Abstract

Seasonal and interannual variations of the barrier layer (BL) and its formation mechanism in the subtropical North and South Pacific were investigated by using raw and gridded Argo profiling float data and various surface flux data in 2003–12 and hydrographic section data from the World Ocean Circulation Experiment Hydrographic Programme. BLs detected by raw Argo profiles, which existed within the sea surface salinity (SSS) front located on the equator side of SSS maxima, were thickest and most frequent in winter and had a temporal scale shorter than 10 days, indicating their transient nature. Surface and subsurface processes for the BL formation suggested by previous studies were evaluated. Poleward Ekman advection of fresher water was dominant as the surface freshening process but cannot explain the observed seasonal variations of the BL. Subsurface equatorward intrusion of high-salinity tropical water was too deep to produce salinity stratification within isothermal layers. These results strongly suggest that BLs in the subtropical Pacific are formed mainly through tilting of the SSS front due to the poleward Ekman flow near the sea surface and the equatorward geostrophic flow in the subsurface. This idea is supported by the dominant contribution of the meridional SSS gradient to the meridional sea surface density gradient within the SSS front and the correspondence between the seasonal variations of the BL and isothermal layer depth. On an interannual time scale, the winter BL thickness in the North and South Pacific was related to the Pacific decadal oscillation and the El Niño–Southern Oscillation, respectively, through the intensity of trade winds controlling isothermal layer depth.

1. Introduction

The barrier layer (BL) is defined as the layer between bases of the mixed layer and the isothermal layer, when the former is shallower than the latter due to salinity stratification (Lukas and Lindstrom 1991). The BL is believed to work as a barrier against the heat and kinetic energy input into the ocean interior. When BLs are formed, kinetic energy transported from the atmosphere to ocean by wind is trapped into the shallower mixed layer and accelerates flow only in the mixed layer (Vialard and Delecluse 1998a). In addition, the cooling effect of entrainment is reduced because the underlying BL water that is entrained into the mixed layer has the same temperature as the mixed layer. For these effects, the BL is thought to play an important role in air–sea interactions such as El Niño–Southern Oscillation (ENSO; Vialard and Delecluse 1998b; Maes and Belamari 2011), the Indian Ocean dipole (Masson et al. 2004), and tropical cyclones (Balaguru et al. 2012).

The mismatch between the isothermal layer depth (ILD) and the mixed layer depth (MLD), that is, the presence of BLs, was first reported in the western equatorial Pacific by using shipboard observation data (Godfrey and Lindstrom 1989; Lukas and Lindstrom 1991). Since then, the interannual variation of BLs and its link to ENSO have been investigated (Ando and McPhaden 1997; Delcroix and McPhaden 2002; Bosc et al. 2009; Qu et al. 2014). The formation of BLs in the western equatorial Pacific has been attributed to freshening near the sea surface by heavy precipitation (Lukas and Lindstrom 1991; Sprintall and Tomczak 1992) and to the tilting process of the meridional sea surface salinity (SSS) front lying on the eastern edge of the warm pool (Cronin and McPhaden 2002). In the latter process, eastward advection of fresher surface water caused by westerly wind bursts plays an important role and is responsible for a dominant time scale of 12–25 days for BLs (Sprintall and McPhaden 1994).

BLs are formed not only in the tropical region but also in the subtropical regions (Sprintall and Tomczak 1992). Analyses of Argo profiling float data revealed the existence of BLs in winter in the subtropical region of the North Pacific (Sato et al. 2004) and each ocean basin (Sato et al. 2006) in association with SSS fronts lying on the equator side of SSS maxima. These BLs observed by Argo float (Sato et al. 2004, 2006) and historical (Mignot et al. 2009) temperature and salinity profiles were thick and showed patchy distribution, implying that the spatial scale of BLs is small.

The formation mechanism of BLs in the subtropical region where evaporation exceeds precipitation has been under discussion. The previous studies suggested that the salinification in the subsurface due to the horizontal intrusion of saline tropical water, which is subducted from the region poleward of the SSS front, into the lower part of isothermal layers in the SSS front results in the winter BL formation (Sprintall and Tomczak 1992; Sato et al. 2004, 2006). In addition, Mignot et al. (2007) analyzed historical temperature and salinity data to point out the importance of the poleward Ekman advection of fresher surface water.

Recent accumulation of Argo profiling float data exceeding 10 yr and construction of various surface flux data enabled us to study surface salinity processes such as SSS variation and its mechanism (e.g., Ren and Riser 2009; Bingham et al. 2012) and the formation and subduction of the North Pacific Tropical Water (NPTW; Katsura et al. 2013) and the South Pacific Tropical Water (SPTW; Zhang and Qu 2014). Based on these results, it is worth validating the formation mechanism of BLs in the subtropical Pacific suggested by previous studies by using Argo and other hydrographic data, particularly because the relationship between the BL formation and the subduction of tropical waters has been suggested. The aim of the present study is to clarify the mechanism of BL formation in the subtropical North and South Pacific and to investigate the seasonal and shorter time-scale variations of BLs. We also investigated the interannual variations of BLs and their relation to dominant climate variations in the Pacific. We believe that the results of this study are important for understanding the BL formation not only in the other subtropical regions but also in the equatorial regions, especially in the northwest equatorial Atlantic where BL formation and maintenance cannot be explained by freshwater flux only and hence the importance of tropical water subduction was suggested, as in the subtropical regions (Sprintall and Tomczak 1992). The data and definition of the BL are explained in section 2. Seasonality and distribution of BLs in the subtropical Pacific are examined in section 3. Formation mechanisms of BLs are validated in section 4. Interannual variation of winter BLs and its relation to climate variations are investigated in section 5. Summary and discussion are given in section 6.

2. Data and method

We used temperature and salinity data from Argo profiling floats in the North and South Pacific in 2003–12, which were downloaded from the ftp site of the Argo Global Data Assembly Center (ftp://usgodae.org/pub/outgoing/argo; ftp://ftp.ifremer.fr/ifremer/argo). Most of the North Pacific float data, which had been downloaded monthly right after the observation, have passed through only real-time quality control, while about 80% of the South Pacific data, which were recently downloaded, have also passed through delay-mode quality control (Wong et al. 2014). We edited these data as outlined in Oka et al. (2007) and selected 13 978 and 9651 profiles in the SSS front region in the northern and southern boxes (defined in section 3), respectively. Typical vertical resolution of these profiles was 2–5 dbar in the upper 200 dbar and was high enough to resolve BLs thicker than 10 dbar. Finally, each profile was vertically interpolated at an interval of 1 dbar using the Akima spline (Akima 1970).

We also used the monthly mean temperature and salinity gridded data based mainly on Argo profiling float observations, named the Grid Point Value of the Monthly Objective Analysis using the Argo data (MOAA_GPV) (Hosoda et al. 2008), in 2003–12. This dataset was made by optimally interpolating the anomalies of Argo-based temperature and salinity data from those of the World Ocean Atlas 2001 climatology (Conkright et al. 2002) onto 1° × 1° grid points at each standard depth. In this study, the temperature and salinity data between 10 and 2000 dbar at each grid point were vertically interpolated at an interval of 1 dbar using the Akima spline.

We also used reanalysis data of precipitation from the Global Precipitation Climatology Project (Huffman et al. 1997; Adler et al. 2003) and wind stress from the National Centers of Environmental Prediction (Kistler et al. 2001). These data for each month from 2003 to 2012 were linearly interpolated onto the same grid points as MOAA_GPV.

In this study, ILD is defined as the depth at which potential temperature θ changes by 0.2°C from the 10-dbar depth (de Boyer Montégut et al. 2007; Mignot et al. 2007, 2012). MLD is defined as the depth at which potential density σθ increases from the 10-dbar depth by an increment equivalent to a temperature decrease of Δθ = 0.2°C at a fixed salinity S, that is,

 
formula

Barrier layer thickness (BLT) is defined as

 
formula

3. Seasonality and persistence of barrier layer

The BLs in the subtropical Pacific from MOAA_GPV were broadly distributed in winter and showed clear seasonality (Fig. 1). In the subtropical North Pacific, BLs thicker than 20 dbar existed in boreal winter at 10°–25°N, 160°E–130°W in association with an SSS front lying on the equator side of the SSS maximum, that is, the NPTW formation region (Fig. 1a). The SSS front weakened and BLs disappeared in boreal summer (Fig. 1b). Similar seasonality of BL distribution was seen in the subtropical South Pacific. In austral winter, BLs were formed in the SSS front region at 5°–20°S, 150°–110°W, which was located on the equator side of the SSS maximum, that is, the SPTW formation region (Fig. 1d). These BLs also disappeared in austral summer as in the North Pacific, although the associated SSS front did not weaken (Fig. 1c). Such seasonality and distribution of BLs are consistent with the previous results based on the World Ocean Atlas climatology (Sprintall and Tomczak 1992; Sato et al. 2004, 2006). The seasonality of BLs in the tropical region differed from that in the subtropical regions. In the western tropical Pacific, thick BLs (BLT > 20 dbar) were distributed at 10°S–10°N west of the date line throughout a year (Fig. 1). Since we focus on BLs in the subtropical Pacific in this study, these BLs in the tropical Pacific will not be pursued in this paper. In the South Pacific, BLs were also formed at 25°–40°S, 125°–85°W in the SSS front region poleward of the SSS maximum in austral winter (Fig. 1d). These are considered to be artificial BLs produced by interpolation processes of MOAA_GPV data because most Argo profiles in this region did not detect BLs (not shown).

Fig. 1.

Distributions of BLs thicker than 20 dbar (gray shading) and salinity at 10-dbar depth (contour) in (a),(c) February and (b),(d) August in the (top) North Pacific and the (bottom) South Pacific based on MOAA_GPV averaged in 2003–12. Thick rectangles indicate the northern box in (a) and (b) and southern box in (c) and (d). Note that a criterion of 20 dbar was used to detect BLs from MOAA_GPV data (Figs. 1, 3) and that of 10 dbar was used for Argo profiles (other figures).

Fig. 1.

Distributions of BLs thicker than 20 dbar (gray shading) and salinity at 10-dbar depth (contour) in (a),(c) February and (b),(d) August in the (top) North Pacific and the (bottom) South Pacific based on MOAA_GPV averaged in 2003–12. Thick rectangles indicate the northern box in (a) and (b) and southern box in (c) and (d). Note that a criterion of 20 dbar was used to detect BLs from MOAA_GPV data (Figs. 1, 3) and that of 10 dbar was used for Argo profiles (other figures).

To further investigate the BLs in the subtropical regions by using Argo float profiles, we defined two boxes, the northern box at 10°–25°N, 155°E–130°W and the southern box at 5°–20°S, 155°–100°W. The distribution of BLs observed by Argo floats in the two boxes corresponded well to the SSS fronts and showed the same seasonality as demonstrated by MOAA_GPV (Fig. 2). In the northern box, the SSS front was stronger and was about 5° wide meridionally in boreal winter (Fig. 2a). BLs thicker than 10 dbar were observed frequently within the SSS front and much less outside the front. In boreal summer, BLs were observed infrequently both within and outside the SSS front (Fig. 2b). In the southern box, thicker BLs were observed within the SSS front in austral winter (Fig. 2d). The number of BLs decreased greatly in austral summer, although the SSS front did not weaken (Fig. 2c).

Fig. 2.

Distributions of BLT (colored dots) from Argo profiles and salinity at 10-dbar depth (contour) from MOAA_GPV in (a),(c) February and (b),(d) August of 2003–12 in the (top) northern box and the (bottom) southern box. Small black dots indicate the position of Argo profiles without BLT > 10 dbar.

Fig. 2.

Distributions of BLT (colored dots) from Argo profiles and salinity at 10-dbar depth (contour) from MOAA_GPV in (a),(c) February and (b),(d) August of 2003–12 in the (top) northern box and the (bottom) southern box. Small black dots indicate the position of Argo profiles without BLT > 10 dbar.

Based on the close relationship between winter BLs and the SSS front, we examine the seasonal variation of BLs in the SSS front in more detail. Since MOAA_GPV grid points with a horizontal SSS gradient higher than 6 (5) × 10−7 m−1 in the northern (southern) box mainly corresponded to the winter BLs (Fig. 3), these grid points are considered the SSS front in the following part of the paper. In the SSS front in the northern box, both the number of Argo profiles with BLs and the observed BLT were at a maximum in February (Figs. 4a,b). Note that the frequency of Argo profiles with BLT > 10 dbar was about 35% even in winter (Fig. 4a), which indicates that BLs had patchy or porous distribution, as suggested by the previous studies (Sato et al. 2004; Mignot et al. 2009). In addition, Argo floats, which typically repeat observations at 10-day intervals (Roemmich et al. 2004), did not observe BLs continuously in about 75% of total cases (Fig. 5a). This implies that the typical temporal scale of BLs is shorter than 10 days and is shorter than that of 12–25 days in the western equatorial Pacific (Sprintall and McPhaden 1994).

Fig. 3.

Histogram of number of 1° × 1° grid points with BLT > 20 dbar with respect to the horizontal SSS gradient in (a) the northern box and (b) the southern box, calculated from average distributions from MOAA_GPV in January–March in (a) and July–September in (b) during 2003–12.

Fig. 3.

Histogram of number of 1° × 1° grid points with BLT > 20 dbar with respect to the horizontal SSS gradient in (a) the northern box and (b) the southern box, calculated from average distributions from MOAA_GPV in January–March in (a) and July–September in (b) during 2003–12.

Fig. 4.

(a) Monthly histogram (bars) of the number of Argo profiles with BLT > 10 dbar and monthly average of their frequency (dots) and (b) monthly average of BLT from Argo profiles with BLT > 10 dbar, calculated for the SSS front in the northern box during 2003–12. Vertical bars indicate the 95% confidence interval based on the standard deviation from Argo profiles with BLT > 10 dbar in each month during 2003–12. (c),(d) As in (a) and (b), but for the southern box.

Fig. 4.

(a) Monthly histogram (bars) of the number of Argo profiles with BLT > 10 dbar and monthly average of their frequency (dots) and (b) monthly average of BLT from Argo profiles with BLT > 10 dbar, calculated for the SSS front in the northern box during 2003–12. Vertical bars indicate the 95% confidence interval based on the standard deviation from Argo profiles with BLT > 10 dbar in each month during 2003–12. (c),(d) As in (a) and (b), but for the southern box.

Fig. 5.

Frequency of the period for which each Argo float continuously observed BLT > 10 dbar in the SSS front in (a) the northern box and (b) the southern box during 2003–12. If, for example, an Argo float observes a BL on 1 Jan for the first time and again on 11 Jan, and does not on 21Jan, the period on the x axis is 11.

Fig. 5.

Frequency of the period for which each Argo float continuously observed BLT > 10 dbar in the SSS front in (a) the northern box and (b) the southern box during 2003–12. If, for example, an Argo float observes a BL on 1 Jan for the first time and again on 11 Jan, and does not on 21Jan, the period on the x axis is 11.

In the SSS front in the southern box, BL frequency was at a maximum in August (Fig. 4c). The observed BLT was also largest in August, showing similar seasonality as in the northern box (Fig. 4d). The frequency of Argo profiles was about 35% even in austral winter, indicating again the patchiness of the BLs’ distribution. In addition, the time scale of most BLs was shorter than 10 days in about 70% of total cases, as in the northern box (Fig. 5b).

4. Formation mechanism of barrier layer

a. Surface and subsurface processes for the BL formation

The BL formation in the subtropical region has been attributed to two processes: freshening near the sea surface and salinification in the subsurface (section 1). The surface freshening in this SSS front region is attributable to precipitation and poleward Ekman advection of fresher water. To examine the contributions of these two effects, we use the mixed layer salinity (MLS) budget equation of Ren and Riser (2009):

 
formula

where Sm is the MLS, t is time, P is precipitation, hm is the MLD, ue is Ekman velocity, and is the horizontal differential operator. Ekman velocity ue was estimated from wind stress data as

 
formula

where τx and τy are the zonal and meridional wind stresses (positive eastward and northward), f is the Coriolis parameter, and ρ0 is the reference density of seawater, taken to be 1025 kg m−3. “Other terms” include the effects of evaporation ES/hm (E is evaporation), geostrophic advection −ugSm (ug is geostrophic velocity), and entrainment −weΔS/hm (we is the entrainment velocity, and ΔS is the difference between MLS and the salinity at 20 dbar below from the mixed layer base). These work to increase MLS in the SSS front region (Katsura et al. 2013) and are neglected. Both terms of precipitation and Ekman advection in Eq. (3) contain the MLD (hm) in their denominator, and these terms multiplied by hm represent advection of salt. We estimated the salt advections by precipitation Aprec and Ekman advection AEk as

 
formula

and

 
formula

respectively.

In the northern box, these two effects were always negative and showed seasonal variations (Fig. 6a). The term AEk was large in boreal winter (November–January) and small in spring to summer (May–August). The term Aprec had a smaller amplitude than AEk and was large in boreal summer to early winter (August–December). The term AEk exceeded Aprec except in August and September and was 2 to 4 times greater in magnitude than Aprec in boreal winter when BLs were formed.

Fig. 6.

Monthly average of AEk (thick curve) and Aprec (thin curve) in (a) the northern box and (b) the southern box during 2003–12. Vertical bars indicate the 95% confidence interval based on the standard deviation of each month during 2003–12.

Fig. 6.

Monthly average of AEk (thick curve) and Aprec (thin curve) in (a) the northern box and (b) the southern box during 2003–12. Vertical bars indicate the 95% confidence interval based on the standard deviation of each month during 2003–12.

The term AEk was dominated by its meridional component, that is, meridional Ekman salt advection [(1/ρ0f)(∂Sm/∂y)τx; not shown]. When we examine the two factors contributing to the meridional Ekman salt advection, ∂Sm/∂y and τx, their amplitudes were at maximum in November and December, respectively (Figs. 7a,b), which resulted in the peak of AEk in December. The seasonal variation of ∂Sm/∂y in the northern box reflected mainly that of MLS in the MLS minimum region south of the SSS front (Figs. 8a,b), which is controlled mainly by precipitation in the intertropical convergence zone (Bingham et al. 2010; Yu 2011). Freshening in the MLS minimum in boreal winter strengthened the SSS front and contributed to the enhancement of the Ekman salt advection.

Fig. 7.

(a) Monthly average of meridional MLS gradient magnitude from MOAA_GPV and (b) zonal wind stress in the northern box during 2003–12. Vertical bars indicate the 95% confidence interval based on the standard deviation of each month during 2003–12. (c),(d) As in (a) and (b), but for the southern box.

Fig. 7.

(a) Monthly average of meridional MLS gradient magnitude from MOAA_GPV and (b) zonal wind stress in the northern box during 2003–12. Vertical bars indicate the 95% confidence interval based on the standard deviation of each month during 2003–12. (c),(d) As in (a) and (b), but for the southern box.

Fig. 8.

(a),(c) Meridional MLS variation during 2003–12 from MOAA_GPV, averaged monthly at (a) 155°E–130°W in the North Pacific and at (c)155°–100°W in the South Pacific. (b),(d) As in (a) and (c), but for meridional MLS gradient.

Fig. 8.

(a),(c) Meridional MLS variation during 2003–12 from MOAA_GPV, averaged monthly at (a) 155°E–130°W in the North Pacific and at (c)155°–100°W in the South Pacific. (b),(d) As in (a) and (c), but for meridional MLS gradient.

In the southern box, AEk was −4 m month−1 with a small seasonal variation and always exceeded Aprec (Fig. 6b). It was dominated by its meridional component (not shown), and the poleward Ekman advection of fresher water [(1/ρ0f)(∂Sm/∂y)τx] was dominant as the surface process, as in the North Pacific. Zonal wind stress was strong in austral winter (July–September; Fig. 7d), as in the northern box. On the other hand, ∂Sm/∂y exhibited an opposite seasonal variation, being large in austral summer–fall and small in austral winter (Fig. 7c), which was determined by the MLS variation near 5°–10°S on the equator side of the SSS front (Figs. 8c,d). This resulted in the small seasonal variation of AEk.

Thus, the meridional Ekman advection was dominant as the surface process both in the North and South Pacific. However, AEk in the South Pacific did not show a clear seasonal variation. The term AEk in the North Pacific was large in boreal winter, although its peak (November–January) was a little different from that of BLs (February). Therefore, the seasonality of BL formation in the subtropical Pacific cannot be fully explained by Ekman advection.

To further investigate the BL formation through subsurface processes including the subduction of tropical waters, we analyzed two meridional sections obtained under the World Ocean Circulation Experiment Hydrographic Programme (WHP) in winter: the P16N section along 152°W in the North Pacific occupied in February to March 2006 and the P17S section along 135°W in the South Pacific observed in July to August 1991. In the P16N section, BLs thicker than 70 dbar were formed at 18°–19°N (Fig. 9) because of the salinity stratification within the isothermal layer (Fig. 10). Just beneath the isothermal layer, NPTW characterized by salinity higher than 35.0 (Shuto 1996) extended equatorward. However, the core (vertical salinity maximum) of NPTW was located at 120 dbar and was deeper than the base of the isothermal layer. This relationship held in the northern box throughout a year; the NPTW core was deeper than the isothermal layer base by more than 30 dbar (Fig. 11a). Furthermore, dissolved oxygen concentration was uniformly 101%–103% in the isothermal layer, while it decreased downward in the underlying layers including the NPTW (Figs. 9c, 10). These facts suggest that it is unlikely that NPTW subducted from higher latitudes had intruded horizontally into the lower part of the isothermal layer to form the observed BLs.

Fig. 9.

Meridional distribution of (a) potential temperature (°C), (b) salinity, and (c) dissolved oxygen concentration (%) in WHP P16N section along 152°W observed in February to March 2006. Thick solid and dashed curves in indicate MLD and ILD, respectively. Triangles at the top of each panel indicate the locations of hydrographic stations. Gray shading in (b) and (c) denotes salinity higher than 35.0 and dissolved oxygen concentration higher than 100%, respectively.

Fig. 9.

Meridional distribution of (a) potential temperature (°C), (b) salinity, and (c) dissolved oxygen concentration (%) in WHP P16N section along 152°W observed in February to March 2006. Thick solid and dashed curves in indicate MLD and ILD, respectively. Triangles at the top of each panel indicate the locations of hydrographic stations. Gray shading in (b) and (c) denotes salinity higher than 35.0 and dissolved oxygen concentration higher than 100%, respectively.

Fig. 10.

Vertical profiles of (a) salinity (thin solid curve) and potential temperature (thin dashed curve) and (b) potential density (thin solid curve) and dissolved oxygen concentration (thin dashed curve) at 19°N in the P16N section. Thick solid and dashed curves denote MLD and ILD, respectively.

Fig. 10.

Vertical profiles of (a) salinity (thin solid curve) and potential temperature (thin dashed curve) and (b) potential density (thin solid curve) and dissolved oxygen concentration (thin dashed curve) at 19°N in the P16N section. Thick solid and dashed curves denote MLD and ILD, respectively.

Fig. 11.

Monthly average of MLD (thick solid curve), ILD (thick dashed curve), and salinity maximum depth (thin solid curve) observed by Argo floats in the SSS front in (a) the northern box and (b) the southern box during 2003–12. Vertical bars indicate the 95% confidence interval based on the standard deviation from Argo profiles with BLT > 10 dbar in each month during 2003–12.

Fig. 11.

Monthly average of MLD (thick solid curve), ILD (thick dashed curve), and salinity maximum depth (thin solid curve) observed by Argo floats in the SSS front in (a) the northern box and (b) the southern box during 2003–12. Vertical bars indicate the 95% confidence interval based on the standard deviation from Argo profiles with BLT > 10 dbar in each month during 2003–12.

A similar relationship between BLs and SPTW characterized by salinity higher than 36.0 (Shuto 1996) was seen in the P17S section, where BLs with a thickness of 30–70 dbar were formed at 10°–13° and 15°S (Fig. 12). Within the BL at 10°S near an SSS front, salinity increased downward, while temperature was almost uniform (Figs. 12b, 13a). This indicates that the BL was not formed by a surface process only; in other words, it was formed, at least partly, through a subsurface process. Nevertheless, the core of SPTW at 130 dbar was deeper than the base of the isothermal layer, which was also seen in Argo profiles in the southern box (Fig. 11b). Furthermore, dissolved oxygen was oversaturated (106%–111%) throughout the BL and decreased downward beneath the ILD (Figs. 12c, 13b). Thus, SPTW was also unlikely to contribute directly to the BL formation.

Fig. 12.

As in Fig. 9, but for P17S section along 135°W observed in July to August 1991. Gray shading in (b) and (c) denotes salinity higher than 36.0 and dissolved oxygen concentration higher than 100%, respectively.

Fig. 12.

As in Fig. 9, but for P17S section along 135°W observed in July to August 1991. Gray shading in (b) and (c) denotes salinity higher than 36.0 and dissolved oxygen concentration higher than 100%, respectively.

Fig. 13.

As in Fig. 10, but for 10°S in the P17S section.

Fig. 13.

As in Fig. 10, but for 10°S in the P17S section.

b. Possibility of BL formation through the tilting of SSS front

In the previous subsection, we examined the possibility of BL formation through the surface and subsurface processes. Meridional Ekman advection is dominant as the surface process but cannot explain the seasonal variation of BLs in either the North or South Pacific, particularly the latter. The intrusion of subducted tropical water in the subsurface also seems unable to contribute directly to the BL formation. These observational facts suggest that BLs are formed primarily because of the tilting of the SSS front, as pointed out by Cronin and McPhaden (2002) for the equatorial Pacific, because there are poleward Ekman flow near the sea surface and equatorward geostrophic flow in the subsurface, both flowing across the zonal SSS front (Fig. 14). Tilting of an SSS front with sufficiently large ILD/MLD could produce salinity stratification in the isothermal layer and leave a BL in its lower part. If such a mechanism is dominant, thicker BLs are likely to be formed in winter above the base of the deeper isothermal layer, which is consistent with the observed seasonality of BLs. In this subsection, we examine the possibility of BL formation through the tilting of the SSS front.

Fig. 14.

Schematic diagram of BL formation through the tilting of an SSS front in the North Pacific. Gray shading indicates formed BL. Thick line indicates an SSS front.

Fig. 14.

Schematic diagram of BL formation through the tilting of an SSS front in the North Pacific. Gray shading indicates formed BL. Thick line indicates an SSS front.

For the BL formation through the tilting of the meridional SSS front, it is necessary that the contribution of the meridional SSS gradient to the meridional sea surface density gradient across the SSS front is much larger than that of the meridional sea surface temperature (SST) gradient. In other words, meridional density ratio Ry (Tippins and Tomczak 2003), defined as

 
formula

must satisfy −1 < Ry < 1 at the SSS front, where α is thermal expansion coefficient, β is salinity contraction coefficient, Ts is SST, and Ss is SSS. If this condition is satisfied, the mixed layer can become shallower than the isothermal layer as a result of the tilting of the SSS front.

In the North Pacific, the magnitude of Ry was small in boreal winter in a zonal band with a meridional width of about 5° in 10°–20°N, 120°E–150°W (Fig. 15a). This band corresponded to both the SSS front and the BL distribution (Figs. 1a, 2a). In the South Pacific, the Ry condition was satisfied in austral winter in 10°–18°S, 170°–100°W (Fig. 15d), which also corresponded to both the SSS front and the BL distribution (Figs. 1d, 2d). These features imply that BLs were formed because of the tilting of the SSS front.

Fig. 15.

As in Fig. 1, but color denotes Ry in regions where −1 < Ry < 1 is satisfied.

Fig. 15.

As in Fig. 1, but color denotes Ry in regions where −1 < Ry < 1 is satisfied.

The small Ry region also existed in association with the SSS front in summer in both the North and South Pacific (Figs. 15b,c), but BLs were formed infrequently there (Figs. 1b,c, 2b,c). This is probably because the preexisting isothermal layers were too shallow. The seasonality of BLs corresponded well to that of ILD (Figs. 4, 11); in the northern (southern) box, BLs were most frequently observed in February (August) when the isothermal layer was deepest and infrequently in boreal (austral) summer when the isothermal layer was shallow.

Thus, it is strongly suggested that the BL formation in the subtropical Pacific is attributable primarily to the tilting of the meridional SSS front, and its seasonality is governed by that in the depth of isothermal layer, which preconditions the BL formation. After deepening of the isothermal/mixed layers that typically occur on a time scale of several days (e.g., de Boyer Montégut et al. 2004; Oka et al. 2007) in the SSS front region, the vertical shear of horizontal flow tilts the SSS front to produce BLs that mostly lasts for shorter than 10 days (Fig. 5). Such events are expected to occur intermittently throughout the SSS front region (Fig. 2) and emerge in the smoothed climatological pictures (Fig. 1; Sato et al. 2004, 2006).

5. Interannual variation of winter barrier layer

Frequency and thickness of thick BLs in winter showed interannual variation both in the northern box and the southern box, with a different tendency between the two hemispheres (Fig. 16). In the northern box, the BL frequency was lowest in 2009, while BLT was largest in the same year. The two quantities showed a negative correlation (coefficient R = −0.53),1 a relation that was not seen on the seasonal time scale (Fig. 4). On the other hand, the two quantities showed a positive correlation (R = 0.73) in the southern box. In other words, thicker BLs tend to be distributed sparsely in the northern box, while thicker BLs tend to be distributed densely in the southern box.

Fig. 16.

Time series during 2003–12 of (a) frequency of Argo profiles with BLT > 10 dbar and (b) BLT from Argo profiles with BLT > 10 dbar, averaged in January–March in the SSS front in the northern box. Vertical bars in (a) and (b) indicate the 95% confidence interval based on the standard deviation of 3-month values of each year and from Argo profiles with BLT > 10 dbar during 3 months of each year, respectively. (c),(d) As in (a) and (b), but for July–September in the southern box.

Fig. 16.

Time series during 2003–12 of (a) frequency of Argo profiles with BLT > 10 dbar and (b) BLT from Argo profiles with BLT > 10 dbar, averaged in January–March in the SSS front in the northern box. Vertical bars in (a) and (b) indicate the 95% confidence interval based on the standard deviation of 3-month values of each year and from Argo profiles with BLT > 10 dbar during 3 months of each year, respectively. (c),(d) As in (a) and (b), but for July–September in the southern box.

In the northern box, the winter BL frequency was positively correlated with the intensity of the winter SSS front (R = 0.63), while the winter BLT was highly correlated with the winter ILD (R = 0.74; Figs. 17a,b). The former relationship means that when the SSS front is strong, the effect of Ekman advection in the surface process AEk is large, facilitating the tilting of the SSS front. The latter indicates that thick BLs tend to be formed when the isothermal layers are deep, which agrees with the seasonality of BLs.

Fig. 17.

Time series during 2003–12 of (a) meridional MLS gradient magnitude from MOAA_GPV and (b) ILD from Argo profiles, averaged in January–March in the SSS front in the northern box. Vertical bars in (a) and (b) indicate the 95% confidence interval based on the standard deviation of 3-month values of each year and from Argo profiles during 3 months of each year, respectively. (c),(d) As in (a) and (b), but for July–September in the southern box.

Fig. 17.

Time series during 2003–12 of (a) meridional MLS gradient magnitude from MOAA_GPV and (b) ILD from Argo profiles, averaged in January–March in the SSS front in the northern box. Vertical bars in (a) and (b) indicate the 95% confidence interval based on the standard deviation of 3-month values of each year and from Argo profiles during 3 months of each year, respectively. (c),(d) As in (a) and (b), but for July–September in the southern box.

These interannual variations were likely to be related to the Pacific decadal oscillation (PDO; Mantua et al. 1997; Fig. 18). The winter BL frequency was highly correlated with the PDO index with a lag of 1 yr (R = 0.81; Fig. 18b). The intensity of the SSS front also showed a positive correlation with the PDO index (R = 0.72; Fig. 18b), implying that the interannual variation of winter BL frequency in the northern box may reflect the PDO-related variation of the SSS front. This PDO-related variation of the SSS front may be related to that of SSS in the NPTW formation region (Katsura et al. 2013). On the other hand, both winter BLT and winter ILD were negatively correlated with the PDO index (R = −0.62 and −0.66 with a lag of 1 yr; Fig. 18c). In addition, τx in the northern box where the northeasterly trade wind is dominant was negative and showed a positive correlation with the PDO index (R = 0.59; Figs. 19a,b). This is consistent with Carton et al. (2008), who demonstrated that winter ILD in the subtropical North Pacific tended to be small in association with weakening of the trade winds during the warm phase of the PDO.

Fig. 18.

(a) Time series of the PDO index, averaged in January–March. The PDO index is from the University of Washington website (http://jisao.washington.edu/pdo/PDO.latest). (b) Lag correlations between the PDO index and frequency of Argo profiles with BLT > 10 dbar, averaged in January–March in the SSS front in the northern box (thick curve) and meridional MLS gradient magnitude from MOAA_GPV in the northern box (thin curve). (c) Lag correlations between the PDO index and BLT from Argo profiles with BLT > 10 dbar (thick curve) and ILD from Argo profiles (thin curve), averaged in January–March in the SSS front in the northern box. A positive lag in (b) and (c) indicates that the PDO index leads. Horizontal dashed lines in (b) and (c) indicate 95% confidence value of noncorrelation test based on t distribution (R = 0.63).

Fig. 18.

(a) Time series of the PDO index, averaged in January–March. The PDO index is from the University of Washington website (http://jisao.washington.edu/pdo/PDO.latest). (b) Lag correlations between the PDO index and frequency of Argo profiles with BLT > 10 dbar, averaged in January–March in the SSS front in the northern box (thick curve) and meridional MLS gradient magnitude from MOAA_GPV in the northern box (thin curve). (c) Lag correlations between the PDO index and BLT from Argo profiles with BLT > 10 dbar (thick curve) and ILD from Argo profiles (thin curve), averaged in January–March in the SSS front in the northern box. A positive lag in (b) and (c) indicates that the PDO index leads. Horizontal dashed lines in (b) and (c) indicate 95% confidence value of noncorrelation test based on t distribution (R = 0.63).

Fig. 19.

(a),(c) Distribution of wind stress during 2003–12 averaged in January–March in the North Pacific in (a) and in July–September in the South Pacific in (c). (b),(d) Time series during 2003–12 of zonal wind stress averaged in January–March in the northern box in (b) and in July–September in the southern box in (d). Vertical bars indicate the 95% confidence interval based on the standard deviation of 3-month values of each year.

Fig. 19.

(a),(c) Distribution of wind stress during 2003–12 averaged in January–March in the North Pacific in (a) and in July–September in the South Pacific in (c). (b),(d) Time series during 2003–12 of zonal wind stress averaged in January–March in the northern box in (b) and in July–September in the southern box in (d). Vertical bars indicate the 95% confidence interval based on the standard deviation of 3-month values of each year.

In the southern box, both winter BLT and BL frequency showed positive correlations with winter ILD (R = 0.90 and 0.60, respectively; Fig. 17d), as the seasonality of BLs. On the other hand, winter BL frequency was little correlated with the intensity of the winter SSS front (R = −0.08; Figs. 17c). The interannual variation of winter BLs in the southern box reflected that of ILD rather than the intensity of the winter SSS front.

Winter BLT and ILD were negatively correlated with the Niño-3 index (R = −0.31 and −0.49; Fig. 20c). This is consistent with Carton et al. (2008), demonstrating that ILD tended to be small (large) in the subtropical South Pacific during El Niño (La Niña) events. In the southern box where the southeasterly trade wind is dominant, τx showed a positive correlation with the Niño-3 index (R = 0.53; Figs. 19c,d), as previous studies demonstrated that the trade wind is stronger during La Niña events (e.g., Wang and McPhaden 2000). Thus, the interannual variation of winter BLs in the southern box may be affected by the ENSO through the intensity of easterly trade wind controlling winter ILD.

Fig. 20.

(a) Time series of the Niño-3 index, averaged in July–September. The Niño-3 index is from the Japan Meteorological Agency website (http://www.data.jma.go.jp/gmd/cpd/data/elnino/index/nino3idx.html). (b) Lag correlations between the annual mean of the Niño-3 index and frequency of Argo profiles with BLT > 10 dbar, averaged in July–September in the SSS front in the southern box (thick curve) and meridional MLS gradient magnitude from MOAA_GPV in the southern box (thin curve). (c) Lag correlations between the annual mean of the Niño-3 index and BLT from Argo profiles with BLT > 10 dbar (thick curve) and ILD from Argo profiles (thin curve), averaged in the SSS front in the southern box. A positive lag in (b) and (c) indicates that the Niño-3 index leads. Horizontal dashed lines in (b) and (c) indicate 95% confidence value of noncorrelation test based on t distribution (R = 0.63).

Fig. 20.

(a) Time series of the Niño-3 index, averaged in July–September. The Niño-3 index is from the Japan Meteorological Agency website (http://www.data.jma.go.jp/gmd/cpd/data/elnino/index/nino3idx.html). (b) Lag correlations between the annual mean of the Niño-3 index and frequency of Argo profiles with BLT > 10 dbar, averaged in July–September in the SSS front in the southern box (thick curve) and meridional MLS gradient magnitude from MOAA_GPV in the southern box (thin curve). (c) Lag correlations between the annual mean of the Niño-3 index and BLT from Argo profiles with BLT > 10 dbar (thick curve) and ILD from Argo profiles (thin curve), averaged in the SSS front in the southern box. A positive lag in (b) and (c) indicates that the Niño-3 index leads. Horizontal dashed lines in (b) and (c) indicate 95% confidence value of noncorrelation test based on t distribution (R = 0.63).

6. Summary and discussion

Seasonal and interannual variations and formation mechanisms of BLs in the subtropical North and South Pacific have been investigated by using Argo profiles, MOAA_GPV gridded Argo data, and the various surface flux data in 2003–12 and hydrographic section data from the World Ocean Circulation Experiment Hydrographic Programme. BLs lying within the SSS fronts located on the equator side of SSS maxima were thickest and most frequent in winter, although they were observed by only about 35% of Argo profiles even in winter. In addition, a temporal scale of BLs was shorter than 10 days. These features indicated that BLs in the subtropical Pacific are a transient phenomenon with small spatial scale.

To clarify the formation mechanisms of BLs in the subtropical Pacific, surface and subsurface processes suggested by previous studies were evaluated. Poleward Ekman advection of fresher water was dominant as the surface freshening process but cannot sufficiently explain the seasonality of BLs, particularly in the South Pacific. Subduction of tropical waters has been considered as the subsurface salinification process, but the dissolved oxygen was saturated coherently within BLs, and the core of subducted tropical waters was too deep to intrude into the lower part of isothermal layers to form BLs. These facts suggested that BLs in the subtropical Pacific are formed primarily through the tilting of the meridional SSS front due to a vertical shear of meridional velocity. This idea was supported by the dominant contribution of the meridional SSS gradient to the meridional sea surface density gradient and the correspondence between the seasonal variations of BLs and ILD.

Interannual variation of BLs showed that thicker BLs tended to be distributed sparsely in the North Pacific, while they tended to be distributed densely in the South Pacific. In the North Pacific, winter BL frequency and BLT were related to the PDO through the intensity of the SSS front and ILD, respectively. On the other hand, interannual variation of winter BLT in the South Pacific was related to that of winter ILD controlled by the ENSO-related easterly trade wind.

This study revealed that the temporal scale of BLs in the subtropical Pacific is shorter than 10 days. It may be related to the variation of poleward fresher surface water transport, considering that the time scale of 12–25 days for the BLs in the western equatorial Pacific was related to the variation in zonal advection of fresher surface water due to westerly wind burst (Sprintall and McPhaden 1994). On the other hand, Mignot et al. (2009) suggested that the high porosity of BLs in the subtropical Pacific is a manifestation of the importance of mesoscale or turbulent processes in the BL formation. Mesoscale and submesoscale eddies may contribute to BL formation in the subtropical Pacific by causing a vertical shear of velocity and meander of the SSS front, hence evoking its tilting. Unfortunately, spatial resolution of Argo profiles is not sufficient to investigate their effects. Observations from SMOS/Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) and Satelite de Aplicaciones Cientificas-D, (SAC-D)/Aquarius satellites, which can detect a correspondence between small-scale structure of SSS fronts and BLs in combination with Argo profiles, and high-resolution ocean general circulation models may be powerful tools. Our analysis also indicated that the subduction of tropical waters is not essential for the formation of BLs in the subtropical Pacific. Sprintall and Tomczak (1992) suggested that the subduction of tropical waters may play an important role in the maintenance of the BL in the tropical region, particularly in the Atlantic where the existence of the BL cannot be explained only by precipitation. The relationship between BLs in the tropical region and the subduction of tropical waters has not been investigated sufficiently. Such studies are needed for understanding of not only the formation mechanism of the BL but also its role in air–sea interaction in the tropical region.

Acknowledgments

The authors are thankful for comments from Frederick M. Bingham, Meghan F. Cronin, Shinya Kouketsu, Ichiro Yasuda, Yutaka Yoshikawa, participants at the “Research Meetings on Air–Sea Interaction” in 2013 held as a part of the Collaborative Research Program of Hydrospheric Atmospheric Research Center, Nagoya University, and two anonymous reviewers. They also thank Kana Nakamoto for her assistance in preparing Argo float data. SK is a research fellow of the Japan Society for the Promotion of Science and supported by the Japan Society for the Promotion of Science (KAKENHI; Grant Number 15J05210). EO is supported by the Japan Society for Promotion of Science (KAKENHI; Grant-in-Aid for Scientific Research (B), 25287118) and the Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT; Grant-in-Aid for Scientific Research on Innovative Areas under Grants 22106007 and 25121502). The Argo float data used in this study were collected and made freely available by the International Argo Project and the national programs that contribute to it (http://www.argo.ucsd.edu; http://www.jcommops.org/argo). Argo is a pilot program of the Global Ocean Observing System.

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Footnotes

1

Based on t distribution, a correlation for sample size N = 10 is significant on 90% and 95% confidence when the magnitude of R is larger than 0.55 and 0.63, respectively (Fisher 1950).