| Citation: | Fan Sun, Fei Yu, Guangcheng Si, Jianfeng Wang, Anqi Xu, Jun Pan, Ying Tang. Characteristics and influencing factors of frontal upwelling in the Yellow Sea in summer[J]. Acta Oceanologica Sinica, 2022, 41(7): 84-96. doi: 10.1007/s13131-021-1967-z
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The Yellow Sea (YS) is a shallow, semienclosed basin located in the Northwest Pacific Ocean and is surrounded by the Korean Peninsula and the Chinese mainland (Fig. 1a). It has an average depth of 44 m and a maximum depth of less than 100 m. Due to the limited depth and geological conditions, the hydrographic properties of the YS are strongly affected by the monsoon system.
In winter, a strong northwesterly wind prevails in the YS, with the effects of surface cooling and wind stirring, and the entire water column in the YS mixes homogenously. During this time, the sea is ventilated, and atmospheric signals can be transmitted throughout the water column. From spring to summer, the surface water begins to warm in association with the increase in solar radiation, and a thermocline begins to form, which isolates the relatively cold water below the thermocline and forms the Yellow Sea Cold Water Mass (YSCWM) (He et al., 1959; Mao et al., 1964; Zhang et al., 1983; Hur et al., 1999; Ren and Zhan, 2005; Yu et al., 2006).
Along the boundary of the YSCWM, the tidal mixing front separates the cold, stratified water on the offshore side from the warm, well-mixed water on the other side (Lü et al., 2010). The formation of the tidal mixing front is closely related to the turbulent kinetic energy induced by the tidal current under the effect of bottom friction (Simpson and Hunter, 1974; Zhao, 1986). The turbulent stress works against the buoyancy force and produces tidal mixing fronts at the bottom. The tidal mixing front has a great impact on the three-dimensional circulation in summer. On the one hand, the tidal mixing front generates a basin-scale cyclonic circulation in the upper layer of the YS, which is known as the Yellow Sea Cold Water Mass circulation (YSCWMC) and has been reported in many observational and numerical studies (Beardsley et al., 1992; Feng et al., 1992; Yanagi and Takahashi, 1993; Naimie et al., 2001; Xu et al., 2003; Xia et al., 2006; Zhou et al., 2015; Lie and Cho, 2016). On the other hand, it triggers frontal upwelling over the slope in the YS (Lü et al., 2010).
Frontal upwelling is an important phenomenon in summer in the YS and exerts a great influence on the distributions of nutrients and biological species. The upwelling carries nutrients (phosphates, nitrates, etc.) from the bottom layer to the upper layer of the YS, which is favourable to the growth and reproduction of phytoplankton. Furthermore, frontal upwelling has a significant effect on the hydrographic features of the YS. In summer, surface cold patches (SCPs) are often observed along the boundary of the YSCWM, especially offshore of the Shandong, Liaodong and Korean peninsulas (Garrett and Loucks, 1976; Xia and Guo, 1983; Lie, 1986; Zou et al., 2001). Xia and Guo (1983) suggested that the sustained SCPs offshore of the Shandong and Liaodong peninsulas are most likely caused by strong upwelling. Thereafter, a numerical model based on thermodynamic equations was applied to describe the upwelling in the YS (Guo and Xia, 1986), and the results indicated that upwellings off Chengshanjiao and the Liaodong Peninsula are mainly induced by centrifugal forces related to the strong tidal current flowing headlands.
Based on satellite images and hydrological investigations, Zhao (1987a, b) found that upwelling mainly exists in the frontal area in the western YS and inferred that upwelling is possibly widespread along the boundary of the YSCWM. Subsequently, the vertical upwelling structure near the frontal area was investigated by a two-dimensional diagnostic model (Bi and Zhao, 1993). Using a three-dimensional nonlinear numerical model, Liu et al. (2003) also suggested that upwelling appears around all fronts in the YS and accounts for SCPs near the frontal area.
A recent hydrological investigation also indicated the existence of frontal upwelling offshore of the Subei Bank and Shandong Peninsula (Yuan et al., 2017). Based on a three-dimensional, wave–tide–circulation coupled numerical model, Lü et al. (2010) demonstrated that the upwelling in the YS is largely induced by the tidal mixing front over the sloping topography, and the large temperature difference across the front leads to a strong baroclinic pressure gradient force in the bottom layer, which triggers upwelling in the bottom layer and downwelling in the upper layer.
Previous studies have mainly focused on the distribution and formation mechanism of frontal upwelling in the YS. However, the factors influencing frontal upwelling strength have rarely been studied. In this study, a three-dimensional hydrodynamic model is applied to solve this problem. The remainder of this paper is organized as follows. In Section 2, observational data and the model configuration as well as its validation are presented. In Section 3, a series of numerical experiments are performed to estimate the effects of several local factors on the intensity of frontal upwelling. Then, the influencing mechanism of the key factors is investigated in Section 4. Finally, conclusions are drawn in Section 5.
Cruise observations were conducted in the western YS during August 19–27, 2015. The cruises covered the sea region west of 124°E, from 32°N to 38.75°N. During this period, there was no tropical cyclone passing over the YS. The temperature was obtained by a SeaBird 911 conductivity-temperature-depth (CTD) profiler and calibrated by SeaBird software with an accuracy of 0.001°C. The CTD investigation was performed along zonal sections in the southwestern YS. Except for the Changjiang River Estuary and Dalian–Chengshanjiao sections, the spatial resolution of most CTD stations was 0.5° in the zonal direction and 1° in the meridional direction. The locations of the CTD stations for the August 2015 cruise are presented in Fig. 1b.
The current measurements were obtained from a mooring Acoustic Doppler Current Profiling (ADCP) located in the western YS (34°N, 122.75°E); the location of the mooring station is presented in Fig. 1b. The ADCP was located at a depth of 44 m with a vertical resolution of 2 m. The observations were conducted from April 8 to October 19, 2015, with a sampling interval of 30 min. To ensure the reliability of the ADCP data, the internal compass was calibrated before launching the ADCP. In addition, the data underwent quality control before analysis, including assessment of horizontal and vertical velocity, percentage of good pings, pitch and roll, echo intensity, correlation magnitude, velocity error, side lobe effects, etc. Ensembles with a percentage of good pings less than 90 were removed. In addition, the first two layers of data (the blind district of the ADCP), data with velocities greater than 2 m/s, and data within 5 m below the sea surface (affected by bubbles and side lobes) were also removed.
Furthermore, a harmonic analysis, which was developed to extract tidal signals from ADCP data, was applied to obtain the tidal currents. When did harmonic analysis of tidal current, eight tidal constituents (M2, S2, K1, O1, N2, K2, P1, and Q1) were adopted, because the time series were long enough (1 month of data with a sampling interval of 30 min), all tidal constituents were extracted successfully, and the total variance of the predicted values accounted for 97.2% of the observed values.
A high-resolution regional circulation model based on the Regional Ocean Modeling System is adopted for the study region. The model covers a domain of 22°–42°N, 117°–140°E with a horizontal resolution of (1/18)°×(1/18)° (Fig. 1a). We adopt a 32-level stretched generalized terrain-following coordinate. For the vertical mixing parameterization, the local closure scheme of Mellor and Yamada (1982) is applied, which is based on the level 2.5 turbulent kinetic energy equations.
The model is driven by the daily wind speed, longwave and shortwave radiation, air temperature, sea level pressure, precipitation, evaporation, and relative humidity, which were provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) through the Interim ECMWF re-analysis dataset with a horizontal resolution of 0.25°. The sea surface temperature (SST) was obtained from Optimum Interpolation Sea Surface Temperature v2.1 with a horizontal resolution of 0.25°, which was supplied by the National Ocean and Atmosphere Administration. Based on these data, the momentum, surface heat and salt fluxes were calculated using bulk formulae (Fairall et al., 2003). The climatological mean sea surface salinity was taken from World Ocean Atlas 2013 (WOA13), and the horizontal resolution from WOA13 was 0.25°. All input forcing datasets are interpolated on the model grid. The monthly mean discharge of the Changjiang River in the model was measured by the Changjiang Water Resource Commission at Datong Station (http://www.cjw.gov.cn/).
The lateral open boundary is forced by monthly means of subtidal sea surface height, velocity, temperature and salinity. Both the boundary data and initial conditions were obtained from the Simple Ocean Data Assimilation (Carton et al., 2018). The tidal forcings with four main harmonic constituents (M2, S2, K1, and O1), which are the most dominant contributors in the YS, are applied to the lateral boundary. The tidal components were derived from the TPXO7 ocean tidal model.
The model is run for 15 years from January 1, 2001 to December 31, 2015. The last 10 years (from 2006 to 2015) are averaged to obtain the climatological upwelling conditions.
Considering the important role that tides play in the YS, the simulated tide is first compared with the observations. The model is run in barotropic mode (setting the temperature to 15°C and salinity to 35) with only tidal forcings added at open boundaries. The modelled co-tidal charts of the M2 constituent (Fig. 2a) show good agreement with previous studies (Wan et al., 1998; Fang et al., 2004; Zhang et al., 2005). Two amphidromic points in the YS are located offshore of Chengshanjiao and Haizhou Bay.
In addition, the harmonic constants of the modelled M2 tide are compared with the observed values (Figs 2b, c). The observed data were derived from 77 tide gauges (shown in Fig. 2a) provided by Wan et al. (1998). The correlation coefficients between the observed and modelled tidal amplitudes and phases are 0.97 and 0.98 (at the 95% confidence level), respectively, with root mean square errors of 22.5 cm and 16.8°, respectively. The comparison suggests a generally satisfactory reproduction of the M2 tide by the model.
Furthermore, the simulated tidal currents are compared with the observed data at the H05 mooring station (Fig. 3). For the depth-mean tidal current, the correlation coefficient between the observed and modelled meridional velocity is 0.94 at the 95% confidence level, and the root mean square error is 0.1 m/s. Similarly, the correlation coefficient between the observed and modelled zonal velocity is 0.97 at the 95% confidence level, with a root mean square error of 0.04 m/s.
To examine whether the model results are able to capture the hydrographic features of the YS, the monthly mean Moderate Resolution Imaging Spectroradiometer (MODIS) SST datasets (https://modis.gsfc.nasa.gov/), with a horizontal resolution of 4 km, are selected for comparison with the model results in August 2015 (Fig. 4). SCPs are easily identified near the coast of the YS, especially offshore Liaodong Peninsula, east of Chengshanjiao on the Shandong Peninsula, Haizhou Bay, Subei Bank, Korean Bay, Kyunggi Bay and offshore Mokpo. Both the MODIS SST and model results show that the temperature in these regions is 2–5°C lower than that in the surrounding waters. The SCPs are stronger near the eastern coast of the YS than the western coast.
The model results match the MODIS SST well; however, there are still some distinctions between them. For example, the area of SCPs offshore Liaodong Peninsula in the model results is larger than that in the MODIS SST, which may be due to the overestimation of the advection effect of the YSCWMC in the model, which could transport cold water from north to south.
In addition, the CTD data conducted in August 2015 are selected to validate the model results (Fig. 5). In summer, the YSCWM is characterized by three cold cores located in the northern, southeastern and southwestern YS, respectively (Fig. 5b), which is in agreement with Weng et al. (1989) and Yu et al. (2006). The northern and southeastern cores are stronger (colder), with the lowest temperatures lower than 6°C, while the southwestern core is weaker (warmer), with temperatures between 8°C and 10°C. Along the boundary of the YSCWM, strong bottom temperature fronts (BTFs) separate the cold water on the offshore side from the warm water on the other side. It should be noted that the simulated BTFs are much stronger than the observations, which may be due to the low resolutions (approximately 0.5° in the zonal direction and 1° in the meridional direction) of the CTD stations.
The distribution of bottom temperature is closely related to the thermocline of the YS. In the shallow region, the water is well mixed due to surface waves and tidal mixing (Qiao et al., 2006). However, in the offshore region, the sea is strongly stratified in the upper layer due to surface heating. To further explore the relationship between the thermocline and bottom temperature, we calculated the maximal vertical temperature gradient as the thermocline strength of the YS. The results show that the thermocline is strong in the central YS but much weaker in the coastal water (Fig. 5c), which causes the bottom water to be warmer near the coast but much colder in the trough. The distribution of the thermocline strength is in agreement with Ge et al. (2006).
Figure 6 shows the temperature distribution along 35°N and 36°N in August. The front and thermocline block the YSCWM at the bottom of the YS, with an envelope line of 10°C. In the frontal area, the isotherm is generally convex and even crops out at the sea surface, which induces SCPs there. In the middle of the YS, the residual water of the Yellow Sea Warm Current, which is warmer and saltier than the surrounding water, separates the YSCWM into western and eastern cores (Xia et al., 2004; Yu et al., 2006).
The comparison between the simulated and observed data shows that the basic temperature distributions of the YS are well represented by the model. However, some defects still persist in the model results; for instance, the thickness of the upper mixed layer is underestimated by simulations (Fig. 4), which may be caused by insufficient surface wave mixing (Qiao et al., 2006; Lü et al., 2010).
Based on multiple years (2006–2015) of model results, the distribution of climatological upwelling velocity at the bottom of the YS in August is shown in Fig. 7a. Upwellings widely occur in the coastal shallow waters of the YS. The upwelling is stronger near the coast of Korea, with the maximum velocity exceeding 5×10−5 m/s; conversely, upwelling near the coast of China is weaker. The distribution of upwelling is in accordance with the SCPs (Fig. 4), both of them are mainly located in offshore Liaodong Peninsula, east of the Shandong Peninsula, Subei Bank and Korean Peninsula.
Furthermore, to better understand the relationship between upwellings and BTFs, the bottom temperature gradient (BTG) is calculated using the following equation:
| $$ {\rm{BTG}} = \sqrt {({\partial T} /\partial x{)^2} + ({\partial T} /{\partial y{)^2}}} , $$ | (1) |
where T denotes the bottom temperature. We choose 3×10−5 °C/m as the critical value of the BTFs according to Liu and Wang (2009); then, the distribution of the BTFs is obtained, as shown in Fig. 7b. The BTFs mainly lie in the coastal YS, with the maximum value exceeding 6×10−4 °C/m, which envelops the YSCWM and induces strong baroclinicity near the frontal area. The distribution of BTFs highly coincides with that of upwellings; both BTFs and upwelling are strong near the boundary of the YSCWM and weak in the interior area. Lü et al. (2010) suggested that strong baroclinicity near the frontal area is the leading cause of frontal upwelling.
The strength of BTFs and upwelling along the coast of the YS (the solid line in Fig. 7b) are represented in Fig. 8 and show significant regional characteristics. Both of them reach extreme values in the offshore regions of (A) Subei Bank, (B) Qingdao, (C–D) Chengshanjiao, (E) Liaodong Peninsula, (F) north of Kyunggi Bay, (G) Boryeong and (H) Mokpo (the positions of A–H are shown in Fig. 7b). Among these positions, the frontal strength is maximal in northern Kyunggi Bay (7.1×10−4 °C/m) and minimal in Haizhou Bay (3.9×10−4 °C/m). Similarly, the mean upwelling velocity is much stronger on the eastern coast of the YS (approximately 3.32×10−5 m/s) than on the western coast (approximately 1.16×10−5 m/s).
The coefficient of the correlation between BTF strength and upwelling velocity is 0.62 in the eastern YS and 0.5 in the western YS, both of them passes significance inspection at the 95% confidence level, which indicates that the BTFs have a certain effect on not only the distribution but also the strength of the upwelling.
Many previous studies have revealed that tidal forcings give rise to the formation of BTFs and related upwellings (Zhao, 1986, 1987b; Lü et al., 2010). Our study further indicates that tidal forcings dominate the semi-monthly variation in bottom upwelling strength (Fig. 9). Accompanied by periodic changes in tidal forcings, upwelling shows a significant spring-neap tidal variation in the YS. During neap tidal phases, the average intensity of bottom upwelling is approximately 2×10−5 m/s. However, the strength doubles to more than 4×10−5 m/s during spring tidal phases.
The analysis above indicates that upwellings widely exist in the frontal area of the YS, and the strength and distribution of the upwelling show significant regional characteristics and largely depend on the BTFs. Strong upwelling always occurs in the strong frontal area and is conducive to forming SCPs.
A characteristic bathymetric feature of the YS is the trough that extends northwestward along the east-central YS, which causes a much steeper slope on the eastern coast and a gentler slope on the western coast. The analysis above also shows that the upwelling in the eastern YS is much stronger than that in the western YS. To investigate the effects of the shelf slope on the upwelling strength, the shelf slopes in the western and eastern YS are set to be identical by setting symmetrical bathymetry in the sensitivity experiment (ExpA). The distribution of the bathymetry in the control run and ExpA is shown in Fig. 10.
The vertical circulation along 35°N (HK section represented in Fig. 7a) is selected to analyse the difference in ExpA (Fig. 11). In the control run, the upwelling is strong along the steep slope on the eastern side of the YS, which brings cold water from the bottom to the upper layer and even reaches the surface of the sea (Fig. 11a); consequently, the thermocline tilts up and ventilates at the sea surface, and the SCPs thus develop offshore of Mokpo (Fig. 4b). However, the upwelling is much weaker and broader on the western side of the YS; as a result, the SCPs in Haizhou Bay are much weaker than those offshore Mokpo.
In ExpA, the bathymetry is set to be symmetrical, and the shelf slope is set to be identical. The double cold cores of the YSCWM disappear in the centre of the YS (Fig. 11b); furthermore, the front near the eastern coast becomes broader and weaker. As a result, the upwelling near the eastern coast is much weaker than that in the control run. In contrast, the upwelling near the western coast in ExpA becomes stronger.
The results show that the shelf slope not only influences the temperature structure but also has a significant effect on the upwelling strength. A steeper slope is more conducive to generating a stronger front and upwelling; in contrast, upwelling along a gentler slope is more likely to be weaker and broader.
Previous studies have indicated that the local wind, topography and stratification have certain impact on the upwelling intensity in the northern South China Sea (Wang et al., 2012, 2014; Shu et al., 2018a, 2018b). However, how external forcings influence the intensity of upwelling in the YS has rarely been investigated. Our analysis above suggests that the upwelling strength is largely determined by the BTFs; moreover, the difference in air temperature between summer and the previous winter could influence the strength of BTFs (Guan, 1963). Thus, we infer that external forcings may influence the intensity of frontal upwelling by changing the strength of BTFs.
To verify our conjecture, several numerical experiments are designed based on the reference month of August 2015. The results for August 2015 are set as the control run (ctl). In each experiment, the air temperature, southerly wind, and precipitation rate are increased by 20% in the previous winter, spring and summer, respectively (Table 1). The change ratios of frontal upwelling in each experiment are analysed.
| Experiment | Forcing conditions |
| Expt1 | air temperature in the previous winter increased by 20% |
| Expt2 | air temperature in spring increased by 20% |
| Expt3 | air temperature in summer increased by 20% |
| Expw1 | southerly wind in the previous winter increased by 20% |
| Expw2 | southerly wind in spring increased by 20% |
| Expw3 | southerly wind in summer increased by 20% |
| Expr1 | precipitation rate in the previous winter increased by 20% |
| Expr2 | precipitation rate in spring increased by 20% |
| Expr3 | precipitation rate in summer increased by 20% |
| Note: The previous winter is defined as December to February, springis defined as March to May, and summer is defined as June to August. | |
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To quantify the influence of external forcings on frontal upwelling, the change ratio (α) of frontal upwelling in each experiment is calculated as follows:
| $$ \alpha = \frac{{{S_{{\rm{exp}}}} - {S_{{\rm{ctl}}}}}}{{{S_{{\rm{ctl}}}}}} \times 100\% , $$ | (2) |
where Sexp and Sctl represent the upwelling strength in the experiment group and control group, respectively. The average change ratio in the entire YS (
| $$ {\alpha _{\rm{A}}} = \frac{{\displaystyle\sum\limits_{i = 1}^k {{\alpha _i}} }}{k} , \; {\alpha _{\rm{W}}} = \frac{{\displaystyle\sum\limits_{i = 1}^m {{\alpha _i}} }}{m},\;{\alpha _{\rm{E}}} = \frac{{\displaystyle\sum\limits_{i = 1}^n {{\alpha _i}} }}{n}, $$ | (3) |
where k denotes the model grid of the entire region of the YS. In addition, the longitude 124°E is selected as the division line of the western YS and eastern YS; thus, m denotes the model grid west of 124°E, and n is the model grid east of 124°E.
The results show that the southerly wind speed and air temperature in summer, as well as the air temperature in the previous winter and spring, significantly impact the strength of frontal upwelling (Fig. 12). Among these forcings, the meridional wind speed in summer is the primary factor. When the southerly wind in summer is increased by 20%, the frontal upwelling in the western YS strengthens by 17.71%; however, the upwelling in the eastern YS weakens by 11.79%.
The secondary factor is the air temperature in summer, followed by the air temperature in the previous winter and spring. When the air temperature in summer is increased, the frontal upwelling in both the western and eastern YS strengthens, with change ratios of +11.05% and +4.4%, respectively. However, when the air temperature in the previous winter and spring is increased, the frontal upwelling in the YS weakens, with change ratios of −3.47% and −2.41%, respectively, which are smaller than those in summer. The influence of precipitation is inappreciable, with change ratios less than 1% (not shown), which can be neglected.
Figure 13 shows the horizontal distribution of the change in magnitude of frontal upwelling in Expt1–Expt3 and Expw3. The results also indicate that an increase in air temperature in the previous winter and spring weakens frontal upwelling in summer (Figs 13a, b); in contrast, an increase in air temperature in summer strengthens frontal upwelling (Fig. 13c). When the southerly wind in summer increases, the upwelling intensifies in the western YS and weakens in the eastern YS (Fig. 13d).
Since the southerly wind speed and air temperature in summer and the air temperature in the previous winter and spring play significant roles in the intensity of frontal upwelling, the influencing mechanisms of these factors are analysed in this section.
The winter process is considered as the key factor influencing the temperature of the bottom water in the YS in summer (Guan, 1963; Zhang and He, 1989; Jiang et al., 2007; Oh et al., 2013; Yang et al., 2014; Li et al., 2015; Zhu et al., 2018). During winter, the entire water column of the YS mixes homogenously due to the strong wind stirring and surface cooling (He et al., 1959), and atmospheric signals can be transmitted throughout the water column. When the air temperature in the previous winter increases, the warm anomaly is transmitted to the bottom of the YS. From spring to summer, the warm anomaly gradually vanishes in the shallow region (Fig. 14a) due to the strong mixing induced by tidal forcing and wind stirring (Qiao et al., 2006). However, in the offshore region, the warm anomaly is preserved due to the strong stratification (Fig. 5c).
To quantify the effect of the vertical mixing process on the variation of bottom temperature anomaly, the vertical diffusion term (VDIF) from February to August 2015 is calculated as follows:
| $$ {\rm{VDIF}} = \sqrt {{\rm{VDIF}}_u^2 + {\rm{VDIF}}_v^2} , $$ | (4) |
where VDIFu and VDIFv denote the vertical diffusion term for u and v, respectively, which are calculated using following formula:
| $$ {\rm{VDI}}{{\rm{F}}_u} = \frac{\partial }{{\partial z}}\left({K_{\rm{v}}}\frac{{\partial u}}{{\partial z}}\right) ,\;{\rm{VDI}}{{\rm{F}}_v} = \frac{\partial }{{\partial z}}\left({K_{\rm{v}}}\frac{{\partial v}}{{\partial z}}\right), $$ | (5) |
where Kv represents vertical eddy viscosity, and u and v represent the zonal and meridional velocity, respectively. The time variation in VDIF along the bottom of the 36°N section is shown in Fig. 14b. The results show that the vertical mixing is much stronger along the coast of the YS than in the trough. In addition, from winter to summer, the strong mixing is sustained in the coastal region and attenuates the warm anomaly there; however, in the offshore region, the warm anomaly does not change much because of the weak mixing. This attenuates the BTFs (Fig. 15a), and frontal upwelling thus slackens due to the weakened baroclinicity.
The results of Expt2 show a similar pattern to Expt1; however, they show smaller magnitudes of the warm anomaly and lower change ratios (Fig. 15b), this is because the stratification begins to form in spring, which restricts the downward transfer of surface heat. When the air temperature in summer increases, the coastal water warms rapidly; however, the bottom water in the central YS does not change much due to the strong stratification (Fig. 5c), which strengthens the BTFs (Fig. 15c) and consequently enhances the frontal upwelling due to the intensified baroclinicity.
When the southerly wind in summer intensifies, the bottom temperature decreases in the western frontal area but increases on the eastern coast (Fig. 15d). This is in accord with the upwelling anomaly in Fig. 13d. The strengthened upwelling in the western YS brings more cold water from the YSCWM to the coastal region along the slope, which makes it colder on the western coast of the YS; in contrast, the attenuated upwelling in the eastern YS makes the bottom water warmer on the eastern coast.
To further explore the influence mechanism of the southerly wind in summer, the u-w anomalies along the 35°N section (HK section in Fig. 7a) and 37.2°N section (CK section in Fig. 7a) in Expw3 are analysed (Fig. 16). In Expw3, the strengthened southerly wind drives more surface water to the east due to the Ekman effect, and the sea surface water thus converges near the eastern coast of the YS and induces a downwelling anomaly in the frontal region. Similarly, the offshore current anomaly near the western coast leads to the divergence of sea surface water and drives an upwelling anomaly along the slope of the western YS. As a result, the upwelling strengthens in the western YS and weakens in the eastern YS due to Ekman pumping.
It should be noted that the southerly wind prevails in summer in the YS, which is conducive to offshore Ekman transport and triggers upwelling along the western coast. Thus, the upwelling in the western YS is the joint effect of the tidal mixing front and Ekman transport.
The mechanism analysis indicates that the air temperature could influence the strength of the frontal upwelling by changing the baroclinicity in the frontal region. At the same time, the meridional wind speed in summer could affect frontal upwelling via Ekman pumping.
A three-dimensional hydrodynamic model is applied to study the characteristics and influencing factors of frontal upwelling in the YS. The results indicate that upwellings widely exist in the frontal area of the YS, which shows significant regional characteristics and is largely dependent on the BTFs.
Sensitivity experiments show that both topography and external forcings have certain effects on the strength of frontal upwelling. A steeper slope is more conducive to generating a stronger front and upwelling; in contrast, upwelling along a gentler slope is more likely to be weaker and broader.
Furthermore, the meridional wind speed and air temperature in summer, as well as the air temperature in the previous winter and spring, have certain impacts on the strength of frontal upwelling. When the southerly wind in summer strengthens, more surface water is driven to the eastern coast of the YS; as a result, the upwelling intensifies in the western YS and weakens in the eastern YS. When the air temperature in the previous winter and spring increases, the warm anomaly is preserved in the YSCWM, which causes the weakening of the BTFs and frontal upwelling. In contrast, when the air temperature in summer increases, the shallow water near the coast of the YS warms rapidly, which intensifies the BTFs and associated upwelling.
We thank the technology support provided by High Performance Computing Center, Institute of Oceanology, Chinese Academy of Sciences.
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Figures(16) / Tables(1)
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Beijing Renhe Information Technology Co. Ltd
Fan Sun, Fei Yu, Guangcheng Si, Jianfeng Wang, Anqi Xu, Jun Pan, Ying Tang. Characteristics and influencing factors of frontal upwelling in the Yellow Sea in summer[J]. Acta Oceanologica Sinica, 2022, 41(7): 84-96. doi: 10.1007/s13131-021-1967-z
| Experiment | Forcing conditions |
| Expt1 | air temperature in the previous winter increased by 20% |
| Expt2 | air temperature in spring increased by 20% |
| Expt3 | air temperature in summer increased by 20% |
| Expw1 | southerly wind in the previous winter increased by 20% |
| Expw2 | southerly wind in spring increased by 20% |
| Expw3 | southerly wind in summer increased by 20% |
| Expr1 | precipitation rate in the previous winter increased by 20% |
| Expr2 | precipitation rate in spring increased by 20% |
| Expr3 | precipitation rate in summer increased by 20% |
| Note: The previous winter is defined as December to February, springis defined as March to May, and summer is defined as June to August. | |
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