Opposing trends of the Subantarctic Mode Water thickness in the South Indian Ocean driven by atmospheric forcing and interior mixing

doi:10.21203/rs.3.rs-2010099/v1

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Opposing trends of the Subantarctic Mode Water thickness in the South Indian Ocean driven by atmospheric forcing and interior mixing

https://doi.org/10.21203/rs.3.rs-2010099/v1

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Formation and subduction of Subantarctic Mode Water (SAMW) contributes to the upper cell of the Southern Ocean overturning circulation and transports anthropogenic heat and carbon into the ocean interior. Understanding of the processes driving change in SAMW is therefore needed to assess the ocean’s capacity to store heat and carbon. An analysis of Argo data reveals that the SAMW thickness increased in the eastern subduction area of the South Indian Ocean (SIO) during 2005−2020, and decreased in the central SIO outside the subduction area. The increasing and decreasing trends of SAMW thickness are driven by enhanced subduction and by erosion through mixing with warmer overlying waters, respectively. The changes in SAMW subduction reflect changes in air-sea exchange. Trends in winter sea level pressure associated with an amplification of the winter atmospheric zonal wave 3 pattern caused increased equatorward flow and marine cold air outbreaks in the eastern SIO, driving larger ocean heat loss, deeper mixed layers, and stronger subduction by lateral induction. SAMW subducts beneath lighter waters that warmed during the 2005−2020 period. Mixing with the warmer overlying water eroded the upper part of the SAMW layer, causing deepening of the SAMW low potential vorticity core, and thinning of the SAMW in the central SIO. These results demonstrate that both anomalous meridional atmospheric circulation and erosion by interior mixing influence the thickness, and hence heat and carbon storage capacity, of the SAMW.

Subantarctic mode water

Thickness variations

Subduction

Mixing

South Indian Ocean

A mode water is defined as a volume of water with nearly homogeneous physical properties between the seasonal and permanent pycnoclines, covering an extended area in a given basin (Hanawa and Talley 2001). Mode waters are formed by deep convection in winter and therefore are vertically well mixed and characterized by low potential vorticity (PV). The Subantarctic Mode Water (SAMW) forms within the Subantarctic Zone, when surface cooling in winter produces deep surface mixed layers north of the Subantarctic Front (McCartney 1979). SAMW spreads equatorward from the formation zone to ventilate the thermocline. The subduction and export of SAMW makes a dominant contribution to ocean uptake and storage of heat and carbon dioxide (Sabine et al. 2004; Sallée et al. 2013; Armour et al. 2016; DeVries et al. 2017; Kolodziejczyk et al. 2019).

The ocean, through its very high heat storage capacity, regulates the rate of warming in response to increasing concentrations of greenhouse gases in the atmosphere (Marshall et al. 2015; Saurral et al. 2019). The marked increase in upper ocean (0−2000 m) heat content in recent decades ((Delworth et al. 2005; Levitus et al. 2012; Long et al. 2014) is dominated by increased heat storage in the southern hemisphere (Roemmich et al. 2015), particularly in SAMW (Gao et al. 2018). The increase in heat storage by SAMW is driven largely by an increase in the volume of the SAMW layer, rather than changes in the temperature of SAMW (Gao et al. 2018; Kolodziejczyk et al. 2019).

Before the 2000s, observations of temperature and salinity in the Southern Ocean were insufficient to quantify the spatial and temporal variability of SAMW volume and subduction. Near-global coverage by Argo floats has revealed that most of the ocean warming in the past decade occurred in the Southern Hemisphere, closely associated with changes in SAMW in the southern Pacific and Indian Ocean (Roemmich et al. 2015; Hakkinen et al. 2016; Llovel and Terray 2016; DeVries et al. 2017; Gao et al. 2018; Kolodziejczyk et al. 2019; Portela et al. 2020). Most earlier studies have focused on thickness and volume variations of SAMW, revealing differences in the spatial pattern of interannual and decadal SAMW variability within each basin (Gao et al. 2018; Meijers et al. 2019; Portela et al. 2020; Cerovečki and Meijers 2021). The SAMW thickness exhibits an out–of–phase pattern in the southwest and southeast of both Indian and Pacific sectors (Meijers et al. 2019; Cerovečki and Meijers 2021). Gao et al. (2018) found the volume of SAMW significantly increased (4.7 ± 0.4 × 10¹³ m³ year^− 1) across the Southern Hemisphere ocean from 2005 to 2015. Qu et al. (2020) found that the circumpolar subduction rate of SAMW increased during the Argo period, which contributed to the observed increase in the SAMW volume. Some recent studies have shown a loss (3.2 ± 2.1 × 10¹³ m³ year^− 1) in SAMW volume in the South Indian Ocean (SIO) over the period 2004–2018 (Hong et al. 2020). This volume loss of SAMW in the SIO was explained by the decreased subduction in the SIO (Hong et al. 2020; Zhang et al. 2021). However, the reduction in subduction does not fully explain the volume reduction of SAMW in the SIO. This implies the existence of other forcing mechanisms influencing the volume of SAMW.

Subduction is defined as the volume flux of water transferred from the winter mixed layer to the permanent pycnocline per unit area (Williams 1991; Qiu and Huang 1995). The subduction process directly links the mode water to atmospheric forcing (Woods 1985; Marshall et al. 1993). After subduction, SAMW follows one of three pathways to the interior of the SIO: the first one is just southwest of Australia, the second one is along the coast of South Australia, the last one is across the South Australia Basin, and all eventually enter the subtropical gyre (Middleton and Bye 2007; Fine et al. 2008; Koch-Larrouy et al. 2010). The SAMW in the ocean interior is no longer directly linked to the atmosphere forcing at this time (where by “the ocean interior” we mean the area occupied by SAMW in the central SIO that lies outside of the SAMW subduction area). Given that different physical processes can drive changes in SAMW volume in the formation region and in the ocean interior, it is useful to consider volume changes in each of these two regions. This study aims to quantify changes in SAMW volume in both the formation regions and in the ocean interior, and to identify the drivers of the observed volume changes. The first goal of this study is to quantify changes in SAMW volume in the subduction area during 2005−2020 and to determine the contribution of subduction to the observed changes in SAMW volume. The second goal is to explore the influence of erosion of SAMW by diapycnal mixing in the ocean interior, where by erosion we refer to loss of volume by mixing across the upper or lower boundaries of the low PV pool that defines the SAMW. In this study, we focus on changes in the thickness and volume of the low PV pool representing the SAMW (rather than changes in isopycnal layers). The paper is organized as follows: Section 2 describes the data and methods used. The interannual variability and trend of the SAMW subduction rate and volume is examined in Section 3. The mechanisms that give rise to the spatial pattern of SAMW thickness trends are identified in Section 4. Discussion and conclusions are provided in Section 5.

2.1 Observations and atmospheric fields

We use the gridded Argo product created by optimally interpolating quality-controlled Argo profiles onto a 1°×1° horizontal grid with 58 non-uniformly spaced vertical levels and monthly resolution during 2005−2020 (Roemmich and Gilson 2009). Many previous studies have used this gridded Argo data set for mode water research (Drushka et al. 2014; Cerovečki and Meijers 2021; Li et al. 2021; Zhang et al. 2021). Atmospheric fields including sea level pressure (SLP), wind velocity, sea surface temperature (SST), geopotential height, potential temperature and air-sea heat fluxes were obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (Hersbach et al. 2020), hereafter referred to as ERA5, focusing on the Argo period (2005−2020). These atmosphere reanalysis fields are able to accurately capture the year-to-year variability and have been used in many studies of SAMW in the Southern Ocean (Meijers et al. 2019; Tamsitt et al. 2020; Cerovečki and Meijers 2021).

2.2 Annual subduction rate

Subduction rate is defined as the volume of mixed layer water entering the thermocline (Woods 1985; Qiu and Huang 1995). Several model and observational studies separated the mean and eddy velocities in their subduction estimates (Kwon 2013; Portela et al. 2020). However, the eddy-induced subduction depends strongly on the choice of eddy-diffusion coefficient and the results obtained with different coefficients vary greatly (Sallée and Rintoul 2011; Hiraike et al. 2016; Langlais et al. 2017). Li et al. (2021) show that the mean flow can also reflect the change in subduction very well. Thus, we exclude the role of eddies in this study and focus on the subduction induced by geostrophic mean flow. We calculated the annual subduction rate, S_ann, following the methodology proposed by Woods (1985) and used in many subsequent studies (Woods 1985; Qiu and Huang 1995; Qu et al. 2020; Li et al. 2021; Jiang et al. 2022):

$${S}_{\text{ann}}=-\overline{({w}_{ek}-\frac{\beta }{f}{\int }_{\text{-}{\text{h}}_{m}}^{0}\text{v dz}\text{)}}+\frac{1}{T}({h}_{m,0}-{h}_{m,1})$$

where w_ek is the Ekman pumping velocity, f is the planetary vorticity, v is the meridional velocity and β is the gradient of the planetary vorticity. We released particles at the base of the mixed layer in September at each horizontal grid point of the 1°×1° gridded Argo product and tracked them in a Lagrangian framework for T = 1 year with a time interval of 10 days. Following Sallée et al. (2010), the geostrophic current at the mixed layer base is calculated from Argo data using a reference pressure of 1500 dbar. h_m,0 denotes the mixed layer depth (MLD) at the release location in September; h_m,1 is the MLD at the location reached in the following September, after one year of drift. The overbar indicates an average over a year along a Lagrangian trajectory. The first term on the right-hand side of Eq. (1) is the contribution from Ekman pumping and the second term represents the contribution from lateral induction arising from horizontal flow across the sloping base of the mixed layer.

2.3 Definition of the mixed layer depth and Ekman heat flux

We defined the MLD using a density threshold increase of Δ_σθ = 0.03 kg m⁻³ from the value at 10 m depth, which was found to provide optimal estimates of the MLD in the Southern Ocean (de Boyer Montégut et al. 2004). Northward Ekman transport of cold Antarctic surface water, driven by the westerly wind, would help to increase the MLD in the SAMW formation regions by cooling the mixed layer (Sallée et al. 2008; Holte et al. 2012). Following Sallée et al. (2010), the integrated Ekman heat flux E_t was given by E_t = ρ_m C_p (U_E ▽ T_m), where ρ_m is the density of the water in the mixed layer, C_p is the specific heat capacity, ▽ is the gradient operator and U_E is the Ekman transport. T_m is mixed layer temperature.

2.4 Definition of the SAMW

The SAMW thickness is determined from vertical profiles of PV. SAMW is formed by deep convection and therefore is well mixed in the vertical and coincides with low PV. The low PV layer provides an excellent tracer of the spread of SAMW into the interior, as PV tends to be conserved away from the sea surface (McCartney 1979). Here PV is defined as $-\frac{f}{\rho }\frac{d\rho }{dz}$, where ρ is the seawater potential density, ρ = σ₀ + 1000 kg m⁻³. Following earlier studies (McDonagh et al. 2005; Hasson et al. 2012; Hong et al. 2020), we define the SAMW in the SIO as water with PV lower than 0.5×10⁻¹⁰ m⁻¹ s⁻¹ and density in the range σ₀ = 26.6−26.9 kg m⁻³. We exclude the water that conforms to the definition of SAMW but is separate from the main body of SAMW when calculating the SAMW volume. This volume of water has the same physical properties as SAMW, but is small and far from the main body of SAMW, and the water body exists for a very short time, usually only one month.

2.5 Definition of the marine cold air outbreaks

Marine cold air outbreaks (MCAO) refer to large-scale advection of cold air over a relatively warm ocean surface, which is often associated with severe mesoscale weather phenomena and polar lows (Carleton and Song 1997; Rasmussen 2003). Although many mesoscale weather systems are too small in size to be represented explicitly in reanalysis data, the larger-scale features of MCAO can help reveal the influence of cold air advection on air-sea heat flux changes. The MCAO index, M, is given by Bracegirdle and Kolstad (2010) as

$$M=\frac{L}{{Z}_{700}}\left(ln{\theta }_{SKT}-ln{\theta }_{700}\right)$$

where L is a scaling height of 7.5 ×10⁵ m; Z₇₀₀ and θ₇₀₀ are the geopotential height and the potential temperature at 700 hPa, respectively. θ_SKT = T_SK (p₀/p_sl) ^R/cp, is the potential skin temperature, where T_SK is the skin temperature (SST over open ocean), R is specific gas constant, c_p is specific heat capacity of air, p₀ is 1000 hPa, and p_sl is the SLP.

3.1 Climatological characteristics of SAMW subduction rate and volume

Long-term mean characteristics of the study area associated with subduction in the SIO are shown in Fig. 1. The pattern of the long-term mean annual subduction rate (Fig. 1a) is similar to earlier studies (Liu and Wu 2012; Qu et al. 2020). High subduction rates (> 100 m year^− 1) are concentrated in the Southeast Indian Ocean (south of Australia). We define the area between the 26.6 and 26.9 kg m⁻³ isopycnal outcrops in winter and 20°E−150°E as the subduction area, and further define the region between the 26.6 and 26.9 kg m⁻³ isopycnal outcrops in winter and 90°E−150°E as the core subduction area (black box in Fig. 1a). Integrating over the density range 26.6−26.9 kg m⁻³ between 20° and 150°E, the mean volumetric subduction rate is 23.1 Sv (1 Sv = 10⁶ m³ s⁻¹) during 2005−2020. This result is consistent with the assessment of 21 Sv in the density range of 26.5–27.1 kg m⁻³ (Zhang et al. 2021). The SAMW layer is thickest (> 400 m) where subduction is largest and thins as it spreads laterally from the high-latitude subduction regions to lower latitudes (Fig. 1b). The thickness of the SAMW is defined as the difference in depth of the upper and lower boundaries of the low PV pool (defined as PV < 0.5 × 10⁻¹⁰ m⁻¹ s⁻¹, shown by the green line in Fig. 1c).

3.2 Interannual variability and trends

We also examined the volume of newly formed SAMW in the subduction area. Following the methodology of Davis et al. (2011), the volume of newly formed SAMW over a year was approximated as the difference between the maximum volume reached at the end of the austral winter-spring formation season and the minimum volume from the previous year. In the SIO subduction zone, the long-term mean annual volume formation is 1.02×10¹⁵ m³ (32.3 Sv). The annual subduction therefore accounts for approximately 72% of the annual volume change of the SAMW in the subduction area, consistent with previous findings (Qu et al. 2020; Li et al. 2021). Detrended variations in the volume of newly formed SAMW are well correlated with variations in the subduction rate (correlation coefficient of 0.77, statistically significant at the 95% confidence level) (Fig. 2). The interannual variability in volume of newly formed SAMW can be explained by interannual variability in the subduction rate, in agreement with (Qu et al. 2020). This suggests that the trend in SAMW volume in the formation region can also be explained by the trend in subduction rate (Qu et al. 2020; Zhang et al. 2021).

The SAMW volumetric subduction rate trend shows clear regional differences (Fig. 3a). Significantly enhanced subduction occurs in the core subduction area south of Australia (110°−150°E), while there is a reduced trend in the central basin (90°−110°E) (Fig. 3a). The subduction rate in the core subduction area (90°−150°E) shows an overall increasing trend of 0.26 ± 0.20 Sv year⁻² at the 95% confidence level (Fig. 3a). The SAMW thickness also exhibits an increasing trend in the subduction area between 90° and 150°E, with a spatial pattern that is consistent with the trend in subduction rate (Fig. 3b). In the SAMW core subduction area, the volume of SAMW increases at a rate of 1.18 ± 0.77×10¹³ m³ year⁻¹ at a 95% confidence level (Fig. 3c). The enhanced subduction (0.82 ± 0.63 ×10¹³ m³ year⁻¹) accounts for approximately 70% of the volume increase of the SAMW in the core subduction area. In contrast, outside the subduction area (indicated by a blue box in Fig. 3b), a significant decreasing trend of the SAMW thickness is identified in the SIO (Fig. 3c). The decreasing trend of volume reaches −3.34 ± 0.27×10¹³ m³ year⁻¹ (−1.06 ± 0.09 Sv year⁻¹) at the 95% confidence level. Although there is a reduced trend (−0.11 ± 0.05 Sv year⁻¹) in the subduction in the central basin (90°−110°E), it cannot explain the volume reduction of the SAMW (−1.06 ± 0.09 Sv year⁻¹) outside the subduction area (blue box in Fig. 3b). This result suggests that mechanisms other than subduction control the volume of SAMW outside the subduction area.

4.1 Forcing mechanisms in the subduction area

The results described in Section 3 suggest that the increasing trend in SAMW volume in the subduction area could be caused by enhanced subduction. The trend of September MLD (Fig. 4a) shows a similar pattern to that of subduction (Fig. 3a). This indicates changes in mixed layer depth are linked to changes in subduction of SAMW, which is consistent with previous studies (Qu et al. 2020; Zhang et al. 2021). The wind stress curl shows an increasing trend (Fig. 4b), associated with enhanced vertical pumping during 2005−2020. The enhancement of subduction is dominated by the lateral induction (79%) associated with deepening of the winter mixed layer (Fig. 4a). Next we attempted to identify the drivers of trends in the mixed layer depth in the SIO. Atmospheric forcing (wind, heat flux and freshwater flux) drives vertical mixing of the upper ocean. Wind-induced mixing plays an important role in the development of mixed layer depth in summer, while its contribution is relatively weak in winter (Dong et al. 2008). Recent studies have found that air-sea heat fluxes and horizontal Ekman heat transport make the dominant contribution to variability in MLD in the SIO, and that the contribution of freshwater flux is weak in the Indian sector of the Southern Ocean (Downes et al. 2017; Köhler et al. 2018). Hence, we consider variability in surface air-sea heat fluxes and Ekman heat transport in winter (July, August and September, JAS), when SAMW is formed. Winter mean westerly wind shows an increasing trend in the region south of Australia during 2005−2020 (Fig. 5a). Stronger westerlies south of Australia increased the Ekman transport of cold water from the south, cooling and deepening the winter mixed layer (Fig. 5b). Air-sea heat flux in winter also shows a decreasing trend (i.e., larger ocean heat loss) in the region south of Australia (Fig. 5c). In the same area, ocean heat loss by Ekman heat transport and air-sea exchange both increased at the trend of −0.96 ± 0.62 W m⁻² year⁻¹ and −1.43 ± 1.02 W m⁻² year⁻¹, respectively, at the 95% confidence level. The correlation of detrended winter mean MLD anomalies with anomalies in Ekman heat transport and air-sea heat flux is −0.65 and −0.57, respectively, and both satisfy the 95% confidence level. These results indicate that variability in wintertime mixed layer depth is associated with changes in both Ekman heat transport and air-sea heat exchange.

The analysis above confirms that air-sea heat fluxes are important in modulating the MLD (Dong et al. 2008; Hong et al. 2020). What, then, controls the variability and trend of the air-sea heat fluxes in this region? Recent studies based on the Southern Ocean Flux Station (SOFS) mooring south of Australia have found that extreme turbulent heat loss events are associated with cold air flowing from higher southern latitudes (Schulz et al. 2012; Tamsitt et al. 2020). Atmospheric reanalysis data suggest that the frequency of MCAO in the SIO has changed over the period from 2005 to 2020. Figure 5d shows an increasing trend of wintertime MCAO (0.017 ± 0.008 year⁻¹ at the 95% confidence) in the region south of Australia. The correlation coefficient between the detrended winter mean MCAO anomaly and detrended winter mean air-sea heat flux anomaly reaches −0.92 at the 95% confidence level. Thus, a prime driver of increasing air-sea heat loss south of Australia is increasing advection of cold air, increasing the temperature difference between air and ocean.

Tamsitt et al. (2020) and Cerovečki and Meijers (2021) showed that the interannual variability of wintertime MLD is strongly correlated with the interannual variability of wintertime SLP. Next we examine the relationship between wintertime SLP and subduction in the SIO. The correlation of annual subduction rate in the core subduction area with wintertime averaged SLP resembles a zonal wavenumber 3 (ZW3) pattern (Cai et al. 1999; Raphael 2004; Schlosser et al. 2018), suggesting the variability of subduction rate is closely related to the ZW3 atmospheric mode (Fig. 6a). ZW3 is an important asymmetric part of the large scale atmospheric circulation, characterized by three high and three low-pressure centers around the Southern Hemisphere extratropics (Cai et al. 1999). Previous studies have shown that ZW3 is tightly associated with the meridional flow in the extratropical Southern Hemisphere, which has significant impacts on meridional heat transport (Raphael 2004). Figure 6b shows a composite of trends during the period 2005−2020 of wintertime SLP, wind and MCAO. The trend of winter (JAS) mean SLP during 2005−2020 shows a ZW3-like pattern, and deepening of the polar lows south of Australia and South Africa and an increase in SLP in the central SIO (Fig. 6b). Notably, the MCAO trend is consistent with the trend in the meridional wind, with northward wind anomalies co-located with larger MCAO, and vice-versa. This result indicates that anomalous meridional atmospheric circulation associated with a circumpolar pressure anomaly with a ZW3 pattern, and the corresponding enhancement or weakening of wintertime ocean heat loss through the transport of more or less cold air and cold water, plays a central role in the observed opposing trends of SAMW subduction in the central and eastern SIO.

4.2 Mechanisms of SAMW variation outside the subduction area

As mentioned above, the SAMW subduction shows an increasing trend that drives corresponding increases in thickness in the subduction area (Fig. 3a). In contrast, a strong thinning trend is observed outside the subduction areas (Figs. 3b). What, then, controls the variability and trend in SAMW thickness outside the subduction area? Earlier studies investigated the volume changes of the SAMW by examining depth changes in isopycnals representing the SAMW boundary (Kolodziejczyk et al. 2019; Meijers et al. 2019; Portela et al. 2020; Zhang et al. 2021). In this study, we focus on the volume change in SAMW, where the SAMW pool is defined by water with PV < 0.5×10⁻¹⁰ m⁻¹ s⁻¹. Changes in thickness of SAMW therefore reflect changes in the distribution of PV contours that mark the upper and lower boundary of the SAMW layer (Fig. 1c). The PV contour defining the upper boundary of the SAMW pool deepened between 60° and 100°E outside the subduction area and shoaled between 100° E and 150°E in the core subduction area (Fig. 7a), while the depth of the lower boundary did not change much (Fig. 7b). The thickness trends in (outside) the subduction area therefore reflect changes in depth of the PV contour defining the upper boundary of the SAMW pool. We choose the 35°S band to investigate SAMW thickness variability in the ocean interior, away from the subduction region (Fig. 7c). Above the upper boundary of the SAMW, the water warms, becomes less dense, and the 0.5×10⁻¹⁰ m⁻¹ s⁻¹ PV contour deepens. In locations where warming of the water overlying SAMW is less obvious (e.g., between 100°E and 140°E), the depth of the PV boundary does not change. West of 100°E, the upper 200 m of the water column warmed significantly in the mid-latitudes of the SIO (Fig. 7d). Changes in depth of the upper boundary may therefore be linked to changes in the temperature of the water above SAMW, where the strongest warming occurs. Warming of the overlying water increases the stratification, hence PV, at the upper boundary of the SAMW. Our results indicate that erosion of SAMW through mixing with overlying water that is warmer and higher in PV causes the PV contour defining the top of the SAMW layer to descend, reducing the thickness of the SAMW layer in the interior of the SIO.

The focus of our study has been on the drivers of trends in SAMW thickness, volume and subduction in the SIO over the past 15 years. Two distinct areas are found with opposing trends of SAMW thickness: an increase in the eastern subduction area of the SIO and a decrease in the central SIO outside the subduction area. In the SAMW core subduction area of the SIO, the increasing trend in volume reaches 1.18 ± 0.77×10¹³ m³ year⁻¹ at the 95% confidence level. Outside the SAMW subduction area, the decreasing trend of volume reaches −3.34 ± 0.27×10¹³ m³ year⁻¹ at the 95% confidence level. We find that trends of different sign in the formation region south of Australia and in the central part of the basin are linked to different processes: increased volume in the formation region is the result of stronger subduction, in turn linked to anomalous atmospheric forcing, while decreases in volume in the central SIO reflect erosion of the low vorticity signature of SAMW by mixing with warmer, more stratified water above.

Several other recent studies have exploited the unprecedented coverage in space and time of the Argo data set to explore the variability of SAMW (Gao et al. 2018; Kolodziejczyk et al. 2019; Hong et al. 2020; Qu et al. 2020; Cerovečki and Meijers 2021; Xu et al. 2021). From our work and these recent studies, a common view is beginning to emerge. The thickness and volume of SAMW have displayed interannual variability and apparent trends during the Argo period. The strongest variability is observed in the Indian and Pacific basins, where the mode water pool is well developed in comparison to the Atlantic. Both the interannual variability and longer-term trends can be linked to changes in wind forcing and its impact on air-sea heat loss, mixed layer depth, and subduction by lateral induction (Qu et al. 2020; Zhang et al. 2021). The increasing trend in SAMW subduction rate is closely connected to wintertime atmospheric surface pressure anomalies, as found by earlier studies (Hong et al. 2020; Cerovečki and Meijers 2021). While different studies have emphasized links to different modes of climate variability, such as the SAM (Meijers et al. 2019; Qu et al. 2020; Zhang et al. 2021) and ENSO (Meijers et al. 2019), they arrive at a common understanding of how wind influences mixed layer depth and SAMW subduction. Stronger meridional winds intensify mixed layer heat loss and deepen the wintertime mixed layer, causing an increase in formation of the SAMW (Tamsitt et al. 2020; Cerovečki and Meijers 2021). The MCAO provides a useful index of the strength and frequency of cold-air outbreaks associated with anomalies in meridional wind. We find the MCAO index has a positive trend over the period considered. The results of our study find the increasing trends in SAMW subduction rate are closely connected to wintertime atmospheric surface pressure anomalies and corresponding westerly winds and MCAO. This variability of the wintertime SLP is shown to be associated with the ZW3 pattern, resulting in a strong enhancement of wintertime surface ocean heat loss anomalies and MLD anomalies in the subduction area south of Australia. Our results provide further evidence that changes in wind associated with changes in ZW3 have driven increasing trends in subduction, through changes in the influence of meridional winds on air-sea heat exchange, and of zonal winds on Ekman heat transport.

Our analysis suggests that different physical processes are responsible for the contrasting trends in SAMW volume in the two regions. In the formation region, increased subduction explains the increase in volume, as found by earlier authors (e.g. Qu et al., 2020; Li et al., 2021). The thinning of the SAMW in the ocean interior, however, cannot be explained by changes in subduction. Instead, we find that the thinning of the SAMW can be explained by mixing across the upper boundary of the SAMW layer. Water overlying SAMW at lower latitudes warmed during the Argo era as a result of increased flow of warm waters from the western Pacific via the Indonesian Throughflow (Zhang et al. 2018; Vidya et al. 2020). The warming increased the potential vorticity at the upper boundary of the SAMW pool. Here we relate the thinning of the SAMW thickness to erosion caused by mixing with the warmer, higher PV water above. The decrease in thickness in the central of the SIO is dominated by deepening of the PV contour defining the upper boundary of the SAMW layer; this deepening is large where warming of the overlying water is large, and weak where there is little change in temperature of the overlying water. While other studies have highlighted how diapycnal transformation can transfer mass between different density classes within SAMW (Portela et al. 2020), here we emphasize how increases in PV at the boundary of the SAMW pool can result in erosion through mixing and a loss of volume of low-PV SAMW. Taken together, our results and those from the recent studies cited above provide a powerful illustration of how Argo is contributing to deeper understanding of the drivers of ocean variability relevant to climate.

Acknowledgments

This work is supported by National Key R&D Program of China (No. 2018YFA0605701) and Chinese Arctic and Antarctic Administration (IRASCC2020-2022). This work is also supported in part by the Centre for Southern Hemisphere Oceans Research, a partnership between CSIRO and the Qingdao National Laboratory for Marine Science and Technology, by the Earth Systems and Climate Change Hub of the Australian Government’s National Environmental Science Program, and by the Australian Antarctic Program Partnership.

Funding

This work is supported by National Key R&D Program of China (No. 2018YFA0605701) and Chinese Arctic and Antarctic Administration (IRASCC2020-2022-02-01-03).

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author contributions All authors contributed to the study conception and design. Jindong Jiang designed the research and performed the analysis. The first draft of the manuscript was written by Jindong Jiang and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Data availability statement

The European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) reanalysis product was downloaded at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means?tab=overview. The gridded Argo product used in this study are openly available from http://sio-argo.ucsd.edu/RG_Climatology.html.

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Opposing trends of the Subantarctic Mode Water thickness in the South Indian Ocean driven by atmospheric forcing and interior mixing

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Abstract

Figures

1 Introduction

2 Data And Methods

2.1 Observations and atmospheric fields

2.2 Annual subduction rate

2.3 Definition of the mixed layer depth and Ekman heat flux

2.4 Definition of the SAMW

2.5 Definition of the marine cold air outbreaks

3 Samw Volume And Subduction And Their Variations

3.1 Climatological characteristics of SAMW subduction rate and volume

3.2 Interannual variability and trends

4. Mechanisms Driving Variability In Samw Volume

4.1 Forcing mechanisms in the subduction area

4.2 Mechanisms of SAMW variation outside the subduction area

5. Discussion And Conclusion

Declarations

References

Additional Declarations

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