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ABSTRACT

  1. Top of page
  2. ABSTRACT
  3. 1. Introduction
  4. 2. Data sources and analyses
  5. 3. Results and discussion
  6. 4. Summary
  7. 5. Acknowledgments
  8. References

Dissolved inorganic carbon (DIC) was measured from 1992 to 2008 at two time-series sites in the subarctic western North Pacific; this region is a source of atmospheric CO2 in winter due to vertical mixing of deep waters rich in DIC. To estimate the decadal DIC increase resulting from CO2 uptake from the atmosphere, we corrected DIC for the contribution of biological activity below the temperature minimum (Tmin) layer (∼100 m), which is the remnant of the mixed layer from the preceding winter. Decadal DIC increases in the Tmin layer and upper intermediate water (1.3–1.5 μmol kg−1 yr−1; 100–200 m) were higher than those expected from oceanic equilibration with increasing atmospheric CO2 and those previously reported in the open North Pacific. The increase in water column CO2 was estimated to be 0.40 ± 0.08 mol m−2 yr−1. The decadal DIC change in the Tmin layer affects winter CO2 emission. The increase of atmospheric xCO2 in winter (2.1 ± 0.0 ppm yr−1) is higher than that of oceanic xCO2 (0.7 ± 0.5 ppm yr−1) that calculated from DIC and total alkalinity in the Tmin layer. This difference suggests reduction of CO2 emission in winter is possibly controlled by the increase of total alkalinity.


1. Introduction

  1. Top of page
  2. ABSTRACT
  3. 1. Introduction
  4. 2. Data sources and analyses
  5. 3. Results and discussion
  6. 4. Summary
  7. 5. Acknowledgments
  8. References

Anthropogenic CO2 was taken up by the global ocean at a rate of 2.2 ± 0.4 PgC yr−1 during the 1990s (Denman et al., 2007). The most fundamental and reliable approach to the direct detection of the CO2 uptake rate and its variation is to make more accurate and longer time-series observations at fixed stations, for example, station ALOHA in the subtropical North Pacific Ocean (e.g. Dore et al., 2003), BATS in the subtropical western North Atlantic Ocean (e.g. Bates et al., 2002), ESTOC in the subtropical eastern North Atlantic Ocean (e.g. Santana-Casiano et al., 2007), Ocean Station Papa (OSP) in the subarctic eastern North Pacific (e.g. Wong and Chan, 1991) and stations KNOT (44°N, 155°E) (e.g. Tsurushima et al., 2002) and K2 (47°N, 160°E) (e.g. Honda et al., 2006) in the subarctic western North Pacific Ocean (Fig. 1). Time-series observations are essential to understanding temporal variation of dissolved inorganic carbon (DIC) in the ocean.

image

Figure 1. Sampling stations and main ocean currents in the subarctic western North Pacific. The Kuroshio and Oyashio are the subtropical and subarctic western boundary currents in this region, respectively. This is modified from Yasuda et al. (1996).

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Increases of DIC in the surface waters from 1997 to 2001 and in the subsurface waters from 1992 to 2001 were detected by time-series observations at KNOT (Tanaka et al., 2003; Wakita et al., 2005). DIC is positively correlated with AOU in the subsurface water due to the decomposition of organic matter. AOU was calculated by subtracting the observed concentration of dissolved oxygen (DO) from the saturated concentration calculated from temperature and salinity with the equation of Weiss (1970). A linear increase in AOU is superimposed on a bidecadal oscillation of AOU in the Oyashio region (near the subarctic western North Pacific) (Ono et al., 2001). Because the previously reported DIC increases in the subarctic western North Pacific are based on time-series data only from the 10-year period 1992 to 2001 (Wakita et al., 2005), more accurate and longer time-series data are required to confirm the increase of DIC.

At least annually since 1997, the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) has conducted hydrographic observations at KNOT or K2 in the subarctic western North Pacific (Fig. 1). Hydrographic studies in this region were also conducted by other organizations between 1992 and 2003 (e.g. Tsurushima et al., 2002; Wakita et al., 2005). In this study, we compiled data obtained by JAMSTEC and others and investigated the temporal variation of DIC and related properties [AOU and total alkalinity (TA)] below the winter mixed layer of the subarctic western North Pacific for 1992–2008. We also discuss the decadal increase of DIC resulting from the uptake of CO2 from the atmosphere through gas exchange at the air–sea interface.

2. Data sources and analyses

  1. Top of page
  2. ABSTRACT
  3. 1. Introduction
  4. 2. Data sources and analyses
  5. 3. Results and discussion
  6. 4. Summary
  7. 5. Acknowledgments
  8. References

We prepared a set of data to investigate long-term climate change in the subarctic western North Pacific. All data were collected from the observations at the Japanese time-series stations KNOT and K2 from 1992 to 2008, which were made in 61 CTD casts on 44 cruises at KNOT and in 28 CTD casts on 15 cruises at K2; these cruises were made by seven research vessels: T/S Hokusei Maru (Hokkaido University), T/S Oshoro Maru (Hokkaido University), R/V Bosei Maru (Tokai University), R/V Hakuho Maru (Tokyo University), R/V Kaiyo Maru (Japan Fisheries Agency), R/V Hakurei No. 2 (Metal Mining Agency of Japan), R/V Natsushima (JAMSTEC) and R/V Mirai (JAMSTEC) (Tsurushima et al., 2002; Wakita et al., 2005; Watanabe et al., 2007). Approximately, 60% of all observations were done from the R/V Mirai. Data sets from K2 from 1999 to 2006 (Watanabe et al., 2007) are published at the Carbon Dioxide Information and Analysis Center (http://cdiac.ornl.gov/) and the JAMSTEC data web site (http://www.godac.jamstec.go.jp/k2/index.html). DIC and TA were measured by using coulometric and potentiometric techniques, respectively. The precision of both DIC and TA was ±0.1% or better from duplicate determinations. TA from July 2000 to July 2001 during T/S Hokusei Maru cruise was determined by the improved single-point titration method, with precision of ±0.2% from duplicate determinations (Wakita et al., 2005). The DIC and TA values were determined with calibration against certified reference material provided by Prof. A. G. Dickson (Scripps Institution of Oceanography). The DO and nutrient concentrations from JAMSTEC observations were measured with an automatic titrator and a continuous flow analyser, respectively (e.g. Watanabe et al., 2007). We merged the KNOT data obtained by JAMSTEC cruises with those published by Wakita et al. (2005) and Tsurushima et al. (2002) for T/S Hokusei Maru, T/S Oshoro Maru, R/V Bosei Maru and R/V Hakuho Maru cruises. In addition, we added the oceanic physical and chemical data from KNOT and K2 collected as part of WOCE–P1 (1999) (http://whpo.ucsd.edu/data_access/show_cruise?ExpoCode=49KA199905_1) and WESTCOSMIC (1998, 1999) (http://www.kanso.co.jp/ocean/html-doc/english/top1.html).

The values of DIC, TA, DO and nutrients (silicate, phosphate and nitrate) had systematic errors among cruises, because the analytical methods used for these determinations and the precision and standards for analysis varied slightly from cruise to cruise. These systematic errors probably derive from the standardization because of the absence of a common reference material. DIC data for 1992–1997 during T/S Hokusei Maru cruise by Wakita et al. (2005) were not calibrated against certified reference material.

To investigate the temporal variation of chemical properties from the winter mixed layer to intermediate water, we corrected the systematic errors by assuming that ocean chemical properties in the North Pacific Deep Water (NPDW) were constant in our study area from 1992 to 2008 (Wakita et al., 2005; Watanabe et al., 2007). NPDW was defined as the water mass between 27.69σθ (∼2000 db) and 27.77σθ (∼3500 db), because chlorofluorocarbons were not detected below 27.69σθ (Watanabe et al., 2001) and the bottom water deeper than the NPDW in the western North Pacific expanding from the Samoan Passage is characterized by potential temperature (θ) lower than 1.2 °C (≈27.77σθ) (Johnson et al., 1994). Because the residence time of NPDW is ∼500 years (Stuiver et al., 1983), we can assume that the NPDW did not change significantly from 1992 to 2008 for the purpose of investigating the temporal variations in shallower waters.

The values of the systematic errors and factors were –6–19 μmol kg−1 for DIC, –15–8 μmol kg−1 for TA, 0.82–0.97 for DO, 0.95–1.09 for silicate, 0.98–1.12 for phosphate and 0.96–1.04 for nitrate. We corrected the values of these properties at the isopycnal surfaces of NPDW (σθ= 27.69, 27.70, 27.71, 27.72, 27.73, 27.74, 27.75, 27.76 and 27.77) to fit the mean observed values from 2006 to 2008 at the same isopycnal surfaces. The values at each of these isopycnal surfaces were obtained by linear interpolation. The minimum systematic errors were ±0.2% for DIC and TA, ±3% for DO and ±1% for nutrients. The standard deviations of DIC, TA, DO, silicate, phosphate and nitrate values in NPDW after the corrections were estimated to be ±1.9, ±1.3, ±1.5, ±1.0, ±0.01 and ±0.1 μmol kg−1, respectively. These values agree well with the measurement precision for these properties and serve for use in evaluations of the temporal variation of chemical properties.

Because KNOT and K2 are both located in the western subarctic gyre (Fig. 1) and we lacked sufficient decadal time-series data for either station, we combined data from KNOT and K2. The typical water column structure in this region has a minimum temperature (Tmin) layer at about 26.5σθ (∼100 m), which is the remnant of the mixed layer from the preceding winter; the maximum temperature layer is at about 27.1σθ (∼370 m) (Fig. 2) (e.g. Osafune and Yasuda, 2006). Because KNOT is located just North of the Subarctic Front (Fig. 1), data obtained there on some days (10 and 11 May 1999 (MR99–K02); 5 June 1999 (HO99–1); 22 July 1999 (HO99–3)) include no Tmin layer as a result of the migration of subtropical water (Tsurushima et al., 2002). Data from these days were excluded from the analysis of the Tmin layer in this study.

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Figure 2. Typical vertical profile of potential temperature (θ) in the western subarctic gyre by using averages of all data from 1992 to 2008 at stations KNOT and K2. The symbols show the temperature minimum (Tmin) layer (circles) and temperature maximum layer (diamonds).

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We here define the Tmin layer as the remnant of the winter mixed layer in early April, when the surface mixed layer was the coldest in the year (Fig. 3a). The depth, salinity and σθ of the surface mixed layer reached annual maxima from middle March to early April (Figs 3b–d). Because the mean values of depth and σθ in the winter mixed layer in early April (∼120 m, ∼26.5 kg m−3) were similar to those of the Tmin layer over all season from 1992 to 2008 (108 ± 18 m, 26.5 ± 0.1 kg m−3) (Figs 3b and c), in the Tmin layer there was no influence of the surface mixed layer from spring to fall. We can thus define the Tmin layer as the remnant of the winter mixed layer in early April.

image

Figure 3. Seasonal variations of (a) θ, (b) maximum mixed layer depth (MLD), (c) salinity, (d) σθ, (e) DIC, (f) AOU, (g) TA and (h) phosphate (PO4) in the surface mixed layer (circles) and minimum temperature (Tmin) layer (triangles) at stations KNOT (open symbols) and K2 (solid symbols). We also show the seasonal variations of (i) oceanic and atmospheric pCO2 and (j) monthly net air–sea CO2 flux in the surface mixed layer. These figures were plotted by using all data from 1992 to 2008 in order to examine the typical features of seasonal variations at KNOT and K2 and to compare them with the climatological monthly mean from Takahashi et al. (2009). The density criterion in the surface mixed layer was smaller than 0.125 kg m−3 (de Boyer Montégut et al., 2004). Values of oceanic pCO2 (i) were calculated from TA and DIC. The individual pCO2 values calculated in different years are normalized to a reference year 2000 using 1.5 μatm year−1 as the rate of pCO2 increase (Takahashi et al., 2009). Values of monthly net air–sea CO2 flux (j) were estimated with the sea–air pCO2 difference at KNOT and K2 and the climatological monthly mean value of air–sea gas transfer rate for 48°N, 157.5°E as the center of a 4° (latitude) × 5° (longitude) grid cell that is parameterized as a function of (wind speed)2 with a scaling factor of 0.26 from Takahashi et al. (2009) (T09). Positive values indicate effluxes from the sea and negative values influxes from the air. The thick black lines in (i) and (j) are the monthly mean values averaged for KNOT and K2. The other lines in (i) are pCO2 in the seawater (doublet) and in the atmosphere (thin dash) and the doublet line in (j) is the monthly net air–sea CO2 flux. These values are the climatological monthly mean values at 48°N, 157.5°E, the center of the designated box from Takahashi et al. (2009).

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The values of properties on each isopycnal surface (26.6σθ–27.1σθ) were obtained by linear interpolation of discrete bottle sampling data. For the Tmin layer, after the values of Tmin, depth, salinity and σθ were determined from continuous CTD data (1 db resolution), the contents of chemical parameters (DO, DIC, TA and nutrients) on the Tmin isopycnal surface were obtained by linear interpolation of discrete bottle sampling data. This was done because the values of depth, salinity and σθ in the Tmin layer are not necessarily identical to those from discrete bottle sampling.

3. Results and discussion

  1. Top of page
  2. ABSTRACT
  3. 1. Introduction
  4. 2. Data sources and analyses
  5. 3. Results and discussion
  6. 4. Summary
  7. 5. Acknowledgments
  8. References

3.1. Seasonal variations of DIC and related properties in the surface water

In winter, the western subarctic gyre is a source of atmospheric CO2 because of strong vertical mixing; from spring to fall it is a sink for CO2 because of biological production (e.g. Tsurushima et al., 2002; Kawakami et al., 2007). At KNOT and K2, the maximum values of pCO2 and net air–sea CO2 flux occurred in early April (late winter); these maximum values were larger than the climatological mean values for this region reported by Takahashi et al., 2009 (Figs 3i and j). The values of pCO2 in the ocean were calculated from DIC and TA by using the CO2SYS program (Pierrot et al., 2006), by using all data from 1992 to 2008 to examine the typical features of seasonal variation. In this calculation, we used the carbonate dissociation constants of Mehrbach et al. (1973) as refitted by Dickson and Millero (1987). The other properties also reached annual maxima in late winter (Fig. 3): mixed layer depth (∼135 m), salinity (∼33.2), σθ (∼26.5 kg m−3), DIC (∼2130 μmol kg−1), AOU (∼8 μmol kg−1), TA (∼2 240 μmol kg−1) and phosphate (∼1.9 μmol kg−1). The amplitude of seasonal variation of DIC in the surface mixed layer at KNOT (∼160 μmol kg−1) was larger than that at K2 (∼130 μmol kg−1) (Fig. 3e). These amplitudes in the western subarctic gyre are larger than those at other pelagic ocean time-series sites and are mainly attributed to biological production from spring to fall and strong vertical mixing in winter (e.g. Tsurushima et al., 2002). In summer, DIC and phosphate were lower at KNOT than at K2 (Figs 3e and h), which suggests that the difference of seasonal amplitude between KNOT and K2 is caused by differences in biological production (Kawakami et al., 2007). The values of DIC, AOU, TA, phosphate, pCO2 and net air–sea CO2 flux in winter (early April) at KNOT were similar to those in winter at K2 (Fig. 3). During winter, there were no differences in biological production and CO2 emission between KNOT and K2. CO2 emission during winter is controlled by strong vertical mixing of subsurface waters rich in DIC, TA and nutrients because of decomposition of organic matter and dissolution of CaCO3 (e.g. Takahashi et al., 2006). These results indicate that the decadal DIC increase in the Tmin layer is affected by not only the increase of anthropogenic CO2, but also the temporal variation of CO2 emission in winter due to strong vertical mixing.

3.2. Temporal variations of DIC and related properties in the subsurface water

We detected distinct trends in θ, salinity and isopycnal depths in the Tmin and 26.6–26.8σθ layers (Fig. 4, Table 1). There was no apparent DIC increase observed in the subsurface water and AOU significantly decreased in the 26.6–26.8σθ layer (P < 0.05) (Fig. 5, Table 1), even though DIC and AOU reportedly increased from 1992 to 2001 at KNOT (Wakita et al., 2005). These linear regressions model was fitted using the least squares approach.

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Figure 4. Temporal variations of depth (a), θ (b) and salinity (c) from 1992 to 2008 in the temperature minimum (Tmin, circles) and 26.8σθ (triangles) layers at stations KNOT (open symbols) and K2 (solid symbols); note the shifted scales for Tmin (left) and 26.8σθ (right) in panel (b). The depths in the Tmin layer are those determined from continuous CTD data (1 db resolution). Where significant (P < 0.05), linear regressions for 1997 to 2008 are shown for the Tmin (solid lines) and 26.8σθ (dashed lines) layers.

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Table 1.  Rates of increase for DIC and related properties in the western subarctic gyre from 1997 to 2008
LayerDepthθ (°C yr−1)Salinity (yr−1)AOU (μmol kg−1 yr−1)TA (μmol kg−1 yr−1)ΔC*+C280 (μmol kg−1 yr−1)
(m)a(m yr−1)
  1. Note: Error values are the SE of the slope of the linear regression. Bold numbers indicate significant rates derived from linear regressions (P < 0.05).

  2. aAverages and standard deviations at the isopycnal surfaces.

Tmin.108 ± 171.3 ± 0.6 0.039 ± 0.0210.009 ± 0.003−2.1 ± 0.91.6 ± 0.21.3 ± 0.3
26.6σθ121 ± 131.3 ± 0.4−0.020 ± 0.024−0.002 ± 0.002−2.8 ± 0.80.9 ± 0.11.5 ± 0.3
26.7σθ146 ± 162.0 ± 0.5−0.028 ± 0.016−0.003 ± 0.002−3.0 ± 0.60.8 ± 0.11.4 ± 0.3
26.8σθ175 ± 232.4 ± 0.80.025 ± 0.0110.003 ± 0.001−1.8 ± 0.50.5 ± 0.11.3 ± 0.2
26.9σθ222 ± 32−2.2 ± 1.2 0.012 ± 0.010−0.001 ± 0.001−0.4 ± 0.60.5 ± 0.10.8 ± 0.2
27.0σθ287 ± 37−1.3 ± 1.4−0.004 ± 0.007 0.000 ± 0.001−0.3 ± 0.60.5 ± 0.10.7 ± 0.2
27.1σθ375 ± 38−0.3 ± 1.4−0.004 ± 0.007 0.000 ± 0.001−0.2 ± 0.50.5 ± 0.10.4 ± 0.2
image

Figure 5. Temporal variations of AOU (a), DIC (b) and TA (c) for 1992 to 2008 in the temperature minimum (Tmin, circles) and 26.8σθ (triangles) layers at stations KNOT (open symbols) and K2 (solid symbols). Where significant (P < 0.05), linear regressions for 1997 to 2008 are shown for the Tmin (solid lines) and 26.8σθ (dashed lines) layers.

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Long-term trends and bidecadal oscillations of values of θ, salinity, isopycnal depth, AOU and nutrients in the subsurface water in the northwestern subarctic Pacific Ocean are known (Ono et al., 2001; Osafune and Yasuda, 2006; Watanabe et al., 2008). Recently, the bidecadal oscillations were linked to the nodal tidal cycle with an 18.6-year period (e.g. Osafune and Yasuda, 2006), in addition to the already known linkage to the bidecadal component of North Pacific Index (NPI) (Trenberth and Hurrell, 1994; Ono et al., 2001). The isopycnal depths, θ, salinity and AOU in the intermediate water are decreasing when the diurnal tide is strengthening, which occurred from the late 1990s to the late 2000s. It has also been reported that Tmin in the Oyashio upstream (near the subarctic western North Pacific) has a tendency to warm in the periods when the diurnal tide is both strong in the late 1990s and weak in the late 2000s (Osafune and Yasuda, 2006).

Decadal variations of DIC and AOU should be affected by this oscillation. However, we did not detect such DIC and AOU variations in our data collected during 1992–2008, because this period is shorter than a bidecadal cycle and because diurnal tide strengthening occurred from the late 1990s to the late 2000s (e.g. Osafune and Yasuda, 2006). A declining tendency of AOU was observed from the late 1990s (Fig. 5a), which is consistent with the AOU decrease observed from 1997 to 2006 in the North Pacific (Mecking et al., 2008). Because DIC is positively correlated with AOU in the subsurface water (r= 0.99) due to the decomposition of organic matter, decadal trends of DIC corrected for the contribution of organic matter decomposition should be detectable and larger than the decadal DIC trend we observed from 1992 to 2008.

TA significantly increased at rates of 0.5–1.6 μmol kg−1 yr−1 in the subsurface water (P < 0.05) (Fig. 5c, Table 1), despite the lack of a linear trend in TA at KNOT from 1997 to 2001 (Wakita et al., 2005). Also, the increase of potential alkalinity (PA), which is defined as the sum of TA and nitrate and is used to estimate the change in the dissolution of CaCO3, was in the range of 0.5–1.7 μmol kg−1 yr−1 (not shown). The saturation depths of aragonite and calcite were calculated at about 120 m (∼26.6σθ) and 170 m (∼26.8σθ) from TA and DIC data and the CO2SYS program (Pierrot et al., 2006), respectively. Those depths are consistent with previously published results (Feely et al., 2002). The observed TA and PA trends might have been caused by the increase of CaCO3 dissolution resulting from the DIC increase, because anthropogenic CO2 accumulates below the saturation depth of aragonite (∼120 m) in the western subarctic gyre; this saturation depth is shallower than that in the open North Pacific (Feely et al., 2002). This trend is comparable to the TA increases between GEOSECS (early 1970s) and WOCE (early 1990s) estimated by Sarma et al. (2002), which was 0.6 ± 0.4 μmol kg−1 yr−1 in the aragonite saturation horizons of the subarctic region in the North Pacific.

3.3. Estimate of DIC increase due to air–sea CO2 gas exchange

The change in DIC in the subsurface water is controlled by the uptake of atmospheric CO2 through gas exchange at the air–sea interface, the decomposition of organic matter and the dissolution of CaCO3 (e.g. Gruber et al., 1996; Sabine et al., 2002). The decomposition of organic matter includes oxidation and denitrification of organic matter in the subsurface seawater (e.g. Sabine et al., 2002). Oxidation and denitrification of organic matter are related to AOU and N*[=(nitrate + nitrite) − 16 × (phosphate) + 2.90] as an index of nitrogen fixation–denitrification (Deutsch et al., 2001), respectively.

The change of DIC from the pre-industrial period caused by the oceanic uptake of CO2 from the atmosphere through gas exchange (ΔC*) is defined as follows:

  • image

where DICm, AOUm and TAm are the measured values. TA° is the preformed TA estimated using the equation of Sabine et al. (2002). The effect of decomposition from N* would be small, but not trivial: Watanabe et al. (2008) demonstrated a linear increase of N* on 26.8σθ surface superimposed on a bidecadal oscillation. Ceq280 is the theoretical DIC content of waters in equilibrium with the pre-industrial atmospheric CO2 (280 μatm). Because Ceq280 over time remains constant and its trend can be cancelled out, we calculated ΔC*+Ceq280 and its trend represents the DIC increase caused by the uptake of CO2 from the atmosphere through the gas exchange at the air–sea interface.

ΔC*+Ceq280 has significantly increased at 0.7–1.5 (average 1.2 ± 0.3) μmol kg−1 yr−1 (P < 0.05) (Fig. 6, Table 1). These estimated increases in the winter mixed layer and upper intermediate water (Tmin and 26.6σθ–26.8σθ layers), which are between 100 and 200 m thick, are greater than those in deeper water (26.9σθ–27.0σθ); ΔC*+Ceq280 has remained unchanged below 27.1σθ. We estimated the increase of DIC accumulated in the water column to be 0.15 ± 0.04 mol m−2 yr−1 in the surface mixing layer and 0.25 ± 0.07 mol m−2 yr−1 in the intermediate water (100–400 m), using the ΔC*+Ceq280 increase and the thickness of the average depth on each isopycnal surface from Tmin to 27.1σθ at increments of 0.1σθ (Table 1). The total DIC inventory change in the surface and intermediate waters (0.40 ± 0.08 mol m−2 yr−1; maximum depth ∼400 m) is related to the CO2 uptake rate; this value is similar to that previously reported in the subarctic western North Pacific [0.66 ± 0.22 mol m−2 yr−1; maximum depth ∼900 m; 1973–1993 (Ono et al., 2000)] and in the global ocean [0.51 ± 0.09 mol m−2 yr−1; 1990s (Denman et al., 2007)].

image

Figure 6. Temporal variations of ΔC*+Ceq280 from 1992 to 2008 in the temperature minimum (Tmin, circles) and 26.8σθ (triangles) layers at stations KNOT (open symbols) and K2 (solid symbols); note the shifted scales for Tmin (left) and 26.8σθ (right). Where significant (P < 0.05), linear regressions for 1997 to 2008 are shown for the Tmin (solid lines) and 26.8σθ (dashed lines) layers.

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This estimated inventory increase in the western subarctic gyre is higher than the anthropogenic CO2 inventory increase in the Alaskan gyre (>45°N along 152°W) (<0.2 mol m−2 yr−1; maximum depth < ∼400 m; 1991/1992–2005/2006) estimated using an extended multiple linear regression technique (Sabine et al., 2008). This different value is the reason why the decadal DIC increase caused by the uptake of CO2 from the atmosphere in the western subarctic gyre is larger than that in the Alaskan gyre despite the same penetration depth in the two gyres.

3.4. Factors controlling the DIC increase due to air–sea CO2 gas exchange

The ΔC* increase reflects the increase in anthropogenic CO2 and the temporal variation in the CO2 difference between atmosphere and ocean in the surface mixed layer at the time of water mass formation (e.g. Gruber et al., 1996; Sabine et al., 2002).

The ΔC*+Ceq280 increase in the Tmin layer in the subarctic western North Pacific would be affected by not only the increase of anthropogenic CO2 but also the temporal variation of a strong CO2 source during winter, because the Tmin layer is a remnant of the preceding winter mixed layer (e.g. Osafune and Yasuda, 2006). The western subarctic areas along the Kuril and western Aleutian arcs are strong CO2 sources during winter owing to convective mixing of deep waters rich in respired CO2 (e.g. Takahashi et al., 2006). This seasonal variation of pCO2 has an opposite pattern to that of other open ocean time-series sites (ALOHA, BATS and OSP) (e.g. Tsurushima et al., 2002), because the primary causes of seasonal change in pCO2 in the subarctic region (K2 and KNOT) and these other time-series sites are seasonal changes in DIC and temperature, respectively (e.g. Takahashi et al., 2006). The temporal variation of CO2 emission in winter must affect that of DIC in the Tmin layer. If the winter increase rate of atmospheric CO2 were higher than that of oceanic CO2 from year-to-year, then the oceanic CO2 uptake over time in this region would increase as a result of the reduction of CO2 emission in winter due to decrease in the CO2 difference between atmosphere and ocean.

The decadal increases of ΔC*+Ceq280 we observed in the Tmin layer (1.3 ± 0.3 μmol kg−1 yr−1) were higher than expected from oceanic equilibration with increased anthropogenic CO2 in the atmosphere (0.7 μmol kg−1 yr−1), when calculated using the increase of atmospheric CO2 (1.9 ppm yr−1) (Foster et al., 2007) and the Revelle factor in the Tmin layer (15.6 ± 0.4) at constant TA. This Revelle factor is consistent with previous results in winter (Takahashi et al., 2006). This ΔC*+Ceq280 increase was larger than the anthropogenic DIC increase since the 1990s at other open North Pacific stations [<1.1 μmol kg−1 yr−1; <30°N along 149°E (WHP P10) (Murata et al., 2009), <1.0 μmol kg−1 yr−1; 145°E–140°W along 30°N (WHP P02), 0–55°N along 152°W (WHP P16) (Sabine et al., 2008)], and is comparable to higher anthropogenic CO2 increases associated with the Kuroshio and California Currents on both edges of the basin (<1.5 μmol kg−1 yr−1; WHP P02) (Sabine et al., 2008).

The CO2 emission in winter is estimated from the difference between atmospheric and oceanic xCO2. We calculated oceanic xCO2 by using the values of DIC and TA in the mixing layer (early April) (DICwin, TAwin). Phosphate and nitrate in the winter mixing layer also were calculated (PO4win, NO3win). DIC, TA, phosphate and nitrate in the Tmin layer (inline image, inline image, inline image, inline image) are referred to as DICwin, TAwin, PO4win and NO3win. Salinity normalized values of DIC, TA, phosphate and nitrate (nDICwin, nTAwin, nPO4win and nNO3win) were used to remove the influence of local evaporation and precipitation change, because salinity in the Tmin layer increased from 1997 to 2008 (Fig. 4c). A salinity of 33.1 was chosen as the constant to correct DIC, TA and nutrient data, as this represents the mean salinity observed in the Tmin layer over this period. For example, nDICwin was calculated by the following equation:

  • image

where Salwin is salinity in the Tmin layer. The values of DIC, AOU, PO4 and NO3 in the Tmin layer (inline image,inline image, inline imageand inline image) were annual minima in winter (Figs 3e, f and h), whereas inline image had no a distinct seasonal variation (Fig. 3g). This increase of observed inline image, inline image and inline image are caused by the decomposition of organic matter after the previous winter (Figs 3e, f and h). We assumed that DO in the winter mixed layer is homogeneously saturated (i.e. AOU = 0) (e.g. Tsurushima et al., 2002), because the degree of saturation of DO in early April is ∼100% (98 ± 2%) because of the strong vertical mixing and air–sea exchange. DICwin, PO4win and NO3win were obtained from the observed inline image, inline image and inline image and decomposition with the following equations:

  • image
  • image
  • image

where C/–O2, P/–O2 and N/–O2 are the stoichiometric ratios of carbon, phosphorus and nitrogen to oxygen during the decomposition of organic matter (Anderson and Sarmiento, 1994). We estimated the xCO2 of surface seawater in winter from nDICwin and nTAwin (Figs 7a and b). The contents of atmospheric xCO2 in late winter (at the beginning of April) are cited by GLOBALVIEW-CO2 (2009) from 1997 to 2008 at 44.4°N.

image

Figure 7. Temporal variations of (a) DIC (nDICwin), (b) TA (nTAmin), (c) xCO2, mixing ratio of CO2 by volume in the dried air, in the atmosphere (thin curve) at 44.4°N (GLOBAL VIEW-CO2, 2009) and in the ocean (circles), (d) phosphate (nPO4win), (e) nitrate (nNO3win) and (f) potential density (σθwin) at stations KNOT (open symbols) and K2 (solid symbols) in the winter mixed layer [temperature minimum (Tmin) layer]. Temperature minimum is defined as the remnant of the winter mixed layer in early April. Salinity-normalized DIC (nDICwin), TA (nTAwin), phosphate (nPO4win) and nitrate (nNO3win) data were used to remove the influence of local evaporation and precipitation. Values of oceanic xCO2 in the winter mixed layer were calculated between nTAwin and nDICwin. Regression lines for 1997 to 2008 are shown for nDICwin (dotted line, 1.4 ± 0.3 μmol kg−1 yr−1, P < 0.0001); nTAwin (dotted line, 1.1 ± 0.1 μmol kg−1 yr−1, P < 0.05); atmospheric xCO2 in winter (solid line; 2.1 ± 0.0 ppm yr−1, P < 0.001); oceanic xCO2 in winter (dashed line; 0.7 ± 0.5 ppm yr−1, P≤ 0.10); nPO4win (dotted line, 0.012 ± 0.004 μmol kg−1 yr−1, P < 0.05); and nNO4win (dotted line, 0.20 ± 0.06 μmol kg−1 yr−1, P < 0.05).

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The slope of the linear regression of oceanic xCO2 on time was 0.7 ± 0.5 ppm yr−1 (n= 68), which was significant at the 90% confidence level (P≤ 0.1) (Fig. 7c). This linear regression model was fitted using the weighted least squares approach, because calculated xCO2 in the ocean was dispersing from year-to-year. This annual dispersion was not significantly uniform by Kruskal–Wallis test (P < 0.001), which indicates the necessity of weights. We used the weights as the inverse of variance of oceanic xCO2 every year and obtained the linear regression of oceanic xCO2 in winter. This oceanic CO2 increase is consistent with the direct measurement values from 1995 to 2008 near KNOT and K2 of 1.2–1.5 ppm yr−1 for oceanic pCO2, within standard errors (Dr. Nakaoka, NIES, personal communication).

The increase of atmospheric xCO2 (2.1 ± 0.0 ppm yr−1, n= 12) in winter is significantly higher than that of oceanic xCO2 by the comparison of the two linear regressions (F < 0.001) (Fig. 7c). This significance was tested by using the F-distribution of the maximum likelihood estimate of variance, because the regression of oceanic xCO2 was fitted using the weighted least squares approach. The difference of xCO2 between atmosphere and ocean was calculated to be 1.4 ± 0.5 ppm yr−1. These results suggest that the declining CO2 emissions in winter were due to the declining xCO2 gradient between atmosphere and ocean over time.

The temporal change in the CO2 source in winter could be caused by increase of TA in the winter mixed layer. In the CO2s system calculation from the DIC change at constant TA in the seawater, the oceanic xCO2 increase in the seawater is proportional to the DIC increase. If TA in the seawater increases over time, the oceanic xCO2-increasing trend is smaller than that calculated by the increase of DIC under constant temperature and TA conditions. Applying this theoretical case to KNOT and K2, we estimated the oceanic xCO2 increase to be 0.8 ppm yr−1 by using the increasing values computed from the regression lines of nDICwin (Fig. 7a, DIC = 1.2 × year − 368.4) and nTAwin (Fig. 7b, TA = 1.1 × year − 46.6) at constant Tmin (1.63 °C, mean from 1997 to 2008) (Fig. 8). This estimated increase is similar to that by observed nDICwin and nTAwin (0.7 ± 0.5 ppm yr−1, Fig. 7c) and is considerably smaller than that using computed nDICwin increasing values and a constant nTAwin value (2230 μmol kg−1 in 1997; 3.9 ppm yr−1) (Fig. 8). Thus, the increasing trend of nTAwin could inhibit the decadal increase of oceanic xCO2 against the nDICwin increase, which suggests a reduction of CO2 emissions in winter. This indicates that TA increase favours the uptake of CO2 in the ocean.

image

Figure 8. Temporal variations of atmospheric CO2 (thin line) at 44.4°N [GLOBAL VIEW-CO2, 2009]; means of oceanic xCO2 for the subarctic western North Pacific (diamonds); theoretical xCO2 in the ocean calculated using increasing values computed between the regression lines of nDICwin (nDICwin= 1.2 × year − 368.4, Fig. 7a) and nTAwin (TA = 1.1 × year − 46.6, Fig. 7b) at constant temperature minimum (Tmin) (1.63 °C, mean from 1997 to 2008) (asterisks); and that using computed nDICwin increasing values and constant value of nTAwin (2230 μmol kg−1 in 1997, Fig. 7b) (pluses) and Tmin from 1997 to 2008 at stations KNOT and K2 in the winter mixed layer. Regression lines for 1997 to 2008 are shown for atmospheric CO2 in winter (solid line; 2.1 ± 0.0 ppm yr−1, P < 0.001); oceanic CO2 in winter calculated between observed nDICwin and nTAwin (dashed line; 0.7 ± 0.5 ppm yr−1, P≤ 0.10); theoretical CO2 in the ocean calculated using increasing values of nDICwin and nTAwin at constant Tmin (doublet line, 0.8 ppm yr−1); and that calculated using the increasing values of nDICwin and constant value of nTAwin and Tmin (chain line, 3.9 ppm yr−1).

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If increases of atmospheric and oceanic xCO2 in winter continue in the future at the same rates as those from 1997 to 2008, the gradient between the atmosphere and ocean in winter might gradually decrease with time. Additional time-series data are required to confirm the factors controlling the temporal change of CO2 emission in winter and to evaluate this speculation.

In addition to decadal increase of nDICwin and nTAwin, the salinity, depth, nPO4win and nNO3win in the winter mixed layer (Tmin layer) also have significantly increased during the years 1997–2008 (P < 0.05) (Figs 4a and c and 7d and e), while σθ remained constant (Fig. 7f). The increasing trend of nTAwin, nPO4win and nNO3win may be caused by the enhanced winter convective mixing of deep waters rich in DIC, TA and nutrients. This increasing of nPO4win (Fig. 7d) will follow the increasing trend of phosphate during the 1989–1993 period in the winter mixed layer of the subarctic western North Pacific (Ono et al., 2002). In contrast, multi-decadal decreasing trends of salinity, density and phosphate in the winter mixed layer from the 1970s to the 1990s in the Oyashio region and near the subarctic western North Pacific were thought to have been caused by the occurrence of surface stratification (Ono et al., 2001, 2002). Moreover, the temporal variability of depth and CO2 emissions from the winter mixed layer must be relevant to atmospheric forcing (wind speed, etc.). The temporal variations of AOU on the isopycnal surface 26.7–27.2σθ in the Oyashio region and wintertime wind stress curl anomaly around this region are negatively and positively correlated with the bidecadal component of NPI, respectively (Ono et al., 2001; Ishi and Hanawa, 2005). Because DIC is positively correlated with AOU in the subsurface water (r= 0.99) due to the decomposition of organic matter, temporal variation of DIC also possibly has a bidecadal oscillation. Further investigation of the atmospheric effect is required to detect whether there is enhanced winter convective mixing of deep waters or not. The relationships among temporal variability of winter CO2 emissions and atmospheric forcing or climate index must be investigated in the near future. In the future, more accurate and longer time-series data will be required to evaluate these speculations.

4. Summary

  1. Top of page
  2. ABSTRACT
  3. 1. Introduction
  4. 2. Data sources and analyses
  5. 3. Results and discussion
  6. 4. Summary
  7. 5. Acknowledgments
  8. References

DIC and related chemical species have been measured from 1992 to 2008 at Stations KNOT (44°N, 155°E) and K2 (47°N, 160°E) in the subarctic western North Pacific in the western subarctic gyre. The surface mixed layer there in winter is a source of atmospheric CO2 owing to strong vertical mixing (∼100 m) and from spring to fall it is a sink for CO2 because of biological production (e.g. Tsurushima et al., 2002) (Fig. 3i). This seasonal variation of pCO2 has an opposite pattern to that of other time-series sites (ALOHA, BATS and OSP) (e.g. Tsurushima et al., 2002), because the primary cause for seasonal change in the subarctic region is seasonal DIC change (e.g. Takahashi et al., 2006). The temporal change of CO2 emission in winter must affect that of DIC in the Tmin layer. Decadal DIC increase below the Tmin layer is affected not only by the increase of anthropogenic CO2 but also by temporal change of a strong CO2 source during winter, because the typical water column structure here has the Tmin layer at ∼26.5σθ (∼100 m) (Figs 2 and 3d), which is the remnant of the mixed layer from the preceding winter.

To estimate the decadal increase of DIC resulting from the uptake of CO2 from gas exchange with the atmosphere, we corrected DIC for the contribution of the biological activity by calculating ΔC* (e.g. Gruber et al., 1996; Sabine et al., 2002). Decadal changes of corrected DIC have significantly increased at 0.7–1.5 (avg. 1.2 ± 0.2) μmol kg−1 yr−1 in the subsurface water from 1997 to 2008 (Fig. 6, Table 1). These estimated increases in the winter mixed layer and upper intermediate water (Tmin layer and 26.6–26.8σθ; 100–200 m) are higher than those in the next deeper water layer (26.9–27.0σθ; 200–300 m) and have remained unchanged below 27.1σθ (∼400 m). We estimated the water column inventory of CO2 increase to be 0.40 ± 0.08 mol m−2 yr−1, which is similar to those previously reported for the same region (Ono et al., 2000) and for the global ocean (Bindoff et al., 2007).

The decadal DIC increase by the uptake of CO2 from the atmosphere into the winter mixed layer (Tmin layer) would be affected not only by the increase of anthropogenic CO2 but also the reduction of CO2 emission in winter. The estimated DIC increase in the Tmin layer and in the 26.6–26.8σθ layer (1.3–1.5 μmol kg−1 yr−1) was higher than that expected from oceanic equilibration with increased anthropogenic CO2 in the atmosphere (0.7 μmol kg−1 yr−1) and anthropogenic DIC increase since the 1990s in the other open North Pacific stations (<1.1 μmol kg−1 yr−1) (Sabine et al., 2008; Murata et al., 2009). The increase of atmospheric xCO2 (2.1 ± 0.0 ppm yr−1) in winter (early April) is markedly higher than that of oceanic xCO2 in winter calculated from observed inline image and inline image (0.7 ± 0.5 ppm yr−1) (Fig. 7c), which suggests that the reduction of CO2 emission in winter is due to a decreasing xCO2 gradient between the atmosphere and ocean.

This temporal change of the CO2 source in winter is possibly caused by an increase of nTAwin in the winter mixed layer. The oceanic xCO2 increase calculated from observed inline image and inline image was considerably smaller than that calculated using computed nDICmin increasing values and constant Tmin (1.63 °C, mean from 1997 to 2008) and nTAwin (2230 μmol kg−1in 1997; 3.9 ppm yr−1) (Fig. 8). Thus, the increasing trend of nTAwin would inhibit decadal increase of oceanic xCO2 against nDICwin increasing, which suggests the reduction of CO2 emission in winter. This indicates that TA increase favours the uptake of CO2 in the ocean. Additional time-series data are required to confirm the factors controlling the temporal change of CO2 emission in winter. Moreover, because CO2 efflux from the winter mixed layer must be relevant to atmospheric forcing, the relationships between temporal variability of winter CO2 emissions and atmospheric forcing must be investigated in the near future.

5. Acknowledgments

  1. Top of page
  2. ABSTRACT
  3. 1. Introduction
  4. 2. Data sources and analyses
  5. 3. Results and discussion
  6. 4. Summary
  7. 5. Acknowledgments
  8. References

We acknowledge the staff of Mutsu Institute for Oceanography, JAMSTEC and the captains and crews of the R/V Mirai, R/V Natsushima, T/S Hokusei Maru, T/S Oshoro Maru, R/V Bosei Maru, R/V Hakurei No. 2, R/V Kaiyo and R/V Hakuho Maru for their kind cooperation in the collection of samples and hydrographic measurements during the 1992–2008 cruises. We thank Drs. Y. Kumamoto, H. Kawakami, K. Sasaki, Y. Nakano and T. Fujiki and Mr. K. Matsumoto of JAMSTEC; Dr. S. Nakaoka of the National Institute for Environmental Studies; Drs. T. Midorikawa and M. Ishii of the Meteorological Research Institute; Dr. T. Tanaka of the Japan Atomic Energy Agency; Dr. T. Ono of the Fisheries Research Agency; and Drs. Y. W. Watanabe, H. Y. Inoue and S. Tsunogai of Hokkaido University for their valuable comments and discussion; Dr. H. Narita of Tokai University and Dr. K. Imai of Hokkaido University for their great support onboard; and the staff of Marine Works Japan Co., Ltd. who worked as marine technicians onboard. Finally, we also express our deep thanks to three anonymous reviewers who gave us many useful comments.

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  1. Top of page
  2. ABSTRACT
  3. 1. Introduction
  4. 2. Data sources and analyses
  5. 3. Results and discussion
  6. 4. Summary
  7. 5. Acknowledgments
  8. References
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