GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 26, GB2014, doi: /2010gb003980, 2012

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1 GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 26,, doi: /2010gb003980, C constraints on ocean carbon cycle models Rolf E. Sonnerup 1 and Paul D. Quay 2 Received 28 October 2010; revised 1 March 2012; accepted 28 March 2012; published 10 May [1] The sensitivity of oceanic d 13 C fields to overturning and gas exchange is investigated in a suite of ocean general circulation models. The deep and oceanic mean d 13 C in the models was sensitive to the balance between deep waters forming in the North Atlantic and the Southern Ocean. Increasing the Southern Ocean deep water formation rate to improve deep sea 14 C and AOU fields was detrimental to model-data d 13 C fidelity. A concurrent increase in North Atlantic Deep water would be needed to match the observed 14 C and d 13 C, constraining both the rate and schematics of model deep water formation, respectively, and improving sensitivity to future perturbations. Inter-basin trends in d 13 C were sensitive to the rate of overturning in the models, with high mixing model configurations matching the observations best. Models anthropogenic d 13 C changes, used as a diagnostic of model CO 2 uptake, were in agreement with the observations, except at high southern latitudes (<50 S), where the model d 13 C changes were greater than observed. There were predictive relationships among models uptake of anthropogenic CO 2 and depth-integrated d 13 C changes. Model relationships between model anthropogenic CO 2 uptake and the air-sea d 13 C disequilibrium, and the sea surface d 13 C, depend on preindustrial riverine fluxes of terrestrial organic carbon, and on the wind field used to drive the model circulation, respectively. Among the models tested, the relations among anthropogenic CO 2 uptake and d 13 C changes in the ocean are biased by the OCMIP practice of driving model momentum with one wind field, and gas exchange rates with another. Citation: Sonnerup, R. E., and P. D. Quay (2012), 13 C constraints on ocean carbon cycle models, Global Biogeochem. Cycles, 26,, doi: /2010gb Introduction [2] One of the major goals of the Ocean Carbon Model Intercomparison Project (OCMIP) was development of tracer-based strategies for evaluating the accuracy of global ocean carbon cycle models [Najjar et al., 2007]. In particular, the sensitivity of oceanic nutrient, C, O 2, and biological production fields to ocean model circulation has been highlighted [Najjar et al., 2007], which may provide valuable constraints on ocean models physical parameterizations and forcing [Doney et al., 2004; Gnanadesikan et al., 2001, 2004]. Most of the OCMIP models were carbon cycling models embedded in ocean general circulation models (GCMs), whose implementation details differed widely. To facilitate model comparisons, all of the models had their 1 Joint Institute for Study of the Atmosphere and Ocean, University of Washington, Seattle, Washington, USA. 2 School of Oceanography, University of Washington, Seattle, Washington, USA. Corresponding author: R. E. Sonnerup, Joint Institute for Study of the Atmosphere and Ocean, University of Washington, Seattle, WA 98105, USA. (rolf@u.washington.edu) Copyright 2012 by the American Geophysical Union /12/2010GB gas exchange driven by a common wind field, wind speed dependence, and chemical parameterization. Also, the implementations of the biological cycling of ocean carbon were set to one consistent standard [Orr, 2002]. [3] Within OCMIP, model simulations of chlorofluorocarbon (CFC) uptake and 14 C (natural and bomb produced), as compared with observations, were used as tools for assessing accuracy of model uptake of anthropogenic CO 2 [Matsumoto et al., 2004]. Models that did a fairly good job of reproducing these tracer analogs to anthropogenic CO 2 were reasoned to be the most likely to accurately represent anthropogenic CO 2 inventories in the oceans. One reason these two tracers were applied is that the characteristic timescales of the two tracers (30 years for CFCs, a few thousand years for natural 14 C) bracket that of anthropogenic CO 2 (100 years). While the CFCs provide a key indicator of decadal time-scale, i.e., thermocline, ventilation, Matsumoto et al. [2004] highlighted the importance of the Southern Ocean in controlling century-scale uptake of 14 C, noting that this important region is critically sensitive to the models applied surface forcing and physical (mixing) parameterizations. This is important because over longer timescales, anthropogenic CO 2 uptake by the sea will be sensitive to the rate at which deep water formation occurs, and how effectively newly formed deep waters are equilibrated with respect to atmospheric CO 2. 1of16

2 [4] Gnanadesikan et al. [2001] investigated the relationships among overturning and biological production in a family of GCMs, all built on a common architecture, but whose mixing rates were varied, globally and in the Southern Ocean only. In their experiments, nutrient cycling pathways and rates were highly sensitive to, in particular, the level of vertical mixing prescribed in the model. Gnanadesikan et al. [2004] investigated the influence that the intensity of vertical and horizontal mixing assigned exerted on new production, deep ocean apparent oxygen utilization (AOU = O 2 at atmospheric saturation O 2 measured ) and 14 C and implied circulation pathways and rates. Matsumoto et al. [2004] also explored, within this same model geometry and physics, the effects that varying isopycnal and vertical mixing coefficients, and changes in the wind field would have on the model s CFC, natural 14 C, and anthropogenic CO 2 uptake. [5] The models summarized in Gnanadesikan et al. [2001, 2004] were all built on the foundation of the Modular Ocean Model (MOM), on a 4 by 4 grid with 24 vertical levels. These models do not resolve effects of small scale shear dispersion and turbulent meso-scale eddies, but rely on a Gent-McWilliams (GM) scheme [Gent and McWilliams, 1990] to parameterize the along-isopycnal tracer transport resulting from non-resolved processes. While these coarse global ocean models have obvious limitations, some of the coarse grid model setups provide higher fidelity to observed oceanic tracer and anthropogenic CO 2 burdens than do many higher resolution GCMs [Matsumoto et al., 2004]. Among the family of coarse models tested by Gnanadesikan et al. [2001, 2004], two provide fairly accurate simulations (hindcasts) of the ocean CFC, bomb 14 C, and anthropogenic CO 2 inventories [Matsumoto et al., 2004]. If the uptake of CFCs and bomb 14 C provide a meaningful test of models CO 2 uptake, then these models ought to be able to provide fairly accurate forecasts of the future of oceanic uptake of anthropogenic CO 2, provided the large-scale circulation is largely steady over centennial timescales. [6] Here we evaluate the d 13 C of DIC (d 13 C = (( 13 C/ 12 C) sample /( 13 C/ 12 C) std 1) 1000, where the standard is pee-dee belemnite) tracer as a constraint on air-sea exchange and deep and thermocline ventilation pathways in this same suite of models. The long air-sea equilibration time for sea surface d 13 C provides an estimate of the balance of gas exchange and overturning, providing key tests of ocean models longer (millennial) timescale equilibration to and uptake of the anthropogenic CO 2 perturbation. Because of the temperature dependence of air-sea gas exchange fractionation for d 13 C, the meridional gradient in the d 13 C air-sea disequilibrium is substantial relative to the global mean d 13 C disequilibrium, making d 13 C a sensitive tracer to high latitude gas exchange and water mass formation rates. Also, anthropogenic changes of d 13 C in the ocean provide a high signal-to-noise tracer of anthropogenic CO 2, reflecting the entire anthropogenic CO 2 timescale, providing a key test of model ventilation pathways over the 200 year course of the industrial revolution. [7] Our first task is to evaluate the models representations of the oceanic d 13 C fields. In this, we find that the deep d 13 C of the models (and the real ocean) are sensitive to the relative proportions of Northern- versus Southern- origin deep waters. Taking a closer look at the models air-sea equilibration timescales, we evaluate their anthropogenic d 13 C changes. The so-called d 13 C Suess Effect has an advantage over CFCs and 14 C in that the d 13 C perturbation is caused by CO 2 from fossil fuel and land use changes, so its evolution in the atmosphere and oceans tracks anthropogenic CO 2 s. Because the air-sea equilibration timescale for d 13 C is 10 times longer than for CO 2 [Broecker and Peng, 1974], it does not provide a perfect analogy to anthropogenic CO 2, however. The longer equilibration time provides an opportunity to use the air-sea d 13 C disequilibrium to evaluate the balance between overturning and gas exchange at high latitudes, potentially yielding improved constraints on models century and longer timescale forecasts of oceanic anthropogenic CO 2 uptake. [8] We compare models using different wind fields, and evaluate the constraint that d 13 C places on the wind speed dependence of air-sea gas exchange in the models. We evaluate the impacts of differing mixing rates in the ocean interior on the oceanic d 13 C fields and anthropogenic d 13 C changes, by considering anthropogenic d 13 C responses in the full suite of coarse-resolution GCMs tested by Gnanadesikan et al. [2001, 2004]. Using these, we evaluate the global relations among d 13 C perturbations and anthropogenic CO 2 uptake in the MOM model suite to evaluate the models relations among the depth-integrated d 13 C change, sea surface d 13 C change, air-sea disequilibrium, and the oceanic uptake of anthropogenic CO 2. We use these global relations and d 13 C observations to estimate oceanic uptake of anthropogenic CO 2 to 1995, and to identify model configurations most likely to provide accurate CO 2 uptake forecasts. 2. Model Descriptions and Experiments [9] We used the Modular Ocean Model, Version 3 ( MOM-3 )[Pacanowski and Griffies, 1999] with zonal and meridional grid resolution of 4 and 4.5, respectively, and 24 vertical levels. All versions included a Gent-McWilliams [Gent and McWilliams, 1990] mixing scheme, and were driven by steady climatological winds that varied seasonally. Vertical mixing in the upper ocean was prescribed as either 0.15, 0.3, or 0.6 cm 2 s 1, with along-isopycnal mixing set at either 1000 or 2000 m 2 s 1. The OCMIP-2 geochemical model that calculates organic matter production by restoring (t = 30 days) sea-surface PO 4 levels to seasonal climatological data was included. A more complete description of the model versions (LoLo, HiHi, LoHi, HiLo, P2, LoLoHS, and P2A) can be found in Gnanadesikan et al. [2004]. The LoLo, P2 and P2A models response to anthropogenic CO 2 were included in the Orr [2002] and Matsumoto et al. [2004] model intercomparison studies as part of OCMIP. [10] The OCMIP carbon cycling scheme carries five biogeochemicals: phosphate, dissolved oxygen (O 2 ), dissolved inorganic carbon (DIC), alkalinity (ALK), and dissolved organic phosphorous (DOP). At the sea surface dissolved CO 2 was computed at each time step (from DIC and ALK) to determine air-sea CO 2 exchange fluxes. Gas exchange piston velocities were computed using sea-ice cover, sea surface temperature (SST), and satellite (SSMI) winds using a quadratic dependence on wind speeds [Wanninkhof, 1992; Orr, 2002]. Organic matter is generated when model phosphate is restored to monthly mean climatological values [Louanchi and Najjar, 2000] on a 30-day 2of16

3 Figure 1. (top) The atmospheric d 13 C history derived from ice core, firn, and air measurements (dots) [Francey et al., 1999], and used to drive the ocean general circulation model (line), and (bottom) station locations of the d 13 C of DIC measurements used for comparison with the ocean general circulation model results [Quay et al., 2003, 2007]. e-folding timescale. 2 = 3 of the surface phosphate removal is converted to DOP which follows the water, decaying on a 6 month timescale, while the remainder ( 1 = 3) remineralizes directly below at depths >75 m following a canonical power law function mimicking the chemical effects of sinking organic particles [Martin et al., 1987]. DIC and O 2 production and consumption, respectively, follow DOP and phosphate in the ratios C:P = 117:1 and O 2 :P = 170:0 [Anderson and Sarmiento, 1994]. [11] We added 13 C to the OCMIP geochemical cycling scheme (see auxiliary material). 1 The equilibrium fractionation between DIC and atmospheric CO 2 (ɛ DIC-g ) was calculated from ɛ DIC-g = *SST( C) [Zhang et al., 1995]. The kinetic fractionation during CO 2 gas invasion was a linear function of SST matching the 0.81 at 21 C and 0.95 at 5 C determined empirically by Zhang et al. 1 Auxiliary materials are available in the HTML. doi: / 2010GB [1995]. Fractionation during organic matter formation was calculated using the 22 difference observed between compilations of sea surface d 13 C of DIC data [Quay et al., 2003] and particulate organic matter data [Goericke and Fry, 1994], while calcium carbonate formed was 1 enriched relative to DIC [Bonneau et al., 1980]. The model assumed that no 13 C/ 12 C fractionation occurred during remineralization of organic matter and dissolution of calcium carbonate. [12] The general circulation model s 13 CO 2 and 12 CO 2 fields were equilibrated (15,000 model years) with the preindustrial atmosphere, 278 ppm CO 2 and d 13 C= 6.28 for 1737 [Francey et al., 1999]. The model was then forced with the OCMIP atmospheric pco 2 history from a smoothing spline fit through the Siple ice core and Mauna-Loa CO 2 records [Orr, 2002]. The temporal evolution of the d 13 Cof atmospheric CO 2 (Figure 1) was taken from a spline fit through the Law Dome, Antarctica, ice core and firn record augmented by the Cape Grim air archive after of16

4 Table 1. Oceanic Mean d 13 C and Surface d 13 C in 1995 From the Suite of GCMs Tested a Model Vert. Mix (cm 2 s 1 ) Horiz. Mix (m 2 s 1 ) Mean d 13 C ( ) Surface d 13 C ( ) Comments LoLo LoHi HiLo LoLoHS enhanced vmix in southern ocean HiHi P enhanced vmix in southern ocean P2A enhanced vmix in southern ocean, ECMWF winds, adjusted salt fluxes Our variants LoLo-EC LoLo with ECMWF winds P2A-HR P2A with NCEP winds P2A-Krakauer P2A with Krakauer et al. s [2006] wind speed dependence of gas exchange P2-EC P2 with ECMWF winds Observations a The NCEP and ECMWF wind-forcing products are from Kalnay et al. [1996] and Trenberth et al. [1989]. [Francey et al., 1999]. The models neglect riverine transports of organic carbon, which are on the order of 0.6 Gt Cyr 1 [Sarmiento and Sundquist, 1992; Siegenthaler and Sarmiento, 1993], and which would otherwise deplete the pre-industrial oceans d 13 C by on average 0.2 [Tans et al., 1993; Heimann and Maier-Reimer, 1996], so we subtract that offset from the model d 13 C in the comparisons that follow. 3. Data Comparisons [13] For model-data comparisons we used the d 13 C data compilation of Quay et al. [2003] (Figure 1), amended by d 13 C measurements from the Atlantic Ocean in the 1990s and 2000s [Quay et al., 2007]. For the anthropogenic changes in d 13 C (the d 13 C Suess effect, Figure 1), we used comparisons of d 13 C measurements made decades apart in time [Quay et al., 2003; Gruber et al., 1999], in some cases using d 13 C s correlations with concurrent nutrient and hydrographic parameters (via multiple linear regression - MLR) to account for seasonal and spatial aliasing of the data set comparisons [Quay et al., 2007; McNeil et al., 2001; Sonnerup et al., 2000]. We also relied on isopycnal trends of preformed d 13 C dated using CFC ages [Körtzinger et al., 2003; Sonnerup et al., 1999], and time series measurements of d 13 C in the Subtropical North Atlantic [Keeling et al., 2004] and North Pacific [Quay et al., 2003; Keeling et al., 2004] Oceans. In the discussion we also make model comparisons to the GLODAP compilation of deep sea D 14 C data and reconstruction of upper ocean pre-bomb D 14 C values [Key et al., 2004]. 4. Results [14] In the comparisons that follow we highlight results from three MOM configurations, LoLo, HiHi, and P2A. (The LoLo, HiHi and P2A model configurations were LL, HH and PRINCE2A in Gnanadesikan et al. [2004], while LoLo and P2A appeared as #11 - PRINCE, and #19-SW, respectively in Matsumoto et al. [2004].) The nomenclature LoLo indicates that low vertical (0.15 cm 2 s 1 ) and low horizontal (1000 m 2 s 1 ) mixing rates were used, respectively (see Gnanadesikan et al. [2001] for details), while HiHi s corresponding mixing rates were 0.6 cm 2 s 1 and 2000 m 2 s 1. In P2A, LoLo was adjusted in the Southern Ocean to improve model-data fidelity in the deep sea AOU and D 14 C fields, primarily by enhancing Southern Ocean overturning and deep water production. This was done by increasing the vertical mixing rate to 1.0 cm 2 s 1 south of 50 S, using ECMWF reanalysis winds, which are more intense than NCEP in the Southern Ocean, and using adjusted (larger) salt fluxes in the Southern Ocean [Gnanadesikan et al., 2004]. P2A s deep-sea D 14 C and AOU fields are, relative to LoLo, in much better agreement with the observations [Matsumoto et al., 2004; Gnanadesikan et al., 2004]. LoLo, HiHi, and P2A s d 13 C and DIC fields spanned the range of MOM variants we tested, and were selected here because these model configurations and their AOU and D 14 C fields had already been documented, and they produced realistic pycnocline depths and CFC uptake [Gnanadesikan et al., 2004; Matsumoto et al., 2004] The d 13 C of the Deep Sea [15] All of the models we tested overpredicted the deep sea, and oceanic mean, d 13 C significantly (Table 1). The mean deep sea d 13 C is controlled by a balance of remineralization of organic matter, which tends to decrease deep sea d 13 C because d 13 C org 21, and input of sinking surface water, which in turn depends on air-sea exchange and organic carbon export. In the OCMIP carbon cycling scheme, d 13 C org is remineralized in Redfield proportion (with d 13 C org 21 ) yielding a Dd 13 C/DPO 4 slope of 1:1.1 in the deep Pacific Ocean that is in agreement with the observations. The models deep sea phosphate levels are in agreement (typically <0.1 mmol kg 1 ) with the observations. To investigate the cause of the models d 13 C overprediction, we compare the air-sea gas exchange influences on d 13 C in the deep sea, in both data and model fields. [16] To isolate the effects of air-sea exchange, we normalized for biological cycling using the air-sea exchange d 13 C tracer [Broecker and Maier-Reimer, 1992; Lynch- Stieglitz et al., 1995]: d 13 C as ¼ d 13 C 2:9 1:1 *PO 4 Here, 1.1 represents Redfield remineralization of organic matter, d 13 C is that measured, and 2.9 is a constant, in, ð1þ 4of16

5 Figure 2. Meridional plots of (top) deep (>2000 m) d 13 C as observations from the Atlantic (red), Indian (green) and Pacific (blue) oceans, and d 13 C as simulated by the ocean GCMs (middle) P2A and (bottom) LOLO. In the model simulations, each symbol represents a grid cell from along 25 W (red), 88 E (green), and 180 W (blue), and the solid lines are the depth-weighted averages along those sections. The models d 13 C as were defined to yield a mean deep Pacific d 13 C as of zero, which required coefficients (equation (1)) of 3.52 and 3.75 in LOLO and P2A, respectively. selected to yield a mean d 13 C as =0 in the deep North Pacific Ocean, based on observations [Broecker and Maier- Reimer, 1992]. In the models LoLo and P2A, for d 13 C as to equal zero in the deep North Pacific, this constant would need to be higher, i.e., 3.52 and 3.75, respectively, because they overpredict the deep ocean d 13 C. d 13 C as accounts, via phosphate, for the impacts of biological cycling on d 13 C, and thus represents the cumulative contribution that air-sea exchange has made to the sample s d 13 C [Broecker and Maier-Reimer, 1992]. [17] Meridional trends in the deep sea d 13 C as reveal some interesting features (Figure 2). In the Atlantic basin, deep d 13 C as is controlled by mixing between two contrasting endmembers: North Atlantic Deep Water (NADW), whose d 13 C as is < 0.5, and Southern Ocean deep waters (SODW), whose d 13 C as is >0.2. These trends are reflected in the models as well. The meridional trends in deep-sea d 13 C as indicate that the d 13 C as in the deep Atlantic, and thus the mean d 13 C, is controlled by a balance between NADW, whose d 13 C as < 0, and SODW, whose d 13 C as > 0. Thus gas exchange increases Southern Ocean deep waters d 13 C, and decreases NADW source waters d 13 C. The mean d 13 Cof the deep Pacific and Indian Oceans reflects the relative contributions of NADW and SODW and their air-sea exchange signatures. [18] The reason that the North Atlantic and Southern Ocean end-member deep waters have distinctly different airsea exchange signatures can be understood from the meridional trends in the air-sea disequilibrium of d 13 C (Figure 3) in the surface ocean and from the formation histories of these deep waters. The observed d 13 C in the surface ocean is relatively uniform compared to the range in d 13 C in equilibrium 5of16

6 Figure 3. The meridional trend, along 25 W, in sea surface d 13 C (magenta circles) and the d 13 C value of waters in gas-exchange equilibrium with the atmosphere (gray circles) during 1995, and the gas-exchange piston velocity (solid line) used in the model P2A. with the atmosphere due to the slow air-sea equilibration time of the 13 C/ 12 C ratio of the entire DIC pool [Broecker and Peng, 1974]. The temperature dependence of air-sea d 13 C fractionation means that air-sea exchange drives the sea surface d 13 C higher in cold waters (2.7 at 0 C in 1995) at high latitudes, and lower in warm waters (0.4 at 20 C in 1995) at low latitudes [Zhang et al., 1995]. The deep d 13 C as trends (Figure 2) indicate that Southern Ocean deep waters have spent enough time at the sea surface in the Southern Ocean for air-sea gas exchange to enrich d 13 C as. This is also evident in the d 13 C values, which achieve the highest values anywhere in the ocean at 45 S (Figures 4 and 5) due to the complementary enriching effects of gas exchange and biological carbon export there. In contrast, Figure 4. The 1995 annual mean sea surface d 13 C of DIC in the model P2A. 6of16

7 Figure 5. Meridional trends in (top) sea surface d 13 C of DIC from observations normalized to 1995 (dots) [Quay et al., 2003], compared with 1995 zonal mean d 13 C of DIC in the MOM model P2A (lines), and (bottom) the d 13 C as (equation (1)) calculated from those values using the observational coefficient, 2.9. Green symbols are from the Atlantic Ocean, blue symbols are from the Pacific Ocean, and magenta symbols are from the Indian Ocean. NADW exhibits the lowest d 13 C as of the deep sea (Figure 2). This is due to the overturning circulation structure of the North Atlantic Ocean where newly formed deep waters that are exported southwards are replaced, at the sea surface, by northward traveling subtropical waters. The Subpolar North Atlantic surface waters have, as noted before, been in contact with the atmosphere for long enough (>10 yrs) to have fully absorbed the anthropogenic d 13 C perturbation [Körtzinger et al., 2003; Olsen et al., 2006; Quay et al., 2007] and, apparently, also the subtropical air-sea d 13 C equilibration signal (toward lower d 13 C values), before sinking as newly formed NADW (Figure 2). Thus the low d 13 C as of NADW reflects its preceding long surface residence history in the warmer subtropics, which is not reset to lower d 13 C as during those waters shorter surface residence time in the colder subpolar North Atlantic. Because the d 13 C as of NADW is depleted relative to the mean d 13 C as, and relative to the d 13 C as of southern source deep waters, the d 13 C as of the deep sea is set by the relative proportions and air-sea equilibration extents of these two major sources of deep waters. [19] To estimate the relative contributions of NADW and Southern source deep waters, we used the data and models PO 4 and salinity (S) signatures in the deep sea (Z > 2000 m). 7of16

8 We computed preformed phosphate, or PO [Broecker, 1974], using AOU to correct for remineralization of organic matter: PO ¼ ½PO 4 Š AOU P ð2þ O 2 Where P/O 2 is the Redfield ratio in observations (1:175 [Anderson and Sarmiento, 1994]), or in the models (1:170). In the observations, the deep sea PO versus S plot indicates that Indo-Pacific deep waters are comprised of 40% NADW and 60% Weddell Sea Bottom Water (WSBW) [Broecker et al., 1998]. In LoLo these proportions are 33% NADW and 67% SODW. The weaker model contribution of NADW is reflected in the modeled mean ocean d 13 Cat 0.63 being 0.13 higher than observed (Table 1). In P2A, the deep water mass proportions are 18% NADW and 82% SODW, yielding an oceanic mean d 13 C, 0.94, that is overestimated more significantly, by 0.4. [20] We used a budget of deep sea 14 C to estimate the deep water formation rates in the models. In P2A, the mean deep (>2000 m) D 14 Cis 200, in reasonable agreement with the observations ( 175 ) [Gnanadesikan et al., 2004; Matsumoto et al., 2004; Key et al., 2004], with NADW having D 14 C 50, and SODW s D 14 Cis 160. Using the relative proportions estimated from PO and S, the weighted mean D 14 C of new deep waters is 140. A total of 40 Sv deep water formation is required to equal decay to P2A s mean deep sea D 14 Cof 200. Of these 40 Sv, 7 Sv is NADW, which agrees with the 7.5 Sv of waters which flow Southward across 40 N deeper than 2000 m in the model Atlantic, and the remaining 33 Sv is SODW. In LoLo, the D 14 C derived deep water formation rate is only 20 Sv, with the same 7 Sv coming from NADW, and only 13 Sv from SODW, yielding a deep sea D 14 C that is underestimated significantly, 270. [21] These calculations indicate that P2A s enhanced Southern Ocean overturning, while yielding more realistic deep sea D 14 C and AOU [Gnanadesikan et al., 2004], yielded a significant overestimate of the deep sea d 13 C due to P2A s overweighting of SODW compared to the nearequal balance between northern and southern source deep waters in the real ocean (and in LoLo). Apparently, to simultaneously match the deep D 14 C and d 13 C the model would require an enhancement of both deep water formation rates. Relatively smaller enhancements to LoLo s NADW formation rate would be required, relative to the significant changes in SODW implemented in P2A, to match the deep sea D 14 C because NADW s D 14 C( 50 ) is much higher than SODW s ( 160 ). [22] Murnane and Sarmiento [2000], using an earlier and coarser MOM setup with different biological and gas exchange parameterizations, estimated that in preindustrial times there was 120 Gt C yr 1 of carbon isotope anomaly transported in the ocean interior from the Southern to the Northern Hemisphere. This transport would have maintained a north to south gradient in the d 13 C of atmospheric CO 2 in preindustrial time, unless it was balanced by net northern hemisphere uptake of 5 GtCyr 1 CO 2 by the terrestrial biosphere. In all of our MOM variants, however, this transport is an order of magnitude smaller, ranging from 4 to 10 Gt C yr 1 in preindustrial times and 3 to 6 Gt C yr 1 during the 1990s. While our model runs do not support a significant preindustrial interhemispheric gradient in atmospheric d 13 C, or alternatively a major terrestrial CO 2 sink in the preindustrial northern hemisphere, this conclusion should be taken with caution as it apparently depends upon the ocean model used, and must depend on the relative production rates of northern- versus southern-hemisphere origin deep waters The d 13 C of the Sea Surface [23] The d 13 C of the sea surface (Figure 4) reflects local balances of air-sea exchange, net biological production, and circulation, providing an integrated picture of all aspects of the model s C-cycling scheme. Here we compare the ocean models sea surface d 13 C values against the WOCE/OACES database collected during 1989 to 1999 and normalized, based on estimates of the anthropogenic d 13 C change, to the year 1995 [Quay et al., 2003]. Due to ocean uptake of anthropogenic d 13 C, the d 13 C of the surface ocean and model surface DIC was decreasing on average by about decade 1 during the 1990s [Quay et al., 2003]. As a result, a 1990s model-data comparison tests simultaneously the model s steady state d 13 C fields, and simulation of the oceanic d 13 C Suess effect. For example, a model overprediction of the 1990s d 13 C in the upper ocean could be due to overestimation of the pre-industrial d 13 C, and/or underestimation of the anthropogenic d 13 C decrease. [24] The models meridional surface d 13 C and d 13 C as trends, although exaggerated in amplitude, generally follow the trends observed in the Oceans, north of 50 S (Figure 5). In all of the MOM variants we tested, d 13 C values of Southern Ocean surface waters were too high by on the order of 0.5, as discussed above. The magnitude of this southern ocean d 13 C mismatch varied zonally, however. While the d 13 C of surface waters at 66 S was around 1.8 in the models, the observed sea surface d 13 C declines south of 60 S to values as low as 0.8 along some cruise sections (170 E and 90 E, for example), but to only 1.7 along others (105 W, for example). There is a possible seasonal bias in observed d 13 C in the Southern Ocean because most cruises there occur in summer. In the models Southern Ocean, d 13 C values at the sea surface are highest in summertime, so seasonal aliasing of the observations would not explain the model data d 13 C misfit. However, the PO 4 climatology of the Southern Ocean also suffers from sparse wintertime coverage [MacCready and Quay, 2001], which would bias toward lower summertime PO 4 values and higher sea surface d 13 C in the models. It is also possible that model neglect of lower C:P ratios observed in Southern Ocean biological production [Arrigo et al., 2002] contributes to the models d 13 C overestimate. Alternatively, the models d 13 C overestimate could be due to excess air-sea equilibration of surface waters which would also yield an overestimate of the anthropogenic d 13 C decrease in this century, as discussed below. [25] Inter basin differences in the surface d 13 C are prominent features in the data and models. The mean low latitude (40 S to 40 N) d 13 C decreases from the Atlantic to the Pacific to the Indian Ocean (Figure 5). This inter basin trend could be due either to a trend in organic carbon export rates, or different residence times (and resulting air-sea d 13 C equilibration) at the sea surface due to global-scale inter basin transports of surface waters. Although the model 8of16

9 Figure 6. The time rate of change of sea surface d 13 C of DIC simulated during in the model P2A. Units are decade 1. Indian Ocean s area averaged organic carbon export production was lower than in the Atlantic and Pacific basins north of 40 S, the low latitude Pacific s C export rates exceed the Atlantic s. The d 13 C trends overall imply that Indian Ocean waters have resided at the sea surface the longest time, while Atlantic Ocean surface waters have, compared to the other basins, been more recently renewed. The models tendency to overpredict the tropical Atlantic s surface d 13 C could be due, in part, to local riverine input of terrestrial organic carbon. If the Amazon River s (20% of global riverine transport) DOC remineralizes on < decadal timescales, then the models d 13 C of sea surface DIC in the tropical Atlantic (30 Sto30 N, 10% of ocean area) would need to be adjusted downward by twice the 0.2 applied globally here. The inter basin differences were inversely proportional to the level of vertical mixing prescribed in the models. Models with more vigorous vertical mixing and resulting overturning, like HiHi, tended toward smaller inter basin d 13 C differences that were more representative of those observed. [26] The sea surface d 13 C as exhibits the same meridional structure and inter basin trends as observed (Figure 5). The low latitude surface d 13 C as is highest in the Atlantic Ocean, and decreases to the Pacific then Indian Oceans. The inter basin trends in d 13 C as imply that it is the inter basin differences in the d 13 C equilibration with the atmosphere, reflecting seawater s residence times at the surface and the air-sea gas exchange rate, that drives the inter-basin differences in d 13 C. Although the models Southern Ocean (south of 60 S) d 13 C as were higher than observed, the overestimation in d 13 C as was much less (<1/2) than the overestimation of d 13 C. This suggests that the d 13 C overestimation is related, in part, to model overestimation of biological organic carbon production. It is unlikely that the models underestimate deep mixing, bringing up respiration-derived 13 C depleted organic carbon, as their dominant ventilation pathway is deep convection in the Southern Ocean [Gnanadesikan et al., 2004] The Anthropogenic d 13 C Response [27] The d 13 C Suess effect provides a useful measure of how well the models processes governing uptake of anthropogenic CO 2 represent the real ocean s. The magnitude of the d 13 C change at the sea surface reflects the local strength of overturning, which dilutes and therefore slows the response, and air-sea exchange, which enhances the response. In regions where upwelling replenishes surface water faster than air-sea exchange can equilibrate the water, like at the equator, the d 13 C changes will be smaller than in regions with long surface water residence times, like the subtropics, where d 13 C can fully equilibrate, and keep pace with, the atmospheric d 13 C change (Figure 6). In the following comparisons we ignore the small additional decreases in ocean d 13 C due to sea surface warming. A 0.2 C decade 1 increase in sea surface temperature would lead to d 13 C decreases of up to 0.02 decade 1 in the real ocean but not in the models (A. Gnanadesikan, personal communication, 2011). 9of16

10 Figure 7. The 1978 to 1995 change in the d 13 C of DIC along 92 E in the Indian Ocean (top) in the model P2A and (bottom) derived from observations comparing GEOSECS with WOCE [Sonnerup et al., 2000]. For P2A, the RMS model-data error was decade 1. [28] Because the models yield fairly representative CFC fields [Matsumoto et al., 2004], the predicted 13 C changes are expected to be fairly representative over most of the world ocean. Globally, the models d 13 C changes agreed well with the observations, indicating that in general they achieve an accurate balance of air-sea exchange and ventilation of underlying waters. The area-weighted observed mean sea surface d 13 C change between the 1970s and 1990s was estimated at decade 1 [Quay et al., 2003], compared with 0.14 decade 1 in P2A (Figure 6). [29] Basinwide area-weighted mean d 13 C changes in MOM agreed well with those available from compilations of data available over the past three decades. In the Indian Ocean, the mean sea surface d 13 C change from 55 S 0 N, 75 E 120 E was 0.16 decade 1 [Sonnerup et al., 2000], and from 60 S 5 N basinwide was 0.14 decade 1 [Quay et al., 2003]. Corresponding d 13 C changes in P2A were slightly, but not significantly, greater at 0.18 and 0.16 decade 1, respectively. In the Pacific, the reverse was true. Basinwide d 13 C changes from 1970 to 1993, 60 S 55 N were estimated at 0.18 decade 1 [Quay et al., 2003] and P2A s corresponding change was 0.16 decade 1. The Atlantic Ocean d 13 C change for the time period , from 50 Sto65 N[Quay et al., 2007], on an areally weighted basis was decade 1, slightly smaller than simulated by P2A, 0.20 decade 1. [30] When considered over decades for which the data were available, the sea surface d 13 C changes in the Atlantic (1980s and 1990s) and Pacific (1970s and 1980s) Oceans are comparable ( 0.18 decade 1 [Quay et al., 2003]) and are significantly larger than in the Indian Ocean basin ( 0.14 decade 1 during [Quay et al., 2003]). This difference is smaller when the same time periods are compared, however. For example, using the time periods over which data were available (as above), in the model P2A the Atlantic, Pacific and Indian Ocean d 13 C changes were 0.2, 0.16, and 0.16 decade 1, respectively. However, taken over , the Atlantic, Pacific, and Indian Ocean changes in P2A were comparable, 0.16, 0.16 and 0.15 decade 1, respectively. [31] Despite some regional and specific differences in the modeled d 13 C changes versus observations, the meridional trends and mean basin changes were fairly representative. For example, in the Indian Ocean, the overall meridional pattern and magnitude of the P2A d 13 C change during ( E) agreed well with that observed between GEOSECS in 1978 and WOCE in 1995 (Figure 7). The models meridional trend in and maximum depth penetration of the d 13 C change were comparable to those observed (Figure 7). The data show the strongest gradient in surface changes at S, which were at a similar location in the models, but not as strong. 10 of 16

11 Figure 8. (top) Meridional trends in the time rate of change of the sea surface d 13 C of DIC in the Atlantic (red), Pacific (green), and Indian Oceans (blue) from MOM P2A (lines) compared with the observations (symbols). For P2A, the model-data RMS agreement was decade 1 in the Indian Ocean, 0.02 decade 1 in the Pacific Ocean, and 0.05 decade 1 in the Atlantic Ocean. (bottom) The meridional trend in surface layer RC in the South Indian Ocean (large circles) [Sonnerup et al., 2000; Sabine et al., 1999] and South of Tasmania (small circles) [McNeil et al., 2001] compared with that simulated in the MOM model LOLO (solid line), LOLOHSMIX (dash-dotted line), and P2A (dashed line). [32] P2A s d 13 C changes, and meridional trends in d 13 C changes, were in reasonably good agreement with the observations (Figure 8). P2A s root-mean square (RMS) agreement with available surface d 13 C changes was decade 1, smaller than typical uncertainties in the sea surface d 13 C change (0.03 decade 1 ). In the Pacific basin, the model Southern Hemisphere d 13 C changes were in excellent agreement with the d 13 C changes we have available based on back-calculations using preformed d 13 C and CFC ages [Sonnerup et al., 1999]. The North Pacific d 13 C changes predicted by P2A for the 1970s and 1980s were at the low end of the range indicated by the Hawaii Time Series [Quay et al., 2003; Keeling et al., 2004] and by preformed d 13 C[Sonnerup et al., 1999]. However, in the North Pacific, the P2A d 13 C change agreed (RMS = 0.13, comparable to uncertainties in the reconstruction) with the total industrial-era anthropogenic d 13 C change reconstructed along 165 E[Sonnerup et al., 2007]. In the Indian Ocean, P2A s d 13 C changes were in agreement with the observations south of 40 S, but were larger, by 0.05 decade 1, in the subtropical and equatorial Indian Ocean north of 40 S. [33] The global ocean mean depth-integrated d 13 C change between the 1970s and 1990s was estimated at m decade 1 [Quay et al., 2003], with which the average in P2A, 64 m decade 1 agreed well. The Indian Ocean average during , m decade 1 [Sonnerup et al., 2000] was overestimated by P2A ( 84 m decade 1 ). In the North Atlantic Ocean (0 65 N), the depth integrated change of m decade 1 [Quay et al., 2007] was underestimated by P2A ( 114 m decade 1 ). P2A s underestimate of the depth-integrated change is consistent with P2A s Atlantic overturning being slower than in the real ocean. 11 of 16

12 [34] In locations where we had both anthropogenic d 13 C and DIC change estimates, we compared model with observed ratios of those changes defining RC ¼ Dd13 C DDIC Because of the 10 longer air-sea equilibration time for d 13 C compared with DIC, oceanic RC values are very sensitive to surface water renewal times [McNeil et al., 2001], and can provide valuable constraints in key water mass formation regions where uptake of anthropogenic CO 2 is important and sensitive to change. Unfortunately, RC observations are limited to date to a pair of time series observations [Quay et al., 2003; Keeling et al., 2004], an evaluation of d 13 C and DIC trends on isopycnals in the North Atlantic Ocean [Körtzinger et al., 2003], and to a pair of MLR-guided comparisons of historical with 1990s d 13 C -DIC data sets in the Indian Ocean [Sonnerup et al., 2000; Sabine et al., 1999] and south of Australia [McNeil et al., 2001]. [35] In the North Atlantic, Körtzinger et al. [2003] reconstructed RC in gas exchange equilibrium with the atmospheric changes during the 1970s 1990s, (mmol kg 1 ) 1. Our models yielded smaller RC on the order of (mmol kg 1 ) 1, implying shorter surface water exposure times than observed. In the subtropical North Pacific Ocean, P2A and LOLO matched the time series RC estimate of umol 1 kg based on d 13 C and DIC measured at station ALOHA (22 45 N, 158 W) during [Keeling et al., 2004]. [36] In the South Indian Ocean, where we have the most extensive coverage of RC, the base model, LoLo, overall overestimated RC, and failed to reproduce the meridional RC decrease South of 50 S (Figure 8). Because a few of our MOM variants were explicitly altered from the base LoLo version to enhance bottom water formation and overturning rates in the Southern Ocean only, it is worth exploring the model RC responses to these changes. Enhanced vertical mixing (to 1.0 cm 2 s 1 ) in the Southern Ocean (LLHS), did not improve the meridional trend in Southern Ocean RC (Figure 8). The addition, to LLHS, of enhanced salt fluxes, use of ECMWF winds, and enhanced bottom water production (via restoring), did improve the meridional RC trend (P2A). However, the models RC were still larger than observed, consistent with the sea surface d 13 C overestimate and the sea surface d 13 C change overestimate in this region (Figure 7). These all imply that either the models surface water exposure times in the Southern Ocean are too long, or that the gas exchange rate is too high there, or both. 5. Global Model Relations Among the Anthropogenic CO 2 Perturbations [37] In this section we focus on the MOM models global mean anthropogenic signals: we compare their surface and mean anthropogenic d 13 C changes, air sea d 13 C disequilibrium, and anthropogenic CO 2 uptake across models and with available observations. Among the model variants examined here, the relationship between surface d 13 C change and CO 2 uptake rate during the 1970s and 1990s was linear (Figure 9). Models with relatively sluggish overturning, like LoHi, had relatively large surface d 13 C decreases and low ð3þ CO 2 uptake rates, which means high model RC values. Rapidly overturning models (like HiLo) had small surface d 13 C changes for their higher CO 2 uptake rates (i.e., lower RC). Using NCEP winds [Kalnay et al., 1996] yielded a predictive relationship CO 2 uptake ¼ 4:7 þ 23:2* Dd 13 C sfc [38] Where CO 2 uptake is the model CO 2 uptake (Gt. Cyr 1 ) and Dd 13 C sfc is the global average sea-surface d 13 C change rate ( decade 1 ) during The standard error of the CO 2 uptake estimate from a sea-surface d 13 C change rate estimate is 1.4 Gt C yr 1. This relationship predicts a global ocean CO 2 uptake of 1 Gt C yr 1 from the 1970s 1990s global mean sea surface d 13 C change rate determined from observations, 0.16 decade 1 [Quay et al., 2003]. However, this result depends on the wind fields used to drive the model. Models driven by ECMWF winds yielded 0.2 Gt C per year higher CO 2 uptake for a given sea surface d 13 C change rate, and come closer to the surface ocean d 13 C change and integrated CO 2 uptake of 1.7 Gt C yr 1 observed [Quay et al., 2003]. However, these models all follow the OCMIP standard wherein the sea surface gas exchange rate is driven by SSMI (satellite scatterometry) winds, regardless of the wind field used to drive the physical circulation. It is likely that the models 13 C 12 C change relationship, which is sensitive to the balance between overturning and gas exchange, would agree better with the observations if the gas exchange and overturning were driven by the same wind field. That is to say, the shift in the surface d 13 C versus CO 2 uptake relationship that occurs when switching from NCEP to ECMWF winds (Figure 9) could be caused by the fact that the natural link between overturning and gas exchange is disrupted by the OCMIP practice of driving the model s momentum with one wind product, and gas exchange with another. [39] The relationship between models anthropogenic CO 2 uptake and depth-integrated d 13 C change (Figure 9) does not depend on the wind field used to drive model momentum. Anthropogenic CO 2 uptake can be determined from observations of the depth integrated 13 C change using: Z CO 2 uptake ¼ 0:95 0:021 Dd 13 Cz ðþdz [40] Where CO 2 uptake is the integrated CO 2 uptake rate in the model (Gt. C yr-1) and R Dd 13 C(z)dz is the depth-integrated d 13 C change ( m) during The R Dd 13 C(z)dz estimated by Quay et al. [2003] was 130 m, which yields a CO 2 uptake rate of 1.7 Gt C yr 1 using equation (5), as compared with the Quay et al. [2003] estimate of Gt C yr 1 based on the 1990s air-sea disequilibrium, and s integrated d 13 C changes applied in the atmospheric CO 2 and 13 CO 2 budget approaches of Quay et al. [1992], Tans et al. [1993], and Heimann and Maier Reimer [1996]. Quay et al. [2003] constrained a 1-D box-diffusion model [Oeschger et al., 1975] to match both s d 13 C and bomb 14 C changes, yielding a global CO 2 uptake rate of Gt C yr 1, which agrees with the result from equation (5). ð4þ ð5þ 12 of 16

13 Figure 9. The anthropogenic CO 2 uptake rate versus (a) surface ocean d 13 C changes, (b) air-sea d 13 C disequilibrium, (c) depth-integrated d 13 C changes, and (d) RC, predicted by a family of MOM models described in Gnanadesikan et al. [2004] and in Table 1, driven by ECMWF winds (asterisks), and by NCEP winds (circles). Models are identified by number as listed in Table 3. [41] As established by Tans et al. [1993], the air-sea d 13 C disequilibrium (Dd 13 C a-s ) at any time, coupled with an estimate of the ocean s global air-sea CO 2 exchange rate, can be used to determine oceanic uptake of anthropogenic CO 2. Among the models, the relationship between air-sea d 13 C disequilibrium and CO 2 uptake is: CO 2 uptake ¼ 1:56 4:07 Dd 13 C a-s 1995 Dd 13 C a-s preindustrial [42] This approach depends on the preindustrial air-sea d 13 C disequilibrium (Dd 13 C a-s preindustrial ) which was driven by riverine fluxes of terrestrial organic carbon to the oceans and the observed 21 depletion of that organic carbon relative to atmospheric d 13 C. Sarmiento and Sundquist s [1992] estimate of the riverine organic carbon flux, 0.6 Gt. Cyr 1, yields a mean preindustrial air-sea disequilibrium of 0.2 [Tans et al., 1993]. A recent joint inversion of atmosphere and ocean CO 2 fields [Jacobson et al., 2007] estimated the preindustrial riverine flux to be on the order of ð6þ 0.4 Gt C yr 1, however, which implies a smaller preindustrial d 13 C disequilibrium of The Quay et al. [2003] compilation of global d 13 C data yielded an air-sea disequilibrium value of 0.6 in 1995, which yields (equation (6)) a global CO 2 uptake rate of 1.7 Gt C yr 1 using the Sarmiento and Sundquist [1992] riverine flux. This result agrees with that based on the depth-integrated d 13 C change [Quay et al., 2003] and estimates of global ocean CO 2 uptake [McNeil et al., 2003]. The preindustrial riverine flux of 0.4 Gt. C yr 1 [Jacobson et al., 2007] predicts a lower 1990s CO 2 uptake rate of only 1.3 Gt C yr 1. However, the intercept in equation (6) depends on the gross air-sea CO 2 exchange flux, which would need to be known with certainty before this approach could be used to distinguish the two preindustrial riverine flux scenarios. 6. Discussion [43] Models limitations in simulating d 13 C in the Southern Ocean were also evident in their 14 C simulations. While 13 of 16

14 Table 2. Pre-bomb Volume-Weighted Mean D 14 C Values in the Model Year 1955, and D 14 C Observations, With the Bomb Component Removed, From the GLODAP Gridded Data Set [Key et al., 2004] a Model Southern Ocean Deep D 14 C( ) Pacific Deep D 14 C( ) Southern Ocean Surface D 14 C( ) Ocean Surface (60 S 60 N) D 14 C( ) LoLo P2A HiHi Observations a The Southern and Deep Oceans are defined as south of 53 S, and deeper than 2000 m, respectively. The deep Pacific was defined as north of 20 Sin the Pacific Basin. The ocean surface mean D 14 C was restricted to the area 60 Sto60 N where the most quality observations are available. P2A (and HiHi) predict realistic deep Pacific D 14 C [Gnanadesikan et al., 2004], the ventilation processes and pathways bringing 14 C into the deep sea may not be representative of the real ocean s. In the ocean, deep sea D 14 C gradients from the deep Southern Ocean to the deep North Pacific are on the order of 75 (Table 3), with pre-bomb Southern Ocean surface D 14 C values on the order of 110. For P2A, HiHi, and LoLo the Southern Ocean to deep Pacific gradients were on the order of 120 and 152 and 220, with Southern Ocean surface D 14 C values of 95, 67, and 85, respectively (Table 2). From a 14 C perspective, P2A performs best [Gnanadesikan et al., 2004]. However, d 13 C observations add a significant constraint on deep ocean ventilation. Because of the contrasting air-sea exchange d 13 C signatures (d 13 C as ) of NADW and SODW, the deep ocean d 13 C is sensitive to the balance between these two end-members. Our model d 13 C simulations and comparisons, and comparisons to observations indicate that all of the MOM variants exhibit too strong SODW production, relative to NADW production, to ventilate the deep sea. A contributing factor to this problem is the fact that the D 14 C and d 13 C of the Southern Ocean sea surface, and thus newly forming SODW, are too high compared to observations. An increase in NADW production would be more effective, relative to a comparable increase in SODW production, in bringing 14 C into the deep ocean due to the higher D 14 C values of newly formed NADW ( 50 ) relative to SODW ( 110 ). [44] Model-data fidelity in ventilating the deep-sea with respect to C isotopes is an important consideration in assessing the accuracy of model forecasts of ocean uptake of anthropogenic CO 2 during the next century when more of the anthropogenic CO 2 is taken up into the deep sea. Among the models tested, the highest/lowest uptake ratio was 1.5 in 1990 and >2.0 in 2100 (Table 3). Our model d 13 C simulations indicate that unrealistic southern versus northern deep water production ratios imply inaccurate model CO 2 uptake rates in response to future perturbations in the atmosphere, or in water mass production, i.e., of NADW, and circulation changes. The weaker NADW production rates in this suite of models could be due in part to their coarse spatial resolution (A. Gnanadesikan, personal communication, 2011). [45] One simple explanation for the model-data mismatches in the sea surface meridional d 13 C trends could be an exaggerated wind speed dependence of air-sea CO 2 exchange rates in the models. In cold (high latitude) waters, air-sea exchange drives d 13 C higher, while in warm (low latitude) waters, air-sea exchange drives d 13 C lower (Figure 3). If the CO 2 gas-exchange rates were overestimated at high latitudes under high wind speeds, and underestimated in the subtropics and tropics at low wind speeds, the model-data mismatches in d 13 C and d 13 C as would result. This situation would also contribute to the model overprediction of the anthropogenic d 13 C changes (and RC) in the Southern Ocean. [46] When Krakauer et al. [2006] inferred regional air-sea fluxes by inverting ocean interior 14 C data using an ocean model s interior transports, a much weaker dependence of gas exchange (k) on wind speed (t), was required, i.e., k t 0.6, than the quadratic dependence (k t 2 ) used here (and in OCMIP [Wanninkhof, 1992]). Since both gasexchange parameterizations (tuned to 14 C) yield the same global mean air-sea exchange, the Krakauer et al. [2006] relationship indicates relatively larger (than Wanninkhof [1992]) gas exchange rates at low wind speeds, and relatively smaller gas exchange rates at high wind speeds. When we instead used Krakauer et al. s [2006] wind speed Table 3. Global Mean Anthropogenic Perturbation Signals in the Models Tested Model Model Number DIC Increase (Gt. C Yr 1 ) Depth-Integrated d 13 C Change, ( m) Surface d 13 C Change ( decade 1 ) Anthropogenic CO 2 in 1990 (Gt. C) Anthropogenic CO 2 in 2100 Business as Usual IPCC (Gt. C) 1995 Air-Sea Disequilibrium, Area and Piston Velocity Weighted ( ) Surface RC ( (mmol kg 1 ) 1 ) LoLo LoHi HiLo LoLo HS HiHi P P2A Our variants LoLo EC P2A HR P2A-Krakauer P2 EC HiHi EC of 16