Journal of Oceanology and Limnology   2022, Vol. 40 issue(4): 1349-1360     PDF
Institute of Oceanology, Chinese Academy of Sciences

Article Information

ZHU Baisu, YANG Wei, JIANG Chengfei, WANG Tao, WEI Hao
Observations of turbulent mixing and vertical diffusive salt flux in the Changjiang Diluted Water
Journal of Oceanology and Limnology, 40(4): 1349-1360

Article History

Received Jun. 18, 2021
accepted in principle Aug. 2, 2021
accepted for publication Sep. 23, 2021
Observations of turbulent mixing and vertical diffusive salt flux in the Changjiang Diluted Water
Baisu ZHU2, Wei YANG2, Chengfei JIANG2, Tao WANG2, Hao WEI2     
1 School of Marine Science and Technology, Tianjin University, Tianjin 300072, China;
2 Key Laboratory of Marine Environment and Ecology, Ocean University of China, Qingdao 266100, China
Abstract: Based on microstructure measurements from a repeated sampling station southwest of the Jeju Island during summer, we studied the hydrography, pycnocline turbulence, and vertical salt flux in the Changjiang Diluted Water (CDW). The water column was well stratified with the CDW occupied the surface ~20 m. Most of the large turbulent kinetic energy dissipation rate (ε) were found in the bottom boundary layer. Interestingly, intermittent strong turbulence (ε>10-6 W/kg) occurred in the pycnocline, which may induce strong mixing events and increase the vertical diffusive salt flux at the base of CDW by one order of magnitude. The daily-mean vertical diffusive salt flux could reach 4.3 (2.1, 8.9)×10-6 m/s. Both moored velocity measurements and associated wavelet analysis showed the presence of velocity fluctuations when there was strong pycnocline turbulence. The moderate resolution imaging spectroradiometer (MODIS) satellite images further suggest that the velocity fluctuations are induced by the prevailing internal solitary waves (ISWs) which are mainly generated at the shelf break of the East China Sea or the topographic features surrounding Jeju Island. The calculated gradient Richardson number denote the occurrence of shear instability in the pycnocline when strong turbulence presents. The presented results have strong implications for the importance of ISWs in influencing the vertical diffusion of CDW and changes in other properties.
Keywords: turbulence    vertical salt flux    internal solitary wave    Changjiang River plume    

The Changjiang (Yangtze) River is the third longest river in the world and discharges a large amount of fresh water and nutrients into the Yellow Sea and the East China Sea (YECS) (Kim et al., 2009; Song et al., 2013; Kwon et al., 2018). The extension of the Changjiang Diluted Water (CDW) directly alters the distribution of nutrients and primary productivity in the YECS. In addition to the eutrophication caused by the large amount of nutrients entering the sea (Zhao and Guo, 2011; Wang et al., 2019; Zhou et al., 2019), severe hypoxia occurs below the CDW during summer when there is a large freshwater discharge (Zhu et al., 2011; Wang et al., 2012; Zhang et al., 2017; Liblik et al., 2019). Therefore, it is extremely important to understand the physics controlling the spatial extension (both horizontally and vertically) of the CDW and the vertical exchange processes between the CDW and underlying water masses (Zhou et al., 2008; Jiang et al., 2014; Wang et al., 2015).

The mixing of freshwater and underlying salty water to form intermediate-salinity water is key to the dispersion process of diluted water. Previous observations and numerical simulations have investigated the role of different processes, such as tides, wind forcing, and Coriolis forces, in changing the dispersal of a river plume (e.g., Hetland, 2005; Guo and Valle-Levinson, 2007; MacCready et al., 2009; Horner-Devine et al., 2015; Tarya et al., 2015; Wang et al., 2021). Tidal energy is usually several orders of magnitude higher in coastal areas than that in offshore areas, which can enhance vertical mixing and thus affect the plume expansion and diffusion of CDW (Zhu et al., 1999; Wu et al., 2011; Zhang et al., 2014). In the far field, wind forcing ultimately controls the mixing and extension of CDW as it is transported via the wind-induced Ekman flow (Moon et al., 2009; Lee et al., 2014). The Changjiang River discharge is known to change seasonally (Zhu et al., 2001; Gao et al., 2012). The CDW extends northeastward toward Jeju Island during summer and flows southward along the Zhejiang coast in winter (Mao et al., 1963). Numerical studies have revealed that wind forcing and tidal mixing are critical factors in driving northeastward CDW transport and the occurrence of offshore low-salinity paths (Moon et al., 2010; Xuan et al., 2012; Liu et al., 2013; Wu et al., 2014).

Direct turbulence measurements in the Changjiang River plume are very limited, and most have focused on the turbulence properties and influencing mechanisms in the bottom boundary layer (Lozovatsky et al., 2012; Yang et al., 2017; Zhang and Wu, 2018). The mixing properties and associated driving mechanisms below the CDW are poorly understood. Based on turbulence measurements from a zonal section, Matsuno et al. (2006) observed weak turbulence (ε < 10-8 W/kg) just beneath the CDW in the far-field plume. Recently, Wang et al. (2020) showed that the near-surface ε generally decreases with distance from the estuary.

Previous studies have identified the area adjacent to the Changjiang River estuary and regions around Jeju Island and the Korean coast as two hotspots of internal waves (IWs) in the East China Sea (ECS) (Hsu et al., 2000; Li et al., 2008; Tsutsumi et al., 2017). Internal solitary waves (ISWs) can be induced by the interaction between strong tidal currents and topographic features adjacent to the Changjiang River estuary, as based on both in-situ observations (Lozovatsky et al., 2012) and satellite images (Li et al., 2008). In recent studies, strong IW-induced pycnocline turbulence was observed to play an important role in nutrient cycling and growth of the phytoplankton (Yang et al., 2020; Zhang et al., 2020). However, few observations of turbulence and internal waves have been conducted adjacent to the Korean coast and Jeju Island, despite the location being identified based on previous satellite images, as an important site for generation of ISWs in the YECS (Hsu et al., 2000). Although this region is relatively far from the Changjiang River estuary (~340-km away), the CDW carrying large amounts of diluted water, can still reach this region. The influence of ISWs on the pycnocline turbulence and vertical exchanges of freshwater and other materials and properties remains unknown.

This study aims to investigate the features and driving mechanisms of the pycnocline turbulence and vertical diffusive salt flux in the region with the CDW. The remainder of this paper is organized as follows. The observation strategy and data processing are described in Section 2. Section 3 presents the structure of the Changjiang River plume. The properties of hydrography, turbulent mixing, and vertical salt fluxes are presented in Section 4. Section 5 discusses the role of the ISW in changing the pycnocline turbulence and vertical salt flux below the CDW. The conclusions are presented in Section 6.


The data analyzed in this study were mainly obtained from one repeated sampling station (Stn MT1). Stn MT1 (125.50°E, 31.99°N, water depth of ~65 m) is located at the southwest of Jeju Island approximately 340 km northeast of the Changjiang River mouth (Fig. 1). Measurements at Stn MT1 last ~24 h (July 22–23, 2013). Along with the measurements at Stn MT1, observations at a total of 44 transect stations were obtained onboard the same cruise in summer (July 14–31, 2013). Our primary instrument was the vertical microstructure profiler (VMP-200), which was equipped with two high-frequency shear probes with a sampling frequency of 512 Hz. Microscale shear data were used to calculate turbulent kinetic energy (TKE) dissipation rate ε. We used the conductivity-temperature-depth profiler (CTD, RBR maestro) with an additional sensor of chlorophyll a, with sampling at 6 Hz, to measure the vertical profiles of temperature, salinity, and chlorophyll a. To obtain the continuous time-depth variations of microscale shear and hydrographic properties, VMP and CTD were deployed once an hour at Stn MT1. For transect stations, only hydrographic properties measured by the CTD were presented and analyzed in the present study.

Fig.1 Schematic of the current system in the ECS (a) and bathymetry of the study area (b) The thick and thin solid arrows are the Kuroshio Current (KC) and Taiwan Warm Current (TWC), respectively. The dotted line near the mouth of the Changjiang River represents the typical path of the Changjiang River plume in summer. The dashed arrow represents the nearshore intrusion branch of the KC. The red triangles in (b) represent the transect stations obtained during the summer of 2013. The location of the repeated sampling station is represented by the red pentacle with the station name indicated nearby.

Under the assumption of isotropic turbulence, ε was calculated as follows:


where v is the kinematic viscosity coefficient, is the variance of the velocity shear, φ(k) is the shear spectrum, and k1 and k2 are the lower and upper limits of the wavenumber for integration, respectively. The upper limit of the wavenumber is determined by fitting the Nasmyth theoretical spectrum to the measured spectra over consecutive segments of 2 m with 50% overlap (for details, please refer to Xu et al., 2020 and Yang et al., 2020). Therefore, we obtained ε profiles with a resolution of 1 m. The vertical eddy diffusivity (Kρ) was calculated using Osborn's formula Kρ=Γ(ε/N2) (Osborn, 1980), where Γ is the mixing efficiency with a constant value of 0.2, and N2 is the squared buoyancy frequency. Stn MT1 also includes the velocity measurements from a 600-kHz acoustic Doppler current profiler (ADCP) moored on the seabed. Velocities were measured with the vertical and temporal resolutions of 0.5 m and 1 min, respectively. The wind speed was measured using the RM YOUNG anemometer at 10-s intervals.


The Changjiang River's discharge varies seasonally, with the largest discharge in summer (~6×104 m3/s) and the smallest in winter (~1×104 m3/s) (Zhu et al., 2001). Figure 2 shows the monthly discharge of the Changjiang River in 2013 as downloaded from the monthly flow data from the ocean sediment bulletin of Datong station. In 2013, the river runoff peaked at ~1.15×1012 m3 in July, and the minimum was in November, which was ~3.48×1011 m3. During our observation period, runoff was the largest, which is typical for summer. Figure 3 shows the spatial distribution of the sea surface temperature and salinity in summer 2013. Figure 3b shows that the CDW spread northeastward from the Changjiang River estuary to Jeju Island in summer. The lowest salinity (S < 29) was found at the transect from the Changjiang River estuary to Jeju Island, which may have been related to the detachment process of low-salinity water (Moon et al., 2010; Xuan et al., 2012). Figure 3b shows the typical paths of the Changjiang River plume in summer (Mao et al., 1963). The CDW has been usually generally defined in previous studies as having a salinity of less than 31 (Chen, 2009; Quan et al., 2013; Bai et al., 2014); this definition has also been adopted within this study. The upper layers of the sampling station (Stn MT1) were covered by the CDW.

Fig.2 Monthly discharge of the Changjiang River in 2013 obtained from the ocean sediment bulletin of Datong station The black vertical bar corresponds to the time when Stn MT1 was measured.
Fig.3 Spatial distribution of sea surface temperature (a) and salinity (b) in summer 2013 Black contours represent the isotherms in (a) and isohalines in (b). The location of the repeated sampling station is represented by the pentacle with the station name indicated nearby.
4 TEMPORAL VARIATION 4.1 Hydrographic property

The time-depth evolutions of temperature, salinity, N2, and chlorophyll a at Stn MT1 are shown in Fig. 4. The surface water at Stn MT1 was relatively hot (T > 26 ℃) and fresh (S < 31). On average, the CDW (S < 31) at Stn MT1 covered the surface 23 m (Fig. 4b).The calculated N2 show that the water column was well stratified with the strongest pycnocline located at the depth range of 10–30 m. The maximum N2 could reach approximately 1.0×10-2/s2 (Fig. 4c). The position of the pycnocline corresponded well with the vertical ranges of CDW. The maximum chlorophyll a (2 μg/L) was concentrated at a depth of 20–30 m within the pycnocline (Fig. 4d).

Fig.4 Time-depth variations of temperature (a) (black contours: isotherms), salinity (b) (black contours: isohalines), squared buoyancy frequency N2 (c), and chlorophyll a (d) at Stn MT1
4.2 Turbulent mixing and vertical salt flux properties

Large ε values (~10-6 W/kg) were observed in the bottom layer (Fig. 5b) because of the bottom friction of strong tidal currents. ε generally had a low level (~10-9 W/kg) in the pycnocline during 6–12 h because of the suppression effect of stratification. The weak turbulence level and strong stratification together induced the smallest Kρ (~10-7 m2/s) in the pycnocline (Fig. 5c). One of the most noticeable features of Stn MT1 was the intermittent large ε within the pycnocline having a depth range from 17 to 20 m. The strongest turbulence (ε > 10-6 W/kg) mainly occurred during 0–5 h, 13–15 h, and 18–24 h within the strong pycnocline. The occurrence of large ε during 18–24 h was accompanied by strong winds (Fig. 5a). However, the large dissipation was likely not induced by the wind-induced turbulence in the surface boundary layer, as the ε at surface had lower values than those within the pycnocline. Strong turbulence usually lasted for several hours in the pycnocline, which further led to a large Kρ (~10-4 m2/s) (Fig. 5c). The driving mechanism of the observed intermittent strong turbulence in the pycnocline at Stn MT1 is examined in Section 5. We suggest the plausible influence of ISWs working at Stn MT1.

Fig.5 Time series of wind at Stn MT1 (a); time series of TKE dissipation rate ε with the isopycnals (b) (black lines); vertical eddy diffusivities Kρ with isohalines (black lines) (c); time-average profile (black line) of the ε with standard deviation shaded (d), vertical eddy diffusivities Kρ with standard deviation shaded (e) The black and red lines in (a) represent wind speed and direction, respectively. The two red lines in (c) are the depths of ∂σθ/∂z > 0.1 kg/m4 and the 31 isohalines which denote the upper and lower boundaries in calculating the vertical salt flux, respectively.

Salinity generally increases with increasing distance offshore within the CDW. One important reason for this increase is the mixing of underlying water. We thus calculated the vertical turbulent salt flux to investigate the vertical diffusion at the boundary of the CDW. This parameter also has important implications for the exchange of other properties between the CDW and the ambient offshore

water. The vertical salt flux is calculated based on Fsalt=Kρ(∂S/∂z), where Kρ and (∂S/∂z) represent the eddy diffusivity and vertical salt gradient, respectively. In this study, we focus on the Fsalt the base of the CDW. The upper limit of the calculation depth range is defined as the depth at which the vertical gradient of the potential density is larger than 0.1 ( > 0.1kg/m4). The lower limit is set to a depth of 31 isohaline. Figure 6a shows that the vertical gradient of the salinity did not change much during the observation period, with time-averaged values of 0.19/m at Stn MT1. In contrast, the corresponding averaged Kρ spanned several orders of magnitude during the observation period (Fig. 6b). Most Kρ show orders of O (10-6) m2/s and occasionally increased up to O (10-4) m2/s.

Fig.6 Time series of the vertical salt gradient (a), eddy diffusivity (b), and vertical salt flux (c) at Stn MT1 All the values are averaged between the initial depth of ∂σθ/∂z > 0.1 kg/m4 and the 31 isohalines. The horizontal black lines and shaded area in (c) denote the averaged vertical salt fluxes and their 95% bootstrap confidence intervals during the corresponding period, respectively.

Figure 6c shows that the calculated Fsalt at Stn MT1 has a similar varying trend with Kρ. The dailyaveraged Fsalt at Stn MT1 was 4.3 (2.1, 8.9)×10-6 m/s. Here, numbers in brackets represent the 95% bootstrapped confidence interval for the mean value. Large values of Fsalt appeared during 0–5 h, 13–15 h, and 18–24 h, which was induced by large Kρ during the period that corresponded to a strong turbulence as discussed above. As shown in Fig. 6c, we selected two periods of 18–24 h and 6–12 h for comparison. The average Fsalt during 18–24 h reached 8.4×10-6 m/s, which was 34 times larger than that during 6–12 h (2.5×10-7 m/s). Because the vertical salt gradient did not change much during the observation period, changes in Fsalt were largely determined by the temporal variations in Kρ (Fig. 6b). The enhanced Fsalt during 18–24 h clearly corresponded to the occurrence of large Kρ and ε as shown in Fig. 5. This highlights the importance of episodic intense mixing events in driving the exchange between the CDW and the underlying water.

5 DISCUSSION 5.1 Strong pycnocline turbulence and passage of internal solitary waves

One interesting phenomenon presented above is the episodic strong pycnocline turbulence, large vertical eddy diffusivity, and vertical salt flux at Stn MT1. Figure 5b & c shows that the large Kρ coincides with the occurrence of a large ε, inducing the large vertical salt flux. Figure 7a & d shows an extensive view of ε within the pycnocline during two representative periods of 13–16 h and 18–24 h when strong turbulence occurs. These two periods were denoted as stages 1 and 2, respectively. There was strong turbulence (ε > 10-6 W/kg) within the pycnocline during both periods (Fig. 7a & d). Along with the occurrence of strong pycnocline turbulence, the pycnocline experienced obvious vertical displacements with an amplitude of ~5 m, especially during stage 2 (18–24 h) (Fig. 7d). Moreover, the intense turbulence seemed to fluctuate in the vertical direction following the displacement of the isopycnals.

Fig.7 Time-depth variations of the density (a, d), horizontal velocity (U) (b, e), and vertical velocity magnitude (W) (c, f) at Stn MT1 during 13–16 h (left panel, stage 1) and 18–24 h (right panel, stage 2), respectively The superimposed plots in (a, d) are profiles of ε.

The measurements of the bottom-moored ADCP allow us to examine in detail the physical process accounting for the observed vertical displacement of the pycnocline. Along with the occurrence of pycnocline displacement during stage 2, both the velocity magnitude and vertical velocity showed signals of fluctuations. The periods of the fluctuation gradually increased from ~12 min to ~16 min, as identified from both the velocity magnitude and vertical velocity. We noted that the measured velocity had different vertical depth coverage for these two stages. As shown clearly in Fig. 8a, velocity measurements from 6 to 16 h had a long vertical coverage, albeit the settings of the ADCP remain unchanged. The reason is not known. We have confirmed that the available measured velocity is reliable.

Fig.8 Time-depth variations of horizontal velocity magnitude (a); depth averaged vertical velocity within a fixed depth range of 3.2–23.2 m above the seabed (b); the wavelet spectra of vertical velocity (c); the averaged wavelet spectra variance within the period of 5–30 min (d) The black solid line in (c) denotes the 95% confidence threshold of the wavelet spectra. The dashed line in (d) represents the corresponding 95% confidence threshold.

The wavelet analysis of the depth-averaged vertical velocity was next performed to identify the periods of fluctuations (Fig. 8). The depth-averaged vertical velocity was calculated within a fixed depth range of 3.2–23.2 m above the seabed (Fig. 8b). Figure 8b shows that there are fluctuations with a period of approximately one hour at 14 h, which is consistent with that shown in Fig. 7c (stage 1). The fluctuation as shown in Fig. 7 during stage 2 is also evident in the wavelet spectrum. Figure 8d shows that the averaged variance has clear peaks within periods of 5–30 min from 18–24 h passing the 95% confidence threshold of the wavelet spectra. We note that although the fluctuations in both velocity magnitude and vertical velocity is well identified, we observed a small isopycnal displacement during stage 1 (Fig. 7a). The main cause for this can be that the hourly-deployed VMP likely did not capture the exact evolution of the pycnocline.

Next, the possible processes that may lead to these fluctuations were examined. One plausible process is the presence of ISWs that pass through the mooring station. The MODIS true color images, as shown in Fig. 9, were created from the calibrated, corrected, and geolocated radiance (Level-1 B), with a spatial resolution of 250 m (bands 1 and 2). Although there was no clear true-color image during our observation period at Stn MT1 (12:00, July 22–12:00, July 23, 2013), we found two cloud-free images taken approximately 1.5 h before the beginning of our measurement (10:25, July 22, 2013, Fig. 9a) and 0.75 h after the end of our measurement (12:45, July 23, 2013, Fig. 9b). As the sampling time of these two satellite images were quite close to our measurement period, these satellite images were thought to be able to reflect the conditions at Stn MT1. Figure 9 shows clear evidence of ISWs that were generated at different sites and propagated in different directions. This indicated multiple generation sites of ISWs in the surrounding area. Interactions frequently occur when different groups of ISWs meet each other.

Fig.9 Subscene of a moderate resolution imaging spectroradiometer (MODIS) true-color image around Stn MT1 collected at 10:25 on July 22, 2013 (a) and 12:45 on July 23, 2013 (b) The region of the satellite image is denoted by a black box in the inserted map. The red dashed lines indicate wave crests of IWs. The black arrows indicate IWs propagation directions and distances between adjacent packets. A–G represents for the number of IWs.

Figure 9 shows that there were two main propagation pathways of the ISW that generally propagate to the west and south. For the same westward propagating direction, the adjacent ISW groups were generally evenly separated by ~40 km. This suggests that these ISWs are periodicity generated through the interaction between tidal currents and bottom topography. Based on synthetic aperture radar images, Hsu et al. (2000) first showed the existence of ISWs propagating from Jeju Island and other small islands near the Korean coast. Based on observations from a nearby station (35 km from Stn MT1), Lee et al. (2006) observed strong ISWs propagating northwestward which mainly appeared during the same tidal phase; they suggested that the wave packets were generated near the shelf break of the ECS, and then propagated to the measurement station. However, it is difficult to relate directly the MODIS-observed ISWs to our mooring observation owing to the complicated distributions of the ISWs as shown in Fig. 9. Mooring observations that last for extended periods may be helpful in answering the properties of ISWs in the surrounding area. Nevertheless, both the in-situ observation and satellite images suggested that the ISW was a prevailing phenomenon around Stn MT1. The concurrence of the ISW and the strong pycnocline turbulence suggest that the prevailing ISWs may play an important role in modifying the pycnocline turbulence at Stn MT1.

5.2 Shear instability

Previous studies have shown that the turbulence in the pycnocline can be efficiently generated via shear instability (Bourgault et al., 2001; Moum et al., 2003). We took the vertical profiles of the buoyancy frequency N and shear Sh, gradient Richardson number Ri, and TKE dissipation rate ε at 15 h as an example (Fig. 10). These profiles were observed during stage 1 when a strong pycnocline turbulence and velocity fluctuations occur. The long vertical coverage of the ADCP measurements in this period allow us to examine the property of Ri in the pycnocline. The gradient Richardson number (Ri=N2/Sh2) can be used to quantitatively describe the relative relationship between the static and dynamic instabilities of the water body. Small-amplitude disturbances in the water are unstable if Ri < 0.25 (Howard, 1961). Figure 10c shows that large ε (> 10-6 W/kg) in the pycnocline occurred at ~19 m. This corresponds well with the layers with large velocity shear and small Ri. Figure 10b shows that we have Ri < 0.25 at the corresponding depth ranges. This indicated that the velocity shear was large enough to cause shear instability and generate strong turbulence in the pycnocline. The other depth range of Ri < 0.25 was found below 45 m, and the bottom friction of tidal currents induced an energetic bottom boundary layer.

Fig.10 Vertical profiles of buoyancy frequency N (dotted line) and shear Sh (solid line) (a); gradient Richardson number Ri (b); TKE dissipation rate ε in 15 h (c) at Stn MT1

Further investigations based on comprehensive field observations in this area are required. Nevertheless, given the prevalence of ISWs at Stn MT1, our results imply that ISWs may play a significant role in facilitating material exchange between the CDW and offshore water masses, thereby influencing the biogeochemical cycle in the ECS. Calculations of the vertical turbulent salt flux show that the calculated values can be increased by one order of magnitude when ISWs are present. Similarly, we can anticipate that ISW-induced pycnocline mixing may play an important role in facilitating heat, momentum, nutrients, and other property exchanges.


Based on observations at one repeated sampling station southwest of the Jeju Island, this study focuses on the properties of hydrography, pycnocline turbulence, and vertical salt flux in the CDW during summer. The CDW spread northeastward from the Changjiang River estuary to Jeju Island during summer, reaching Stn MT1, which is approximately 340 km from the Changjiang River mouth. Stn MT1 was covered by the CDW at the surface. On average, the CDW (bounded by a salinity of 31) occupied the upper 23 m at Stn MT1.

The TKE dissipation rate had a low value in the pycnocline (~10-9 W/kg) during 6–12 h, where stratification inhibited the development of turbulence. In contrast, we observed intermittent intense pycnocline turbulence (ε > 10-6 W/kg) during 0–5 h, 13–5 h, and 18–24 h. The strong turbulence usually lasted several hours and was unlikely to be induced by the strong wind because that the ε at surface had lower values than those in the pycnocline. Further analysis showed that the occurrence of strong turbulence is usually accompanied with evident fluctuations in the velocity measurements. Wavelet analysis confirmed the prevailing vertical fluctuations have periods spanning from 10 min to 1 h. Based on satellite images analyses, we suggest that the fluctuations are likely to be related to the presence of ISWs. Satellite observations showed that there are multiple generation sites of ISWs in the surrounding area. These sites were mainly generated at islands near the Korean coast and the shelf break of the ECS and then propagated to Stn MT1. The available vertical profile of Ri confirmed that the ISW-induced large shear overcomes the suppressing effect of the pycnocline, inducing strong pycnocline turbulence. The daily-averaged vertical salt flux (Fsalt) values under the CDW were 4.3 (2.1, 8.9)×10-6 m/s at Stn MT1. We identified that the large vertical salt flux at Stn MT1 was dominated by the episodic large vertical salt flux driven by the ISW-induced strong pycnocline mixing. During that time, the Kρ was elevated by orders of magnitude and so was the vertical diffusive salt flux.

One interesting question remaining is to what extent is the vertical exchange of CDW influenced by the ISWs. This is largely determined by the probability of occurrence of the ISW in the different parts of the CDW. Numerical simulations or further comprehensive observations are needed to address this question. Nevertheless, in this study, we illustrate that in addition to the recently identified area adjacent to the Changjiang River mouth (Yang et al., 2020; Zhang et al., 2020), the prevailing ISWs in regions southwest of Jeju Island also play an important role in modulating the vertical exchange between the CDW and salty offshore water. This may provide further implications for understanding the biogeochemical cycles in the Changjiang River plume.


The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.


We thank Pengzhao XU of Tianjin University for his help in data processing.

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