Decadal acidification in the water masses of theAtlantic OceanAida F. Ríosa,1, Laure Resplandyb, Maribel I. García-Ibáñeza, Noelia M. Fajara, Anton Veloa, Xose A. Padina,Rik Wanninkhofc, Reiner Steinfeldtd, Gabriel Rosóne, and Fiz F. Péreza

aMarine Research Institute, Spanish National Research Council (IIM-CSIC), E-36208 Vigo, Spain; bScripps Institution of Oceanography, University ofCalifornia, San Diego, La Jolla, CA 92037; cAtlantic Oceanographic and Meteorological Laboratory, National Oceanographic and AtmosphericAdministration, Miami, FL 33149; dOceanography Department, Institute of Environmental Physics, University of Bremen, 28359 Bremen, Germany; andeFaculty of Marine Sciences, University of Vigo, Campus Lagoas-Marcosende, E-36200 Vigo, Spain

Edited by François M. M. Morel, Princeton University, Princeton, NJ, and approved July 1, 2015 (received for review March 16, 2015)

Global ocean acidification is caused primarily by the ocean’s uptakeof CO2 as a consequence of increasing atmospheric CO2 levels. Wepresent observations of the oceanic decrease in pH at the basin scale(50°S–36°N) for the Atlantic Ocean over two decades (1993–2013).Changes in pH associated with the uptake of anthropogenic CO2(ΔpHCant) and with variations caused by biological activity andocean circulation (ΔpHNat) are evaluated for different water masses.Output from an Institut Pierre Simon Laplace climate model is usedto place the results into a longer-term perspective and to elucidatethe mechanisms responsible for pH change. The largest decreases inpH (ΔpH) were observed in central, mode, and intermediate waters,with a maximum ΔpH value in South Atlantic Central Waters of−0.042 ± 0.003. The ΔpH trended toward zero in deep and bottomwaters. Observations and model results show that pH changes gen-erally are dominated by the anthropogenic component, which ac-counts for rates between −0.0015 and −0.0020/y in the centralwaters. The anthropogenic and natural components are of the sameorder of magnitude and reinforce one another in mode and interme-diate waters over the time period. Large negative ΔpHNat valuesobserved in mode and intermediate waters are driven primarily bychanges in CO2 content and are consistent with (i) a poleward shiftof the formation region during the positive phase of the SouthernAnnular Mode in the South Atlantic and (ii) an increase in the rate ofthe water mass formation in the North Atlantic.

ocean acidification | pH | anthropogenic carbon | water masses |climate model

The uptake of anthropogenic CO2 (Cant) by the ocean haslowered seawater pH since preindustrial times. This large-scale and long-term change is referred to as “ocean acidification,”a process that has led to changes in seawater carbonate chemistry(1–3) with impacts on the chemical speciation of seawater andbiogeochemical cycles. A predominant effect is the decrease ofcarbonate ions in seawater that impacts calcareous marine or-ganisms (4–6). The uptake of Cant is the main cause for thegradual reduction of seawater pH, but biological, physical, andchemical “natural” changes in the ocean, such as changes in theoxidation of organic matter, impact pH as well (7, 8).Several studies have focused on ocean acidification in the last

decade. Model-based studies have examined pH changes on aglobal scale (2, 9), and observation-based studies have focusedon time-series stations (10–13) and specific regions such as theNorth Pacific (7, 14) and North Atlantic (8). However, invest-igations of basin-wide pH changes throughout the water columnfrom direct measurements are sparse (15), in large part becauseof a dearth of quality referenced pH measurements.In this study, we present the first (to our knowledge) measure-

ment-based changes in pH along meridional lines in the Atlanticfrom 50°S–36°N using observations from three cruises: OACES/CO2 (1993), CITHER-II (1994), and FICARAM-XV (2013) (Fig.1A and SI Appendix, Table S1). We investigate the total change inpH and refer to it as acidification. The change in pH is separated

into anthropogenic (ΔpHCant) and natural (ΔpHNat) compo-nents and is evaluated for the water masses along the section overtwo decades (1993–2013). Both components are related to Cantuptake and to processes such as the remineralization of organicmatter and changes in water mass. The observed pH changes arecompared with outputs from an Institut Pierre Simon Laplace(IPSL) climate model to place the observations into context and toelucidate the mechanisms controlling anthropogenic and naturalpH changes, which are clearly discerned in climate models.

ResultsMore than 4,000 pH measurements referenced to the seawaterscale (SWS) at 25 °C in the Atlantic Ocean (50°S–36°N) wereexamined to estimate the changes in oceanic pH between 1993and 2013. We used pH measurements referenced to the SWS at25 °C throughout this discussion, because the thermodynamictemperature effect over pH did not affect the interpretation ofthe results. Changes in pH were evaluated for the major watermasses identified along the section based on their hydrographicproperties (16). We differentiated five water masses in the NorthAtlantic following Talley et al. (17) and six water masses in theSouth Atlantic following Mémery et al. (18). Potential density(σθ, σ3, σ4) intervals were used as a reference (Fig. 1 and SIAppendix, Table S2). Furthermore, we divided the study areainto three regions: southern (50°S–14°S), equatorial (14°S–18°N), and northern (18°N–36°N) (Fig. 1).The overall patterns in pH distribution along this section

in the Atlantic were similar in 1993–94 and 2013 (Fig. 2A and

Significance

We provide the first (to our knowledge) observation-basedacidification trends in the water masses of the Atlantic basinover the past two decades and compare them with climatemodel results. Observations and model output confirm that pHchanges in surface layers are dominated by the anthropogeniccomponent. In mode and intermediate waters, the anthropo-genic and natural components are of the same order of mag-nitude and sign. Large changes in the natural component ofnewly formed mode and intermediate waters are associatedwith latitudinal shifts of these water masses caused by theSouthern Annular Mode in the South Atlantic and by changesin the rates of water mass formation in the North Atlantic.

Author contributions: A.F.R., L.R., and F.F.P. designed research; A.F.R., L.R., M.I.G.-I., R.W.,R.S., G.R., and F.F.P. performed research; A.F.R., L.R., M.I.G.-I., N.M.F., A.V., X.A.P., R.W.,R.S., G.R., and F.F.P. analyzed data; and A.F.R., L.R., and M.I.G.-I. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

Freely available online through the PNAS open access option.1To whom correspondence should be addressed. Email: aida@iim.csic.es.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1504613112/-/DCSupplemental.

9950–9955 | PNAS | August 11, 2015 | vol. 112 | no. 32 www.pnas.org/cgi/doi/10.1073/pnas.1504613112

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SI Appendix, Fig. S1). The highest pH values were found in SouthAtlantic Central Water (SACW) and upper North Atlantic Cen-tral Water (uNACW), with values up to 8.05 in the south and 7.9in the north. The upper water values in the equatorial region werebelow 7.6. Along the southern region, the mixing of AntarcticIntermediate Water (AAIW), Subantarctic ModeWater (SAMW),and upper Circumpolar Deep Water (uCDW) in frontal zonesled to intermediate pH values of ∼7.7–7.6. The lowest pH values(

ΔpHNat includes changes in pH related to changes in oceancirculation and/or biological activity, which are driven by naturalvariability and climate change. The pH changes associated with cli-mate change were estimated to be less than 0.0001/y, i.e.,

DiscussionThe observed changes in pH in near-surface/upper waters were ingeneral agreement with changes expected because of anthropogenicCO2. However, there was an appreciable signal resulting from naturalvariability that was particularly pronounced in the intermediate wa-ters and near-frontal systems. Surface layers showed acidificationrates up to −0.0021 ± 0.0012/y in the South Atlantic, and highacidification rates also were observed in the water masses along theventilation pathways, namely, mode waters with rates up to −0.0018±0.0012/y in the South Atlantic and −0.0017 ± 0.0015/y in the NorthAtlantic. Intermediate waters showed changes up to −0.0014 ±0.0007/y, whereas deep waters in the South Atlantic showed smallerchanges of approximately −0.0004 ± 0.0003/y. Although, on aver-age, acidification rates were higher in near-surface waters, thehighest local values were observed in subsurface mode waters be-tween the depths of 200 and 500 m. Higher acidification rates(i.e., more negative pH) in subsurface waters were in agreementwith the high acidification rates observed in the subsurface watersat the ALOHA (A Long-term Oligotrophic Habitat Assessment)and BATS (Bermuda Atlantic Time-Series) time-series stations(12, 14) in the South Atlantic (30) and along a North Pacific sec-tion (7), respectively.For the first time, to our knowledge, our observations confirm

the major role of mode and intermediate waters (MW–IW) atthe basin scale in the acidification of the ocean interior, whichalso was evidenced in the climate models (9). The high rates ofacidification are attributed to the lower buffering capacity ofmode waters compared with surface waters, because mode wa-ters have a lower temperature and AT/CT ratio and therefore aremore sensitive to increasing oceanic CT (9, 10). In addition,mode waters have a larger exposure to the atmosphere, with asurface area-to-volume ratio five to 10 times larger than that ofdeeper waters, thus enabling a larger uptake of atmospheric CO2and, hence, stronger acidification (9).The observed changes in pH in surface waters were largely of

anthropogenic origin (Fig. 4A). The rates associated with anthro-pogenic forcing, ranging from −0.0015 to −0.0020/y, were foundthroughout the Atlantic surface waters from 50°S–36°N and aresimilar to rates previously reported in the South Atlantic (30) andby the European Station for Time Series in the Ocean in the NorthAtlantic (11). Modeling studies have confirmed the dominant roleof atmospheric anthropogenic forcing on pH changes in the surfacelayers (2, 31). We found larger values of ΔpHCant, associated withlarger ΔCant, in the South Atlantic than in the North Atlantic. Thelarger ΔCant in the south compared with the north is attributedpartly to the southern transects of the cruises having been located

in the western Atlantic, whereas the northern transects were lo-cated in the eastern Atlantic. Mode and deep water formation areconcentrated in the western Atlantic in both hemispheres. Watermasses in the northeastern region of the section are expected to beolder than in the southwestern region and to have lower ΔCantvalues. However, another process probably explains why ΔCantand ΔpHCant were weaker in the North Atlantic. In the subpolarregion of the North Atlantic, a weakening in the formation ofLabrador Sea Water led to a decrease in the relative Cant in-ventory of North Atlantic Deep Water (NADW) from 1997 to2003 (32) and to a smaller change in ΔpHCant. In contrast, alarger increase in the Cant inventory was found in the SouthAtlantic compared with the North Atlantic from 1989 to 2005 (33),possibly related to the Southern Annular Mode (SAM) affectingthe uptake of Cant in the South Atlantic and to the North AtlanticOscillation shift impacting ΔpHCant in the North Atlantic (34).Our observations show that the anthropogenic and natural

components had a similar magnitude in the MW–IW (Fig. 4A),indicating that changes in ocean circulation and biological ac-tivity contributed significantly to pH variability in the subsurfacewaters of the Atlantic Ocean over this time period. The obser-vations were placed in the context of changes occurring in alarger space and time domain by comparing them with pHchanges from the IPSL Earth System Model. This model ob-jectively assessed the separation of ΔpH into ΔpHCant andΔpHNat. The distribution of ΔpHCant in IPSL, referred to as“ΔpHCant-IPSL,” followed the distribution obtained from theobservations, with the largest changes in surface, mode, and in-termediate waters associated with water mass ventilation andanthropogenic CO2 uptake (Fig. 4C). The good correspondencebetween the model and the observations is reflected by a cor-relation between ΔpHCant-IPSL and ΔpHCant of 0.92 ± 0.11and an intercept of −0.0009 ± 0.0019 (r2 = 0.83, P < 0.01).The IPSL simulations spanned the period from 1850 to 2014

and included the entire Atlantic Ocean, allowing the in-terannual-to-decadal variability of ΔpHNat determined duringthe 1993–94 and 2013 cruises to be placed in a larger context.Because climate models statistically represent the natural vari-ability of the ocean–atmosphere system but not necessarily itsexact timing (28), the variability patterns of ΔpHNat-IPSL aredescribed in terms of the SD of the values along the cruisetransect and are compared with the amplitude of the observedΔpHNat [abs(ΔpHNat)] (Fig. 3 C and F). The comparison be-tween the model and the observations therefore was not exact,because one is an SD over 164 y and the other is the differencebetween two sections over 20 y. The observed changes and

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modeled ΔpHNat variability presented similar patterns, withlarge changes in the surface layers and in the MW–IW of thesouthern and northern regions (Fig. 3 B and E). The ΔpHNat inthe equatorial region was smaller in the model than in the ob-servations. However, the observed ΔpHNat was uncertain insurface, mode, and intermediate waters in the equatorial region,because these water masses are compressed into a thin layer ofabout 120 m with few measurements.The model output was used to elucidate the controls of the large

ΔpHNat in the MW–IW of the northern and southern regions.The observations showed a strong relationship between ΔpHNatand ΔNO3 (Fig. 3 B and E) and between ΔpHNat and the ap-parent oxygen utilization (AOU) (SI Appendix, Fig. S3), whichsuggests that pHNat changes were mostly the result of changes inCT from biological remineralization. The strong relationship be-tween ΔpHNat and ΔNO3 also was found in the MW–IW of theIPSL model, with 0.013 units of pH change per micromole of NO3(r2 = 0.93). The model showed that 80% of the ΔpHNat could beexplained by changes in CT, whereas AT accounted for 15–20% ofthe changes, and salinity accounted for less than 10% of thechanges (Fig. 5A). For the pHNat variations attributed to CTchanges, 50–65% corresponded to the physical transport of CT byocean circulation, and 15–30% corresponded to in situ biologicalremineralization of organic matter within the water mass (Fig. 5A).The strong correlation between ΔpHNat and ΔNO3 supports thenotion that the increase in CT controlled the observed pHNatchanges but that transport of respired carbon was the main con-tributor, rather than local biological remineralization.The largest observed and modeled pHNat changes in the

MW–IW occurred where the water masses were formed and sub-jected to variability in surface forcing south of 40°S (Fig. 3C and F).In the South Atlantic, the modeled ΔpHNat in newly formed waterdepended on the latitude where the formation occurred (Fig. 5B).Formation at higher latitudes led to the subduction of higher-CT/lower-AT waters, thereby decreasing ΔpHNat, with the oppositeholding true if formation occurred at lower latitudes. In agree-ment with previous studies (35, 36), the model results suggest thatthe SAM might explain part of the latitudinal shift. The positive

phase of the SAM shifts westerly winds and the MW–IW sub-duction poleward (Fig. 5B). Additionally, the positive phase ofSAM increases the upwelling, northward Ekman transport, andsubduction of CT-enriched CDW into the MW–IW (37), therebymaking ΔpHNat more negative. This mechanism was supportedfurther by the higher AOU found in association with lower pHNatin both the observations (SI Appendix, Fig. S3) and the model (Fig.5B). It explains the large observed decrease in pHNat in theMW–IW south of 40°S between 1993 and 2013 (Fig. 3C), becausein this period the SAM trended positive.In the North Atlantic, at the mode and intermediate outcrop,

ΔpHNat variability in the model depended on the volume ofnewly formed water (Fig. 5C). When larger volumes of MW–IWwere formed, a larger proportion of the deeper CO2- and AOU-rich waters of northern origin were subducted (SI Appendix, Fig.S4), leading to more negative ΔpHNat. There is observationalevidence that the winter-mixed layer depth (38), volume, andAOU content (39) of the MW–IW in the North Atlantic haveincreased over the past decades. This mechanism could explainthe decrease in pHNat observed in the MW–IW in the NorthAtlantic between 1993 and 2013.In summary, the observations and model show that decreases in

the pH of near-surface waters are dominated by the contributionof Cant. In the MW–IW, anthropogenic and natural componentsare of the same order of magnitude and are in the same directionfrom 1993 to 2013, with natural changes reinforcing the anthro-pogenic acidification signal. The observations and model outputconfirm that, although carbonate chemistry and geochemicalproperties of the water masses are crucial for explaining long-termchanges in pH and oxygen levels (3, 9), changes in ocean circu-lation and biological production (13, 14, 40) also exert a largeimpact on pH on interannual-to-decadal time scales in subsurfacewaters. Based on projections of future increases in atmosphericCO2 and the associated penetration of Cant into intermediate anddeep waters, the contribution of anthropogenic forcing to theacidification of subsurface waters will increase with time andeventually will exceed natural variability and trends.

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Fig. 5. ΔpHNat in mode and intermediate waters (MW–IW) over the Atlantic Ocean (80°S–65°N) in the IPSL model. (A) Contribution to ΔpHNat associatedwith changes in salinity (S, cyan), changes in normalized AT (nAT, red), and changes in normalized CT (nCT) caused by physical transport (blue) and biologicalactivity (green). (B and C) ΔpHNat time-series in newly formed MW–IW in the South Atlantic (B) and North Atlantic (C). Anomalies in latitude, volume offormed waters, AOU, SAM index, and North Atlantic Oscillation (NAO) index also are shown with their correlation coefficient to ΔpHNat.

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Materials and MethodsData Processing. To obtain the changes in the variables (pH, Cant, Cant-TTD, θ,and NO3) between 1993–94 and 2013, we used the position and depth of the 100stations of the FICARAM-XV line as a base. Data from the 94 stations of CITHER-IIand the 42 stations of OACES/CO2 that coincided with the FICARAM-XV line wereinterpolated to the station positions and depths of FICARAM-XV using aDelaunay triangulation to obtain an interpolated dataset with the same grid forboth periods. This interpolated dataset allowed us to determine differences inthe variables over the 20-y time period. For Table 1, we determined an averageand SD for all of the values in a particular water mass (“layer”) for each region.More details on the datasets can be found in SI Appendix, Table S1.

Uncertainties. The uncertainty of ΔpH amounted to 0.0035 based on the ana-lytical uncertainty of each pH dataset (0.001, 0.003, and 0.0015 for OACES/CO2,CITHER-II, and FICARAM-XV, respectively). The uncertainty of Cant was based ona propagation of error for each of the variables used in the calculation thatyielded an SD of ΔCant of 2.7 μmol/kg. This calculation translates to an un-certainty of 0.005 in ΔpHCant and ΔpHNat, which is the maximum error forΔpHCant as shown in SI Appendix, SI Text.

The IPSL Climate Model. The low-resolution (LR) IPSL climate model (IPSL-CM5A-LR), which participated in the Coupled Model Intercomparison Project Phase 5 (10)was used. The IPSL simulations covered the period from1850 to 2014. They includedsensitivity experiments separating anthropogenic perturbations from natural vari-ability and climate-induced feedbacks. Four IPSL simulations were investigated: (i)the historical run from 1850 to 2005, with increasing CO2 concentrations andchanges in radiative forcing such as volcanoes and aerosols; (ii) an “intermediate”representative concentration pathway (RCP4.5) for the period 2006–2014, charac-terized by an additional radiative forcing of 4.5 W/m2 and corresponding to a CO2atmospheric concentration of 538 ppm in 2100; (iii) a sensitivity experiment(esmFdbk2) from 1850 to 2014 that included the increased radiative forcing ofscenario RCP4.5 but with no increase in atmospheric CO2 (this scenario represents

climate change and variability without Cant entering the ocean and corre-sponding to ΔpHCant); and (iv) a control simulation (piControl) from 1850 to2014 that included only internal variability in the model with no changes inforcing or atmospheric CO2. This simulation was used to correct for possiblemodel drift. The esmFdbk2 simulation was used to isolate pHNat, that is, thecontribution of natural variability and climate change feedbacks, such aschanges in ocean circulation and biological activity, from the chemical effectsof increasing CO2 concentration. Once the pHNat contribution was removedfrom the historical run, ΔpHCant-IPSL was computed from the differencebetween 2013 and 1993.5 at the 111 profiles of the FICARAM-XV sectionusing the model pixel closest to the station location (Fig. 1B). TheΔpHNat-IPSL was estimated using the interannual anomaly of pHNat overthe 164 y of the simulation, and std(ΔpHNat-IPSL) was based on the 95%confidence interval of ΔpHNat-IPSL (±1.96 × SD, i.e., 3.92 × SD). Althoughthe model results were compared with observations along the cruisetransect (Fig. 1B), the processes regulating ΔpHNat in the MW–IW werecomputed for the entire Atlantic basin (80°S–65°N). The SAM index wascomputed based on sea-level pressure.

ACKNOWLEDGMENTS. We thank the officers and crews of the NationalOceanographic and Atmospheric Administration (NOAA) ship MalcolmBaldrige, Research Vessel (R/V) Maurice Ewing, and R/V Hespérides, along withthe scientific and technical teams, for their support during the OACES/CO2,CITHER-II, and FICARAM-XV cruises; Gail Derr of the Atlantic Oceanographicand Meteorological Laboratory of the NOAA for copyediting the manu-script; and the editor and two anonymous reviewers for their critical readingand constructive comments. This research was supported by the SpanishMinistry of Sciences and Innovation and was cofunded by the European Re-gional Development Fund 2007–2012 (FEDER) through the Carbon Transportand Acidification Rates in the North Atlantic Project (CTM2010-17141/MAR),by the European Union Seventh Framework Programme CARBOCHANGEproject under Grant Agreement 264879, and by the Office of Atmosphericand Oceanic Research of the NOAA.

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Ríos et al. PNAS | August 11, 2015 | vol. 112 | no. 32 | 9955

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http://www.pnas.org/lookup/suppl/doi:10.1073/pnas.1504613112/-/DCSupplemental/pnas.1504613112.sapp.pdfhttp://www.pnas.org/lookup/suppl/doi:10.1073/pnas.1504613112/-/DCSupplemental/pnas.1504613112.sapp.pdf

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Supplementary Information (SI) for “Decadal acidification in the water masses of the Atlantic Ocean”

Authors: Aida F. Rios, Laure Resplandy, Maribel I. García-Ibañez, Noelia M. Fajar, Anton Velo, Xose A. Padin, Rik Wanninkhof, Reiner Steinfeldt, Gabriel Roson, F.F. Pérez

Files in the SI Appendix: Tables S1 to S3 Figures S1 to S4 SI Text References S1 to S26

Supplementary Information: Table S1.

Table S1 provides a compilation of the precision of all the measurements. Salinity and pH measured at 25˚C on the seawater scale (pH25SWS) are dimensionless, CFCs are in pmol·kg-1, and other variables are in µmol·kg-1. Temperature, salinity, pH, CFCs, CT, AT, O2, and nutrients (nitrate, NO3; phosphate, PO4; silicate, SiO4) were measured during the OACES/CO2 (A16) cruise in July-August 1993 (S1, S2), the CITHER-II (A17) cruise in January-March 1994 (S3), and the FICARAM-XV cruise in March-May 2013 (S4) (Fig. 1a, (S5)). Temperature and salinity were obtained using conductivity-temperature-depth (CTD) probes. O2 was measured using potentiometric methods based on the Winkler method. Nutrients were analyzed by colorimetric methods (S6). pH was measured using a potentiometric method on the NBS scale (S7) during the CITHER-II cruise and by spectrophotometric methods on the total scale (S8) during the FICARAM-XV and OACES/CO2 cruises. All pH data and results reported used the SWS scale at 25ºC (pH25SWS). AT was analyzed using potentiometric methods (S9, S10). CT was analyzed using coulometric methods during the OACES/CO2 and CITHER-II cruises (S11) based on the use of certified reference materials (S12). CT was also calculated from pH and AT using thermodynamic equations (S13) refitted by Dickson and Millero (S14), with an error of 1.7, 3.1, and 2.4 μmol·kg-1 for the OACES/CO2, CITHER-II, and FICARAM-XV cruises, respectively. CFCs, which were used in the TTD method, were measured by electron capture gas chromatography methods (S15) during the OACES/CO2 and CITHER-II cruises. Cruise reports describe the methods used during the cruises in further detail (S1, S3, S4). Further details about pH and CT quality controls used during the OACES/CO2, CITHER-II and FICARAM-XV cruises are provided in the SI Text.

Table S1.

Cruise Salinity O2 NO3 PO4 SiO4 pH25SWS AT CT CFC

OACES 0.005 0.31 0.099 0.007 0.056 0.001 2 1.9 0.005

CITHER 0.002 0.78 0.05 0.004 0.09 0.003 1.7 1.7 0.005

FICARAM 0.002 0.50 0.06 0.010 0.04 0.0015 0.92 1.7

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Supplementary Information: Table S2.

The section was divided into layers according to the spreading of the main water masses as shown in Table S2. The section was divided into five layers in the North Atlantic and six layers in the South Atlantic. Potential density intervals (σθ, σ3, σ4) were used to compute the observed potential temperature and salinity for 2013. The density boundaries for the IPSL model (in italics) were computed with the modeled potential temperature and salinity for 2013. Nominal depths of the isopycnal layers are in parentheses. Water mass acronyms are as follows: SACW (South Atlantic Central Water), NACW (North Atlantic Central Water), SAMW (Subantarctic Mode Water), AAIW (Antarctic Intermediate Water), CDW (Circumpolar Deep Water), NADW (North Atlantic Deep Water), and AABW (Antarctic Bottom Water). The lowercase first letter “u” and “l” denotes the “upper” and “lower” varieties of the water masses. Table S2.

South Atlantic North Atlantic

Layers Potential density intervals (kg m-3) Layers Potential density intervals (kg m-3)

SACW 100 m to σθ < 26.5 (200 m) 5 m to σθ < 26.9 (250 m) uNACW 100 m to σθ < 27.0 (250 m) 5 m to σθ < 27.4 (500 m)

SAMW 26.5 < σθ < 27.0 (400 m) 26.9 < σθ < 27.34 (600 m) lNACW 27.0 < σθ < 27.3 (400 m) 27.0 < σθ < 27.3 (400 m)

AAIW 27.0 < σθ < 27.4 (1100 m) 27.34 < σθ < 27.72 (1500 m) AAIW 27.3 < σθ < 27.74 (1100 m) 27.3 < σθ < 27.74 (1100 m)

uCDW- uNADW σθ > 27.4 and σ3 < 41.47 (3000 m) σθ > 27.72 and σ3 < 41.48 (2700 m) uNADW σθ > 27.74 and σ3 < 41.47 (3000 m) σθ > 27.74 and σ3 < 41.47 (3000 m)

lCDW- lNADW σ3 > 41.47 and σ4 < 45.90 (4000 m) σ3 > 41.48 and σ4 < 45.95 (4000 m) lNADW σ3 > 41.47 σ3 > 41.47

AABW σ4 > 45.90 σ4 > 45.95

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Supplementary Information: Table S3. 

To correct for changes in ΔpHNat and ΔNO3 caused by the mixing of preformed quantities from 1993-2013, the changes in potential temperature (Δθ) were used. To apply the correction, correlations of ΔpHNat and ΔNO3 versus Δθ were determined for each of the water masses (layers) and regions. Some layers of adjacent regions where the slopes were similar were merged. In Table S3, the slopes of ΔNO3 (in µmol·kg-1) are denoted by regular text, and the slopes of ΔpHNat are denoted by italicized text. ΔpHNat and ΔNO3 were corrected for the effects of mixing through Δθ by subtracting the product between the slope and Δθ for each grouped layer and region. The difference between ΔpHNat with and without the mixing correction was 0.0007±0.0045, whereas the difference between ΔNO3 with and without the mixing correction was -0.05±0.31 µmol·kg-1 (see Table S2 for the water mass acronyms). Table S3

Water mass Southern Equatorial Northern SACW / uNACW 0.195

-0.0097

SAMW / lNACW -0.673 0.0286

0.649 -0.0446 AAIW -0.226 / -0.0057

uCDW / uNADW 0.712 / -0.0595 lCDW / lNADW

1.039 / -0.0595 AABW

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Supplementary Information: Figure S1.

Fig. S1. Vertical distributions of pH at 25ºC on the seawater scale (SWS) along the 1993-94 section. Ocean Data View is used for mapping with depth on a stretched-top-part scale.

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Supplementary Information: Figure S2.

Fig. S2. ΔpHCant versus ΔCant-TTD (blue circles) and ΔpHCant versus ΔCant-φCTº (red squares). The error bars represent the standard error of the mean. The resulting relationships are: ΔpHCant*1000 = -1.9±0.1·ΔCant-TTD – 1.35±0.95; r2 = 0.96; p-level

6

Supplementary Information: Figure S3.

Fig. S3. Vertical distribution of changes in Apparent Oxygen Utilization (ΔAOU) in µmol·kg-1 from 199394 to 2013. There is a good correlation between ΔpHNat and ΔAOU (r2=0.78).

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Supplementary Information: Figure S4.

Fig. S4. North Atlantic total inorganic carbon (CT, in µmol·kg-1) in the IPSL sensitivity experiment with no anthropogenic increase in CO2 (esmFdbk2) at the depth of the annual maximum mixed layer for each point (i.e., at the depth where the water masses outcrop). Contours indicate the probability for mode and intermediate waters to outcrop (1 where they outcrop every year and 0 where they never outcrop). During the years when large volumes of mode and intermediate waters are formed, a larger proportion of northern high CT waters are subducted, leading to lower pHNat (negative correlation between ΔpHNat and volume formed on Fig. 5c).

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Supplementary Information: Text

ΔpH uncertainties: The precision of the pH measurements was 0.001, 0.003, and 0.0015 for the OACES/CO2, CITHER-II, and FICARAM-XV cruises, respectively. The overall ΔpH uncertainty of 0.0035 was obtained by error propagation. As described below, the final uncertainty in ΔpHCant and ΔpHNat of 0.005 was obtained based on the uncertainty of ΔCant. To check for regional biases in the 1993-94 cruises (OACES/CO2 and CITHER-II), and to test the uncertainties associated with interpolating sample locations using the Delaunay triangulation method, the database was randomly split into two sections, ensuring that the three regions were equally represented. This process was repeated 10 times, and the average results showed no biases (Table S4). The pH uncertainty associated with the interpolation method was of the same order as the uncertainties of the measurements, ranging from -0.004 to +0.004 for the anthropogenic and natural components of pH. Depending on the number of observations (population) in each water mass (layer) and region, the level of detectable change in pH was lower than the uncertainties in the individual measurements based on a Student T test. The ΔpH (p-level >0.05) values that were not statistically significant in Table 1 are shown in italicized text.

Estimation of anthropogenic CO2 with the φCTº and TTD methods: Estimations of anthropogenic CO2 (Cant) concentrations were obtained for the OACES/CO2 (1993), CITHER-II (1994), and FICARAM-XV (2013) cruises by applying the φCT0 method (S16, S17) and the transit time distribution (TTD) method (S18). The φCT0 method is a CO2-based method that follows the principles of the ΔC* approach (S19); it requires measurements of CT, AT, O2, temperature, and nutrients to estimate Cant. The TTD method is a transient tracer-based method that commonly uses CFC-11 and CFC-12 measurements as proxies for the Cant signal instead of CO2 measurements. Since the CFC data from the FICARAM-XV cruise were not available, we computed Cant with the TTD method for 2013 using the CFC data from the OACES/CO2 and CITHER-II cruises, assuming a transient steady state with an annual rate of increase in storage of 1.69% (S20). The uncertainty of the φCT0 approach was 5.2 μmol·kg-1 (S16), while the uncertainty of the TTD approach was 6 μmol·kg-1 for individual Cant estimates (S18). The estimated uncertainty of the CO2-based methods was larger than the standard deviation of Cant values below the deepest Cant penetration depth; the propagated errors may be the maximum estimate of the random variability (S21). We calculated the uncertainty propagation from the standard deviation of ΔCant (2.7 μmol·kg-1, n = 713) below the 2000 m depth, which amounted to an uncertainty of 0.005 in ΔpHCant and ΔpHNat.

The uncertainty in ΔCant can be influenced by methodological and analytical biases. The back-calculation techniques (S17, S19) are based on several “conservative” parameters (preindustrial CO2 disequilibrium, preformed AT, Redfield ratios) that are well-known. The observed uncertainty in ΔCant was less than the analytical uncertainty in the Cant determination because biases generated by the parameterization of AT, CT, and the Redfield ratios were canceled out for a steady state ocean. However, we cannot discount biases in the calculation if this assumption does not hold. The ΔCant uncertainties associated with the

9

interpolation of the samples using the Delaunay method ranged from -1.3 to +1.3 µmol·kg-1 (Table S4) and were lower than the uncertainties in the individual parameters using the Cant estimation. They were also lower than those calculated from the standard deviation of the φCT0-Cant values below the 2000 m depth.

pH and CT quality control: pH was measured by potentiometric methods during the CITHER-II cruise. An internal consistency was thus performed to check for potential biases. Other inorganic carbon parameters were measured: CT, AT, and the sea-surface fugacity of CO2 (fCO2). Corrections for the measured pH for each station based on surface fCO2 can be found in a CDIAC report (S3). An AT correction was also proposed in agreement with those from CARINA and GLODAP (S22). The difference between the measured and calculated pH (on the SWS scale at 25ºC) from CT and AT was -0.0007, with a standard deviation of 0.006 without bias. The scatter in the difference between the observed and calculated pH was due to the combined error of the three inorganic carbon system variables (pH, CT, and AT). Propagating an analytical error of 0.003 for pH (the maximum value during the CITHER-II cruise) and an error of 1.5 µmol·kg-1 for CT and AT yielded a standard deviation of 0.006 in the difference in the measured and calculated pH. Thus, the uncertainties reported in Table S1 are internally consistent and without bias.

A second source of bias is related to the quality of the CO2 data obtained during 1993-94 and 2013) cruises. We used the CARINA/GLODAP data quality protocols (S22, S23) as a double check for possible biases. The quality protocol was applied to samples at depths greater than 3000 m. We compared the CO2 data from the 1993 and 1994 cruises with the 2013 cruise and estimated the offsets using the analysis crossover methodology for each cruise in each hemisphere (S22, S23). We found that both comparisons had small offsets in CT (Fig. S5). The comparison between the 1993 and 2013 cruises (North Atlantic; Fig. S5a), and between the 1994 and 2013 cruises (South Atlantic; Fig. S5b), showed differences of 1.4±2.8 µmol·kg-1 for the northern part of the section (OACES/CO2 and FICARAM-XV) and 2.8±3.1 µmol·kg-1 for the southern part of the section (CITHER-II and FICARAM-XV). The direct comparison provides a bias around the expected uncertainties (2.7 µmol·kg-1).

The crossover analysis performed in the North Atlantic yielded nine offset values (Table S5), with an average weighted offset of -1.3±2.6 µmol·kg-1 for OACES/CO2 and 0.1±2.7 µmol·kg-1 for FICARAM-XV. The standard deviations are close to those estimated below 2000 m. The average weighted offset difference showed an increase of 1.4 μmol·kg−1 from 1993-2013, which is consistent with the previous values given in Wanninkhof et al. (S24) of 2-3 μmol·kg−1 for depths greater than 2000 m for the period 1989-2005 using discrete partial pressure of CO2 (pCO2) measurements. For the South Atlantic, the crossover analysis yielded seven values (Table S6), with an average weighted offset of 1.2±2.1 µmol·kg-1 for CITHER-II and 4.4±2.7 µmol·kg-1 for FICARAM-XV. Again, the standard deviations were close to the expected uncertainty (2.7 µmol·kg-1). The average weighted offset difference showed an increase of 3.2 μmol·kg−1 from 1994-2013, which is consistent with the rate of increase in CT of 0.12±0.05 μmol·kg−1·yr−1 found by van Heuven et al. (S25). The change in Cant at depth was slightly higher due to the deep penetration of the AABW (S26). The standard deviation of

10

these offsets were close to the Cant uncertainty propagation calculated from the standard deviation of ΔCant (2.7 μmol·kg-1), resulting in an uncertainty of 0.005 in pH that could be the maximum error of ΔpHCant and ΔpHNat.

Supplementary Information: Table S4.

Table S4 represents the average of the mean values (ΔpH, ΔpHCant, ΔpHNat, and ΔCant) for each water mass and region obtained for the 10 iterations of the Delaunay interpolation of CITHER and OACES stations to the FICARAM station position. The database was randomly split into two sections. The ΔpH, ΔpHCant, and ΔpHNat values listed below are multiplied by 1000 (see Table S2 for the water mass acronyms).

Table S4.

Region Layer ΔpH *103

ΔpHCant *103

ΔpHNat *103

ΔCant µmol·kg-1

SACW 0 -2 1 0.6 SAMW -1 -1 0 0.1

Southern AAIW 0 -2 1 0.6 50ºS - 14ºS uCDW -2 1 0 0.0

lCDW -4 1 -2 0.2 AABW -3 4 -4 -0.3 SACW -4 -3 -2 -0.5 SAMW -1 -4 3 1.2

Equatorial AAIW 0 -3 1 0.3 14ºS - 18ºN uCDW 0 0 0 -0.2

lCDW 1 1 1 -0.4 AABW 0 4 0 -0.3 uNACW 3 3 1 -1.3

Northern lNACW 3 -1 2 0.1 18ºN - 36ºN AAIW 3 -1 4 0.5

uNADW 1 0 1 0.0 lNADW 0 0 1 0.2

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Supplementary Information: Figure S5

Fig. S5. Crossover results for the comparison between CT (µmol·kg-1) measurements from the OACES/CO2 cruise (red crosses) and the northern half of the FICARAM-XV section (blue dots) (a) and comparison of CT (µmol·kg-1) measurements from the CITHER-II cruise (red crosses) and the southern half of the FICARAM-XV section (blue dots) (b).

a b

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Supplementary Information: Table S5

Table S5. Offsets from the crossover analysis of CT measured during OACES/CO2 (1993) and FICARAM-XV (2013) in the North Atlantic (µmol·kg-1).

Cruise expocodes (section) Year OACES/CO2 FICARAM‐XV TTONAS_1-7 (TTO-NAS) 1981 -1.6±1.5 TTOTAS_1-3 (TTO-TAS) 1982 -1.0±3.2 -8.5±2.1 06MT19960613 (06MT362) 1996 -1.7±2.7 29HE19980730 (29HE050) 1998 -1.4±1.8 33RO19980123 (AR01) 1998 -0.2±1.5 2.6±2.2 33RO20030604 (A16N) 2003 -0.5±3.2 3.1±3.0 74DI19980423 (A16N) 1998 0.7±3.5 29AH20110128 (A05) 2011 -5.8±2.3 -1.8±2.4 29HE20100405 (A06) 2010 1.4±1.7 5.0±1.7 Weighted average -1.3±2.6 0.1±2.7

Supplementary Information: Table S6

Table S6. Offsets from the crossover analysis of CT measured during CITHER-II (1994) and FICARAM-XV (2013) in the South Atlantic (µmol·kg-1).

Cruise expocodes (section) Year CITHER‐II FICARAM‐XV 318MSAVE_1-5 (SAVE) 1987 5.2±5.2 10.3±2.8 06MT22_5 (A10) 1993 0.0±1.8 1.8±2.3 316N142_3 (A15) 1994 0.0±4.0 3.3±2.3 35TH19990712 (Equalant 99) 1999 3.8±2.7 6.3±2.9 49NZ20031106 (BEAGLE; A10) 2003 1.5±2.4 2.4±2.8 740H20090307 2009 0.0±1.0 3.8±5.1 33RO20110926 2011 1.7±2.0 3.8±2.4 weighted average 1.2±2.1 4.4±2.7

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