., 2005a; Watson and Garabato,2005; Bouttes et al., 2009; Skinner et al., 2010). In particular,it has been recently shown that the deep stratification inducedby enhanced brine sinking can strongly decrease CO2 duringthe LGM relative to the preindustrial and simultaneously in-crease the upper to deep oceanδ13C gradient, in line withdata (Bouttes et al., 2010, 2011).

Moreover, if the sinking of brines is not taken into account,the mechanisms already tested are not sufficient to explainthe entire glacial-interglacial CO2 change in models of inter-mediate complexity (EMICs) or General Circulation Models(GCMs), as there is no physical mechanism to account for asufficient glacial deep stratification and reduced circulation.Only box models have been able to perform a simulationof the last termination carbon cycle evolution by imposingthe evolution of the oceanic circulation and mixing inferredfrom proxy data (Kohler et al., 2005a). Yet box models canbe over-sensitive to changes in high latitudes (Archer et al.,2003). Additionally, because of their simplicity, the reasonsfor such changes in mixing and circulation that are crucial forthe amplitude of the CO2 change (more than 45 ppm of the∼90 ppm change;Kohler et al., 2005a) could not be tested.

In this study we use a climate model of intermediate com-plexity to explore the impact of two main oceanic mecha-nisms during the termination: the sinking of brines, whichalters the circulation and mixing of water masses and has notyet been tested in transient simulations, and iron fertiliza-tion. Two other processes that are not independent are alsoconsidered: the amplification of the effects of the sinking ofbrines by its feedback on diffusion and the amplification ofthe oceanic uptake of carbon by the carbonate compensationmechanism.

2 Methods

2.1 The Earth system model of intermediate complexityCLIMBER-2

We use the CLIMBER-2 coupled intermediate complexitymodel (Petoukhov et al., 2000; Ganopolski et al., 2001),which is well suited to perform the long runs of sev-eral thousands of years requested to study the deglaciation.

Clim. Past, 8, 149–170, 2012 www.clim-past.net/8/149/2012/

N. Bouttes et al.: Ocean processes during the last termination 151

CLIMBER-2’s atmosphere has a coarse resolution of 10◦ inlatitude by 51◦ in longitude, which is precise enough to takeinto account geographical changes, while allowing the modelto be fast enough to run long simulations. The ocean is sub-divided into three zonally averaged basins with a resolutionof 21 depth levels by 2.5◦ latitude. It includes a carbon cyclemodel with the fractionation of13C (Brovkin et al., 2002a).In addition to modules simulating the ocean, atmosphere,and continental biosphere dynamics, the model also includesa model of carbonate compensation (Brovkin et al., 2007;Archer, 1991). The coupling between CLIMBER-2 and thecarbonate compensation model has been discussed in detailin Brovkin et al.(2007). Moreover, three mechanisms havebeen added in the present study: the sinking of brines, ironfertilization, and stratification-dependent diffusion.

2.2 Additional mechanisms

2.2.1 Iron fertilization

Iron fertilization relies on the removal of the iron limita-tion in the “High Nutrient Low Chlorophyll” (HNLC) areasthanks to the supply of glacial atmospheric dust which con-tains iron (Martin, 1990; Bopp et al., 2003; Brovkin et al.,2007; Tagliabue et al., 2009). According to a proxy-basedstudy of the change of productivity, this effect would havebeen restrained to the areas north of the modern-day Antarc-tic polar front (Kohfeld et al., 2005). In the model, it issimply taken into account by forcing the marine biology touse all the nutrients that would otherwise be left in the At-lantic and Indian sectors of the Sub-Antarctic surface ocean(30◦ S to 50◦ S) during the glacial period as previously done(Brovkin et al., 2007). This is a simple parameterization ofthe effect of iron fertilization as the iron cycle is not simu-lated in the model. As done inBouttes et al.(2011), we usea parameter to vary this effect between 0 and 1. This param-eter is first set to 1 to explore the maximum potential effectof this mechanism. In the last section, we use a combinationof the three mechanisms fromBouttes et al.(2011) in whichthis parameter is set to 0.3.

2.2.2 Sinking of brines

The version of CLIMBER-2 used here contains a parameter-ization of the sinking of brines that has been studied in LGMconditions (Bouttes et al., 2010). Brines are small pocketsof very salty water rejected by sea ice formation as sea iceis mainly formed of fresh water. In the standard version ofCLIMBER-2, the flux of salt rejected to the ocean is mixedin the surface oceanic cell whose volume is quite large due tothe coarse resolution. Yet, as brines are very dense becauseof their high salt content, instead of this dilution they shouldrapidly sink to the deep ocean where the local topographypermits it. During glacial periods, the Antarctic ice sheetprogressively extends and covers the continental shelves. In

combination with the concomitant sea level fall due to in-creasing ice sheets volume, it leads to a reduction of the vol-ume of water above the continental shelf. The brines rejectedfrom the intense sea ice formation are less diluted and are re-leased closer to the shelf break. The dense water from brinescan then more easily sink along the continental slope to thedeep ocean. To avoid the dilution of such an effect, the sink-ing of brines to the deep ocean has been parameterized inCLIMBER-2 (Bouttes et al., 2010). The relative importanceof this brine mechanism is set by the parameter frac, whichis the fraction of salt rejected by sea ice formation that sinksto the bottom of the ocean. The rest of the salt (1− frac)is diluted in the corresponding surface oceanic cell as donein the standard version. When frac = 0 no salt sinks to theabyss as it is entirely mixed in the surface oceanic cell (con-trol simulation), whereas frac = 1 is the maximum effect ofthe brine mechanism when all the rejected salt sinks to thebottom of the ocean. This mechanism was shown to result ina net glacial atmospheric CO2 decrease relative to the prein-dustrial as well as increased1δ13Coceanand increased atmo-sphericδ13Catm (Bouttes et al., 2010, 2011).

2.2.3 Stratification-dependent diffusion

As the sinking of brines tends to modify the stratificationstate of the ocean (the deep water becomes denser), it shouldmodify the vertical diffusion. The more stratified the oceanbecomes, the more energy it requires to mix water masses,implying a lower diffusion. Yet in the standard version ofCLIMBER-2, the vertical diffusion coefficientKz is set bya fixed profile and cannot evolve. A parameterization ofthe vertical diffusion coefficient was therefore introduced(Bouttes et al., 2010) so that vertical diffusion becomes inter-active and dependent of the stratification state of the ocean.This allows a more physical representation of the diffusion,which can play a significant role for the ocean circulation(Marzeion et al., 2007) and potentially influence the carboncycle (Bouttes et al., 2009). The physical parameterization ofthe vertical diffusion coefficientKz was introduced depend-ing on the vertical density gradient (Marzeion et al., 2007) inthe deep ocean (below 2000 m) as follows:

Kz ∝ N−α (1)

whereα is a parameter andN = (−gρ0

∂ρ∂z

)12 is the local buoy-

ancy frequency, withg the gravity acceleration,ρ0 a refer-ence density, and∂ρ

∂zthe vertical density gradient. The pa-

rameterα controls the sensitivity of the vertical diffusivity tochanges in stratification. A previous study exploring its roleduring the LGM has shown that it could vary between 0.7and 0.9 (Bouttes et al., 2011). We first use the maximumvalue of 0.9 to test the maximum impact of this mechanism.In the last section we use a combination of the three mecha-nisms fromBouttes et al.(2011) whereα = 0.7.

The impact of the evolution of these mechanisms is firststudied in an idealized case with a fixed climate (set to the

www.clim-past.net/8/149/2012/ Clim. Past, 8, 149–170, 2012


LGM) to assess the effect of each of the mechanisms with-out the complication of a changing climate. We then explorethe evolution of the carbon cycle when the climate evolvesfrom the LGM to the Holocene. To disentangle the effects ofthe ocean and vegetation, the simulations are run with eitherinteractive or fixed vegetation (“fixed veg”).

2.3 Initial conditions

The transient simulations start from initial values taken fromequilibrium simulations of the Last Glacial Maximum cli-mate and carbon cycle state (Bouttes et al., 2011). The LGMconditions simultaneously imposed in all equilibrium simu-lations are the 21 kyr BP insolation (Berger, 1978), LGM icesheets (Peltier, 2004), and atmospheric CO2 for the radia-tive code (190 ppm;Monnin et al., 2001; Lourantou et al.,2010). The atmospheric CO2 concentration is prescribed inthe radiative code in order to correctly simulate the climateas previously done (Brovkin et al., 2007). The model is thussemi-coupled with respect to the climate and carbon cycle.CH4 and N2O are not explicitly considered in the model, butthe CO2 level of 190 ppm can be considered as an “equivalentCO2” for a CO2 level of 167 ppm which would also considerthe change of CH4 and N2O (Schneider von Deimling et al.,2006). To account for a glacial sea level fall of∼120 m,salinity and mean nutrient concentrations are increased by3.3 % (Brovkin et al., 2007). To ensure equilibrium for thecarbon cycle, glacial simulations were run for 50 000 years.The transient simulations analysed in this study start from theequilibrium state of these 50 000 year LGM simulations.

At the end of the 50 000 year simulation, the globalmean surface air temperature with the preindustrial bound-ary conditions is 14.1◦C. With the LGM conditions, the cli-mate is 3.7◦C colder. The effect of the dust is not takeninto account in this study. According toSchneider vonDeimling et al. (2006), it would cool the global climateby an additional 1.35± 0.35◦C, yielding an approximately5.05± 0.35◦C colder climate during the LGM compared tothe preindustrial.

With no additional mechanism nor carbonate compensa-tion, the obtained LGM CO2 is around 300 ppm. When car-bonate compensation is taken into account, CO2 is approxi-mately 260 ppm. In the other simulations carbonate compen-sation is always included. With iron fertilization the LGMCO2 is around 230 ppm, it falls to around 215 ppm with thesinking of brines. For the stratification-dependent diffusion,the α parameter is first set to its maximum value inferredfrom a previous study, i.e. 0.9 (Bouttes et al., 2011). The190 ppm level is reached with either the sinking of brinescombined with the stratification-dependent diffusion or thesinking of brines with iron fertilization. The effect of the dif-ferent processes influencing the CO2 level during the LGM,including the solubility effect and the role of the additionalmechanisms, has been previously studied inBouttes et al.(2009, 2010, 2011).

2.4 Evolution of the forcing

During deglaciation, the insolation, sea level, ice sheets, andCO2 evolved. The insolation evolution is calculated fromBerger(1978). In the first part of this study, the CO2 evolu-tion (Monnin et al., 2001; Lourantou et al., 2010) is imposedfor the climate modules of the model as it is used to computethe changing radiative forcing, but it is not used for the car-bon cycle part of the model. The CO2 data are on the EDC3age scale (Parrenin et al., 2007). Prescribing the CO2 level al-lows us to obtain a coherent climate even when the CO2 cal-culated by the carbon cycle is different from the one recordedin ice cores. Because we focus on the evolution of CO2 only,the effect of CH4 and N2O is not considered. In the secondpart, the model is used in an interactive mode, i.e. the CO2calculated by the carbon cycle module is now used to com-pute the radiative scheme, no CO2 value is prescribed.

The sea level change is taken into account by changingthe global mean salinity and nutrient concentrations basedon sea level data (Waelbroeck et al., 2002). This is a globaleffect that does not take into account the addition of fresh wa-ter fluxes in restricted areas. Indeed, although abrupt eventstook place during the last termination (Keigwin et al., 1991),rapid climate changes that can be triggered by the additionof fresh water fluxes (Ganopolski and Rahmstorf, 2001) arebeyond the scope of this study, which focuses on the generaltrends during the transition. The geography is thus not di-rectly changed and the closing-opening of the Bering Straitis not taken into account.

The ice sheet evolution is simply imposed by interpolationbetween LGM and Late Holocene states based on the sealevel data. First, a sea level coefficient is computed:

slcoeff =sl − slctrl

sllgm − slctrland 0< slcoeff < 1 (2)

with sl the sea level of the considered time step, slctrl themodern sea level and sllgm the LGM sea level. Then, fromslcoeff we compute the area of the Northern Hemisphere icesheets in a given latitudinal sector as:

arealgm × sl23coeff (3)

with arealgm the LGM ice sheets area (Peltier, 2004). Thenorthern limit of the ice sheets is given by the CLIMBER-2continental limit. The southern limit is computed from thisarea. The height of the ice sheets is calculated as:

oroctrl +(orolgm − orocrtl

)× sl

13coeff (4)

with oroctrl the modern orography and orolgm the LGM orog-raphy (Peltier, 2004). This very simple ice sheet evolutionformulation was initially developed for longer term simula-tions for which no information about ice sheet extent andheight was precisely known. It provides an ice sheets evolu-tion consistent with the sea level evolution. Such a parame-terization should allow the study of a full glacial-interglacialcycle in the future.



0 2000 4000 6000 8000 10000years

0.0

0.2

0.4

0.6

0.8

1.0

iron

iron

no ironor declining iron

no iron

Iron fertilizationa

0 2000 4000 6000 8000 10000years

0.0

0.2

0.4

0.6

0.8

1.0

frac

brines

no brinesor declining brines

no brines

Brinesb

linear decline of iron / brines ("linear")

brutal halt of iron / brines ("abrupt")

Fig. 1. Evolution scenarios for iron fertilization and the sinkingof brines with a constant climate. The two processes are active atthe beginning of the simulations; then they stop. This stop can besudden or follow a linear decline.

In the following we test three oceanic mechanisms (ironfertilization, sinking of brines and stratification-dependentdiffusion). We explore different scenarios for their evolutionin order to simulate the CO2 and atmospheric and oceanicδ13C evolution during the last deglaciation, and compare theresults with proxy data to constrain the possible scenarios.

3 Results and discussion

3.1 Evolution of the mechanisms under a constant LGMclimate: sensitivity studies

We first analyze sensitivity studies to compare the impactof the mechanisms (with different scenarios) on the evolu-tion of the carbon cycle with a constant climate and assessthe role of each mechanism alone. In these idealized sim-ulations the climate is set by glacial boundary conditions.Atmospheric CO2 is prescribed to 190 ppm (Monnin et al.,2001); the northern ice sheets (Peltier, 2004) and the orbitalparameter values (Berger, 1978) correspond to the situationat 21 kyr BP.

0 2000 4000 6000 8000 10000

190

200

210

220

230

240

250

260

CO

2 (

ppm

)

iron

iron no iron or declining iron

a

0 2000 4000 6000 8000 10000

190

200

210

220

230

240

250

260

CO

2 (

ppm

)

brines no brines or declining brines

brines b

0 2000 4000 6000 8000 10000years

190

200

210

220

230

240

250

260

CO

2 (

ppm

)

brines-Kz c



Fig. 2. Evolution of atmospheric CO2 with a constant climate forthree mechanisms:(a) iron fertilization, (b) sinking of brines and(c) sinking of brines and interactive vertical diffusion.

3.1.1 Scenarios for the sinking of brines and ironfertilization

Two idealized scenarios are tested for the evolution of thesinking of brines and iron fertilization (Fig. 1). Both mech-anisms are active at the beginning of the simulations, andthen stopped. This halt can either be instantaneous (scenario“abrupt”) or linear in time (scenario “linear”). The evolutionimposed for the brines and iron mechanism is the same sothat we can compare their responses in time.

3.1.2 Impact of stopping iron fertilization

The halt of iron fertilization leads to an increase of atmo-spheric CO2 as the biological pump is weakened (Fig. 2a).CO2 increases by 29 ppm (Table 1) in both scenarios. Theequilibrium is rapidly reached for the abrupt halt of iron fer-tilization (Scenario “abrupt”). To compare the time neededby the system to reach a near-equilibrium state, we considerthe time when the anomaly of a considered variable (definedas the difference between its value and its initial value) has



0 2000 4000 6000 8000 10000 12000

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

∆δ1

3Cocean(p

erm

il)


iron a

0 2000 4000 6000 8000 10000 12000

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

∆δ1

3Cocean(p

erm

il)

brines b

0 2000 4000 6000 8000 10000 12000years

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

∆δ1

3Cocean(p

erm

il)

brinesno brines or declining brines

brines-Kz

c



Fig. 3. Evolution of oceanic1δ13Coceanwith a constant climate forthree mechanisms:(a) iron fertilization, (b) sinking of brines and(c) sinking of brines and interactive vertical diffusion.

Table 1. Amplitude of change between the beginning and the endof the simulations under a constant glacial climate as observed onFigs. 2, 3 and 4. “Iron” corresponds to iron fertilization, “Brines”to the sinking of brines, and Brines-Kz to the sinking of brines andinteractive diffusion.

CO2 1δ13Cocean δ13Catm(ppm) (‰) (‰)

Iron 29 −0.12 −0.25Brines 40 −0.57 −0.25Brines-Kz 61 −1.1 −0.34

reached 95 % of the anomaly of the equilibrium state (Ta-ble 2). In the “abrupt” scenario, the system has reached 95 %of the equilibrium value∼100 years after the stop of fertil-ization, i.e. very quickly compared to the time scale of thetermination (a few thousand years). In the “linear” scenario,the response of the carbon cycle follows the forcing and ittakes∼4400 years for the system to reach 95 % of the equi-librium value.

0 2000 4000 6000 8000 10000 120006.9

6.8

6.7

6.6

6.5

6.4

δ13Catm

(perm

il)


iron a

0 2000 4000 6000 8000 10000 120006.9

6.8

6.7

6.6

6.5

6.4

δ13Catm

(perm

il)

brines b

0 2000 4000 6000 8000 10000 12000years

6.9

6.8

6.7

6.6

6.5

6.4

δ13Catm

(perm

il)brinesno brines or declining brines

brines-Kz

c



Fig. 4. Evolution of atmosphericδ13Catm with a constant climatefor three mechanisms:(a) iron fertilization, (b) sinking of brinesand(c) sinking of brines and interactive vertical diffusion.

The impact of iron fertilization onδ13Cocean is verysmall (Fig. 3a). We consider the mean vertical gradient(1δ13Cocean) of δ13Coceanin the Atlantic between the upper(−2000 m to 0 m) and deep (−5000 m to−3000 m) ocean.The modification of the gradient is only∼0.1 ‰ (Table 1).On the other hand, the change ofδ13Catm is larger (Fig. 4a)as it is decreased by 0.25 ‰ (Table 1).

3.1.3 Impact of stopping the sinking of brines

Stopping the brine sinking mechanism leads to a larger at-mospheric CO2 increase than stopping the iron fertilization(Fig. 2b) with a change of 40 ppm (Table 1). This effect ofthe brine sinking is not the maximum possible effect (whichwould be obtained for frac = 1), but corresponds to a morerealistic case (frac = 1 is very idealistic as it would require nomixing at all) with frac = 0.6, which is in the middle of therange of probable values according to proxy data (Boutteset al., 2011). The response of the system to the abrupt haltof brine sinking takes more time than in the case of the ironfertilization. In the abrupt scenario, 95 % of the equilibriumvalue is reached 900 years after the stop (Table 2). Indeed,



Table 2. Time for the anomaly of the considered variable (definedas the difference between its value and the initial value) to reach95 % of the equilibrium anomaly value (equilibrium anomaly valuetaken as the difference between the value at year 12 000 of the sim-ulations and the initial value) under a constant glacial climate for(a) CO2, (b) 1δ13Cocean, and (c)δ13Catm. “Iron” corresponds toiron fertilization, “Brines” to the sinking of brines, and Brines-Kz

to the sinking of brines and interactive diffusion. The two scenariosfor iron fertilization and the sinking of brines (“abrupt” and “lin-ear”) are defined in Fig. 1.

(a) CO2

“abrupt” scenario “linear” scenario

Iron 120 years 4360 yearsBrines 900 years 4370 yearsBrines-Kz 4270 years 7440 years

(b) 1δ13Cocean


(c) δ13Catm


the brine sinking mechanism involves changes in the ther-mohaline circulation through enhanced vertical stratification(Bouttes et al., 2010). The thermohaline circulation takesmore time to equilibrate than the biological activity. Haltingthe sinking of brines stops the transport of salt to the deepocean. This transport of salt during the glacial period is re-sponsible for a density increase of the deep waters comparedto upper waters and therefore a greater vertical stratificationrelative to the preindustrial. This leads to a more isolatedglacial deep water mass that can store a larger amount car-bon. When the vertical salt transport is stopped, the stratifica-tion breaks down and the thermohaline circulation changes:both the North Atlantic and Southern ocean overturning cellsbecome more vigorous (Fig. 5). Indeed, with the stratifica-tion induced by the sinking of brines the maximum of theNADW export is around 15 Sv compared to around 20 Svwithout it. When the stratification breaks down, the for-mation of deep water intensifies rapidly to 22 Sv in around1500 years. It then decreases more slowly back to 20 Sv.The atmospheric CO2 follows the evolution of the oceaniccirculation as the carbon stored in the abyss is progressivelyreleased when the overturning circulation increases.

In the “linear” scenario the thermohaline circulation hasmore time to adapt and the evolution is smoother. Themaximum export of NADW increases gradually from 15 Svto around 20 Sv, the latter being reached after around

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4500 years (Fig. 5). Hence, the time to reach 95 % of theequilibrium value is very similar to the time in the experi-ment with iron fertilization (∼4400 years, Table 2).

The amplitude of the1δ13Coceandecrease is more signif-icant with the brine sinking mechanism than with the ironfertilization mechanism (Fig. 3), with a decrease of the ver-tical gradient of∼0.57 ‰. The induced stratification hasa large impact on the verticalδ13Cocean gradient as it re-duces the mixing between the13C enriched upper waterand 13C depleted deep waters. As a result, it better pre-serves the vertical gradient due to biological activity (Boutteset al., 2010). In contrast, the change inδ13Catm is simi-lar to the one induced by suppression of the iron fertiliza-tion. The sinking of brines has an important impact on both1δ13Coceanandδ13Catm because it efficiently increases up-per oceanδ13C and decreases deep oceanδ13C. When thestratification breaks down, it leads to a decrease of upperoceanδ13C andδ13Catm. The iron fertilization mechanismhas a smaller effect on1δ13Coceanpartly because remineral-ization not only takes place in the deep ocean, but also above.Even if the surfaceδ13Coceanis significantly increased withiron fertilization (as well asδ13Catm), the deep (−5000 m to−3000 m)δ13Coceanis relatively less modifed (the reminer-alization also releases12C in intermediate waters) and there-fore1δ13Coceanchanges less than with the sinking of brines.



3.1.4 Impact of stopping the sinking of brines with thestratification-dependent diffusion included

The addition of the stratification-dependent diffusion mainlyamplifies the impact of the brine sinking mechanism. Be-cause of the lower vertical diffusion induced by the enhancedvertical density gradient, the deep water mass is even moreisolated at the beginning of the simulation. It yields a lowerinitial CO2 level (Fig. 2c), higher initial1δ13Cocean(Fig. 3c)(Bouttes et al., 2011), and higher initialδ13Catm (Fig. 4c).When the brine sinking stops, it thus leads to a larger CO2increase reaching 61 ppm (Table 1).

Moreover, the interactive diffusion induces a delay in theoceanic circulation response. After a first rapid increaseof the export of North Atlantic Deep Water similar to theone in the simulation without the interactive diffusion (itreaches 20 Sv after around 500 years), the maximum exportof NADW very slowly increases of around 1 Sv in around3500 years (Fig. 5). As the stratification breaks down, the dif-fusion coefficent which is interactively computed increasesas well. Because the mixing increases, it tends to diminishthe density gradient and the export of water. As a conse-quence, it leads to the same delay in the carbon evolution.Indeed, with the interactive diffusion, the diffusion coeffi-cient is lower at the beginning of the simulation because ofthe enhanced stratification. When the stratification collapses,the diffusion coefficient progressively increases because thevertical density gradient decreases. Yet it remains smallerthan in the simulation without interactive diffusion (until thevertical density gradient is the same), so that the mixing isless important and the change of circulation smaller than inthe fixed diffusion simulation. Because of this delay, the CO2reaches 95 % of the equilibrium value∼4300 years after thesudden halt of brine sinking, i.e.∼3400 years later than withthe brines mechanism alone. Similarly, in the “linear” sce-nario it takes∼7400 years for the system to reach 95 % ofthe equilibrium value, i.e.∼3100 years later compared to thebrines alone.

The halt of the sinking of brines with the stratification-dependent diffusion also leads to a decrease of bothδ13Catmand1δ13Cocean. The amplitude is slightly greater than withbrines alone forδ13Catm (change of 0.34 ‰, Table 1) becauseof the amplification due to the interactive diffusion. The am-plitude is, however, much higher for1δ13Cocean with theinteractive diffusion, which plays an important role in theocean. It isolates even more the deep ocean which stronglydecreases the deep oceanδ13C. The additional delay becauseof the progressive return to modern diffusion values is appar-ent in both cases withδ13C reaching 95 % of the equilibriumvalue approximately 3800–3900 years later than with brinesalone. In the “linear” scenario, the ocean has more time toadapt and this delay is reduced to 2500–2700 years.

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Fig. 6. Evolution scenarios for(a) iron fertilization and(b) the sink-ing of brines during the last deglaciation. The two processes areactive at the beginning of the simulations then stop. The iron fer-tilization decline follows the dust transport as recorded in ice cores(Wolff et al., 2006) on the EDC3 age model (Parrenin et al., 2007).The halt of the sinking of brines follows two scenarios: a suddenhalt (“abrupt”) or a linear decline (“linear”).

3.2 Evolution of the mechanisms during the lastdeglaciation with prescribed CO2

We now consider iron fertilization and the sinking of brinesin the context of the global warming and ice sheet retreat ofthe last deglaciation. As described in the method section,in these simulations the three boundary conditions that arethe atmospheric CO2, ice sheets, and orbital parameters varythrough time. Atmospheric CO2 and ice sheets vary accord-ing to proxy data. The vegetation is either interactively cal-culated by the terrestrial biosphere model (VECODE) andtherefore evolving with time according to the climate andCO2 concentration imposed or fixed to the glacial distribu-tion as calculated in the glacial simulations (“fixed veg”) inorder to separate the impact of the ocean from the one of thevegetation. Iron fertilization and the sinking of brines followdifferent scenarios (Fig. 6). The evolution of iron fertiliza-tion is based on iron flux records (Wolff et al., 2006) on theEDC3 age model (Parrenin et al., 2007). It is indeed mod-ulated by a parameter iron that can evolve between 0 and 1following the iron flux record. The parameter is at its maxi-mum (iron = 1) at the Last Glacial Maximum and close to 0at the beginning of the Holocene (Fig. 6a). The evolution ofthe sinking of brines (which can not be directly constrained)is set by the same two idealised scenarios as in the previouspart.



The halt of the sinking of brines imposed in the modelwould, in reality, be due to the change of topography aroundAntarctica (Fig. 7). Indeed, the sinking of brines would de-pend on the volume of water above the shelves. It wouldthus depend on two variables: the evolution of sea level andthe advance/retreat of the Antarctic ice sheet on the shelves.During interglacials, the volume of water above the continen-tal shelves is important and some mixing of the salt rejectedby sea ice formation happens. The salty dense water can thusnot easily sink to the bottom of the ocean (Fig. 7a). Duringthe glaciation, the Antarctic ice sheet progressively increasesboth in volume and extension (Fig. 7b). Because of the exten-sion of the ice sheet and the sea level fall, the volume of waterabove the continental shelves is reduced and the salt less di-luted. Moreover, the release of salt increases as more sea iceis formed (in particular as the seasonality seems to increase;Gersonde et al., 2005). The salt rejected by sea ice formationcan accumulate more and create very dense water suscepti-ble to flow more easily down to the abyss. This is modelledby an increase of the fraction of salt that sinks to the deepocean, the frac parameter. When the ice sheet reaches itsmaximum extent, i.e. when the continental shelves are cov-ered, a few thousand years after the Last Glacial Maximum(Ritz et al., 2001; Huybrechts, 2002), the sea ice formationis shifted to the open ocean. The absence of shelf where thebrines sink, accumulate, and create very dense water suscep-tible to flow down to the abyss, prevents the deep sinkingof brines (Fig. 7c). In the open ocean, the dilution of thebrines released by sea ice is more important and the effectof the brine-generated dense water disappears. If the conti-nental shelves are all covered simultaneously, it results in anabrupt halt of the sinking of brines. Alternatively, the haltof the sinking of brines can be linked to the sea level rise,which increases the volume of water above the continentalshelf leading to more mixing and less sinking of dense water.It corresponds to a more progressive reduction of the sinkingof brines, which can be first approximated by a linear de-crease. These two extreme scenarios (“linear” and “abrupt”)of the halt of the sinking of brines are both tested. The twoscenarios explore the two extreme cases, a more probableone would lie between the two. According to proxy data, theWest Antarctic ice sheet advanced to the outer shelf in mostregions (Anderson et al., 2002). Because the glaciation anddeglaciation are not symetrical with respect to the sea levelchange and advance and retreat of the Antarctic ice sheet onthe continental shelves, the evolution of the sinking of brineswould also not be symetrical. In particular, according to data,the Antarctic ice sheet melting starts later than the northernones, around 14 kyr BP (Clark et al., 2009; Mackintosh et al.,2011). At that time, the sea level is already higher than at theLGM because the Northern ice sheet started to melt earlier.In association with the input of fresh water from the melt-ing of the Antarctic ice sheet, it would prevent the importantsinking of the brines to happen again. It is thus not possi-ble to exclude that some sinking of the brines occurred again

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Fig. 7. Schematic representation of the sinking of brines during(a) interglacial, (b) glacial and(c) deglacial periods. The maindrivers of the fraction of salt sinking to the deep ocean (frac) arethe Antarctic ice sheet extent on the continental shelf and sea levelwhich govern the volume of water above the continental shelf. Theless water there is, the less brines are mixed and the more they cansink into the deep ocean. When sea ice formation is shifted to theopen ocean, brines are mixed and the sinking stops.

(although not at the very beginning of the deglaciation sinceit was inhibited by the presence of the Antarcic ice sheet onthe shelves), yet it would be relatively less important. How-ever, this possibility is beyond the scope of this study, whichexplores the mean trend during the deglaciation, and wouldrequire further work to focus on the effect of a brief activa-tion of the sinking of brines during the deglaciation, probablyin link with more rapid events.



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Fig. 8. Evolution of atmospheric CO2 during the last deglaciation with different oceanic mechanisms and comparison with data:(a) control(CTRL) runs without and with carbonate compensation (CC), all other simulations are with carbonate compensation,(b) simulations withiron fertilization, (c) simulations with the sinking of brines (two scenarios as defined in Fig. 6),(d) simulations with the sinking of brines(two scenarios as defined in Fig. 6) and iron fertilization,(e) simulations with the sinking of brines (two scenarios as defined in Fig. 6) andinteractive vertical diffusion coefficient (Kz). Each simulation has either an interactive vegetation or a fixed glacial vegetation (“fixed veg”).The data are fromMonnin et al.(2001); Lourantou et al.(2010).



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Fig. 9. Evolution of the carbon stock from the terrestrial bio-sphere (GtC) during the deglaciation for the simulations as definedin Fig. 6, when the terrestrial biosphere is interactive.

3.2.1 Control simulations of the evolution of the carboncycle during the deglaciation

Without carbonate compensation, the initial value of atmo-spheric CO2 at−21 000 years is 298 ppm (Fig. 8a) due to theopposite effects of oceanic and vegetation changes (Brovkinet al., 2007; Bouttes et al., 2010). The effect of changingthe boundary conditions to the LGM ones (orbital parame-ters, ice sheets and atmospheric CO2) is to decrease CO2 by24 ppm, mainly because of the colder climate which resultsin greater solubility of CO2 in the glacial ocean compared tothe preindustrial. The increase of nutrient concentrations dueto the sea level fall of approximately 120 m also reduces CO2relative to the preindustrial since the biological production isenhanced. This effect is relatively small as CO2 is reducedby 3 ppm. Yet, the sea level fall also increases the globaloceanic salinity, which decreases CO2 solubility in the ocean,thus increasing CO2. The simulated CO2 increase due to theglobal salinity increase is of 7 ppm. Finally, the terrestrialbiosphere carbon content is reduced by∼650 GtC comparedto the Holocene (Fig. 9), which releases carbon into the at-mosphere leading to an increase of CO2 of 38 ppm in themodel. This effect does not take into account the increase ofterrestrial biosphere carbon content on shelf areas previouslyflooded, which would be between 182 and 417 GtC (Mon-tenegro et al., 2006; Joos et al., 2004). Although the oceanpartially stores some of the released carbon, part of it remainsin the atmosphere. This effect prevails and the simulated at-mospheric CO2 is 298 ppm at the LGM, a value very differentfrom the data (∼190 ppm). For more details on these differ-ent effects we refer toBrovkin et al.(2007) andBouttes et al.(2010).

From this initial state, in the control glacial simulationwithout carbonate compensation (CTRL), the atmosphericCO2 slightly decreases from 298 ppm 21 000 years ago to280 ppm 10 000 years ago when the terrestrial biosphere evo-lution is taken into account (Fig. 8a) whereas CO2 increases

to 320 ppm when the vegetation is fixed. CO2 increases be-cause of the warming and diminished global oceanic nutrientconcentrations. The decrease of salinity tends to counteractthe increase, but the overall evolution is still a CO2 increasewhen the vegetation is fixed (“fixed veg”). When the evolu-tion of vegetation is accounted for (interactive vegetation), itresults in a CO2 decrease as the terrestrial biosphere carboncontent progressively increases (Fig. 9). This effect prevailsleading to the simulated decrease of atmospheric CO2.

With carbonate compensation (CTRL-CC), the uptake ofcarbon by the ocean is amplified during the LGM, whichresults in a lower glacial CO2 in the initial state, around260 ppm (Fig. 8a). When the vegetation is fixed, the evo-lution of CO2 in the transient simulation is the same as inthe previous simulation with a 20 ppm increase. When thevegetation is interactive, the CO2 remains roughly constantbecause the terrestrial biosphere carbon content increases,which acts to decrease CO2 and counteracts the CO2 increasefrom oceanic processes.

The evolution ofδ13Coceanin the ocean is a good indica-tor of the physical processes involved and an important con-straint. One of the more striking features of the changes fromthe glacial to the interglacial state is the increase in the deepSouthern Oceanδ13Cocean value. Hence, we focus on theevolution of δ13C at one site in the deep Southern Ocean.We compare the simulation results to the record from coreMD07-3076Q (Skinner et al., 2010; Waelbroeck et al., 2011),which has a good resolution and is well dated. The simu-latedδ13Coceanat that site shows an increase of∼0.3 ‰ only(Fig. 10a), a small amplitude compared to the measured totalvariation of∼1.3 ‰.

Atmosphericδ13Catm is sensitive to the evolution of theterrestrial biosphere (Fig. 11a). The difference betweenthe simulatedδ13Catm with fixed vegetation (“fixed veg”)and interactive vegetation gets greater with time and equals∼0.4 ‰ at−10 000 years. With fixed vegetation, the changesin δ13Catm are only due to processes taking place in theocean. Asδ13Coceandoes not change much, it induces a con-stantδ13Catm value. The difference between the simulationswith interactive vegetation and “fixed veg” is only due to theterrestrial biosphere whose carbon content progressively in-creases (Fig. 8). Since the biosphere preferentially takes thelight 12C over13C during photosynthesis, the atmosphere be-comes enriched in13C andδ13Catm increases (Fig. 11a). Yet,this trend disagrees with the data showing a “W ” shape, sug-gesting a more complex evolution of mechanisms.

Even when taking carbonate compensation into account,the computed CO2, atmospheric and deep oceanicδ13C evo-lutions are far from reproducing the evolution depicted by thedata, underlining the need for additional mechanisms to ex-plain the carbon cycle evolution. In the following, we test thethree additional oceanic mechanisms described before duringthe deglaciation and assess their impact on the carbon cycleevolution when the global climate warms.



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Fig. 10. Evolution of deep Southern Oceanδ13C during the last deglaciation with different oceanic mechanisms and comparison withdata: (a) control (CTRL) runs without and with carbonate compensation (CC), all other simulations are with carbonate compensation,(b) simulations with iron fertilization,(c) simulations with the sinking of brines (two scenarios as defined in Fig. 6),(d) simulations withthe sinking of brines (two scenarios as defined in Fig. 6) and iron fertilization,(e) simulations with the sinking of brines (two scenarios asdefined in Fig. 6) and interactive vertical diffusion coefficient (Kz). Each simulation has either an interactive vegetation or a fixed glacialvegetation (“fixed veg”). The data are fromWaelbroeck et al.(2011).



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Fig. 11.Evolution of atmosphericδ13Catmduring the last deglaciation with different oceanic mechanisms and comparison with data:(a) con-trol (CTRL) runs without and with carbonate compensation (CC), all other simulations are with carbonate compensation,(b) simulationswith iron fertilization, (c) simulations with the sinking of brines (two scenarios as defined in Fig. 6),(d) simulations with the sinking ofbrines (two scenarios as defined in Fig. 6) and iron fertilization,(e)simulations with the sinking of brines (two scenarios as defined in Fig. 6)and interactive vertical diffusion coefficient (Kz). Each simulation has either an interactive vegetation or a fixed glacial vegetation (“fixedveg”). The data are fromLourantou et al.(2010).



3.2.2 Impact of iron fertilization

The simulated atmospheric CO2 evolution improves whenincluding the iron fertilization mechanism and rises from∼230 ppm at−21 000 years to∼260 ppm at−10 000 years(Fig. 8b). As the idealized experiment with a fixed climatehas shown, the iron fertilization reacts quickly to the imposedforcing and the response thus follows the iron availability.The amplitude of the CO2 change due to iron fertilization isprobably over-estimated in this simulation as a state-of-the-art GCM including an iron cycle indicates a more probablemodern to LGM CO2 decline of 15–20 ppm due to iron fer-tilization (Bopp et al., 2003; Tagliabue et al., 2009).

The computed LGM deep oceanδ13C evolution also im-proves (Fig. 10b), yet its amplitude is clearly not largeenough (the glacial value is∼0 ‰ compared to∼ −1 ‰ inthe data). Theδ13Catm evolution changes as well (Fig. 11b).The initial glacial value is increased by 0.2 ‰ compared tothe control simulation. Following the evolution of iron flux,iron fertilization decreases during the deglaciation. Simi-larly to the terrestrial biosphere, marine biology preferen-tially uses12C over13C, which decreasesδ13C in the deepocean and increases it in the upper ocean and atmosphere.When iron fertilization becomes lower, the biological pumpdecreases and the deep ocean oceanδ13C increases whileδ13Catm decreases. In the atmosphere, because this effectis of the same amplitude as the effect of the terrestrial bio-sphere, but with an opposite signe, the overall simulated evo-lution of δ13Catm is flat.

3.2.3 Impact of the sinking of brines

Taking into account the halt of the sinking of brines improvesthe computed CO2 evolution (Fig. 8c). Atmospheric CO2 in-creases from∼220 ppm at−21 000 years to∼260 ppm at−10 000 years. The transition is however different for thetwo brine scenarios. When the sinking of brines is suddenlystopped (referred as “abrupt” in the figure captions) the CO2rapidly increases. The degassing due to the break down ofthe stratification and reorganisation of the thermohaline cir-culation (Fig. 12) takes approximately 3000 years to reachthe level of the control evolution. The linear reduction ofthe sinking of brines (“linear”) globally follows the forcing,which results in a smoother increase of atmospheric CO2.Yet, although the CO2 evolution is slightly closer to the datawhen including the sinking of brines than with iron fertiliza-tion, none of them alone can account for the entire CO2 riseduring the deglaciation (Fig. 8), which is mainly due to themismatch of the initial states compared to the data.

The evolution of the deep oceanδ13C is improved com-pared to the control simulations (Fig. 10c) as the initial LGMδ13Coceanvalue is closer to the data (the simulatedδ13Coceanis ∼0 ‰ compared to∼0.3 ‰ in the control simulations and∼ −1 ‰ in the data). It is nonetheless still too high comparedto the data.

The sinking of brines has a more striking impact onδ13Catm (Fig. 11c). The abrupt halt of the sinking of brinesat−18 000 years leads to a decrease ofδ13Catm as the carbonfrom the deep ocean characterized by lowδ13C is released tothe atmosphere. The decrease is larger when the vegetation isfixed because it only accounts for the oceanic change while inthe simulation with interactive vegetation the increase of ter-restrial biosphere carbon content (which increasesδ13Catm)counteracts the oceanic effect. When the halt of the sinkingof brines is more progressive, the change ofδ13Catm due tothe ocean takes place later so that when the vegetation is in-teractive, the change due to the vegetation cancels out the onefrom the ocean and no decrease is simulated.

3.2.4 Impact of the sinking of brines and ironfertilization

With both the sinking of brines and iron fertilization includedin the model, the entire amplitude of the CO2 rise from∼190 ppm at−21 000 years to∼260 ppm at−10 000 years issimulated (Fig. 8d). The “abrupt” scenario leads to an earlyincrease of CO2, which begins in advance compared to thedata (around 1000 years in advance). The “linear” scenariois more similar to the data evolution. The separate effects ofthe sinking of brines and iron fertilization globally reinforceeach other. Indeed, the sinking of brines alters the ocean dy-namics while iron fertilization changes the marine biology.The sinking of brines induces a slight reduction of the sur-face nutrient concentration, hence a diminished effect of ironfertilization, yet the impact on atmospheric CO2 is very small(a few ppm only). Thus, the two mechanisms are almost in-dependent of each other and their effects linearly add to eachother. This combined effect is responsible for the very steepincrease of CO2 in the “abrupt” scenario as both mechanismshave a fast response of their own.

Yet, the evolution ofδ13Cocean is still relatively differentfrom the data (Fig. 10d), with a decrease of∼0.7 ‰ com-pared to∼1.3 ‰ in the data, mostly because of the mismatchbetween the initial value and the data. The sinking of brineshas an important effect onδ13Coceanbut the iron fertilizationhas a very small effect and the addition of the two cannot ac-count for the entire measured evolution during deglaciation.

The combination of the sinking of brines and iron fertil-ization yields better results for theδ13Catm evolution whenthe vegetation is fixed (Fig. 11d, dotted lines). In particu-lar, between−18 000 years and−15 000 years the halt of thesinking of brines in addition to the diminishing iron fertil-ization produces a simulatedδ13Catm decrease closer to thedata. Yet when the vegetation is interactive (solid lines) thiseffect is counteracted by the increase ofδ13Catm due to theexpansion of the vegetation.



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3.2.5 Impact of the sinking of brines andstratification-dependent diffusion

With a combination of the sinking of brines and thestratification-dependent diffusion, the amplitude of the CO2increase is also in line with the data (Fig. 8e). As observedwith a constant climate forcing, the effect of the brine in-duced stratification is amplified, the deep water mass is fur-ther isolated and stores more carbon at the LGM. The in-teractive diffusion also generates a delay in the oceanic re-sponse to the breakdown of the stratification and CO2 is moreprogressively released. Hence the scenario that best agreeswith the CO2 record is now the “abrupt” scenario whereasthe “linear” scenario is delayed and rises too late.

Contrary to the simulation with the sinking of brines andiron fertilization, the computed deep oceanδ13C is signifi-cantly improved (Fig. 10e) and the amplitude of the increasecloser to the data. The interactive diffusion also amplifies theimpact of the brines onδ13Cocean, which is further decreasedin the LGM and then increases to the Holocene value dur-ing the deglaciation. The scenario that best matches the dataevolution is again the “abrupt” scenario, the “linear” scenarioyielding too late a rising.

However, the simulatedδ13Catm does not really improve(Fig. 11e). It appears that the maxima of the “W ” shapecorrespond to the values of the simulations with interactive

vegetation while the minima are close to the values of the“fixed veg” simulations. Overall theδ13Catm record seemsto oscillate between these two states, which could indicate amore complex evolution of the vegetation that a simple lin-ear increase during the transition. The vegetation could beginto increase later that in the simulation, then decrease around−13 000–12 000 years and then increase again (Kohler et al.,2005a). It confirms that the evolution of the terrestrial bio-sphere has an important impact onδ13Catm (Lourantou et al.,2010) and should be studied in more details in the future.

It results that the CO2 evolution can be simulated in agree-ment with data either with the combination of brines and ironfertilisation or brines and interactive diffusion. However, theevolution ofδ13Coceanbetter match the data with the brineand interactive diffusion combination while theδ13Catm isslightly better with the brines and iron combination. In thefollowing we thus take the three mechanisms simultaneouslyinto account. Because the CO2 is simulated in agreementwith data, we also change the version of the model to a fullycarbon-climate coupled version. The simulations are thus notforced by a CO2 record anymore.

3.3 Evolution of the mechanisms during the lastdeglaciation with interactive CO2

Contrary to the previous section, here the climate and car-bon models are fully coupled and atmospheric CO2 is nolonger prescribed but interactively computed. Because of thischange in the version of the model, it is required to simulatenew initial glacial conditions. We first evaluate these newglacial equilibrium runs before exploring the evolution of theinteractive carbon cycle during the deglaciation.

3.3.1 Initial glacial conditions

We first carry out two glacial equilibrium simulations with(“LGM-all”) and without (“LGM-ctrl”) the additional mech-anisms studied. The runs start from previous glacial equilib-rium runs (Bouttes et al., 2011) performed with prescribedCO2 values (190 ppm) for the climate model. The values ofthe parameters for the additional mechanisms included in the“LGM-all” simulation are based on the results from ensem-ble simulations (Bouttes et al., 2011) (frac = 0.6 for the sink-ing of brines, iron = 0.3 for iron fertilization and alpha = 0.7for the stratification dependand diffusion). With these threeadditional mechanisms (“LGM-all”), the climate at the endof the 50 000 year simulation is slightly colder compared tothe standard glacial simulation (0.3◦C colder). The globalair surface temperature during the LGM is 4◦C colder com-pared to the preindustrial. In the “LGM-ctrl” run, CO2 in-creases from∼254 ppm and equilibrates close to preindus-trial level (∼284 ppm) (Fig. 13). The atmospheric CO2 levelis higher than the CO2 prescribed due to the carbon-climatefeedbacks. Indeed, higher CO2 leads to higher temperature,which mainly reduces ocean solubility and further increases



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atmospheric CO2 until it equilibrates. On the contrary, the“LGM-all” run is stable and the simulated CO2 remains atthe glacial level of∼190 ppm. Because of the deep stratifica-tion induced by the sinking of brines, the interactive diffusionand the iron fertilization, the deep ocean contains more car-bon, hence the relatively low simulated CO2. Based on thesemechanisms, because atmospheric CO2 is now interactive,it is possible to study the temporal evolution of CO2 duringthe deglaciation. Indeed, the ends of these equilibrium runsconstitute the initial conditions for the deglacial runs.

3.3.2 Evolution of CO2 and δ13C during the lastdeglaciation with a combination of mechanisms

As done previously, the ice sheet, sea level and insolationevolutions are prescribed. However, atmospheric CO2 is nolonger prescribed. The CO2 concentration used to computethe radiative scheme comes from the CO2 calculated in thecarbon cycle module. The evolution of iron fertilization isagain prescribed following iron flux data and different sce-narios are applied to the brine mechanism (Fig. 14a). Thetwo scenarios explored before (linear decline “linear” and thesudden halt at 18 ky BP “abrupt”) are again considered, andwe also study two additional ones: a sudden halt of the sink-ing of brines at 17 ky BP “abrupt 17 k” and an intermediateone “intermediate”.

In the control transient simulation (“CTRL”), atmosphericCO2 roughly stays around 280 ppm (Fig. 14b). This evolu-tion is due to the terrestrial biosphere, whose carbon contentincrease lowers atmospheric CO2. It counteracts the atmo-spheric CO2 increase due to the rising temperatures causinglower solubility. This evolution widely differs from the data,i.e. a general increase from the glacial level of∼190 ppmuntil the Holocene value of∼260 ppm.

We then consider a combination of the three additionaloceanic mechanisms during the deglaciation. With the

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parameter, grey) based on the dust transport as recorded in ice cores(Wolff et al., 2006) on the EDC3 age model (Parrenin et al., 2007),and sinking of brines (frac parameter, colors),(b) simulated evo-lution of atmospheric CO2 (ppm) for the control run (“CTRL” inbrown, without carbonate compensation: dotted line and with car-bonate compensation: solid line) and with three additional mech-anisms: interactive diffusion, iron fertilization and different brinescenarios as described in(a) compared to data (black),(c) evolutionof deep Southern Oceanδ13C (‰) for the same simulations and(d) of atmosphericδ13C (‰).

combination of iron fertilization, sinking of brines and strat-ification dependent diffusion, the obtained computed transi-tions are mainly driven by the ocean and match the globaldata evolution of CO2 better than the control simulation(Fig. 14b). The scenarios that best match the data are the“abrupt 17 k” and “intermediate” ones that support a rela-tively rapid halt of the sinking of brines when the Antarc-tic ice sheet is at its maximum extent. In these runs, the



simulated deep Southern Oceanδ13C transition is also im-proved, with an increase of∼1 ‰ beginning at 15.5 kyr BP(Fig. 14c). However, if the general trend is captured by themodel, the CO2 plateau during the Bølling-Allerød (from∼14 kyr BP to∼12 kyr BP) is not well represented, underlin-ing the lack of other processes such as abrupt AMOC varia-tions that were not considered in this study.

This global behaviour for CO2 and deep oceanδ13C dur-ing the termination is due to the modification of the oceandynamics and reduced iron fertilization. The halt of the sink-ing of brines results in modifications of the overturning rateduring the transition while iron fertilization induces changesin the biological production. During the glacial period, be-cause of the sinking of brines, both the simulated North At-lantic Deep Water (NADW) and the Antarctic Bottom Wa-ter (AABW) export rates are weaker so that the deep waterenriched in carbon is less mixed with the above water con-taining less carbon. As previously studied (Bouttes et al.,2010, 2011) the deep isolated water then represents an im-portant carbon reservoir. The sinking of brines is responsi-ble for a glacial CO2 change of 39 ppm and the interactivediffusion scheme amplifies it by 16 ppm. During the transi-tion the carbon trapped in the abyss is progressively releasedinto the atmosphere because of the halt of the brines sink andbreak down of the stratification (Fig. 15). In addition, thedecrease in iron fertilization, which accounts for 10 ppm ofthe LGM CO2 change, leads to a reduced biological produc-tion and therefore to a less effective biological pump. Sim-ilarly, the evolution of deep oceanδ13C is governed by theincreasing mixing between surface water with high values ofδ13Coceanand deep water with low values ofδ13Cocean. Be-cause of the change of oceanic circulation the deep valuesincrease and the vertical gradient is diminished. Althoughthe general trend of the oceanδ13C evolution is well sim-ulated with the model, the absolute values are slightly dif-ferent. Because CLIMBER-2 is an intermediate complex-ity model with a low resolution and zonally averaged ocean,it complicates the comparison with the sediment core data.Similar experiments exploring the impacts of the sinking ofbrines with a better resolved 3-D ocean model should lead toa better comparison.

Although the amplitude of the glacial-interglacial Antarc-tic temperature change is underestimated in the model, it ispossible to analyse the relative timing of CO2 and tempera-ture evolution (Fig. 16). The two scenarios that agree bestwith CO2 andδ13C data (“abrupt 17 k” and “intermediate”)result in a lead of temperature relative to CO2 as inferredfrom termination 3 data (Caillon et al., 2003). The halt ofthe sinking of brines not only breaks down the stratification,which increases CO2 and therefore temperature, but also in-duces a decrease in sea ice formation (which is computed bya thermodynamic sea ice model) as the surface waters be-come saltier and warmer. Such an early deglacial retreat ofsea ice is also indicated in the data (Shemesh et al., 2002).Because of the reduced albedo, temperature then increases,

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resulting in a positive feedback. Antarctic temperature thusreacts quicker than CO2 at the beginning of the termination,despite the same unique triggering, i.e. the halt of stratifica-tion due to brines sinking.

Recently, two papers studied the evolution of the carboncycle in the context of glacial-interglacial cycles.Tschumiet al. (2011) run transient simulations testing the sensitivityof various mechanisms in a constant climate. The simula-tions support the hypothesis that a change in the ventilationof the deep ocean played an important role in the variationof CO2 during glacial interglacial cycles. In this study, thechange of deep ocean ventilation was obtained by changingthe windstress whereas in our study the change of deep oceanstratification results from changing the sinking of brines. Ourstudy also supports the important role of the change of deepocean stratification. Furthermore, it demonstrates that it al-lows us to simulate the evolution of CO2 during the lastdeglaciation in agreement with CO2 andδ13C data withoutprescribing CO2. In particular, the interactive carbon-climatesimulation manages to capture not only the right CO2 am-plitude change, but also the right timing. With other mech-anisms,Brovkin et al. (2011) run a full glacial-interglacialevolution of CO2 and northern ice sheets. In this simula-tion the role of the carbonate compensation due to changesin the weathering rate is important. However, although mostof the CO2 evolution is successfully simulated, the timing ofthe CO2 rise during the deglaciation lags the data indicatingthat a mechanism leading to an earlier CO2 change is miss-ing. With the change of deep stratification from the change



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of sinking of brines, it allows us to get this timing right, al-though it relies on scenarios that need to be comfirmed.

4 Conclusions

To summarize, we use the intermediate complexity modelCLIMBER-2 to explore the impact of three oceanic mech-anisms on the evolution of the carbon cycle during thelast deglaciation: iron fertilization, sinking of brines andstratification-dependent diffusion. The carbonate compen-sation mechanism is included in the CLIMBER-2 model,which has already been used to study the LGM carbon cy-cle (Brovkin et al., 2002b, 2007; Bouttes et al., 2009, 2010,2011).

A first set of simulations in a context of a constant LGMclimate has allowed an evaluation of the effect of each mech-anism separately. The iron fertilization of marine biology in-duces the fastest response of the carbon cycle (∼100 years)with a rapid increase in atmospheric CO2 of ∼29 ppm. TheCO2 rise due to the sinking of brines (∼40 ppm) takes longer(almost 1000 years) as it involves the oceanic circulation

which takes more time to equilibrate than the marine biol-ogy. The combination of interactive diffusion with the sink-ing of brines induces an important delay as the vertical dif-fusion has to adjust to the evolving circulation. The carboncycle then takes∼4000 years to equilibrate. The impact ofiron fertilization onδ13Cocean is small (−0.12 ‰). It is im-portant forδ13Catm (−0.25 ‰). The effect of the sinking ofbrines is important on both deep oceanδ13C (−0.57 ‰) andδ13Catm (−0.25 ‰). Adding the stratification-dependent dif-fusion amplifies the effect of the sinking of brines on CO2(61 ppm), deep oceanδ13C (−1.1 ‰) andδ13Catm (−0.34 ‰)due to the decrease in mixing between the deep and upperwaters, which makes the deep water enriched in carbon anddepleted inδ13C even more isolated with more carbon andlower δ13C.

With the varying climate of the last termination, the im-pact of the evolution of these mechanisms is modulated byother changes such as the warming and increase in the ter-restrial biosphere carbon content. In this context, either theassociation of the sinking of brines with iron fertilization orwith interactive diffusion results in a computed atmosphericCO2 increase in agreement with the data. However, only the



combination of brines with interactive diffusion also recon-ciles the simulatedδ13Cocean with the recordedδ13C evo-lution in the deep Southern Ocean. In the latter case, thescenario that best matches the data is the “abrupt” scenario,i.e. a sudden halt of the sinking of brines when the Antarcticice sheet is at its maximum extent. In such a configuration,sea ice formation is shifted to the open ocean instead of theshelf. The dense water from brine rejection is then mixedwith fresher water preventing it from sinking down to theabyss.

Based on the study of these mechanisms during thedeglaciation and previous studies of the possible combina-tions of the mechanisms in glacial conditions (Bouttes et al.,2011), it is possible to use the model in an fully interactivecarbon-climate version. The simulated evolution of CO2 is ingood agreement with the data underlining the powerful im-pact of the combination of the sinking of brines, stratificationdependent diffusion and iron fertilization.

Although the computed CO2 and deep oceanδ13C arein broad agreement with proxy data, the computedδ13Catmpresents important discrepancies with respect to the databoth in magnitude and structure. The persisting mismatchbetween model results and data forδ13Catm points to therole of vegetation, which could modulate theδ13Catm sig-nal inducing low values when the vegetation is reduced andhigh values when the vegetation is increased. The change inthe terrestrial biosphere seems to play a less important rolefor CO2 and deep oceanδ13C, which are mostly driven byoceanic mechanisms. This source discrimination between at-mospheric mixing and isotopic CO2 ratios has been recentlyexplored (Lourantou et al., 2010). δ13Catm data can thus helpto constrain the vegetation evolution which is poorly known.

Theδ13Catm mismatch can also point to the potential roleof abrupt events, which were not considered in this study.Additionally, the lack of abrupt events is underlined by theabsence of the CO2 plateau during the Bolling-Allerod, asthis plateau could also be linked to abrupt events associatedto fresh water fluxes (Stocker and Wright, 1991). Indeed,fresh water fluxes, which can alter the thermohaline circu-lation, have an impact on the carbon cycle (Schmittner andGalbraith, 2008; Kohler et al., 2005b; Menviel et al., 2008b).Taking them into account could possibly improve both theCO2 plateau and theδ13Catm evolution.

Acknowledgements.We thank Victor Brovkin, Andrey Ganopol-ski, Guy Munhoven and Emilie Capron for useful comments anddiscussion. We also thank the editor and two anonymous reviewersfor their comments which helped improve this manuscript.

Edited by: M. Siddall

The publication of this article is financed by CNRS-INSU.

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