1. Introduction
Circulation patterns in the world’s oceans vary regionally, and ocean circulation is driven by the interaction of various external forcings. In general, geostrophic turbulence and eddies are spontaneously generated (Stammer 1997; Tulloch et al. 2011) because of barotropic and baroclinic instabilities (Charney 1947; Eady 1949; Thoppil et al. 2011). In particular, Smith (2007) and Hochet et al. (2015) showed that most of the upper-layer circulation is unstable where the western boundary current exists, and Gill et al. (1974) stated that baroclinic instability is the main forcing in the development of mesoscale eddies. Eddies formed by instabilities interact with the general circulation of the ocean (Holland 1978). Therefore, the various spatiotemporal variabilities of the ocean circulation are caused by the variabilities in the external forcings and the geostrophic turbulence that forms spontaneously. In reality, global oceanic variability includes variability that forms independently of external forcings variation. Such variability can be referred to as “oceanic intrinsic variability” (hereafter “intrinsic variability”). The intrinsic variability can be detected in numerical model experiments with no interannual variation in external forcings (Sgubin et al. 2014; Choi et al. 2018) or in a variety of ensemble experiments with slightly different initial conditions even when interannual external forcings exist (Nonaka et al. 2016; Llovel et al. 2018). As mentioned earlier, in this study, intrinsic variability was defined as a case of variability in experiments that applied the seasonal variation in the external forcings or the climatological annual mean external forcings. This oceanic intrinsic variability is important for understanding the total variability in the upper-layer circulation. The intrinsic variability is mainly concentrated on the midlatitude western boundary currents, their extensions, and eddy-rich regions, such as the Kuroshio (Taguchi et al. 2007; Pierini and Dijkstra 2009), Gulf Stream (Quattrocchi et al. 2012), and Agulhas Current (Dijkstra and De Ruijter 2001; Sgubin et al. 2014). In contrast, oceanic variability in the tropical ocean can be dominated by the variability in atmospheric external forcings rather than intrinsic variability (Penduff et al. 2011; Sérazin et al. 2015; Nonaka et al. 2016). Nonaka et al. (2016) suggested that the potential predictability of interannual variability in the Kuroshio jet is substantially limited by intrinsic variability. They showed that the magnitude of the intrinsic variability is comparable to that of the deterministic wind-driven variability at interannual time scales.
The East Sea (Sea of Japan), the analysis region of this study, is one of the semiclosed marginal seas in the northwestern Pacific surrounded by the Korean Peninsula, Russia, and Japan. In the East Sea, subtropical and subarctic circulations form the subpolar front. In the northern part of the East Sea, there is the formation of deep cold water (called the East Sea Proper Water) below 1°C, which is ventilated into the deeper sea with a residence time of approximately 100 years (Senjyu 1999; Gamo et al. 2014). Because the East Sea has similar characteristics to the open ocean, it is often considered “a miniature of the ocean” (Ichiye 1984; Lee et al. 2011; Gamo et al. 2014) and helps in understanding oceanic physical/dynamical processes on a shorter time scale than the open ocean. The upper-layer circulations of the East Sea have complex variabilities because they are driven by various forcing mechanisms: atmospheric external forcings (such as wind stress and surface heat flux), volume transport flowing through the Korea/Tsushima Strait (KTS), and bottom topography (Yoon 1982a,b,c; Kawabe 1982a,b; Kim and Yoon 1996, 2010; Kim et al. 2020).
The upper-layer circulation in the East Sea can be roughly divided into two parts centered over the subpolar front at approximately 40°N. In the southern part, the Tsushima Warm Current (TWC) with high temperature and salinity flows through the KTS, and it splits into the East Korea Warm Current (EKWC) and the Nearshore Branch (NB), which flow along the east coast of the Korean Peninsula and along the Japanese coast, respectively (Chang et al. 2004; Park et al. 2013; Fig. 1a). The northern part, which is a cold region, is characterized by a large cyclonic circulation maintained year round (Uda 1934; Yarichin 1980; Danchenkov et al. 2006; Yoon and Kim 2009). The subpolar front in the East Sea is a major indicator that divides the warm and cold water sectors, and it is the location where a large variation is observed (Park et al. 2004, 2005). Choi et al. (2009) investigated the interannual variability in the subpolar front using satellite altimeter and hydrographic data, and they also suggested that wind stress is an important external forcing for subpolar front variability through numerical experiments. Choi et al. (2004) analyzed sea surface height (SSH) data from satellite altimeters by using empirical orthogonal function (EOF) analysis and showed that the first mode represents intraseasonal oscillations over the entire East Sea, and the second mode captures the interannual variation in the TWC path. Ito (2014) investigated the effect of surface cooling on the hydrographic conditions in the southwestern part of the East Sea. He showed that when winter cooling was strong, the cold water mass at a depth of 100 m extended farther south than under relatively weak cooling conditions. In the Yamato Basin (YB), Hirose and Ostrovskii (2000) suggested that quasi-biennial variability occurred due to intraseasonal wind stress variation. Thus, various variabilities appeared in several regions of the East Sea driven by external forcings.
(a) Schematic surface current by Park et al. (2013) and (b) bottom topography of the East Sea (Sea of Japan). KTS: Korea/Tsushima Strait, TS: Tsugaru Strait, SS: Soya Strait, UB: Ulleung Basin, YB: Yamato Basin, OS: Oki Spur, JB: Japan Basin.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
However, the East Sea also exhibits significant intrinsic variability in numerical experiments without fluctuations in external forcings, such as the western boundary currents in the open ocean. Holloway et al. (1995) presented that natural variability in kinetic energy in the East Sea appeared in all experiments that applied climatological annual/monthly mean forcings. Choi et al. (2018) analyzed the variability in the surface circulation of the East Sea through the numerical experiments with external forcings of interannual or seasonal variations and confirmed that intrinsic variability is a dominant factor, contributing about 59% and 68% to total variability in terms of 100-m temperature and surface current field, respectively. However, studies on the physical mechanism of the intrinsic variability in the East Sea are insufficient compared to the open ocean and other western boundary current regions.
In this study, the physical mechanism of the intrinsic variability occurring within the East Sea is analyzed by employing a three-dimensional circulation model. We also examine the important external forcings that modulate intrinsic low-frequency variability. In section 2, the numerical model and experimental design are described. The distribution of low-frequency SSH and variability in the upper-layer circulation of the East Sea are analyzed in section 3. Then, the characteristics of the intrinsic low-frequency variability are given in section 4. In section 5, the effects of external forcings on intrinsic low-frequency variability are examined through various numerical experiments. The horizontal distributions of the low-frequency SSH anomaly variability (section 5a) and vertical section of the water temperature (section 5b) are presented in response to each external forcing, and its physical mechanisms (section 5c) are discussed. Finally, a summary and discussion are given in section 6.
2. Numerical model and experimental designs
Horizontal distributions of annual mean wind stress curl and surface heat flux and seasonal variation in the surface heat flux derived from JRA55. A negative value for surface heat flux indicates the heat released from the ocean to the atmosphere.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
Parameter values used in the numerical model.
In this study, the numerical experiments can be fundamentally divided into three types (Table 2). The first experiment (hereafter Forced-Interannual-Exp) includes all external forcings with interannual variation, and the second experiment (hereafter Intrinsic-Seasonal-Exp) uses the climatological monthly mean for the external forcings (hereafter seasonal forcings), which includes seasonal variation but no interannual variation. The last experiment (hereafter Intrinsic-Constant-Exp) uses the climatological annual mean for all external forcings without any temporal variations (hereafter constant forcings), just as Pierini et al. (2009) applied constant wind forcing. Intrinsic variability may generally appear under constant or seasonal external forcings (Holloway et al. 1995; Dewar 2003; Sérazin et al. 2015). Intrinsic-Seasonal-Exp and Intrinsic-Constant-Exp are defined as the intrinsic process experiments in this study. All experiments were conducted for a total of 95 years from an initial state at rest. In the case of the intrinsic process experiments (Fig. 3), 80 years of spinup were performed according to each experimental condition, and the last 15 years were used for analysis. In Forced-Interannual-Exp, for spinup integration (72 years), the conditions of the external forcings are the same as the conditions of Intrinsic-Seasonal-Exp. Then, from the 73rd year, external forcings with interannual variation are applied from 1993 to 2015. At this time, there may be a discontinuity between seasonal and interannual variations in the external force fields. To resolve them, the first 8 years (1993–2000) are considered an adjustment period, and the last 15 years (2001–15) are used for analysis as in the intrinsic process experiments. In this study, 5-month low-pass filtering is performed at each grid point to remove high-frequency variability and focus on low-frequency variability in all experiments. In addition, the analysis focuses on the intrinsic variability occurring within the East Sea.
Design of numerical experiments depending on the external forcing variation. VT indicates the volume transport flowing through the Korea/Tsushima Strait.
All experiments are conducted for 95 years from an initial state at rest. In the case of intrinsic process experiments, 80 years are defined for a spinup period, and the numerical results of the last 15 years are employed for analysis. In Forced-Interannual-Exp, the numerical model is driven by the climatological monthly mean forcing for spinup integration (72 years) and then applied to the external forcing with the interannual variation.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
3. Distribution of mean SSH and SSH variability
(a) RMS of the low-frequency SSH (cm; shaded) observed by the satellite altimeters and long-term mean absolute sea level (cm; line) from 2001 to 2015. (b) As in (a), but for Forced-Interannual-Exp. Black rectangular boxes indicate regions with particularly large RMSs for the SSH anomalies.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
The distribution of the annual mean low-frequency SSH simulated from Forced-Interannual-Exp is similar to that derived from satellite altimeter data (Fig. 4). In the SSH fields derived from observation and model results, the NB flowing northeastward along the Japanese coast and the EKWC flowing northward along the Korean coast distinctly appear. The EKWC flowing northward separates from the coast at approximately 39°N and then meanders northeastward. The RMSs of the low-frequency SSH in Forced-Interannual-Exp and satellite altimetry are large in the southern part of the East Sea, particularly over the separation region of the EKWC and the YB (Fig. 4). These two regions are where warm eddy activities are frequently observed in the East Sea (Isoda 1994; Morimoto et al. 2000; Shin et al. 2005). In the southern part of the East Sea, although the variability in the upper-layer circulation in Forced-Interannual-Exp is generally similar to that from satellite observations, the simulated variability appears to extend further north by approximately 1°–1.5° compared to the observation data. Furthermore, the variability in the SSH in Forced-Interannual-Exp is larger than the observation in the western part of the Tsugaru Strait. This region is near the outflow boundary region, and numerical disturbance may appear if the inflow water does not flow out smoothly. Despite the different distributions of the flow variability between the model results and observations in the western part of the Tsugaru Strait, the numerical model results are considered reasonable in analyzing the variability of the upper-layer circulation in the East Sea. Therefore, in this study, the separation region of the EKWC and the YB, where the RMSs of the SSH are high, are intensively investigated.
Figures 5 and 6 present the time series of the spatially averaged low-frequency SSH anomalies in the two regions from satellite altimetry and Forced-Interannual-Exp. In the separation region of the EKWC (Fig. 5), the correlation coefficient of the low-pass filtered SSH anomaly between the satellite altimetry and Forced-Interannual-Exp is approximately 0.50 [the 90% confidence level is 0.582 when the number of degrees of freedom is approximately 7 by using the effective degree of freedom (Bretherton et al. 1999)]. When the spatially averaged low-frequency SSH anomaly is positive, the EKWC separates from the Korean coast north of 41°N (Figs. 5a,b,e). When the SSH anomaly turns negative, the EKWC weakens, or warm eddies are separated from the EKWC (Figs. 5a,c,d). Then, while it changes to a positive anomaly again, the EKWC flowing northward becomes strong once more (Figs. 5a,e). When the SSH anomaly is positive in the YB, crest-shaped waves or warm eddies coupled with the TWC meandering develop (Figs. 6a,c,e). The waves weaken or eddies are separated from the TWC when changing to a negative anomaly (Figs. 6a,d). In other words, the variability in the upper-layer circulation in the southern part of the East Sea is largely related to the meandering current system and eddy activities.
(a) Time series of the spatially averaged SSH anomaly (cm) for CMEMS (black line) and Forced-Interannual-Exp (red line) in the separation region of the EKWC, where the variability is large (black rectangle in bottom panels). (b)–(e) The horizontal distributions of the low-frequency SSH along with surface current from Forced-Interannual-Exp.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
As in Fig. 5, but in the Yamato Basin and blue line in (a) indicates the time series of the spatial-averaged low-frequency SSH anomaly in Forced-Interannual-Exp.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
4. Intrinsic low-frequency variability in the East Sea
Before the investigation of the intrinsic low-frequency variability in the East Sea, the distributions of the upper-layer circulation are analyzed (bottom panels of Fig. 7). In all experiments, the TWC flowing through the KTS bifurcates into the NB flowing along the Japanese coast and the EKWC flowing along the east coast of the Korean Peninsula, and the cyclonic gyre is simulated in the northern part. In Forced-Interannual-Exp and Intrinsic-Seasonal-Exp, the EKWC separates from the east coast of the Korean Peninsula at approximately 40°N, and then the current meanders eastward in the area south of 39°N (Figs. 7d,e). On the other hand, in Intrinsic-Constant-Exp, the current separated from the coast meanders eastward between 38° and 41°N (Fig. 7f). In addition, the cyclonic gyre appears to be limited to the north of 41°N. The differences in the distributions of the annual mean surface current [in the central part (37.5°–42°N) of the East Sea] can cause a difference in the variability in the upper-layer circulation of the East Sea.
The horizontal distributions of (top) RMSs of the low-frequency SSH (cm) and (bottom) the long-term annual mean low-frequency SSH (cm) along with the surface current (cm s−1) in (a),(d) Forced-Interannual-Exp, (b),(e) Intrinsic-Seasonal-Exp, and (c),(f) Intrinsic-Constant-Exp. The white line indicates the depth of the bottom topography in (a)–(c).
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
Figure 7 (top panels) shows the distributions of the RMS of the low-frequency SSH in all experiments. In all intrinsic process experiments, as with Forced-Interannual-Exp, the variability is relatively large in the separation region of the EKWC and YB. However, the flow variability in Intrinsic-Constant extends farther north than in other experiments. As mentioned in the distribution of the annual mean surface current, the current, which is separated from the east coast of the Korean Peninsula, meanders eastward farther north compared to other experiments. Therefore, the ratio (
(a) Intrinsic-Seasonal-Exp (
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
In Intrinsic-Seasonal-Exp, the ratio (
There is large different in the intrinsic variability and upper-layer circulation between Intrinsic-Constant-Exp and Intrinsic-Seasonal-Exp (Fig. 7). In particular, in Intrinsic-Constant-Exp, the intrinsic variability north of 40°N is abnormally larger than that in Intrinsic-Seasonal-Exp. We can infer the impact of the seasonal variability in the external forcings. This will be discussed in section 6.
5. Effects of external forcings on intrinsic low-frequency variability
Various numerical experiments have confirmed that intrinsic variability is important for understanding the total variability in the upper-layer circulation (Sérazin et al. 2015; Choi et al. 2018). In this section, additional numerical experiments are conducted to identify which external forcings have major effects on the intrinsic variability in the East Sea based on realistic climatological monthly mean forcings rather than climatological annual mean forcings (Table 3). According to the applied external force field, the experiments are subdivided into four cases as follows: applying 1) only the volume transport through the KTS, 2) only the wind stress, 3) the volume transport with wind stress, and 4) the volume transport with surface heat flux. Additionally, 5-month low-pass filtering is performed for all results. For example, Seasonal_VT applies only volume transport, without applying wind stress and surface heat flux.
Design of numerical experiments depending on the applied external forcings. All experiments are based on the climatological monthly mean data (with seasonal variation). “None” means that no external forcings were applied.
a. Horizontal distributions of the upper-layer circulation variability
Figure 9 shows the variability in the upper-layer circulation and annual mean surface current in response to the external forcing fields based on experiments that applied seasonal variation forcings. In all experiments, the variabilities in the upper-layer circulation are large around the area where the meandering current’s main path resides. First, in the experiment (Seasonal_VT) in which only the volume transport of the TWC was applied, most of the TWC flowing along the Japanese coast turns northwestward near the Oki Spur (OS) and then flows northward along the east coast of the Korean Peninsula. The flow northward separates from the coast at approximately 41°N, and meanders flow eastward (Fig. 9e). At this time, the variability in the upper-layer circulation is mainly represented by the meandering current flowing eastward near 41°–42°N (Fig. 9a). In the experiment where only wind stress is applied (Seasonal_Wind), the variability in the SSH anomaly is significantly smaller than that of the other experiments because a constant counterclockwise current is shown in the northern part due to the dominant positive wind stress curl (Figs. 2a and 9b,f). Therefore, the volume transport of the TWC rather than the wind stress is one of the main external forcings causing intrinsic variability in the East Sea.
(top) RMSs of the low-frequency SSH and (bottom) the distributions of the annual mean surface current (cm s−1) along with the long-term mean of low-frequency SSH (cm) for 15 years in (a),(e) Seasonal_VT, (b),(f) Seasonal_Wind, (c),(g) Seasonal_VT_Wind, and (d),(h) Seasonal_VT_Qnet. The white line indicates the depth of the bottom topography in (a)–(d).
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
The cyclonic gyre driven by the wind stress in the northern part and northward flow along the Korean coast is simulated in Seasonal_VT_Wind (with the mean seasonal variability of the volume transport and wind stress; Fig. 9g). In this case, the flow variability is relatively large around the subpolar front (38°–40°N) formed by the confluence of the current flowing northward along the east coast of the Korean Peninsula and the cyclonic gyre in the northern part of the East Sea (Fig. 9c). The variability had a relatively wide range compared to Seasonal_VT and increased by approximately 38.3% over the East Sea. In Seasonal_VT_Qnet, which applied the volume transport and surface heat flux, a large variability appears around the meandering current from the northern part of the East Sea, similar to Seasonal_VT (Figs. 9d,h). However, unlike Seasonal_VT, Seasonal_VT_Qnet shows a relatively small flow variability, which indicates that the surface heat flux weakens the flow variability. Surface cooling in winter leads to the development of a cold water area in the northern part and causes ventilation. In Seasonal_VT_Qnet (Fig. 9h), the EKWC flows stably northward throughout the years along the east coast of the Korean Peninsula. The EKWC flows up to 42°N because the cyclonic gyre in the northern part does not appear due to no wind stress forcing. The EKWC is separated from the east coast of the Korean Peninsula near 42°N, and then the current flows eastward with weak meandering.
b. Vertical profile
The vertical sections of the water temperature for each experiment are analyzed along the 134°E line, which crosses the north–south center of the East Sea (Fig. 10). In Seasonal_VT, the heat transport through the KTS cannot be released into the atmosphere, but only through the Tsugaru and Soya Straits. The heat emission is not sufficient compared to the heat inflow through the KTS, and as a result, heat accumulates in the East Sea. In addition, since there is no effect of atmospheric external forcings such as wind stress or surface heat flux, a stratified structure develops in the upper layer with insufficient vertical mixing (Fig. 10a). The eastward currents are dominant in the central East Sea (Fig. 9e), and the flow variability is large here, especially between 40° and 42°N (Fig. 9a). As there is no heat exchange through both the atmosphere and lateral open boundary fields in Seasonal_Wind, which does not apply to the volume transport of the TWC and surface heat flux, this experiment can be regarded as a closed-basin experiment. A large cyclonic gyre is formed throughout the East Sea (Fig. 9f) and upwelling develops (Fig. 10b). As a result, the mixed layer below 5°C strongly develops, and the upper-layer thickness becomes thicker (Fig. 10b). When the upper layer is thick, it is difficult to form large flow variability because stronger energy from external forcings is needed. (Fig. 9b). In Seasonal_VT_Wind, as in Seasonal_VT, since there is no heat exchange with the atmosphere, the heat amount through the KTS accumulates in the upper layer. However, within 100 m of the upper layer, the mixed layer develops relatively clearly compared to Seasonal_VT (Fig. 10c) due to the wind stress. In this experiment, the northward current along the eastern coast of the Korean Peninsula separates at approximately 42°N, and then the current flows eastward toward the Tsugaru and Soya Straits, and the southwestward currents driven by the wind stress develop along the Russian coast (Fig. 9g). As there are various current patterns around these two main flows, the flow variability is larger and expands more widely than Seasonal_VT (Fig. 9c). In Seasonal_VT_Qnet, ventilation develops along with the formation of cold water in the northern part rather than in other experiments (Seasonal_VT, Seasonal_Wind, Seasonal_VT_Wind) due to thermal interaction with the atmosphere (Fig. 10d). The formation of cold water in the northern part greatly enhances the meridional water temperature gradient between 40° and 42°N. As a result, it is considered that the flow variability is weakened because the eastward current separating from the coast appears to have a straight path.
The vertical structure of the annual-mean water temperature (°C) along the 134°E line in (a) Seasonal_VT, (b) Seasonal_Wind, (c) Seasonal_VT_Wind, (d) Seasonal_VT_Qnet, and (e) Intrinsic-Seasonal-Exp. The contour interval is 1°C.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
In Intrinsic-Seasonal-Exp, the 2°C isotherm is located at a depth of 250 m which is shallower than that in the other experiments except for Seasonal_VT_Qnet (Fig. 10e). These characteristics appear similarly in the reanalysis data (HYCOM; not shown here). Upwelling occurs at approximately 40°–42°N in Intrinsic-Seasonal-Exp, which is a wider range than Seasonal_VT_Qnet. As the mixed layer develops in the area north of 40°N, the upper-layer thickness becomes thicker, and the flow variability is smaller. As wind stress and surface heat flux work together, cold water formation is facilitated in the northern part of the East Sea. The cold water corresponding to the East Sea Intermediate Water/East Sea Proper Water (ESIW/ESPW), which is mainly formed in the northern part, especially off Vladivostok, is ventilated and flows southwestward along the North Korea–Russia coast in the middle layer (Yoon and Kawamura 2002; Postlethwaite et al. 2005). As the cold water is ventilated to the southern part in Seasonal_VT_Qnet and Intrinsic-Seasonal-Exp, the ESIW corresponding to 1°–5°C is near a depth of 200–300 m. As a result, the upper-layer thickness in the southern part is relatively thinner than that in other experiments such as Seasonal_VT, Seasonal_Wind, and Seasonal_VT_Wind.
c. Physical mechanism of intrinsic variability
To investigate why intrinsic variability occurs in the East Sea, the time–longitude diagram of the meridionally mean (39.5°–43°N) low-frequency SSH anomaly is investigated based on Seasonal_VT, which is the simplest experiment showing the process of intrinsic variability among the experiments with seasonal variation (Fig. 11a). The positive/negative SSH anomalies formed near the eastern boundary (140°E) propagate westward to the western boundary (130°E), like to the westward propagating Rossby wave signal (Fig. 11a). The transit time and phase speed (=Cp) of the signal are approximately 2–3 years (from 140° to 130°E) and −0.90 cm s−1, respectively. This westward propagating signal can be explained using the properties of Rossby waves in this region (Yoon and Suginohara 1977; Kim and Yoon 1996; Seung and Kim 2011). The typical velocity of the surface mean current (U) estimated in Seasonal_VT is approximately 4.15 cm s−1 in this region, and the intrinsic phase speed (CI = Cp − U) of the intrinsic Rossby wave is inferred to be approximately −5.05 cm s−1. We can calculate the intrinsic phase speed of the Rossby wave (=βk−2; k is the wavenumber, β ≈ 1.8 × 10−13 s−1 cm−1) using the theoretical equation. At this time, the wavenumber (k) can be estimated with the wavelength (L ≈ 333.1 km), which was determined to be the distance between the crests in the long-term annual mean SSH. The theoretical intrinsic phase speed of the Rossby wave is approximately −5.06 cm s−1, which shows reasonably good agreement. The phase speeds of the Rossby waves appear to be different depending on the various experimental conditions (not shown here). However, in all experiments, the appearance of westward propagation of the SSH anomaly is essentially a manifestation of the Rossby wave. As various external forcings are applied, the signal of the Rossby wave is weakened or disturbed, and westward propagation may not appear clearly. In the case of Intrinsic-Seasonal-Exp (Fig. 11b), when analyzing the meridionally mean (37°–40°N) low-frequency SSH anomaly, the westward propagation speed is approximately −0.43 cm s−1. It is smaller than that of Seasonal_VT (−0.90 cm s−1). One of the reasons for the weakening of the westward propagation speed is thought to be the development of a strong eastward current (approximately 7.31 cm s−1) due to the development of the subpolar front by the atmospheric external forcings. Although the westward propagation of the Rossby wave applied with various external forcings is weaker than in the case of Seasonal_VT, the westward propagation of the Rossby wave seems to be one of the important physical mechanisms for the intrinsic variability in the upper-layer circulation of the East Sea.
Longitude–time diagram for the meridionally mean low-frequency sea surface height anomaly (SSHA) from (a) Seasonal_VT and (b) Intrinsic-Seasonal-Exp.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
To analyze the spatial and temporal structures of intrinsic variability in the East Sea, EOF analysis is performed using a zonal-mean low-frequency velocity (5-month low-pass filtered) anomaly at a depth of 90 m in a large variability region (130°–139°E, 36°–42°N), based on Intrinsic-Seasonal-Exp. The first two EOFs account for approximately 54% of the total variance. The spatial distributions of the two modes show different positive peaks (Fig. 12a).
The first mode explains approximately 31.7% of the total variance, and the positive peak appears as a dipole structure around the zonal-mean eastward flow axis (Fig. 12). Through the spatial pattern of the EOF analysis, the first mode can account for the north–south movement of the eastward flow axis, and the principal component of the first mode (PC-1st mode) has a strong positive correlation (correlation coefficient = 0.70) with the time series of the eastward flow axis (Fig. 13a). In the second EOF mode, the positive peak is distributed at the same latitude where the zonal-mean eastward current speed is the largest at a depth of 90 m (Fig. 12). The PC-2nd mode and the intensification of the zonal-mean current are similar (correlation coefficient = 0.81; Fig. 13b). These spatiotemporal patterns of EOFs also exist in other experiments such as Seasonal_VT, Seasonal_VT_Wind and Seasonal_VT_Qnet (not shown here). These results are similar to the EOF analysis for the meandering variability in the Kuroshio Extension region by Taguchi et al. (2007).
(a) The first (blue line) and second (red line) EOFs of the zonal-mean low-frequency velocity (u) anomaly at a depth of 90 m in Intrinsic-Seasonal-Exp. (b) Long-term mean of zonal-mean low-frequency velocity (u) at a depth of 90 m.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
(a) The PC time series of the 1st EOF (blue solid line) of the zonal-mean low-frequency velocity (u velocity) anomalies and the latitude of the eastward jet (black dashed line) at a depth of 90 m. (b) The PC time series of the second EOF mode (red solid line) and the zonal-mean low-frequency velocity at a depth of 90 m (black dashed line) in Intrinsic-Seasonal-Exp.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
Although the results of the experiments according to each external forcing are different, all the experiments show that the physical processes of the intrinsic variability in the East Sea can be formed by the westward propagation of the Rossby wave and changes in the north–south movement of the eastward flow axis and the strength of the eastward flow. Therefore, the intrinsic variability in the East Sea occurs as the westward propagation of the Rossby wave formed at the eastern boundary changes the eastward flow axis to the north–south or the intensity of the eastward flow. It is known that the negative (positive) eddy momentum flux associated with the Rossby wave causes the mean flow axis to move southward (northward), and the mean flow intensifies (weakens) in the convergence (divergence) zone of the eddy momentum flux (Lorenz 2014). We can find the effect of the eddy momentum flux on the mean flow in this experiment, for example, in the case of the 84th year. The 8-month mean eddy momentum flux (
(a) The zonal-mean 8-month averaged eddy momentum flux from May to December in the 84th year, and (b) zonal-mean monthly low-frequency velocity (u) at a depth of 90 m in the 84th year in Seasonal_VT. The blue shaded area indicates the convergence area of the eddy momentum flux.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
6. Conclusions and discussion
The various variabilities in the upper-layer circulation of the East Sea are caused by the variation of the external forcings. The variabilities appear to be large in the southern part, especially in the separation region of the EKWC and the YB. These variabilities are mainly caused by the TWC meandering or eddy activity. The intrinsic variability occurring within the East Sea is also represented in the numerical model experiments applied with external forcings such as climatological annual/monthly mean forcings, similar to other midlatitude western boundary current regions. The intrinsic variability is also largely distributed around the main path of the upper-layer circulation driven by each external forcing. The intrinsic variability in Intrinsic-Seasonal-Exp made a large contribution (approximately 59.6%) to the total variability in the upper-layer circulation over the East Sea.
As discussed in section 4, when compared with Intrinsic-Seasonal-Exp, Intrinsic-Constant-Exp shows a distinct difference in the distribution of the flow variability (Figs. 7b,c). In general, surface cooling due to strong wind stress and surface heat flux in winter is dominant in the East Sea (Fig. 2). Due to these external forcings in winter, the cyclonic gyre and a vertical structure of homogeneous water temperature, along with the formation of cold water, develop in the northern part. In the case of the experiment under constant forcings, the wind stress and surface cooling are weaker than those of the climatological external forcings in winter. When comparing the annual mean SST between the intrinsic process experiments, the cold water below 10°C is distributed over a narrower range in the northern part in Intrinsic-Constant-Exp (Fig. 15). The difference is also evident in the vertical structures of the water temperature along the 134°E line (Fig. 16), which is one of the major areas where deep convection and outcrop occur off the coast of Vladivostok (Kawamura and Wu 1998; Yoon and Kawamura 2002). In Intrinsic-Constant-Exp along the 134°E line, the 8°C isotherm is located at a depth of 100 m between 40° and 42°N, but the upwelling is less pronounced than that of Intrinsic-Seasonal-Exp (Figs. 16a,b). On the other hand, in Intrinsic-Seasonal-Exp, the outcrop of the cold water below 1°C is evident between 40° and 42°N in February, indicating that deep convection is actively occurring (Fig. 16c). Cold water, which is mainly formed off Vladivostok in Russia, flows southwestward in the middle layer along the coasts of Russia and North Korea. As the ventilation becomes stronger, the 2°C isotherm is located at a shallower depth in the southern part of the East Sea (Figs. 16b,c). In winter, the water temperature is vertically homogeneous, and the mixed layer depth develops thickly in the northern part. In this case, strong external forcing energy (momentum/thermal energy) is required to cause variability in the upper-layer circulation. The reason for the smaller variability in the northern part of Intrinsic-Seasonal-Exp than in Intrinsic-Constant-Exp is that much of the cold water is formed by the positive wind stress curl and strong cooling, especially in winter.
The distributions of the annual mean sea surface temperature (°C) in (a) Intrinsic-Constant-Exp and (b) Intrinsic-Seasonal-Exp.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
The vertical structures of the climatological annual mean water temperature (°C) in (a) Intrinsic-Constant-Exp and (b) Intrinsic-Seasonal-Exp, and (c) climatological monthly mean in February in Intrinsic-Seasonal-Exp along the 134°E line. The contour interval is 1°C.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
In other words, since the constant forcings have weaker surface cooling and wind stress compared to the external forcings in winter, the cold water formation area in the northern part is narrow. Therefore, the meandering area moves northward, and the flow variability extends to the north. As mentioned above, through both experiments with constant and seasonal forcings, it is possible to explain that the flow variabilities in the northern part (north of 40°N) of the East Sea in Intrinsic-Seasonal-Exp are smaller than those in the southern part (south of 40°N) due to cold water formation by surface heat flux in winter. Even in the southern part of the East Sea, there is weak variability along the Japanese coast. This is because the Nearshore Branch flows along the Japanese coast in a stable state due to the bottom topography beta effect (Kawabe 1982a,b; Kim et al. 2020).
In this study, it is confirmed once again that intrinsic variability is important in the total variability in the upper-layer circulation of the East Sea. In areas with large flow variability, westward propagation by the Rossby wave appears. The strength of the eastward jet changes in the area with converging/diverging eddy momentum flux, and the axis of the eastward current changes to north–south according to the sign of the eddy momentum flux, which is associated with the Rossby wave (Fig. 14). The dynamics of the intrinsic variability can be understood through these physical processes.
The variability is significantly small in Seasonal_Wind, which is only applied with the wind stress, but the variability in Seasonal_VT is large in the meandering region separated from the coast. This finding suggests that the volume transport flowing through the KTS, rather than the wind stress, is an important forcing factor in forming the intrinsic variability. In Seasonal_VT_Wind, the northern circulation of the East Sea caused by the wind stress and the northward flow caused by the volume transport of the TWC meet to form the subpolar front, and various flow patterns appear around it. Therefore, the wind stress enhances and expands the intrinsic variability formed by the volume transport of the TWC. In Seasonal_VT_Qnet, strong surface cooling in winter develops cold water formation and ventilation in the northern part with smaller variability than that in Seasonal_VT. As a mechanism of intrinsic variability, in this study, the eastward jet axis and intensity changes caused by the Rossby wave propagating westward were mentioned (Figs. 11–13). When comparing SSH anomaly over time between Seasonal_VT and Sesonal_VT_Qnet, Seasonal_VT_Qnet shows less obvious westward propagation than Seasonal_VT (not shown here). This suggests that as the westward propagation of the Rossby wave is weakened, it remains stable with small change in the axis or intensity of the eastward jet. The fact that a stable state is maintained when such a strong eastward jet appears is also similar to the Kuroshio Extension system (Qiu and Chen 2005, 2010).
Additionally, the difference in the intrinsic low-frequency variability of the upper-layer circulation is analyzed in response to the intensity of each forcing from 70% to 130% based on Intrinsic-Seasonal-Exp (Fig. 17). In the case of an experiment in which only the volume transport intensity of the TWC is varied (blue line in Fig. 17), the increasing rate of the flow variability is the greatest as the strength of the external forcing increases. As only wind stress intensity increases, the rate of the flow variability also increases (yellow line in Fig. 17), but the rate is smaller than the experiment in which only volume transport intensity is changed. On the other hand, when the intensity of the surface heat flux is increased, the flow variability gradually decreases (red line in Fig. 17). When only the atmospheric forcings (both wind stress and surface heat flux) are simultaneously increased, the flow variability decreases (green line in Fig. 17), similar to the red line in Fig. 17. However, the flow variability increases in the experiment in which the intensity of all external forcings increased (black line in Fig. 17). Through the above extra experiments, it is confirmed that the change in the intensity of the volume transport among various external forcings has a greater effect on the flow variability than wind stress and/or surface heat flux. This suggests that to predict the future state of the upper-layer circulation in the East Sea, it is necessary to pay attention to the seasonal variation in the volume transport through the KTS.
Spatial-mean RMS of the low-frequency SSH (cm) over the East Sea depending on the intensity of each external forcing based on Intrinsic-Seasonal-Exp. Each line indicates that the intensity of one or two external forcings changes and that of the other external forcings is maintained at 100% strength of the external forcing. For example, “Only the VT” indicates that the volume transport intensity changes from 70% to 130% and a 100% intensity of the other external forcings (wind stress and surface heat flux) is applied. In the case of Intrinsic-Seasonal-Exp, the intensity of all external forcings changes.
Citation: Journal of Physical Oceanography 54, 3; 10.1175/JPO-D-23-0030.1
In the YB, one of the areas where the intrinsic variability was large, it is also considered affected by the bottom topography along with the other external forcings. Some parts of the NB, flowing along the Japanese coast due to the bottom topographic effect (Kawabe 1982a,b; Kim et al. 2020), have a meandering path that escapes the bottom topography effect. Previous studies also showed that the propagation of the topographic Rossby wave was also an important mechanism underlying the variability in the Antarctic Circumpolar Current system (Weijer et al. 2007; Sgubin et al. 2014). Morie et al. (2015) reported that the number of waves of the TWC meander appears to be approximately 3 or 4 due to the limited east–west scale in the East Sea at the point of the standing Rossby wave, and the position where the ridge develops corresponds to the area north of the OS. Therefore, it is necessary to separately investigate whether the wavenumber of the TWC meandering is due to the bottom topography or the east–west spatial scale.
As mentioned in the introduction, intrinsic variability can be found through various ensemble simulations (Leroux et al. 2018; Llovel et al. 2018). In the future, it will be necessary to understand the total variability by using more accurate signals of intrinsic variability through the ensemble experiments.
Acknowledgments.
This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2022-01210 and supported by the Korea Institute of Marine Science and Technology Promotion (KIMST) funded by the Ministry of Oceans and Fisheries (KIMST-20220033) and the Agency of Korea Coast Guard (20220463). The main calculations were performed by using the supercomputing resource of the Korea Meteorological Administration (National Center for Meteorological Supercomputer). We thank reviewers for time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.
Data availability statement.
The data analyzed in this study are available from public websites. The SSH data were obtained from the Copernicus Marine and Environment Monitoring Service (CMEMS; http://marine.copernicus.eu). For the atmospheric external forcings, JRA-55 reanalysis data were provided by the NCAR/UCAR Research Data Archive (accessible via http://rda.ucar.edu/ under dataset number ds628.0).
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