Seasonal Variability and Underlying Dynamical Processes of Sea Surface Temperature Fronts in Zhoushan and Its Adjacent Seas

Abstract

The oceanic fronts play an important role in marine ecosystems and fisheries. This study investigates the seasonal variability of sea surface temperature (SST) fronts in Zhoushan and its adjacent seas for the period 1982–2021. The influences of various underlying dynamic processes on the fronts are also discussed. The horizontal gradient of SST is calculated as frontal intensity, and a threshold value of 0.03 °C/km is set to count the frontal frequency. The fronts in Zhoushan and its adjacent seas show significant seasonal variability, with high (0.1 °C/km and 60–90%) and low (0.03 °C/km and 30–60%) frontal activity in winter and summer, respectively. In summer, the fronts along Jiangsu and the north of the Changjiang River Estuary show higher frontal intensity and frequency, which is mainly influenced by the Changjiang diluted water and southerly wind, and fronts around Zhoushan Island are highly related with Zhoushan upwelling. In winter, the fronts strengthen into regular bands offshore and parallel to the coast, which are mainly influenced by coastal currents. Frontal intensity and frequency show a more significant long-term increasing trend in winter than in summer.

1. Introduction

Ocean fronts typically occur in a narrow strip with a high horizontal gradient in physically, chemically, or biologically relevant properties and often form between two water masses with significantly different characteristics, such as temperature, salinity, and density [1,2,3]. Frontal waters typically contain abundant nutrients [4], which are beneficial in promoting phytoplankton growth [5], increasing marine primary productivity, providing abundant bait for fish and other species, and further affecting marine fisheries and marine ecosystems [6,7,8]. Fronts also play an important role in marine pollution. In the frontal zone, the convergence of seawater is commonly enhanced, which can concentrate substances, such as oil pollution, microplastics, and heavy metals, posing a threat to the ecosystem [9,10,11]. The strong non-linear properties of mesoscale and submesoscale fronts in the ocean further increase the heat flux coefficient, enhancing heat exchange at the air–sea interface and tuning air–sea interactions [12,13,14,15]. Therefore, understanding the variability and the dynamic mechanisms of the main fronts in offshore and nearshore waters is of considerable importance.

In recent decades, high-resolution remote sensing data have been widely used in the study of variability in regional ocean fronts on multiple spatial-temporal scales [16,17,18]. Various studies have shown that frontogenesis involves many different dynamic processes [19,20]. Strong western boundary currents, such as the Kuroshio and Gulf Stream, intersect with low-temperature and low-salinity continental shelf waters to form major ocean fronts [21]. Coastal upwelling is another important driver of ocean fronts, which brings low-temperature bottom water to the sea surface [22,23]. Topography is also an important factor in front generation, and sloping terrain can easily induce front formation [24,25,26]. Some studies have found a significant correlation between sea surface temperature (SST) fronts and wind, suggesting that an increase in the wind-driven upwelling increases the frequency of fronts [22,27]. Meanwhile, global climate change would have a profound effect on large-scale oceanic fronts, resulting in several degrees of latitudinal shift [7,28].

Numerous previous studies focus on the detection methods, characteristics, and mechanisms of ocean fronts near the East China Sea (ECS) and pay attention to the influence of ocean fronts on the biochemical environment. The types of ocean fronts in ECS have been systematically summarized based on hydrological observations from 1934 to 1988, along with the seasonal variations in the Kuroshio front and the coastal front in Zhejiang [29,30]. He et al. (1995) [31] identified five types of fronts, namely shelf-break front, thermohaline front, estuarine front, tidal front, and upwelling front, using satellite SST and altimeter data and presented the locations of eight main frontal zones in eastern China Seas. Ning et al. (1998) [32] pointed out that SST data are more suitable for distinguishing and identifying water masses and fronts in ECS during winter, while water color data are more effective in detecting the fronts during summer and fall. Hickox et al. (2000) [33] and Park et al. (2006) [34] calculated the front frequency to approximate the distribution of the main fronts in the Yellow Sea, ECS, and northern South China Sea and analyzed the seasonal variation in the frontal intensity.

However, the majority of the above-mentioned studies focus on large- to meso-scale fronts near the China seas and are based on relatively short-term satellite observation data. Zhoushan and its adjacent seas, as a special part of ECS, are located in the coastal area of Zhejiang, China. Major surface features surrounding Zhoushan Island can be found in the previous studies, including those in the ECS. The SST isotherms are mostly parallel to the isobaths, with a southwest–northeast orientation [35,36,37]; they are mainly dominated by a monsoon with a northerly wind during winter and southerly wind during summer, and the alongshore component of wind stress can drive coastal upwelling during the summer [35]. Along the 20 m isobaths, from the north to the east and south of Zhoushan Island, two major southward coastal currents, namely, the Yellow Sea coastal current and ECS coastal current, persist along the Jiangsu and Zhejiang coasts [38]. These currents can be enhanced by the discharge of Changjiang River and weakened by the southerly summer wind. The inshore branch of the Taiwan Warm current, a northward coastal current, flows near the 50 m isobaths off the southeast of the Zhejiang coast. Changjiang River carries a substantial amount of freshwater and terrestrial materials passing through Zhoushan Island [33,39,40]. The ocean fronts in this area show great diversity and are influenced by numerous physical processes of ocean dynamics. However, few direct studies have been performed on the frontal variability around the Zhoushan Island, and the underlying mechanisms of frontogenesis remain to be extensively discussed.

This study aims to investigate the variability in the fronts in Zhoushan and its adjacent seas based on 40 years of high-resolution SST data. The influences of oceanic dynamics on the front are discussed in different seasons. This study will comprehensively describe the characteristics of seasonal evolution of fronts and their underlying mechanisms in this area. The remainder of this paper is organized as follows: Section 2 describes the data and methodology used in this study, Section 3 analyzes the results, Section 4 provides a comprehensive discussion, and Section 5 presents the conclusions.

2. Materials and Methods

2.1. Study Area

Zhoushan and its adjacent seas are located in the east of Zhejiang Province, China, bounded by the Changjiang River Estuary and Hangzhou Bay to the north, ECS to the east, and Fujian offshore to the south (Figure 1). The coastal bathymetry is primarily northeast–southwest, shallower than 100 m, and has relatively rapid changes in the depth of the water in the east of the Zhoushan Island, as shown by the isobaths in Figure 1. The study area had abundant fishing resources. However, the occurrence of marine heatwaves poses a threat to the marine ecosystem, resulting in alterations in the productivity of marine fish catching and the structure of the community.

2.2. Data

2.2.1. SST Data

The global Operational SST and Sea Ice Analysis (OSTIA) reprocessed analysis product used in this study was obtained from the Copernicus Marine Environment Monitoring Service (CMEMS) [41]. This product provides daily gap-free maps of foundation SST and ice concentration (referred to as an L4 product). This product is a satellite and in situ foundation SST analysis created using the OSTIA system using reprocessed ESA SST CCI, C3S EUMETSAT, and REMSS satellite data and in situ data from the HadIOD dataset. The product is available from 1 October 1981 on a global regular grid at 0.05° × 0.05° resolution. The time range of the OSTIA SST data used in this study is from 1 January 1982 to 31 December 2021. Data can be found at DOI (product): https://doi.org/10.48670/moi-00168 (accessed on 4 June 2023).

Since the OSTIA SST is a product that has already been well quality controlled and provided by CMEMS, these data have been pre-processed for analysis of seasonal and spatial variability based on the calculation of climatological monthly mean SST and SST fronts. The climatological monthly mean SST is calculated from the daily SST data. For example, the monthly mean SST of January each year is calculated first, and then the mean SST of January each year from 1982 to 2021 is used to calculate the monthly mean SST of the climate state. The same method is used for the other months. Then, the horizontal gradient of the climatological monthly mean SST is calculated to analyze the spatial distribution characteristics of the SST fronts.

2.2.2. Current Data

The current data were obtained from the GLORYS12V1 reanalysis product, which is also designed and implemented in the CMEMS framework. GLORYS12 is a global ocean eddy-resolving oceanic numerical model output on a standard regular grid at 1/12° (approximately 8 km) and at 50 standard levels from 1993 to the present. The model is largely based on the current real-time global forecasting CMEMS system. The model component is the NEMO platform driven at the surface by ECMWF ERA-Interim, followed by ERA5 reanalysis for recent years. Observations are assimilated by means of a reduced-order Kalman filter. Along-track altimeter data (sea level anomaly), satellite SST, sea ice concentration, and in situ temperature and salinity vertical profiles are jointly assimilated. This product includes daily and monthly mean files for temperature, salinity, currents, sea level, mixed layer depth, and ice parameters from the top to the bottom. The monthly climatology is downloaded directly and used in this study. This data can be accessed from DOI (product): https://doi.org/10.48670/moi-00021 (accessed on 28 December 2023).

2.2.3. Wind Data

The wind data were obtained from ERA5 monthly averaged data on single levels from 1940 to the present. The ERA5 is the fifth-generation ECMWF reanalysis for the global climate and weather. The reanalysis involves model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. This study used monthly data with a spatial resolution of 0.25°, and a period from January 1982 to December 2021 were used. The climatological monthly average wind was obtained by averaging the corresponding monthly data from 1982 to 2021.This data can be accessed at: https://doi.org/10.24381/cds.f17050d7 (accessed on 10 October 2024).

2.3. Methods

2.3.1. Front Detection

The fronts in Zhoushan and its adjacent seas were detected by calculating the horizontal gradient of the SST. The gradient magnitudes are treated as frontal intensity and are calculated as follows:

$$gra{d}_{\left(x,y\right)}=\sqrt{{gra{d}_x}^2+{gra{d}_y}^2},$$

(1)

where $gra{d}_{\left(x,y\right)}$ is the horizontal gradient at the SST data grid point $(x,y)$, and $gra{d}_x$ and $gra{d}_y$ are the gradient components in the x and y direction as follows:

$$gra{d}_x={\displaystyle \frac{1}{4}}{\displaystyle \frac{\overline{T}·Gx}{dx}},$$

(2)

$$gra{d}_y={\displaystyle \frac{1}{4}}{\displaystyle \frac{\overline{T}·Gy}{dy}},$$

(3)

in which

$$\overline{T}=\left[\begin{array}{ccc}{T}_{\left(x-1,y+1\right)}& T_{\left(x,y+1\right)}& T_{\left(x+1,y+1\right)}\\ T_{\left(x-1,y\right)}& T_{\left(x,y\right)}& T_{\left(x+1,y\right)}\\ T_{\left(x-1,y-1\right)}& T_{\left(x,y-1\right)}& T_{\left(x+1,y-1\right)}\end{array}\right],$$

(4)

$$Gx=\left[\begin{array}{ccc}-1& 0& 1\\ -2& 0& 2\\ -1& 0& 1\end{array}\right];Gy=\left[\begin{array}{ccc}-1& -2& 1\\ 0& 0& 0\\ 1& 2& 1\end{array}\right].$$

(5)

In Formula (5), the Sobel operators $Gx$ and $Gy$, consisting of two 3 × 3 convolution kernels, are used to calculate the gradients $gra{d}_{\left(x,y\right)}$ in the x and y directions, respectively. And $Gy$ is $Gx$ rotated by 90° counter-clockwise. The Sobel operator is known as a simple and effective way of enhancing the visibility of edges in digital images [42,43] and is widely used in a variety of applications. Meanwhile, this operator is easy to use and not only produces good detection results, but also has a smooth suppression effect on noise. $\overline{T}$ is equal to the SST data T in a 3 × 3 convolution kernels composed of the Sobel operator (as shown in Formula (4)). In Formulas (2) and (3), $dx$ is the distance in the x direction between points $(x-1,y)$ and $(x+1,y)$, and $dy$ is the distance in the y direction between points $(x,y-1)$ and $(x,y+1)$. The magnitude of the horizontal SST gradient computed by Formulas (1)–(5) is described as the frontal intensity in this study.

2.3.2. Frontal Frequency

After detecting the daily SST gradients based on the daily SST data, the frontal frequency ($Fp$) can be calculated in each daily gradient map as a ratio of the number of fronts ($N_{front}$) to the number of valid data ($N_{valid}$) during a given time period [44,45]. The $Fp$ is calculated as follows:

$$Fp={\displaystyle \frac{N_{front}}{N_{valid}}}.$$

(6)

A gradient threshold (0.03 °C/km) for the occurrence of coastal fronts is determined based on the results of reprocessing analyses of daily SSTs from OSTIA over a 40-year period, from 1982 to 2021, rather than a pre-defined threshold. Thus, a gradient greater than 0.03 °C/km is considered to be a place or event where an SST front occurred in this study. This threshold is of similar magnitude to the thresholds (0.028 °C/km) used in previous studies [38].

3. Results

3.1. Seasonal Variability

Monthly climatological SSTs are calculated for the period 1982–2021, and the spatial pattern of monthly SST variability is shown in Figure 2. The SST around Zhoushan Island and its adjacent seas show significant monthly variations. In spring (from March to May), the SST isotherms trend from the southwest to the northeast. In March and April, the north is dominated by cold water, which mainly comes from the remnants of winter. In May, the 18 °C isotherm began to converge around Zhoushan Island, indicating that a cold central area caused by upwelling began to form. In summer (from June to August), the average SST in the study area reaches its maximum. However, an evident cold-water center is observed in this study area due to the influence of upwelling. The temperature difference between the center and the periphery of the cold water mass is less than 0.5 °C in June, but exceeds 0.5 °C in July and August. In autumn (from September to November), when the summer upwelling enters the stage of subsidence, the cold-water mass gradually disappears. In September, weak cold-water masses still remained in the center of the study area. Meanwhile, in October and November, the temperature of near-shore water in Zhejiang gradually dropped, and the isothermal distribution returned to the southwest–northeast direction. In winter (from December to January), the isotherms of the mean SST are parallel to the coast of Zhejiang province and the densest in four seasons. The SST gradually increases from the west to the east surrounding the sea waters of Zhoushan Island due to the mixing of cold coastal waters from the north (offshore of Jiangsu) and warm currents from the south (offshore of Zhejiang). The difference in SSTs between the east and west of the study area reaches its maximum throughout the year, indicating that mixed water is conducive to the growth of temperature fronts.

The SST fronts in Zhoushan Island and its adjacent seas also show significant seasonal variability from the spatial distribution of the fronts in each climatological month (Figure 3). In spring, strong temperature fronts are observed along the coast of Zhejiang and the northern part of the Changjiang River Estuary, with an intensity of 0.04 °C/km. However, the intensity of the temperature fronts along the coast of Zhejiang gradually decreased from March to May. Meanwhile, the intensity of temperature fronts in the northern portion of the Changjiang River Estuary shows an increasing trend. In summer, strong temperatures persist on the northern side of the Changjiang River Estuary, and the intensity of the temperature front along the coast of Zhejiang gradually decreases. However, the upwelling front near Zhoushan Island gradually intensifies, and the front intensity reaches more than 0.04 °C/km in July and August. In autumn, the temperature front along the coast of Zhejiang and the northern portion of the Changjiang River Estuary gradually intensifies, while the upwelling front in Zhoushan gradually weakens and disappears. In November, the study area is dominated by the Zhejiang-Fujian coastal front, which forms a coastal front area with an intensity of more than 0.04 °C/km. In winter, the coastal front of Zhejiang-Fujian is the strongest among the four seasons, with a front intensity of more than 0.1 °C/km. This coastal front strengthens from December to January and gradually weakens from February.

The high frequency of the front indicates that frontal events are frequently developed, and the sea-water mixing activity is strong. This study used 0.03 °C/km as the frontal threshold. The SST frontal frequency for the climatological month around the Zhoushan Island and adjacent seas is shown in Figure 4. The study area consistently exhibits a high frontal frequency in each month. A significant seasonal variability is also observed. The frontal frequency is highest along the coastal seas in winter (above 90%), and the spatial distribution is similar to the frontal distribution. The frontal activity began to weaken in spring. Two areas with strong frontal activity are separated by the Zhoushan Island in April, May, and June. In the northwest portion of the Zhoushan Island, near the Changjiang River Estuary, the frontal frequency is greater than 60%, with a maximum reaching over 90%. In the southeast of the Zhoushan Island, the total frontal frequency is approximately 60%. The frontal frequency around the Zhoushan Island began to increase in July and August, but it decreased in September and October. The frontal frequency in September and October also reaches a minimum during the year and began to strengthen in November and reached its maximum in winter. The spatial distribution characteristics of frontal activity are also diverse. The frontal frequency is high in the coastal area around the Zhejiang and Changjiang estuaries and low in the offshore area of ECS. In the north of the Changjiang River Estuary, the frontal frequency in spring and summer is higher than in autumn and winter. In the seas around Zhoushan Island, the frontal frequency in summer and winter is higher than that in spring and autumn. The underlying reasons of this phenomenon will be discussed in next section. In the coastal area of Zhejiang-Taizhou, the frontal frequency also shows prominent seasonal variability and is always associated with high frontal activity. The spatial distribution of the frontal frequency and the corresponding frontal intensity is similar, confirming that Zhoushan and its adjacent seas have high frontal activities.

The analysis of the spatial distribution of the SST frontal intensity and frequency indicated that the SST frontal intensity and frequency in the study area have significant seasonal characteristics. The differences in the seasonal characteristics of the front are influenced by different underlying dynamic processes, especially in the summer and in the winter. However, spring and autumn belong to the transitional season, and the frontal characteristics are the result of alternating and integrating different dynamic processes in summer and winter. Taking summer and winter as the representative seasons, this study analyzes the characteristics of seasonal variability in the fronts around Zhoushan and its adjacent seas and discusses the underlying influencing mechanisms. The climatology of frontal intensity and frequency in summer and winter shows significantly different characteristics (Figure 5). The strong frontal zone in the summer is distributed in different areas of the sea with a distinct regional diversity. Meanwhile, the strong frontal zones in the winter show as a regular band. The frontal zone is roughly divided into three subareas (indicated by the dotted lines in Figure 5) based on the intensity and frequency of the frontal zone in summer and winter. Area A1 refers to the north of the Changjiang River Estuary and the coastal waters of Jiangsu, area A2 indicates the southeast of Hangzhou Bay and the seas around the Zhoushan Island, and area A3 denotes the coastal area of Taizhou, which is also part of the coastal waters of Zhejiang. The different potential dynamic processes are not consistent. Consequently, the frontal characteristics in the three defined areas exhibit significant differences, especially in summer. In area A1, the frontal intensity (more than 0.06 °C/km) and the frontal frequency (more than 60%) are concentrated along the coastal areas of Jiangsu in summer. In winter, the maximum frontal intensity (more than 1 °C/km) and frontal frequency (more than 90%) are observed around the Changjiang River Estuary. In area A2, the summer frontal intensity is greater than 0.03 °C/km, with a summer frontal frequency of about 30–70%. Meanwhile, the frontal frequency in the northeast portion of A2 reaches over 60%. In area A3, a strong frontal zone is located near the coast of Taizhou, with a frontal intensity of about 0.03 °C/km and a frontal frequency near 60% in summer. In winter, the frontal intensity is more than 0.09 °C/km, with a frontal frequency of about 90%.

3.2. Trends in Summer and Winter Fronts

This study aims to further investigate the long-term trends in frontal intensity and frontal frequency in the three subareas in both winter and summer. The annual mean anomalies (annual mean minus multiyear mean) are calculated for each area, and the long-term linear trend from 1982 to 2021 is analyzed (Figure 6). In area A1 (Figure 6a,b), the frontal intensity and frontal frequency show an increasing trend both in summer and winter, but they are more significant in winter. For example, the linear increasing rates of frontal intensity in summer and winter are 2.5 × ${10}^{-6}$ °C/km/year and 1.6 × ${10}^{-4}$ °C/km/year, respectively, but the latter is significantly higher than the former. The linear increasing rates in frontal frequency for summer and winter are 0.05%/year and 0.23%/year, respectively, while the latter is only more than four times that of the former. In area A2, the long-term trends in frontal intensity and frontal frequency in summer and winter are similar to those in region A1, with some differences in specific values. However, the frontal intensity and the frontal frequency in area A3 show a decreasing trend in summer, while they show an increasing trend in winter. In the same region, the long-term trends show significant differences across the different seasons. The trend in winter is larger than that in summer, and the difference in frontal intensity is much larger than the difference in frontal frequency. The regional differences are also evident for the same season. The frontal intensity and frequency in summer show an increasing trend for A1 and A2, but the latter is larger, while A3 shows a decreasing trend. However, the frontal intensity and frontal frequency in winter show an increasing trend in all three regions, but the differences between the specific values are not as significant as those in summer.

Figure 7 shows the spatial distribution of the long-term trends in frontal intensity and frequency in summer and winter from 1982 to 2021, where the black dots represent the grid points that passed the 95% significance test. Whether in summer (Figure 7a,b) or winter (Figure 7c,d), the spatial distribution of the black dots that passed the 95% confidence test for frontal intensity and frequency is highly consistent, indicating a local increase in frontal intensity, which leads to a corresponding increase in frontal frequency. The frontal intensity and frontal frequency show an increasing trend in the three sub-areas; however, their specific values are higher in the winter than in the summer, with significant differences in different areas. In Figure 7a, the trend in summer frontal intensity throughout the year is statistically significant around Zhoushan Island, where the cold boundary of the summer also rises. The trend values of the summer frontal intensity vary between $-4\times {10}^{-4}$ °C/km/year and $6\times {10}^{-4}$ °C/km/year, with the highest trend along Zhoushan Island being greater than $6\times {10}^{-4}$ °C/km/year. The trend values for the winter frontal intensity ranged from $5\times {10}^{-4}$ °C/km/year to $1\times {10}^{-3}$ °C/km/year, with the highest trend in the Changjiang River Estuary greater than $1\times {10}^{-3}$ °C/km/year. However, the frontal intensity in some areas decreased during the period 1982–2021 (Figure 7c).

The spatial distribution of the long-term frontal frequency in A1, A2, and A3 is similar to the frontal intensity (Figure 7c,d) because the appearance of frontal activity determines the magnitude of frontal frequency and then influences the frontal intensity. In A1, an increasing trend in summer is mainly located in the Changjiang River Estuary; however, in winter, it occurs primarily in the coastal areas of Jiangsu. The increased rate in winter is higher than that in summer. In A2, the areas with a significant increase in frontal intensity and frequency tendencies are located mainly in the area surrounding the Zhoushan Island in both summer and winter. In A3, there is a stronger increasing trend observed in winter than in summer, with a double band of increasing trends in the near-shore and offshore areas.

The analysis above indicates that the SST fronts around Zhoushan and its adjacent seas have significant seasonal characteristics and spatial differences. Figure 8 shows the spatial distribution of the summer SST frontal intensity from 1982 to 2021. SST frontal intensity in the summer of the three subareas also significantly varies from year to year. For example, the frontal intensity of A1 in 1984, 1988, 1994, and 1998 are significantly stronger than that in other years, with a frontal intensity of more than 0.05 °C/km. In 1986 and 1989, only a few regions demonstrated a positive intensity of 0.03 °C/km. The frontal intensity in area A2 reached 0.03 °C/km in most years and even 0.05 °C/km in 1995, 2006, 2013, and 2018, while in area A3, it was lower in most years.

The spatial distribution of the SST frontal frequency in summer from 1982 to 2021 in the three regions also has different interannual characteristics (Figure 9). In area A1, the frontal frequency of more than 60% occupied most of the area in 1984, 1988, 1998, 2011, and 2014, even with a high frontal frequency of more than 90% even in 1998. Area A2 had a higher frontal frequency in 1984, 1988, 1994, 1995, 2009, and 2018, with the lowest frontal frequency in 1988. The frontal frequency in area A3 is approximately between 30% and 60% during the period 1982–2021. Although the spatial distribution of summer SST frontal intensity and frequency shows large variability, the spatial distribution of winter SST frontal intensity and frequency in each year from 1982 to 2021 is very similar to the climatological spatial distribution of winter SST frontal intensity (Figure 5c) and frequency (Figure 5d).

Long-term trends in SST frontal intensity and frequency can be closely related to climate change. SST in ECS is closely related to El Niño/Southern Oscillation (ENSO). ENSO also modulates precipitation and monsoon over ECS, which further affects the discharge of the Changjiang River, coastal upwelling, and coastal currents. However, the trends in different subareas are not the same. This is due to the frontal activities in each subareas are dominated by different physical processes in different seasons. For example, in summer, area A1 is mainly influenced by the Changjiang River, area A2 by the Zhoushan upwelling, and area A3 by the Zhejiang coastal currents. In winter, all three subareas are mainly influenced by coastal currents. These influences are discussed in the next section. For frontal activities in winter are more frequent and stronger than those in summer, the increase trend in SST frontal intensity and frequency in winter is significantly larger than that in summer. This implies that climate change may have a greater influence on the physical processes controlling winter fronts.

4. Discussion

This study analyzes the seasonal characteristics of SST fronts around Zhoushan Island in ECS during 1982–2021. Similar to most previous studies, the SST fronts in Zhoushan and its adjacent seas have significant seasonal variation, with a spatial distribution of frontal frequency similar to that of Cao et al. (2021) [38]. However, the results in this study show higher frontal frequency, especially in summer. The major SST front distributions agree well with Hickox et al. (2000) [33], and the SST gradient aligns with the findings of Cao et al. (2021) [38]. Given that the threshold (0.03 °C/km) of the SST fronts in this study is different from previous studies, the magnitude of the frontal frequency is also different. The thresholds of 0.1 °C/km and 0.028 °C/km are considered as the threshold in He et al. (2016) [37] and Cao et al. (2021) [38], respectively.

The formation and evolution of oceanic fronts are typically considered to be the results of the interactions between multiple dynamic processes in the ocean and atmosphere. The SST fronts in Zhoushan and its adjacent seas are subjected to the influences of multiple dynamic processes, such as monsoons, coastal upwelling, Changjiang River discharge, and coastal currents. Therefore, the underlying physical mechanisms of the summer and winter fronts in the study area are briefly discussed below, focusing on the influence of wind, summer upwelling, Changjiang River discharge, and coastal currents.

4.1. Influence of Wind on Fronts

Numerous studies suggest that the wind can induce frontal activities through multiple dynamics, and wind-induced coastal upwelling is one of the most well-known factors driving frontogenesis [3,46].

The summer and winter climatological wind patterns are shown in Figure 10 and present a clear characteristic of the monsoon, with southerly wind dominating in summer and northerly wind dominating in winter. Wind-driven upwelling is dominant in the fronts around Zhoushan Island (A2) in summer [38], where the south winds are conducive to Ekman pumping, resulting in significant upwelling and arousing the evolution of the fronts. Ma et al. (2004) [47] suggested that the coastal ocean fronts along Jiangsu (A1) are highly correlated with the alongshore wind. In winter, the north wind could accelerate high-latitude cold coastal water from the north flow south, improving the mixing and interactions with warm water on the shelf in ECS, which is favorable for frontal generation.

The spatial distribution of the frontal intensity and frequency in winter (Figure 5) shows a much higher intensity and frequency than in other seasons. This phenomenon can also be partly explained by the strong north wind in winter. Given that the wind speed in winter is higher than that in other seasons, it can also enhance surface cooling and water mixing in shallow water. However, the research of Cao et al. (2021) [38] demonstrated that the fronts on the shelf in the east of Zhejiang are not completely determined by the wind pattern. He et al. (2016) [48] revealed that there is no obvious relationship between wind stress and front position shift, while the wind can increase the frontal intensity on the nearshore front (A3).

4.2. Influence of Upwelling on Fronts

Upwelling brings cold seawater from the bottom to the upper ocean layer, typically forming a cold central area at the sea surface. When cold seawater collides with the surrounding warm seawater, it always generates upwelling fronts. The frontal intensity and frontal frequency of the upwelling-induced front are directly related to the intensity of the upwelling. The Zhoushan upwelling is an important and famous coastal upwelling in ECS. A number of studies have focused on the Zhoushan upwelling due to the importance of the Zhoushan fishing grounds. Research on Zhoushan summer upwelling was first published in the early 1960s [49]. To date, numerous studies have verified the existence of Zhoushan upwelling using in situ observation data [50] and satellite remote sensing data, and have also analyzed the characteristics of upwelling [51,52].

However, the mechanisms behind the generation of upwelling in Zhoushan are viewed from different perspectives. The remnants northward of the Kuroshio current and the Taiwan Warm Current play an important role in the upwelling of the Zhejiang coastal seas. The non-linear effects of tides and topography can also cause upwelling [53,54,55]. Early studies have shown that upwelling occurs along the Zhejiang coast in winter [50,56], but no significant low-temperature zone is observed in winter, based on the distribution characteristics of the SST. In this study, the temperature front in area A2 in summer is mainly caused by upwelling, with the intensity and frequency of the front being closely related to the upwelling. In winter, the upwelling current on the eastern side of area A2 is the most closely related to the coastal current.

4.3. Influence of Changjiang River on Fronts

River discharge is an important dynamic factor in estuarine frontogenesis. The Changjiang River contributes approximately 79.7% of the total freshwater input to ECS [32], with a significant seasonal variability in discharge, ranging from approximately 10,000 m³/s in winter to 500,000 m³/s in summer [57]. Shelf mixing water plays a key role in the distribution and variation of the fronts due to a significant differences in temperature and salinity between rivers and seas [30]. When rivers discharge large amounts of freshwater into the ocean, strong mixing occurs between river water and seawater, and these interactions can easily generate temperature fronts and salinity fronts in the estuary.

In the northern hemisphere, when rivers flow into the sea, the freshwater is deflected to the right of the flow direction due to the Coriolis force. Accordingly, diluted water from the Changjiang River should flow south to the seas of Hangzhou Bay and Zhoushan Island. However, in summer, Changjiang diluted water mainly influences the south wind, causing large volumes of freshwater to flow to the north and northeast, reaching the Jiangsu coastal areas. This phenomenon explains why the summer frontal intensity and frequency are high in the north of the Changjiang River Estuary and the coastal waters of Jiangsu (area A1). In winter, Changjiang diluted the flow of water south to the seas of Hangzhou Bay and Zhoushan Island, influenced by the Coriolis force and the north wind in the study area. This phenomenon is an important reason for the weak front in the coastal region of Jiangsu in winter.

4.4. Influence of Coastal Currents on Fronts

The Taiwan Strait Current flows from the southwest to the northeast throughout the year in the research area, characterized by high temperature and salinity, mainly outside the 50 m isobaths [39,58].

In summer, the coastal currents in the study area are mainly the warm currents from the Taiwan Strait that move northward. These currents pass through Zhoushan Island and intersect with the cold water caused by the Zhoushan upwelling, which is conducive to the formation of a front around the sea area of the Zhoushan Island in summer (Figure 11a–c). In the area A3, the intensity and frequency of the SST fronts reach 0.03 °C/km and 60%. The frontal activities are mainly influenced by cold coastal waters from the northwest and warm costal currents from the south.

In winter, the coastal currents in the study area mainly flow to the south from the Jiangsu coast and invade ECS [59]. The coastal currents pass through the Changjiang River Estuary and mix with the freshwater from the Changjiang River, resulting in characteristics of low temperature and low salinity (Figure 11d–f). Low-temperature coastal currents form a significant winter SST front with water from the shelf in ECS. Low-temperature northerly winds can also strengthen low-temperature coastal currents and reduce surface temperature, and also intensify the front [38]. Therefore, the winter SST fronts are mainly influenced by coastal currents.

5. Conclusions

This study presents the seasonal variability in the SST fronts in Zhoushan and its adjacent seas. The spatial and temporal variabilities in the monthly frontal intensity and frequency display significant seasonal fluctuations. The fronts in the study area are further divided into three sub-areas according to the spatial diversity of the fronts in summer and winter: A1 is the area along the Jiangsu coast and north of the Changjiang River Estuary, A2 is the area around Zhoushan Island and parts of Hangzhou Bay, and A3 is the area along the coast of Zhejiang-Taizhou. The frontal intensity and frequency and the underlying dynamic process of these areas can be summarized as follows.

Frontal intensity and frequency, along with the main underlying process, are especially different in summer. In area A1, the frontal intensity reaches approximately 0.06 °C/km and has more than 60% of the frontal frequency. In areas A2 and A3, the frontal intensity and frequency reach up to 0.03 °C/km and 60%, respectively. The frontal activities in three subareas are mainly controlled by different dynamic processes. The diluted Changjiang water and the south wind are the primary drivers of the abundant frontal activity in area A1. The Zhoushan upwelling is responsible for the frontal activities in the area A2, which are also highly influenced by wind, unique topography, tide, and the northward remnants of the Kuroshio and the Taiwan Warm Current. In area A3, the frontal activities are mainly influenced by cold coastal waters and warm costal currents. The summer frontal intensity and frequency show a weak spatial and temporal variation trend during 1982–2021.

In winter, the SST fronts in A1, A2, and A3 merge into a large-scale strong frontal zone, which appears as a red band located in the offshore areas and almost parallel to the coast. The frontal intensity and frequency of this strong frontal zone reach up to 0.1 °C/km and more than 90%, respectively. The wind and cold coastal currents of the Jiangsu coast are the main factors that influence the frontal activities in winter. The north wind strengthens the cold coastal currents from the north and carries the diluted Changjiang water to the south. The mixing of cold coastal currents and warm water in ECS generates this strong front zone. The frontal intensity and frequency in A1, A2, and A3 in winter exhibit an increasing trend during the period 1982–2021, and the linear rate of increase is greater in winter than in summer.

Oceanic fronts play an important role in marine pollution, air–sea interactions, marine ecosystems, and marine fisheries. The analysis of the seasonal variability in the fronts and the underlying dynamic process in Zhoushan and its adjacent seas is crucial for the management of fisheries and coastal pollution. Due to the limited resolution of the SST data, there are still some missing values in the coastal areas, which is not conducive to the analysis of finer-scale frontal features in the coastal regions. It is recommended that high-resolution and high-frequency field observations in the region be used in future studies. Studies on the detailed mechanisms of frontogenesis and its vertical characteristics are still lacking. The influence of other factors, such as topography, surface heat flux, and tides, on the evolution of SST fronts in this region will be investigated in the future. Therefore, numerical model experiments will be used in the future to verify the detailed mechanisms of frontal formation.