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Importance of Diurnal Forcing on the Summer Salinity Variability in the East China Sea
YANG YU,a,b,c SHU-HUA CHEN,c YU-HENG TSENG,d XINYU GUO,a,e JIE SHI,a,b GUANGLIANG LIU,fCHAO ZHANG,a YI XU,g AND HUIWANG GAOa,ba

Key Laboratory of Marine Environment and Ecology, Ministry of Education of China, Ocean University of China,
Qingdao, Chinab
Laboratory for Marine Ecology and Environmental Sciences, Qingdao National Laboratory for Marine Science andTechnology, Qingdao, Chinac
Department of Land, Air, and Water Resources, University of California, Davis, Davis, CaliforniadInstitute of Oceanography, National Taiwan University, Taipei, TaiwaneCenter for Marine Environmental Studies, Ehime University, Matsuyama, Japanf
Qilu University of Technology (Shandong Academy of Sciences), Shandong Computer Science Center (National
Supercomputer Center in Jinan), Shandong Provincial Key Laboratory of Computer Networks, Jinan, Chinag
State Key Lab of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China(Manuscript received 16 August 2019, in final form 1 January 2020)
ABSTRACTThe impacts of diurnal atmospheric forcing on the summer salinity change in the East China Sea are investigated using the Regional Ocean Modeling System, forced by the hourly and daily reanalysis of wind andinsolation. The differences between the forcing of these two frequencies reveal a dipole pattern of salinitychange with a positive salinity deviation (1–2 psu) offshore of the Yangtze River estuary, and a negative
deviation (from 21 to 20.5 psu) along the Jiangsu Coast. Further dye tracking experiments confirm thatdiurnal forcing strengthened the northwestward longshore freshwater transport (NLFT) of the Yangtze Riverby 5.2 3 109 m3 and reduced the mean water age of 7 days. Sensitivity experiments using different forcing
combinations suggest that the diurnal wind, that is, the land–sea breeze, is the key to developing the dipole
pattern of salinity change and the NLFT. Through the experiment, the land–sea breeze induced a mean
clockwise circulation offshore of the Yangtze River estuary. The above changes resulted from both thenonlinearity of wind stress averaging (i.e., the square nature of wind stress) and the baroclinic adjustment
related to the diurnal salinity variation, which is directly connected to the diurnal swing of the Yangtze Riverfront. The baroclinic adjustment generated a dipole pattern of vorticity changes offshore of the Yangtze Riverestuary and a coherent northwestward jet current strengthening the NLFT. These processes developed thesummer dipole pattern of the salinity change.

1. Introduction
Because of the diurnal forcing of solar insolation, atmospheric states within the boundary layer, such as theland–sea breeze, feature a strong diurnal cycle. The influence of diurnal forcing also extends to the ocean, affecting the upper-ocean temperature (Sverdrup et al.
1942). The daytime warming generates a ‘‘thermodynamic
diurnal stratified layer’’ (Fairall et al. 1996a) and increases the sea surface temperature (SST). The nocturnal mixing deepens the mixed layer (Bernie et al.
2005) and thus reduces SST (Price et al. 1986). Throughthe nonlinear oceanic adjustment process, the diurnal
SST relates to the seasonal and intraseasonal SST
Corresponding author: Huiwang Gao, hwgao@ouc.edu.cn

variabilities, which are called the ‘‘diurnal effects’’ insome studies.
Recently, the impacts of diurnal forcing on sea surface
salinity (SSS) have drawn considerable attention. The
diurnal cycle of salinity may influence upper ocean
stratification (Lukas and Lindstrom 1991; Montégut
et al. 2007), which in turn affects SST and air–sea fluxesof heat and momentum (Soloviev and Lukas 2006;
Anderson et al. 1996). Although the diurnal SSS variability is small (Cronin and McPhaden 1999), it is appreciable by the adequate in situ instrumentation (Croninand McPhaden 1999; Drushka et al. 2014) and satellite
remote sensing (Fine et al. 2015). Without considering theevents of extreme rainfalls, the diurnal SSS variation over
the tropical ocean is mainly caused by the asymmetricevaporation and mixing during the day and night (Hodges

DOI: 10.1175/JPO-D-19-0200.1
Ó 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright
Policy (www.ametsoc.org/PUBSReuseLicenses).

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and Fratantoni 2014; Fine et al. 2015). The diurnal
warming increases SST during the day, thus resulting
in strong diurnal evaporation, leading to a saltier,warmer, and more stable surface layer. At night, thesurface cooling induces mixing so that the verticalentrainment decreases the SSS.
Further studies also suggest that the diurnal SSS canbe driven by horizontal transport induced by the diurnal forcing, especially in the area near river estuaries.
Shipboard observations for the Maipo River plume(Piñones et al. 2005) and Neuse River plume (ReynoldsFleming and Luettich 2004) suggest that the sea breeze(wind blowing from the ocean toward the land due to the
air pressure differences created by the different heat
capacities of water and land) weakens the expansion ofdiluted water while the land breeze (wind blowing fromthe land to the ocean) plays an opposite role. The diurnal current caused by the land–sea breeze can accountfor 15%–50% of the kinetic energy in surface currents
over the Hudson River plume region (Hunter et al.
2007) that tune up the river plume variability and change
the SSS (Hunter et al. 2010). Besides, the land–sea
breeze can lead to an increase of local dissipation by propagating Poincaré waves away from the coast at the criticallatitude (308N or 308S) and provides significant verticalmixing over the Mississippi River plume region, which
may have a potential contribution to SSS (Zhang et al. 2010).
The actual mechanism for diurnal forcing to drive SSS variation and its ‘‘salinity diurnal effects’’ remains elusive.
Very few studies have considered the impacts of diurnal forcing on a longer time scale (e.g., seasonal or
longer) of salinity change, compared to the studies of
SST response (Thushara and Vinayachandran 2014;
Bernie et al. 2007; Drushka et al. 2014; Fine et al. 2015).
Hunter et al. (2010) demonstrates that the land–sea
breeze modulates the wind kinetic energy input, thusincreasing the net freshwater transport along the Long
Island coast and reducing the freshwater supplied to the
New Jersey coastal current, which significantly changes
the SSS. Using an idealized study, Qu and Hetland(2019) suggested that the simulation error of the river
plume (the SSS change under different wind frequency)is proportional to the fraction of high-frequency windenergy missing. They concluded that 3- or 4-hourly winds
were needed to properly capture the river plume variability(Qu and Hetland 2019). However, both Hunter et al. (2010)
and Qu and Hetland (2019) only focused on the directwind energy input to the ocean without considering
the mechanisms associated with the current response.
The Yangtze River (also called Changjiang River),the sixth-largest river by discharge volume in the world(Wohl 2008; Vorosmarty et al. 1998), accounts for 90%of the total river discharge into the East China Sea

VOLUME 50(ECS) (Shen et al. 1998; Chang and Isobe 2003). Since it
is controlled by runoff and East Asian summer monsoon, the Yangtze River plume expands northeastward
toward the Cheju Island in summer (Mao et al. 1963;
Beardsley et al. 1985; Chang and Isobe 2003; Moon et al.
2009; Zhu et al. 1997). The summer extension of the
Yangtze River plume substantially modifies the physicalproperties of the water mass such as salinity and stratification over the ECS (Wu et al. 2018). Furthermore, theYangtze River plume may induce stratification that canlead to a current change (Kako et al. 2016). The Yangtze
River plume pattern is sensible to the high-frequency
oceanic diurnal variability such as diurnal and subdiurnal tides. Tidal mixing leads to a detachment of the
Yangtze River plume (Lie et al. 2003; Moon et al. 2010;
Shi and Lu 2011; Wu et al. 2011; Rong and Li 2012). The
Stokes drift induced by tidal motion forms a residual
current, which transports Yangtze River freshwater
northwestward along the Jiangsu Coast in the summer(Wu et al. 2014). However, very few studies have focused on the Yangtze River plume response to the diurnal atmospheric forcing. A preliminary study over the
ECS by Yu et al. (2017) suggested that the diurnal
forcing is likely to affect the Yangtze River diluted waterand its front and thus has the potential to change temperature. In this study, we explore the impacts of diurnal
forcing on the summer salinity changes in the ECS andinvestigate the mechanisms that control salinity changes.
This can enhance our understanding of modeling longterm material transport, such as marine debris and oil
spill disasters, in the midlatitude shelf sea.
The structure of this paper is as follows. Section 2
describes the methodology and numerical experiments.
Section 3 presents the results of the model experiments,and section 4 explains the formation mechanism for thesalinity deviation patterns induced by the diurnal forcing. Section 5 examines the sensitivity of the salinity
deviation patterns to the forcing frequency. Conclusions
and suggestions are provided in section 6.

2. Methodology and numerical experimental
designa. Ocean model configuration
In this study, a moderate-resolution Regional Ocean
Modeling System (ROMS) model (Shchepetkin and
McWilliams 2005) is applied to investigate the summer
salinity change induced by the diurnal atmosphericforcing in the ECS. The model has been shown to simulate diurnal and seasonal temperature variations (seeFig. 3 in Yu et al. 2017). The model configuration usedhere is the same as that used in Yu et al. (2017), including
the Mellor–Yamada level-2.5 turbulence closure scheme

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(Mellor and Yamada 1982) for vertical mixing and the
Smagorinsky diffusion parameterization (Smagorinsky1963) for horizontal diffusions. The model resolution is
1/188 (;6 km) and ranges from 248 to 41.38N and from1178 to 1328E (Fig. 1). The model has 30 terrainfollowing ‘‘S’’ levels in the vertical direction with higher
resolutions near the sea surface using the Shchepetkin’s
double stretching function (Shchepetkin and McWilliams2009), and the thickness of the top model layer is lessthan 1 m (Bernie et al. 2005). We integrate the modelfor 5 years from 1 January 2011 to 31 December 2015,and hourly model outputs are stored for analysis.
Before running a 5-yr simulation, the model is spun up
for 30 years, from 1 January 1981 to 31 December 2010,
starting from the climatological temperature, salinity
and flow fields. The Simple Ocean Data Assimilation
Version 3 (SODA3) reanalysis data with a spatial resolution of 1/48 (;27 km) and a temporal resolution of
5 days (Carton et al. 2018) is used to create the lowfrequency lateral boundary conditions of sea surface
height (SSH), currents, temperature and salinity. Ten
principal tidal constituents—M 2, S2, N2, K2, K1, O1,
P1, Q1, Mf, and Mm—derived from the Oregon State
University global inverse tidal model of TPXO7.0(Egbert et al. 1994; Egbert and Erofeeva 2002), are specified as the high-frequency lateral boundary conditions.

b. Atmospheric forcing and numerical experiments
Atmospheric forcing is critical to temperature andsalinity responses from the diurnal to seasonal timescales, and is therefore described first. Solar insolation
was directly employed using a double exponential absorption function (Paulson and Simpson 1977) with
Jerlov water type II parameters [light absorption parameters for dirty coastal water; see Table 2 in Paulsonand Simpson (1977)]. The radiative cooling caused bylong wave radiation was calculated by the Berliand algorithm, based on the blackbody radiation formula(Berliand 1952). The latent heat, sensible heat, andwind stress were calculated by the COARE 3.0 bulk
formulas (Fairall et al. 1996b; Fairall et al. 2003). The‘‘cool skin’’ effects on sea surface heat and vapor
fluxes were also considered using an empirical correction scheme (Fairall et al. 1996a).
The 6-hourly National Centers for Environmental
Prediction–National Center for Atmospheric Research(NCEP–NCAR) reanalysis data (Kalnay et al. 1996) areused to provide atmospheric forcing for the model
spinup run, including wind speed (10 m), solar radiation,
air temperature (2 m), air pressure (2 m), precipitation
rate, cloud fraction, and relative humidity. However, forthe 5-yr sensitivity experiments, the surface winds andsolar radiation, which control the oceanic diurnal cycle in

635

FIG. 1. Model domain and bottom topography. Contour lines
indicate water depth (m). Red circles show river estuary locations.
The hatches along Jiangsu Coast mark the region selected to calculate the northwestward transport of Yangtze River freshwater.
The black pentagram is the buoy site used in the study.

the ECS (see Table 2 in Yu et al. 2017), are replaced by
the fifth generation of the European Centre for MediumRange Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate (ERA5) dataset (Copernicus
Climate Change Service 2017). This reanalysis is a stateof-the-art atmospheric reanalysis product, which provides
hourly estimates of the meteorological parameters with a
1/48 resolution. The hourly output data allow us to conduct
sensitivity experiments with different time resolutions.
Because the model resolution (1/188) is much higher
than the reanalysis data, atmospheric forcing was linearly interpolated to each model point for every time
step. Table 1 shows four sensitivity experiments incombinations of daily mean and hourly diurnal data ofsea surface wind and solar radiation obtained from the
ERA5 dataset. Other atmospheric forcing variables
used daily mean values, averaged from the 6-hourly
NCEP–NCAR data in the four sensitivity experiments.

c. River discharge
Freshwater input from rivers, especially the Yangtze
River, is another key factor contributing to the SSS
distribution in summer (Kim et al. 2009; Moon et al.

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TABLE 1. List of model experiments conducted in this study. The
daily 10-m wind is obtained by averaging hourly 10-m winds withina day. The same procedure is applied to daily solar heating.
Forcing type
Daily case
Diurnal case
Case 1Case 2

Daily 10-m wind; daily solar heating
Hourly 10-m wind; hourly solar heating
Hourly 10-m wind; daily solar heating
Daily 10-m wind; hourly solar heating2009). The model had ten rivers inside the model domain, for example, the Yangtze, Yellow, Huaihe,
Liaohe, Haihe, Luanhe, Minjiang, Qiantang, Yalu, and
Han Rivers (river estuaries are shown in Fig. 1).
Because the observed river runoff shows significantlyinterannual variability (Senjyu et al. 2006; also see
Fig. 2) and the Yangtze River can account for 90% of
the total river discharge into the ECS (Shen et al. 1998;
Chang and Isobe 2003), monthly river discharge datafrom January 2011 to December 2015 at the Datong
Station (Ministry of Water Resources 2011, 2012, 2013,2014, 2015) are used in this study to account for the
Yangtze River discharge (Fig. 2). Climatological monthly
mean discharge data (not shown), derived from the
Global River Discharge Project (http://daac.ornl.gov/
RIVDIS/rivdis.shtml) (Vorosmarty et al. 1998) are used
for other rivers. In the model, the river diluted water wasdischarged into all model layers (30 layers) at the upstream region of the river with 0 psu. The river temperature was derived from the climatological monthly
SODA3 data at the nearest grid point because no observational data are available. We note that the river
freshwater usually includes meltwater, which normallyoccurs in the early spring. This implies that the modeledriver temperatures might be higher than the real values
if the meltwater effect is ignored, such as in this study.

3. Model resultsa. Summertime salinity in the ECS
The modeled summertime salinity in the ECS is initially verified by a comparison with field observationaldata, obtained from a summer cruise that was conductedby Ocean University of China from 5 to 25 July 2011.
The detailed information for this summer cruise can befound in Quan et al. (2013).
Compared to observations (Fig. 3a), the spatial distribution of salinity at the 5-m depth is reasonably
reproduced by both the diurnal case (the hourly
forcing case; Fig. 3b) and daily case (the daily forcing
case; Fig. 3c). The salinity distribution clearly shows afreshwater plume pattern with the salinity less than 32
psu, which extends northeastward from the Yangtze

FIG. 2. The discharge rate of the Yangtze River for each monthfrom 2011 to 2015.

River estuary to the Cheju island. These results are
consistent with the previous studies (Mao et al. 1963;
Beardsley et al. 1985; Su and Weng 1994; Chang andIsobe 2003; Moon et al. 2009; Zhu et al. 1997). However, alarge difference (about 12 psu) exists between the simulated and observed salinities in the vicinity of the Yangtze
River estuary (e.g., the location with the lowest salinity
in Fig. 3a). This is possibly caused by model errors andthe nominal 6-km resolution river mouth topography
used in the model that cannot capture the detailed salinity change in the river/ocean interaction. However,
the model can still reasonably simulate the summertime salinity in the ECS. The root-mean-square error(RMSE) is 2.84 psu in the diurnal case, slightly better
than that in the daily case (2.98 psu). The relative salinity biases, defined as the ratio of the model salinity
bias to the observed salinity [i.e., (Smodel 2 Sobs)/Sobs,
where Smodel and Sobs are simulated and observed salinities, respectively], in both the diurnal and daily cases
are between 220% and 20% in more than 90% of thehydrological stations (Fig. 3d).

b. Time variation of salinity at the outer zone of the
Yangtze River estuary
We further verify modeled SST and SSS in the ECS
by comparing results with observations at a buoy site(1248E, 318N) outside of the Yangtze River estuary from
1 May to 31 October 2015. This buoy was operated by
Xiamen University and provided hourly SST and SSS(Figs. 4a,b). Unfortunately, due to the malfunction of
the salinity sensor, no salinity observations are available
from 11 July to 23 September (Fig. 4b) when the model
river freshwater front passes this site from the diurnal case
(Figs. 4c–e). Nevertheless, the rest of SSS observations still

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FIG. 3. Distributions of salinity at 5-m depth from the (a) summer cruise, (b) diurnal case, and (c) daily case.
(d) Scatterplot diagram for model errors. Blue dashed lines in (d) represent the relative salinity deviation. Modelsalinities in (b) and (c) are time-averaged values over the duration of the summer cruise. However, model snapshot
values corresponding to the exact times of the observational data are used in (d).

provide a great opportunity to verify the model performance. To highlight the impacts of diurnal atmosphericforcing on SST and SSS changes, the tidal signals in boththe SST and SSS time series are removed (Figs. 4a,b) using
the T-tide toolbox (Pawlowicz et al. 2002).
Similar to the temperature response reported by Yu
et al. (2017), the diurnal forcing decreases the systematic
bias of SST about 0.58C (Fig. 4a) due to its direct modulation of surface heat fluxes and vertical mixing (Yuet al. 2017). Regarding to the SSS, a RMSE difference of
0.24 psu is found between the diurnal case and the dailycase but the diurnal forcing does not improve the salinity
simulation at this station, that is, larger RMSE for SSS in
the diurnal case than in the daily case (Fig. 4b). One
possible reason is the 28 NCEP–NCAR daily precipitation data used in both simulations does not capture
the intensity of a heavy precipitation event near this sitefrom 11 to 12 May (figures not shown), causing themodel’s SSS bias from negative (before 11 May) topositive (after 12 May). This is evidenced by a muchlarger SSS drop in the observation than in both diurnal and daily cases during that day (Fig. 4b).
Nevertheless, the model reasonably simulates the diurnal SST and SSS variations at this buoy site. During theobservational period from May to October, the average
diurnal amplitude changes (daily maximum minus daily
minimum) of SST and SSS from the diurnal case are 0.228C(red line in Fig. 5a) and 0.06 psu (red line in Fig. 5b), respectively, while those from observations are 0.238C for
SST (black line in Fig. 5a) and 0.07 psu for SSS (black line
in Fig. 5b). The correlation of diurnal SST between thediurnal case and buoy observation is 0.94 (P , 0.01;
Fig. 5a) and that of diurnal SSS is 0.62 (P , 0.01; Fig. 5b).

c. Dipole-pattern salinity deviation induced by
diurnal forcing in summertime
While the model simulations from both the diurnal caseand the daily case for salinity in the ECS are comparable

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FIG. 4. Time series of detided hourly (a) SST and (b) SSS from 1 May to 31 Oct 2015 for the diurnal case (red curve), the daily case(blue curve), and observations (black curve) at the buoy site (318N, 1248E). The spatial distribution of daily mean SSS on (c) 28 Jul,(d) 5 Aug, and (e) 15 Aug 2015 in the diurnal case. Buoy temperature and salinity are measured at the depth of 0.5 m, and thus themodel SST and SSS are linearly interpolated to this depth. Contour lines in (c)–(e) represent the salinity field and the black pentagram is the buoy site.

(Figs. 3 and 4), the discrepancies between these two numerical experiments do exist, indicating that the diurnal
forcing may regulate the salinity distribution in summer.
The diluted water, by the extension of the Yangtze River
freshwater, is commonly identified by the 32-psu isohaline (Kako et al. 2016; Su and Weng 1994). This 32-psu
isohaline only reached the southwest of Cheju Islandin the diurnal case (Fig. 3b) but almost surrounded Cheju
Island in the daily case (Fig. 3c). This implies that the

Yangtze River plume can expand more northeastward
in the daily case than in the diurnal case (Fig. 3b
versus Fig. 3c).
To understand this summertime salinity variation induced by the diurnal forcing in detail, we present themonthly SSS difference between the diurnal case andthe daily case from May to August 2011 in Fig. 6. A
dipole-pattern SSS difference is clearly shown in the
ECS; a positive 1–2-psu salinity difference (i.e., diurnal

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We further examined the causes in the following
sections.

d. Quantification of freshwater transport
To quantify the impacts of diurnal forcing on the
Yangtze River freshwater transport, a few experimentswith dye tracer tracking were conducted, using thepassive tracer-tracking model in ROMS. In the passive
tracer-tracking model, the dye tracer, which is treatedas a scalar in a model, does not interact with any model
variable and is only transported by advection and diffusion. Dye tracers are released from the Yangtze Riverestuary with a concentration of 100, which can represent
the Yangtze River freshwater proportion. In the dye
tracking experiments, the water age of Yangtze River
freshwater is calculated based on the constituentoriented age and residence time (CART) theory(Deleersnijder et al. 2001; Delhez et al. 1999). The
water age is defined as the elapsed time since thewater mass leaves the place where the passive dye
tracer is released. It is a useful measure of the timescale for general matter transport and has been successfully applied to many coastal studies, especiallyfor Yangtze River freshwater water transport (Zhuand Wu 2018; Wang et al. 2015).
In the passive tracer-tracking model, the dye tracer
concentration and water age are calculated using thefollowing equations:

FIG. 5. Diurnal variations (hourly data minus their dailymean) of (a) SST and (b) SSS at the buoy site. Data are averaged
during the observation period from May to October 2015. The
black line denotes the buoy observation, and the red line is thediurnal case.

forcing increases the SSS) outside the Yangtze Riverestuary and a negative difference from 21 to 20.5
psu (i.e., diurnal forcing decreases the SSS) in Jiangsu
Coast. The range of this dipole pattern evolved over time.
The positive SSS difference was extended northeastward(shading color in Figs. 6a–c) to the vicinity of Cheju
Island, from May to July, when the Yangtze River dilutewater expanded northwestward (gray dashed lines in
Figs. 6a–c). Consequently, its magnitude gradually decreased from July to August as the freshwater expansion slowed down (Figs. 6c,d). The negative SSS
difference region continuously expanded northwest
along the Jiangsu Coast from May to August (Figs. 6a–d).
Apparently, this dipole-pattern of salinity difference
was induced by the diurnal forcing, which was the only
difference between these two numerical experiments.

›C
1 =  (VC 2 K  =C) 5 0 ,
›t

(1)

›a
1 =  (Va 2 K  =a) 5 C ,
›t

(2)

a
a5 ,
C

(3)

where C is the dye concentration, V the velocity vector,
K the diffusivity tensor, a the age concentration, and a
the water age (the average elapsed time since the dye
tracer released).
The distributions of dye concentration (Figs. 7a,b) andwater age (Figs. 7d,e), in both the diurnal case and dailycase, clearly show a plume pattern that originated fromthe Yangtze River diluted water. Due to mixing anddilution processes, the dye concentration decreases
with the increasing distance away from the river mouth(Figs. 7a,b). The simulated water age in the Jiangsu
Coast ranges from 80 to 160 days, with an average of
120 days, and this result is consistent with a previous
study (Zhu and Wu 2018). A dipole pattern is also
found in the dye concentration difference between thediurnal case and the daily case (Fig. 7c). The negative
dye concentration deviation (from 26 to 21) outside

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FIG. 6. Monthly mean differences of SSS between the diurnal case and the daily case in (a) May, (b) June, (c) July,and (d) August 2011. Gray dashed lines show monthly SSS in the daily case.

of the Yangtze River estuary and the positive deviation (1–3) in Jiangsu Coast echoes our early discussionthat the diurnal forcing enhanced more Yangtze River
freshwater transport northwestward along Jiangsu
Coast rather than heading northeastward. The water
age difference between these two experiments alsosuggests this change; positive water age deviation of
5–10 days in the northeast region of the Yangtze River
plume and negative deviation from 210 to 25 days in
Jiangsu Coast (Fig. 7f). The shorter water age near the
Jiangsu Coast suggests that it took less time to transport the Yangtze River freshwater northwestward
along Jiangsu Coast in the diurnal case than in thedaily case.
To quantify this enhanced freshwater transport, we
calculated the changes of the volume and freshwater
age of NLFT in the selected region, shown as the hatch
area in Fig. 7f. Using the dye concentration, which

also represents freshwater proportion in water mass,
the freshwater volume and freshwater age of NLFT
can be estimated using the following equations:

ð
C
dy ,
(4)
FV 5
CIni
FA 5

1
V

ð


a dy ,(5)

where FV and FA are the freshwater volume and age,respectively, C the passive tracer concentration, CIni
the initial tracer concentration when the tracer is released and is set to 100 in this study, a the water age
calculated from Eq. (3), hi the time average operator,
V the total water volume in the selected region, and dy
the differential volume.
The average volume of the NLFT in the selected region from May to August during the 5-yr-period (fromMARCH 2020

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FIG. 7. Distributions of (top) dye tracer concentration and (bottom) water age of Yangtze River diluted water in (a),(d) the diurnal case,(b),(e) the daily case and (c),(f) the difference between the diurnal case and the daily case. Values for this figure are averaged over May–
August from 5 years of simulation. Results in the region where water age was above 200 days were not shown to avoid excessive values ofwater age in (d) and (e). The areas surrounded by black and red dashed lines are selected regions used to calculate salinity deviations in
Fig. 8 and Table 2. The hatching in (f) is the selected region for the NLFT calculation.

2011 to 2015) sensitivity experiments was 10.40 3 1010
and 9.88 3 1010 m3 in the diurnal case and the daily case
(Table 2), respectively. Compared to the daily case, thevolume of NLFT was increased by 0.52 3 1010 m3(;5%) and the freshwater age of NLFT was decreasedby 7 days (;4%) (Table 2) in the diurnal case. Thesechanges in the volume and freshwater age of NLFT inthe diurnal case correspond to the reduced SSS in the P
region (by 0.9 psu, ;4%) and the increased SSS in the N
region (by 1.7 psu, ;7%) (Table 2; see Fig. 7c for the P
and N regions). The volume difference of NLFT correlates very well with the salinity deviation in the P region(negative correlation r 5 20.98, p , 0.01) and correlates
moderately with the salinity deviation in the N region(positive correlation r 5 0.69, p , 0.2) over the 5-yrperiod model integration (Fig. 8).

4. Mechanisms study

1 shows very similar salinity result to that of the diurnal case; decreased and increased SSS by 0.9 and1.6 psu over regions P and N, respectively. This isassociated with increased mean volume of NLFT
(5.3 3 109 m3) and decreased freshwater age by 8 days
(Table 2). On the other hand, the case 2 shows almost
no difference in salinity compared to the daily case
(Table 2). These results suggest that the diurnal windeffect alone (case 1) can sufficiently explain the dipole pattern of the salinity difference and the changes
in NLFT in the diurnal case, while the direct heating
induced by the diurnal insolation (case 2) plays norole on the salinity changes.

TABLE 2. Average sea surface salinity in the P and N regions (seeFig. 7c) from May to August during the 5-yr-period model integration and the volume and freshwater age of northwestward
longshore freshwater transport (NLFT) of diluted Yangtze River
water in different experiments.

a. Key diurnal factor contributing to salinity changes
To further clarify the mechanism involved in thesalinity changes, we first carried out two sensitivity
experiments (Table 1) to address the key factor in thediurnal forcing. Either the wind (case 1) or solar insolation (case 2) is changed from daily to hourly while
the rest of the configurations is kept the same as thosein the daily case. Compared to the daily case, the case

NLFT

Daily case
Diurnal case
Case 1Case 2

Salinityin region
P (psu)Salinityin region
N (psu)

20.3
19.4
19.4
20.3

24.0
25.7
25.6
24.0

Mean
volumeWater(31010 m3) age (day)
9.88
10.40
10.41
9.87

166
159
158
166

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FIG. 8. Volume (black dashed line) and freshwater age (blue dashed line) differences of
Yangtze River NLFT in selected region shown in Fig. 1 and the SSS differences in the P (red line)
and N (green line) regions between the diurnal case and the daily case. The P and N regions areshown in Fig. 7. Values for this figure are averaged from May to August of each year.

b. Salinity budget and clockwise circulation anomaly
The above sensitivity experiments suggest that thediurnal wind is the primary contributor to the summertime salinity change. To further explore how thediurnal wind generates the dipole pattern of the salinity
difference in the ECS, we first evaluate the changes ofthe seasonal mean (from May to August over the 5-yr
integration) salinity budget between the diurnal caseand the daily case in the mixed layer. The mixed layer
salinity budget can be expressed as follows (Kakoet al. 2016):›Sm(E 2 P)Sm
5 2U=  Sm 1
1 residual,
›t
hm

(6)

where Sm is the mixed layer salinity, U the horizontal
current vector in the mixed layer, E and P the evaporation and precipitation at the sea surface, respectively, and hm the mixed layer depth. The mixed layer
depth in this study is defined as the minimum depth ofthe vertical density gradient greater than 0.01 kg m21(Thomson and Fine 2003). The term on the left-handside of Eq. (6) is the local change rate (or tendency) of
salinity in the mixed layer. The three items on the righthand side of Eq. (6) are horizontal advection, surface
salination forcing, and residual term, respectively. The
residual term includes salinity diffusion and entrainment
from the bottom of the mixed layer.
The difference of the salinity tendency between thediurnal case and the daily case shows a dipole pattern insummer (Fig. 9a), a positive change of 1–2 3 1026 psu s21
outside of the Yangtze River estuary and a negativechange from 25 to 21 3 1026 psu s21 in the Jiangsu
Coast. If we integrate this tendency difference for aperiod of one month (over 30 days), we obtain salinitychanges on the order of 1 psu, consistent with the salinity changes presented in section 3. The dipole-likesalinity tendency difference (Fig. 9a) was mainly causedby the horizontal advection (Fig. 9b) and the surface salination forcing (Fig. 9c). The residual term has only limited
impact on this salinity tendency difference (Fig. 9d).
Interestingly, the signs of the horizontal advection(Fig. 9b) and surface salination forcing (Fig. 9c) are
opposite and this implies a large compensation between
these two terms. And as expected, this compensation
mainly exists at the western side of the ocean domain(i.e., close to the coastal region), the reasons are twofold.
As the surface salination forcing is modulated by theratio of the salinity Sm to the local mixed layer depth hm.
Moving away from the coast, the faster deepening rateof the mixed layer depth (figure not shown) overpowers
the slower salinity increasing rate and, as a result,quickly damps out the surface salination forcing toward
the east (i.e., away from the coast). But toward thecoastal region, where the mixed layer is shallower andthe salinity change becomes important in the surface
salination forcing term, the positive salinity advection(e.g., Sm increases) enhances negative salination forcing (e.g., a negative response as E 2 P in Eq. (6) is
negative; Figs. 9b,c) and vice versa, acting like a restoration force. While the horizontal advection andsurface salination forcing had the same magnitude, thehorizontal advection (Fig. 9b) had the same sign as thesalinity tendency (Fig. 9a). This means that although

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FIG. 9. Distribution of (a) salinity change rate, (b) horizontal advection, (c) surface salination forcing, and (d) the
residual term differences between the diurnal case and the daily case in the mixed layer salinity budget.

there was strong competition between the advection
and surface salination forcing (Figs. 9b,c), the changes
caused by the advection term (Fig. 9b) still play adominant role in forming the dipole pattern of the salinity difference between the diurnal and the daily casein this study.
The summer (average from May to August) SSS andthe ocean surface flow for the diurnal case, the dailycase, and their differences are further provided inFig. 10. Both the diurnal case (Fig. 10a) and the dailycase (Fig. 10b) show that the Yangtze River diluted
water had two expansion branches in summer. One
was the northeastward offshore freshwater transport
path conducted by the East Asian summer monsoon(Mao et al. 1963; Beardsley et al. 1985; Chang andIsobe 2003; Moon et al. 2009; Zhu et al. 1997) and theother was the NLFT conducted by the residual currents(Wu et al. 2014). The surface flow difference (Fig. 10c)further suggested a clockwise circulation difference,
which was induced by the diurnal wind in the frontal
region of Yangtze River plume in summer. As discussed above, the advection term dominates the salinity tendency changes between the diurnal case andthe daily case. This clockwise frontal circulation anomaly (CFCA) results in a decrease in east-northeastward
transport of Yangtze River freshwater and an increasein north-northwestward NLFT of Yangtze River freshwater (Fig. 10c).

c. Flow response to land–sea breeze
To better understand this CFCA, induced mainly by
the diurnal wind, we further examine the summer(May–August) 10-m wind and surface flow differences(the diurnal case minus the daily case) over the Yangtze

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FIG. 10. Distribution of summertime (average from May to August over the 5-yr-period model simulation) SSS
and surface flow field in (a) the diurnal case, (b) the daily case and (c) their differences. (d) SSS and surface flow
differences between the dailyWS case and the daily case in section 4c. Contour lines and shaded colors indicate
salinity, and the blue vectors represent the flow field.

River plume region, where the water age was less than
200 days in the dye tracking experiments (Figs. 7d,e).
Figure 11a shows the time series of the hourly mean
(averaged over the same hour during the 5-yr model
integration) zonal wind (10-m U wind) difference between these two experiments. Since the coastline orients approximately north-southward, the U wind isrepresentative to show the land–sea breeze feature.
The land breeze reached a maximal offshore windspeed of 0.4 m s21 at 0300 local time (LT) while the sea
breeze was at 2000 LT with an onshore wind speed of
0.4 m s21 (Fig. 11a). We noted that, although Fig. 11asuggests a land–sea breeze feature, the averaged windspeed in Fig. 11a is most likely much weaker than thediurnal U-wind variation of any day at any location(usually few meters per second). This small value wasdue to the change of the coastline orientation and thecomplex topography over the land (Lin et al. 2019;

Huang et al. 2016). Therefore, a long-term averageover a large area (as Fig. 11) would underestimate themagnitude of the land–sea breeze variation.
There was also a subdiurnal wind variation between
the diurnal case and the daily case (0600–0800 LT and
1800–2000 LT in Fig. 11a). To examine the influence ofthe subdiurnal wind signal on the dipole-pattern salinity
deviation, an experiment with an idealized diurnal wind
forcing was conducted. The idealized diurnal wind wascreated by superimposing sinusoidal diurnal wind onto
the daily case wind at each point and the magnitude of
the sinusoidal wind was similar to the diurnal windmagnitude change in the diurnal case. The difference of
this idealized case and the daily case can almost reproduce the dipole pattern and magnitude of the SSS
change (figure not shown) discussed above. This implies
that the diurnal wind signal plays the primary role in the
dipole-pattern salinity change in this study.

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FIG. 11. (a) Time series of hourly mean 10-m U wind speed (black line), surface eastward flow (blue dashed line),and northward flow (red dashed line) differences between the diurnal case and the daily case in the Yangtze River
plume region (where the water age was less than 200 days in dye tracking experiments) averaged from May to August
over the 5-yr-period model integration; the distributions of SSS in the diurnal case (shading color), the 10-m wind(black vectors) and surface flow (blue vectors) differences between the diurnal case and the daily case at (b) the land
breeze of 0300 LT and (c) the sea breeze of 2000 LT; and (d) the daily mean distributions of SSS (shading color) in thediurnal case and surface flow difference (blue vectors) between the diurnal case and the daily case.

The 10-m wind field presents a clockwise rotation due
to land–sea breeze and the Coriolis effect, leading to aclockwise surface flow deflection response (Figs. 11b–d).
The deflection angle of the surface ocean current direction from 10-m wind vector reached its maximum
value of 908 at the sea breeze (Fig. 11c), when the surface
wind direction aligns with the mean southeasterly monsoonal wind. The deflection angle can also be less than 208
in other times (figure not shown). Therefore, by integrating this diurnal ocean flow field, the asymmetric flow
response to the land–sea breeze eventually forms aclockwise circulation (the CFCA; Fig. 11d).
The upper-ocean current is mainly driven by surface
wind stress, which is proportional to the square of thesurface wind. However, the daily mean of the hourly
surface wind was used in the daily case. To further explore the contribution of the nonlinearity of wind stress,

that is, the square nature of wind stress, on the dipolepattern salinity change, we carried out another experiment (called dailyWS case) that is the same as the dailycase but uses the daily mean of the hourly wind stressdata from the diurnal case. Figure 10d shows the SSS
and surface flow differences between the dailyWSand daily case. The pattern of the differences in generalagreed well with that between the diurnal and daily cases (Fig. 10c), but with a smaller magnitude. Overall,
the nonlinearity effect contributed about a half of thedipole-pattern SSS change and the CFCA caused by thediurnal wind effect (Fig. 10c versus Fig. 10d).

d. The Ekman effectDuring the sea breeze, the 908 surface flow deflection
relative to the 10-m wind field (Fig. 11c), associatedwith the clockwise rotating flow profile spiral (Figs. 12a–d),

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FIG. 12. Regionally averaged 10-m wind (black vectors) and ocean flow (blue vectors) differences between the diurnal case and the dailycase over the Yangtze River plume region at local time (a) 0300, (b) 0900, (c) 2000, and (d) 2300 LT in summer (average from May toAugust over the 5-yr-period model integration); the decomposition of the flow profile into (e)–(h) Ekman effects and (i)–(l) the current
residual (original currents minus the Ekman effects); and (m)–(o) the average flow in the mixed layer at different time (local tine) of theday. Vector colors in (m)–(o) represent the time during the day. Deflection angle u is the angle between the 10-m wind and the surface
flow; the positive u means the surface flow is deflected to the right relative to the wind.

suggests that the CFCA response to the land–sea breeze
may potentially come from the Ekman effect, that is, due tothe Yangtze River plume, the associated low-density surface freshwater enhances stratification and reduces verticalmixing to adjust the Ekman response. Thus, we further
examined the Ekman layer effect on the CFCA quantitatively. Following Ekman (1905), the wind-driven Ekman
current can be described by the following equations:



›u
›
›u
m
,
2fy 5
›t
›z ›z


›y
›
›y
m
,
1 fu 5
›t
›z ›z

(7)

(8)

where u and y are eastward and northward Ekman
current components, f is the Coriolis frequency, and m is

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FIG. 13. (a) Distributions of the salinity difference (shading color) between the sea breeze (red dashed line) andland breeze (black dashed line); (b) spatial and (c) regression relations between the horizontal gradient of the day–night salinity difference [salinity at sea breeze minus the salinity at land breeze; shading color in (b) and x-axis datain (c)] and the daily mean flow difference between the diurnal case and the daily case [blue vectors in (b) and y-axis
data in (c)]; and (d) background salinity (shading color) and the daily mean flow difference (blue vectors) between
the diurnal forcing run and the daily forcing run in diagnostic experiments.

the viscosity coefficient. Under the steady state assumption with the boundary conditions below›u t›y t y(9)m 5 x ; m 5 , at z 5 0,
›z r
›z r
u 5 y 5 0,

atz 5 2D ,(10)

where t x and t y are eastward and northward wind stresscomponents, respectively, r is water density and D is thewater depth, Eqs. (7) and (8) have the following analytical solution:"#
z1D
sinh (1 1 i)
h
df
1 jtj
pi
"
# ,
v 5 u 1 iy 5 pﬃﬃﬃﬃﬃﬃ exp i u 2
r4
fmDcosh (1 1 i)
df
(11)

sﬃﬃﬃﬃﬃﬃ
2m
,
df 5
f

(12)

where v is the Ekman current; t is the wind stress andcan be expressed as a plural form t 5 t x 1 it y 5
jtjexp(iu), where u is the wind direction angle and jj is
the absolute norm operator; and df is a critical depth.
The critical depth df has a relationship with the Ekman
depth (depth of Ekman layer) of DE 5 pdf.
The Ekman effect can be estimated using Eqs. (11)and (12), which were used to derive the Ekman current,
directly forced by the surface wind stress. The deflection
angle of the diurnal-wind-induced Ekman current relative to the diurnal wind field varied from 24.98 to 51.68(Figs. 12e–h). However, after removing the Ekman effect, the residual diurnal currents are still similar to theoriginal ones (Figs. 12i–l versus Figs. 12a–d, respectively).

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FIG. 14. Differences of (a) the local change rate of the relative vorticity, (b) horizontal advection terms, (c) divergence term, (d) tilting
term, (e) solenoidal term, and (f) the residual term between the diurnal case and the daily case.

This is because the derived Ekman current (Figs. 12e–h)
is one order smaller than the modeled diurnal current(Figs. 12a–d). We further quantify the contributionof the derived Ekman effect to the total diurnal current effect in the mixed layer, using their u andy components of the flow vector deviations. The derived Ekman effect can count for only 9.7% of themodeled diurnal current, leaving 90.3% to otherprocesses (Figs. 12m–o).

e. Diurnal front swing and baroclinic adjustment
Section 4d indicates that the Ekman effect cannot
fully explain the flow changes in the diurnal case. We
further diagnosed the potential causes of the CFCA
using the vorticity budget. Before this, we analyzed the
SSS front variation due to the diurnal winds as it may
result in the change of baroclinicity. The land–sea breeze
causes the swinging (i.e., day–night variation of isohalines) of the Yangtze River front, producing the SSS

difference (dSSS) between the sea breeze (2000 LT)
and the land breeze (0300 LT) (Fig. 13a). The largedSSS gradient showed a similar pattern to the CFCA
(Fig. 13b) and the correlation between these two
fields was 0.62 ( p , 0.01; Fig. 13c). An additional
sensitivity experiment also confirmed this connection. When the model salinity and temperature were
fixed (i.e., the density is fixed) to the model initialconditions (i.e., 0000 UTC 1 January 2011) for both
the diurnal and daily cases during the 5-yr integration, the CFCA disappeared with a small differencesin the flow field (Fig. 13d). This implies that the SSS
variation (the baroclinic adjustment) due to the diurnal winds might be important to the CFCA formation and, in consequence, the dipole pattern of the
SSS change.
To further clarify this baroclinic adjustment process,we performed the budget analysis of the vertical component of the vorticity using the following equation:

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649





›za
›za
›za
›u ›y
1
52 u
1y
2 za
›x ›y
›t
›x
›y




›u ›w ›y ›w
1 ›r ›p ›r ›p
2
1 2
2
1
›z ›y ›z ›x
r ›x ›y ›y ›x
1 residual ,(13)

where za 5 z 1 f is the vertical component of the absolute vorticity; z 5 [(›y/›x) 2 (›u/›y)] the relative
vorticity; f the planetary vorticity; u, y, and w the eastward, northward, and vertical current components, respectively; r the density; and p the pressure derived
from the hydrostatic balance relation(p 5 rgz). The lefthand side of Eq. (13) is the local change rate (or tendency) of the relative vorticity. The terms, in sequence,on the right-hand side are the horizontal advection, divergence, tilting, solenoidal (or baroclinic) and residual,
respectively.
Figure 14 shows the May–August differences of vorticity budget terms between the diurnal case and the dailycase over the 5-yr simulation. The vorticity tendency
differences between these two experiments show a positive and negative pair of vorticities change offshore of the
Yangtze River estuary (Fig. 14a), which can explain thenorthwestward jetlike current difference. This pair ofvorticity change induces the jetlike current anomaly
between these two vorticity anomalies, thus transporting more freshwater to the south of Jiangsu
Coast, where the northward current along Jiangsu
Coast (driven by both tides and winds in summer) carries more freshwater to the entire Jiangsu coastal waters.
The jetlike current thus enhances the NLFT of freshwater (also means less freshwater transport eastnortheastward), forming the dipole pattern of SSS
change (Figs. 10c and 14a). The positive change in thevorticity tendency dipole (Fig. 14a) is mainly causedby the advection term (Fig. 14b) with the aid of divergence term (Fig. 14c), and the negative change
comes mostly from the solenoidal (baroclinicity)
term (Fig. 14e). The tilting (Fig. 14d) and residual
terms (Fig. 14f) have little contribution to the vorticity tendency difference and thus can be ignored.
This vorticity tendency difference can be explainedby the compensation between the baroclinicity andadvection terms. As the fresh river water flows into
the ocean, the baroclinicity may be generated fromthe frontal jet, causing the negative vorticity tendency on the light side of the front due to the compression (Figs. 10a,b). Our results suggest more baroclinicity
is generated in the diurnal case than in the daily case,leading to a more negative vorticity tendency along
the front. The northward migration (advection) of
the river front and the stronger compression of

FIG. 15. Distribution of summer (average from May to August
over the 5-yr-period model simulation) SSH and surface flow differences between the diurnal case and the daily case. Shaded colors
indicate the SSH difference, and the blue vectors represent the flow
field difference between the two cases.

baroclinicity lead to the observed pair of vorticity
change.
However, the change of outer part current of the
CFCA is caused by a different mechanism. The jetlike
current, induced by the diurnal forcing, transports
more Yangtze River freshwater northwestward along
Jiangsu Coast in summer and increases the mean (May–
August) SSH over the region (Fig. 15). The enhanced
NLFT induced by the diurnal wind weakens the northeastward Yangtze River freshwater transport branch
and reduces the mean SSH in the northeast of the
Yangtze River plume region. Therefore, an SSH gradient appears and forms the outer part current of
CFCA through the geostrophic adjustment (Fig. 15).

5. Sensitivity to forcing frequency
We carried out three additional sensitivity experiments to examine the influence of surface wind forcing
frequency on the dipole-pattern salinity change induced by the diurnal wind. The three experiments wereconducted using different frequencies of surface wind
forcing: 3 hourly (3H), 6 hourly (6H), and 12 hourly(12H). All other setups are exactly the same as those of
the diurnal and daily cases.
During May–August, similar dipole pattern of salinitychange (deviated from the daily case) also appeared in
all these experiments (Figs. 16b–d). The strength of
this dipole pattern of salinity change grew with theincreased forcing frequency (Fig. 16). Specifically, the3H case almost reproduced the dipole pattern of
the salinity change in the diurnal case (Figs. 16a,b).
This implies that a minimum of 3-hourly wind frequency

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FIG. 16. Summer (May–August) SSS difference between different time interval simulation groups (a) diurnal
case 2 daily case, (b) 3H case 2 daily case, (c) 6H case 2 daily case, and (d) 12H case 2 daily case.

is required to accurately simulate the oceanic responseof the diurnal forcing, a similar conclusion obtained in
Qu and Hetland (2019). However, our results suggestthat both the direct influence of wind kinetic energy
input, proposed by Hunter et al. (2010) and Qu andHetland (2019), and the baroclinic adjustment process(as discussed in section 4) are essential for this dipole
pattern salinity change.

6. Conclusions
This study investigates the impacts of diurnal atmospheric forcing on the summer salinity change in the
ECS. A moderate-resolution ROMS model was forced
respectively by the hourly and daily ECMWF ERA5
reanalysis data from 2011 to 2015. Compared with adaily frequency forcing experiment (the daily case),
the hourly atmospheric forcing (the diurnal case) increased the salinity by 1–2 psu outside of the Yangtze
River estuary and decreased by 0.5–1 psu in the Jiangsu
Coast, causing a dipole pattern of salinity change inthe ECS. Dye tracking experiments confirm that the diurnal forcing transported more Yangtze River freshwater

northwestward along the Jiangsu Coast, rather thanheading northeastward in summer. The volume of NLFT
was increased by 5.2 3 109 m3 and the mean water age
was reduced by 7 days.
Further sensitivity experiments, using diurnal wind or
diurnal insolation, suggest that the wind field was themost effective factor contributing to the dipole patternof the salinity difference and the large changes in the
NLFT. The diurnal wind, that is, the land–sea breeze,
produced a diurnal swing of Yangtze River freshwater front, which then formed a CFCA outside of
the Yangtze River estuary through baroclinic adjustment. This CFCA was responsible for the summertime dipole pattern of the salinity difference
between the diurnal case and the daily case; it hindered thenortheastward offshore freshwater transport of Yangtze
River and strengthened the NLFT in summer.
This study demonstrates that diurnal forcing canmodulate long-term material transport in the ECS, although diurnal atmospheric forcing only contributed
5% to the mean volume of NLFT in summer (Table 2
and Fig. 7c). The enhanced NLFT and the dipole patternof salinity difference are clearly shown in the 5-yr modelMARCH 2020

YU ET AL.

simulations (Fig. 8). A 1-psu salinity change may havegreat impacts on the marine ecosystem (Doney et al.
2011; Hoegh-Guldberg and Bruno 2010). In this respect,
diurnal forcing can be very important to the highecological-activity marginal seas at midlatitudes, suchas the ECS.
Furthermore, we explored the sensitivity of the wind
forcing frequency to the dipole pattern formation of thesalinity change. A 3-hourly wind can reproduce thissummer dipole pattern of salinity change in the ECS.
Though our results are similar to the conclusion suggested by Qu and Hetland (2019), we noticed that themechanism behind this results from both the direct kinetic energy input and the baroclinic adjustment induced by the diurnal winds.
Acknowledgments. This work was supported by
NSFC-Shandong Joint Fund for Marine Ecology andEnvironmental Sciences (U1606404) and the YouthFoundation of Shandong Academy of Sciences(2019QN0026). Y. Yu thanks the China ScholarshipCouncil (CSC) for supporting his stay in the UnitedStates. We thank Prof. Wensheng Jiang in Ocean
University of China for providing the cruise data. The
buoy data were collected via a research project funded by
the Ocean Public Welfare Scientific Research Project,State Oceanic Administration People’s Republic ofChina through Grant 200905012 (subtask 200905012-6).
The authors are very grateful to two anonymous reviewers for their constructive comments and suggestions.
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