JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 117, C02022, doi:10.1029/2011JC007246, 2012
Seasonal thermocline in the China Seas and northwestern
Pacific Ocean
Jiajia Hao,1,2 Yongli Chen,1 Fan Wang,1 and Pengfei Lin2
Received 29 April 2011; revised 1 December 2011; accepted 12 December 2011; published 11 February 2012.
[1] Climatological seasonal variations of the thermocline in the China Seas and
northwestern Pacific Ocean were studied using historical data from 1930 through 2001
(707,624 profiles). The quantitative roles of surface thermal buoyancy (Bq), haline
buoyancy flux (Bp), and total buoyancy flux (B) against the wind-induced mixing (t) in
different seasons and regions were also explored using the buoyancy ratio (R = ∣Bq/Bp∣) and
the Monin-Obukhov depth ratio (d), respectively. The thermocline has obvious seasonal
variations in the study area north of 20°N. There is no thermocline along the west coast of
the Bohai Sea (BS), Yellow Sea (YS), and northern East China Sea from December to
March resulting from surface cooling and wind mixing. The significantly different
variation of the thermocline strength on and off the Chinese shelf is mainly caused by the
fact that the thermal stratification is enhanced by bottom tidal mixing on the shelf. The d
indicates that the thermocline depth on the Chinese shelf is mainly dominated by B in
summer, while it is dominated by t in winter. It reveals an opposite feature in the
Kuroshio region; the dominating factor is B in winter, associated with the large heat
buoyancy loss there. South of 20°N, the dominating factor is similar to that on the shelf,
with the more obvious B dominant characteristic during the monsoon transition periods.
The R demonstrates that B is mainly controlled by Bq all year round, with some
sporadically Bp-dominated regions in the tropical area in winter and in the BS and
eastern YS in September.
Citation: Hao, J., Y. Chen, F. Wang, and P. Lin (2012), Seasonal thermocline in the China Seas and northwestern Pacific Ocean,
J. Geophys. Res., 117, C02022, doi:10.1029/2011JC007246.
1. Introduction
[2] The Bohai Sea (BS) and Yellow Sea (YS), which are
surrounded by China and Korea, and the East China Sea
(ECS) constitute one of the largest continental shelves and
are the most biologically productive seas in the world
(Figure 1). Because of their proximity to the western
boundary current of the North Pacific Ocean subtropical
gyre, the Kuroshio, and their exposure to the strongest
monsoon system in the world, the physical, chemical, and
biological environments of the BS, YS, and ECS are deeply
influenced by open ocean and atmospheric variability, such
as lateral momentum and energy inputs, surface heating and
cooling, and wind stress forcing over a broad spectra of
temporal and spatial scales.
[3] The seasonal cycle of a thermohaline structure, especially the thermocline, is one of the most significant signals
in the BS, YS, and ECS. Mao and Qiu [1964] first indicated
1
Key Laboratory of Ocean Circulation and Waves, Institute of
Oceanology, Chinese Academy of Sciences, Qingdao, China.
2
State Key Laboratory of Numerical Modeling for Atmospheric
Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric
Physics, Chinese Academy of Sciences, Beijing, China.
Copyright 2012 by the American Geophysical Union.
0148-0227/12/2011JC007246
the seasonal variability of the thermocline in the China Seas.
Since then, many observations confirmed that the thermocline occurs in spring, matures in summer, diminishes in
autumn, and vanishes in winter [Lan et al., 1985; Yu, 1988;
Tu, 1992; Chu et al., 1997; Zou et al., 2001; Ge et al., 2006;
Park and Chu, 2007]. In the YS, the strong thermocline
associated with the Yellow Sea cold water mass (YSCWM)
[Mao and Qiu, 1964] mainly lies on the slope west of the YS
trough in summer and moves to the central YS in autumn,
influenced by tidal and turbulent mixing [Zhao, 1989; Wang
et al., 1998]. The inversion thermocline exists in coastal
areas of the YS and ECS in winter and spring [Mao and Qiu,
1964; Lan et al., 1993; Lan, 1997; Ding, 1994; Ding and
Lan, 1995] and is deeply influenced by strong salinity
fronts and the development and weakening of the coastal
and warm currents [Guan, 1999, 2000; Hao et al., 2010].
[4] The South China Sea (SCS) thermocline has an evident seasonal variability [Xu et al., 1993; Chu et al., 1998,
1999; Chen et al., 2001]. Liu et al. [2000, 2001] found that
the thermocline is thinnest and weakest in winter, thickest in
spring, and strongest in summer and fall. Such a seasonal
variability is affected by the Ekman downwelling (upwelling) that is due to the anticyclonic (cyclonic) wind stress curl
[Chu et al., 1998]. In the northwestern Pacific Ocean
(NWP), researchers are mainly interested in the relationship
C02022
1 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
C02022
Figure 1. Topography for the China Seas and Northwest Pacific Ocean (NWP). The contour interval is
25 m between 0 and 100 m, 300 m between 100 and 1000 m, and 1000 m between 1000 and 5000 m.
Abbreviations are used for the Bohai Sea (BS), northern Yellow Sea (NYS), southern Yellow Sea
(SYS), YS cold water mass (YSCWM), East China Sea (ECS), ECS cold eddy (ECSCE), northern South
China Sea (NSCS), and Japan Sea (JS). The symbols indicate YSCWM (solid circle), ECSCE (diamond),
slope (triangle), and open ocean (solid star), respectively.
between thermocline depth and climate variability [Wang
et al., 2000; McGregor et al., 2004; Zhang et al., 2007].
They usually use a representative isotherm depth as a proxy
for thermocline depth. Only very few studies described the
seasonal variability of the thermocline characteristics in the
NWP [Zhou et al., 2002; Wang et al., 2008; Zhang et al.,
2009]. The thermocline is deeper in winter and shallower
in summer, lasting from May to November in the temperate
zone of the NWP [Zhang et al., 2009].
[5] These previous studies mainly focused on analyzing
thermocline characteristics (depth, thickness, and strength),
and very few studies examined the quantitative roles of
thermal, haline (due to freshwater), and net buoyancy
against the mechanical mixing in the China Seas using
observations. Park and Chu [2007] explored the relative
importance of wind mixing and surface thermal buoyancy
forcing in the mixed layer in the southern YS and ECS using
four surveys (September 1992, February, May, and September 1993) and found that wind mixing is the primary
driver during May and September in the study areas while
the surface thermal buoyancy fluxes are more important
during February 1993 in the Kuroshio area. All these earlier
reports on the thermocline were based on limited data
collected during individual surveys and therefore did not
provide a comprehensive picture of the thermocline process
in the region.
[6] In this study, we make use of historic hydrographic
data in the past several decades to describe distribution and
evolution of the seasonal thermocline in the China Seas and
NWP (110°E–140°E, 10°N–40°N) and to understand the
quantitative roles of surface thermal, haline buoyancy flux,
and total buoyancy flux against the wind-induced mixing in
different seasons and regions. Section 2 gives a description
of the data sets and methods; section 3 discusses the occurrence frequency and characteristics of the thermocline; and
section 4 examines the dominant driving mechanisms associated with surface thermal and haline buoyancy fluxes and
with wind stress. Conclusions are presented in section 5.
2. Data and Methods
2.1. Hydrographic Data Set
[7] Historical temperature data (Figure 2) used in the
present study were selected from the Ocean Science Database, Institute of Oceanology, Chinese Academy of Sciences (OSD-IOCAS) [Wang et al., 2004], which collected
2 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
C02022
and warming trends [Tang et al., 2009]. In the present study,
the temperature data, including quality controlled 707,624
profiles mainly during 1958 and 2000 (Figure 2b), are used
to calculate occurrence frequency and characteristics of the
thermocline. Meanwhile, the sea surface salinity (S0) is
computed using the observations with salinity (302,740
salinity profiles) to calculate haline buoyancy, which will be
given in section 2.3.
Figure 2. (a) Spatial and (b) temporal distributions of the
temperature data from OSD-IOCAS in the China Seas and
adjacent waters.
hydrographic observation data from 1930 through 2001
from various Chinese marine hydrological surveys and
international data sets, including the World Ocean Database
2001 (WOD01) at the National Ocean Data Center
[Conkright et al., 2002]. The data, including ocean station
data (Nansen bottle), conductivity-temperature-depth (CTD),
mechanical bathythermograph (MBT), and expandable
bathythermograph (XBT) data (72%, 1.5%, 12.9%, and
13.6% of the total, respectively), cover more coastal regions
(Figure 2a) compared with the WOD01. The primary quality
control of these data follows the methods outlined by Boyer
and Levitus [1994]. Further quality control methods were
developed and applied to prevent repeated, wrong, or manmade data from entering the database [Wang et al., 2004].
Several steps of the computer-manpower-integrated quality
control procedure were carried out, including inspections and
eliminations of duplicate profiles, inversed and duplicated
depths and densities in individual profiles, and statisticalbased criterion ranges of parameters varying with depth,
season, and location. The historical data were at 28 standard
depths (0, 5, 10, 15, 20, 25, 30, 50, 75, 100, 125, 150, 200,
250, 300, 400, 500, 600, 700 m, etc.) and on the bottom, and
each profile was interpolated by a piecewise cubic spline
method [Akima, 1970] to obtain 1 m vertical resolution. The
data set has already been used in studies on thermodynamic
structures in the ECS [Chen et al., 2004; Hao et al., 2010]
2.2. Thermocline Detection
[8] In order to study the distribution and variability of
thermocline depth (TD), thickness (DD), bottom (TB), and
strength (TS), it is necessary to determine upper and lower
thermocline bounds accurately. The widely used conventional method is the gradient criterion (GC) method, in
which the vertical gradient of temperature is required to be
larger than a certain fixed value. The gradient criterion is
subjective because there is no objective way to determine the
criteria. For example, the criterion 0.2°C/m is suitable on the
Chinese shelf (≤200 m) [Mao and Qiu, 1964; Lan et al.,
1985; Yu, 1988; Tu, 1992; Liu et al., 2000; Zou et al.,
2001], 0.05°C/m is proper off the Chinese shelf (>200 m)
[Zhou et al., 2002; Wang et al., 2008; Zhang et al., 2009],
while 0.1°C/m was also used on the slop in the northern SCS
[Pan et al., 2006]. Obviously, the criterion is chosen artificially and varies with different regions. Thus, a simple
objective method for determining thermocline is needed.
[9] Chu et al. [1997] developed a thermal parametric
model to analyze observed regional sea temperature profiles
based on a layered structure of temperature fields. Similar to
this parametric model, the work by Ge et al. [2003, 2006]
introduced a quasi-step-function approximation (QFA)
method, in which three line segments are used to fit the three
layers (surface mixed layer (SML), thermocline, and bottom
mixed layer (BML)) of the vertical temperature profiles on
the Chinese shelf seas (Figures 3a and 3b). A quasi-step
function can be defined by
8
< T ðzÞ ¼ T u
T ðzÞ ¼ TS ðz TDÞ þ Tu
:
T ðzÞ ¼ T b
z ≤ TD
TD < z < TB;
z ≥ TB
ð1Þ
where z is the depth of the profile, Tu and Tb are the verticalaveraged temperatures of the SML and BML, respectively,
TD and TB are the depths of the top and bottom of the
thermocline, respectively, and TS is the strength of the
thermocline. The initial values of the TD and TB are estimated by the 0.05°C/m gradient criterion, which is relatively
lower than that previously used on the Chinese shelf. Then,
the optimal values of these parameters are calculated through
the least squares adjustment to adjust each temperature
profile to a quasi-step function by minimizing the residuals
between the two curves. As a result, three line segments
identified by this method can fit the three layers on the
Chinese shelf very well. However, the QFA method cannot
be used off the shelf [Hao et al., 2008] because the middle
and lower segments can hardly fit the thermocline and the
BML there (Figures 3c and 3d). In the present research, we
use the QFA method on the shelf and the GC method off the
shelf, with the uniform criterion of 0.05°C/m, which is
widely used off the shelf. With the GC method, a segment is
detected as the thermocline layer if its vertical temperature
3 of 14
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
C02022
C02022
salinity units (psu)), a is the thermal coefficient of expansion
(1.7 104°C1), and b is the coefficient of haline contraction (7.5 104 psu1). E and P are evaporation and
precipitation (m s1), respectively. Cp and r0 are calculated
according to the work by Fofonoff and Millard [1983], and
the values of a and b are from the work by McDougall
[1987], all with the state of S = 35 psu, T = 10°C, and P =
10 dbar. The monthly mean climatology of Q, E, and P are
derived from the Comprehensive Ocean Atmosphere Data
Set (COADS) on a 1° 1° grid for the period 1945–1993
[da Silva et al., 1994]. The climatological monthly mean S0
is calculated from the OSD-IOCAS at the grid with more
than five salinity profiles.
[12] Note that B in (2) includes contributions from both
heat and freshwater fluxes at the sea surface. Net heat and
freshwater fluxes at the sea surface are defined as positive
quantities into the ocean. Positive (negative) B indicates a
buoyancy loss (gain) by the ocean. Surface density increases
(i.e., water column is destabilized) if B > 0, and surface
density decreases (i.e., water column is stabilized) if B < 0.
Figure 3. Climatological monthly mean temperature profiles in the (a) YSCWM, (b) ECSCE, (c) slope, and (d) open
ocean (locations are depicted in Figure 1 by a solid circle,
diamond, triangle, and solid star, respectively).
gradient is >0.05°C/m continuously. TD and TB are defined
as the upper and lower boundary depths of the thermocline
layer, respectively. Then, DD and DT are defined as depth
and temperature differences between TD and TB, respectively. Strength is simply defined as DT/DD, without considering fine structures within the thermocline layer.
[10] Based on the QFA and GC methods, the thermocline
is estimated for each profile. If there are more than two
separated thermoclines from one profile, the strongest one
(with the largest vertical gradient) is selected as the main
thermocline. Then, the thermocline and no-thermocline
profiles are sorted into 1° 1° grids. Assuming the total
sampling number is N and the number with existing thermocline is n in each month and at each grid, P = (n/N) 100% is then called the occurrence frequency. Meanwhile,
monthly mean values of the TD, DD, and TS of the main
thermocline layer were also computed [Wang et al., 2009].
We define the seasons as follows: December–February for
winter, March–May for spring, June–August for summer,
and September–November for autumn.
2.3. Surface Buoyancy Flux (B)
[11] In order to investigate oceanic responses to the
atmospheric forcing (heat and freshwater fluxes), the surface
buoyancy flux (B in m2 s3) was calculated according to
Marshall and Schott [1999] as follows:
gaQ
B ¼ Bq þ Bp ¼ r0 Cp
þ gb ðE PÞS0 ;
ð2Þ
where Bq is thermal buoyancy (which is due to the net heat
flux), Bp is haline buoyancy (which is due to the net freshwater flux), g is gravity (9.8 m s2), Q is the net heat flux
(downward positive; W m2), r0 is the reference water
density (1024 kg m3), Cp is the specific heat of water
(3986.3 J kg1 °C1), S0 is surface salinity (in practical
2.4. Monin-Obukhov Length (L) and Depth Ratio
(∣TD/L∣)
[13] The thermocline depth, defined as the SML depth in
this study, is the layer thickness of vertically uniform temperature and is developed generally by wind stirring and
convection (surface buoyancy flux B), although other mixing mechanisms are also involved, depending on the scale.
In order to examine dominant mixing mechanisms for
developing the thermocline depth, the Monin-Obukhov
length (M-O length, L) and the ratio of thermocline depth to
L:d = ∣TD/L∣ (called the depth ratio) are calculated to
determine forcing regimes [Lombardo and Gregg, 1989;
Lozovatsky et al., 2005], convection regimes (d > 10), wind
forcing regime (d < 1), and combined forcing regimes (1 <
d < 10), which will be discussed in section 4.2 in detail.
[14] The M-O length is the depth at which the windgenerated turbulence is balanced by the buoyancy that is
due to surface warming and freshening (salinization) by
precipitation (evaporation), and the L is calculated using the
formulation
L¼
3
U
;
kB
ð3Þ
where von Kármán’s constant k = 0.41, U* = (t/r0)1/2 is the
friction velocity of the wind stress t (kg m1 s2), and B is
the surface buoyancy flux. The monthly mean climatology
of t is derived from the COADS [da Silva et al., 1994].
3. Seasonal Variation of Thermoclines
3.1. Thermocline Occurrence Frequency
[15] Figure 4 shows the distribution of thermocline
occurrence frequency. In general, south of 20°N (the tropical
NWP and the central SCS) the thermocline occurrence frequency is >90% all year round, with little seasonal variation.
However, the occurrence frequency is higher in July and
lower in January north of 20°N.
[16] In winter (December–February), a homogeneous
structure (occurrence frequency < 10%) occupies almost the
entire shelf area (water depth < 100 m), except in the BS,
4 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
C02022
Figure 4. Bimonthly distributions of thermocline occurrence frequency (%). The contour interval is
20%. Regions with frequencies of <10% are shaded, and contours with frequencies of 90% are indicated
by heavy lines.
eastern YS, western ECS, and the northern SCS, where the
inversion thermocline appears as in the work by Hao et al.
[2010, Figure 4]. Another huge homogeneous area is
located south of the islands of Japan from January to March,
when isotherms near the thermocline in summer reach the
surface and the subduction occurs. This area coincides
roughly with that of the low potential vorticity core of the
subtropical mode water [Kobashi et al., 2006]. In March,
some centers of occurrence infrequency (<10%) appear in
the northern ECS, associated with some cyclonic eddies
there [Guan, 1983].
[17] In May, the thermocline appears frequently and the
homogeneous areas disappear. The frequency increases to
>90% in the central YS and near the ECS cold eddy
(ECSCE) that is a year-round cyclonic eddy centered at
about 31.5°N, 125.5°E [Hu, 1994]. In July, the thermocline
appears in almost the whole study region with the highest
frequency, >90%, except for the coastal area with a water
depth of <50 m, as in the BS, western and eastern YS,
Taiwan Strait, and northeast of the northern SCS. The lowest
frequency, <30%, appears in the shallow area of the western
YS with a water depth <25 m, resulting from tidal mixing.
From September to November, the area with the frequency
of <70% extends from the coastal zone to the whole shelf,
where the water depth is <100 m. The occurrence frequency
dramatically decreases to <10% on the shelf with a water
depth <50 m, except for the inversion thermocline areas. The
frequency near the Ryukyu Islands and south of Japan
decreases to 70% as well.
3.2. Thermocline Strength
[18] Figure 5 indicates seasonal variations of the thermocline strength in the shelf areas and south of the islands of
Japan, which is basically weakest in January and strongest in
July. However, the thermocline strength has little seasonal
variation (0.05°C/m–0.1°C/m) along the Kuroshio and south
of 20°N.
[19] In winter, there is no thermocline (vertical temperature gradient <0.05°C/m) in the northern BS and southern
YS. The strength is <0.05°C/m south of the islands of Japan
from January to March, which well coincides with the areas
with an occurrence frequency of the thermocline of <10%.
The thermocline mainly occurs in the central YS and ECS,
the Taiwan Strait, and northern SCS with strengths up to
0.2°C/m. In other areas, the strengths of the thermocline are
between 0.05°C/m and 0.1°C/m.
[20] In spring, the thermocline north of 20°N is strengthened with increasing sea surface temperature (SST) and
weakening surface wind. In May, the strength of the thermocline is >0.2°C/m in most shelf areas, especially in the
YS and northern ECS. A strong thermocline center appears
south of the Shandong Peninsula, with a strength of about
0.60°C/m (36.5°N, 121.5°E).
[21] In July, the strength of thermocline reaches a peak
with three strong centers in the northern YS, southern YS,
and the southwest of Cheju Island. Their strengths reach
1.4°C/m (37.5°N, 123.5°E), 2.0°C/m (35.5°N, 121.5°E), and
0.8°C/m (31.5°N, 125.5°E), respectively. Below the thermocline, there are cold centers, commonly referred to as the
YSCWM, that remain unchanged and nearly motionless
throughout the summer [Li and Yuan, 1992] and the ECSCE
[Hu, 1994]. In the SCS, the strength reaches 0.4°C/m–
0.5°C/m near the Chinese coast and is 0.1°C/m–0.15°C/m
in other regions. The strength is between 0.1°C/m and
0.15°C/m south of the islands of Japan from July to
September.
5 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
C02022
Figure 5. Bimonthly distributions of thermocline strength (°C/m). The contour interval is 0.05°C/m
between 0.05 and 0.2°C/m and 0.2°C/m above 0.2°C/m. Regions with strengths of <0.05°C/m are shaded,
and contours with strengths of 0.1°C/m are marked by heavy lines.
[22] From September to November, the thermocline is
weakened in the shelf area due to surface cooling and
developing winter monsoon. The strong thermocline centers
in the southern YS and northern YS combine, and move to
the central YS (34.5°N, 122.5°E) with an attenuated strength
of about 1.4°C/m. In November, the thermocline disappears
in a couple of coastal areas in the western YS and northern
SCS.
3.3. Thermocline Depth
[23] As shown in Figure 6, the thermocline north of 20°N
is generally shallow during May–September and deep during November–March. In the tropical NWP and central SCS,
seasonal variations of the thermocline depth and thickness
(Figures 6 and 7) are not obvious, and the thermocline is
relatively shallow and thick in summer and autumn, with an
amplitude of about 25 m.
[24] During September–March, the thermocline depth is
about 15–50 m on the Chinese shelf, with the largest value in
November, when the probability and strength of the thermocline are relatively low (Figures 4 and 5). The thermocline depth is significantly large near the Ryukyu Islands,
with a peak of about 240 m in March. This large thermocline
depth results from the disappearance of the surface seasonal
thermocline in winter and mainly reveals the permanent
thermocline depth (Figure 3c). In May–July, the surface
seasonal thermocline occurs and matures; the depth is about
5–20 m on the shelf and south of the islands of Japan and
about 20–50 m along the Kuroshio, with the smallest value
in July. The depth near the Yangtze River Estuary is <5 m all
year round, resulting from the downward buoyancy flux
caused by freshwater.
[25] It is noteworthy that the thermocline depth in the
northern SCS decreases toward the southeast in winter,
while it increases in summer. In winter, the upper Ekman
transport is directed to the right of the northeasterly wind,
which causes water to pile up in the northwestern SCS,
increases the depth of the SML, and deepens the thermocline
there [Liu et al., 2000]. It is the opposite in summer.
3.4. Thermocline Thickness
[26] The thermocline is thick during July–November and
thin during January–May (Figure 7), with about two months’
lag compared to the thermocline depth change. During January–May, the thermocline thickness is about 10–20 m on
the shelf and about 20–50 m south of the islands of Japan,
with the smallest value in March. In July–November, the
thickness increases with a peak of about 190 m near the
Ryukyu Islands in September. It should be pointed out that
the contours of the thermocline depth and thickness on the
shelf almost follow the bathymetry (Figure 1), with a relatively larger value in the central YS, indicating that the tidal
mixing in the shallow regions, such as in the waters with
depths less than 50 m, is important to the development of the
thermocline depth.
4. Forcing on the Thermocline
4.1. Thermal Buoyancy, Haline Buoyancy, and
Buoyancy Ratio (R)
[27] Based on equation (2), the monthly mean total
buoyancy flux and its components (thermal and haline
buoyancy fluxes) are presented in Figure 8. A buoyancy gain
is evident in most of the study area from April through
September (Figure 8c), associated with high solar heating in
6 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
C02022
Figure 6. Bimonthly distributions of the thermocline depth (m). The contour interval is 5 m between 0
and 20 m, 25 m between 50 and 100 m, and 50 m between 100 and 200 m. Regions with depths of
<20 m and >75 m are shaded.
summer. In particular, a relatively large total buoyancy flux
(on the order of 107 m2 s3) can be seen from May to
July in the BS and YS. Such a strong buoyancy gain stabilizes the upper layer of the water column and causes the
SML to shoal, creating a multilayer structure (Figures 3a–
3c). On the other hand, there is a substantial buoyancy loss
in the study area during November and February, especially
in the Kuroshio area, with the largest value of 2 107 m2
s3 in January that even lasts until March. The upward
buoyancy flux mixes the surface water with deeper water,
and the thermocline is at its deepest (it usually fills the whole
water column as in Figures 3a–3c) during winter. The
Figure 7. Same as Figure 6, but for the thermocline thickness (m).
7 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
Figure 8. (a) Thermal buoyancy flux (Bq), (b) haline buoyancy flux (Bp), and (c) total buoyancy flux (B).
The negative values (ocean surface gains buoyancy) are shaded, and the contour intervals are 2, 0.4, and
2 108 m2 s3, respectively. Small dots mark the grid cells with actual observations in Figure 8a, and
mark those with more than five salinity profiles in Figures 8b and 8c.
8 of 14
C02022
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
C02022
Figure 9. Bimonthly distributions of the buoyancy flux ratio (R = ∣Bq/Bp∣). Small dots mark the grid
cells with more than five salinity profiles.
spatiotemporal distribution of the total buoyancy flux is
consistent with those of the thermocline (Figures 4–7).
[28] Consistent with the total buoyancy flux, both thermal
and haline buoyancy fluxes tend to stabilize the water from
April through September over most of the study area, and
both thermal and haline buoyancy fluxes result in destabilization during November to February (Figures 8a and 8b). In
order to explore the relative impact on the upper ocean
buoyancy of thermal and haline effects, the absolute value of
the buoyancy ratio R = ∣Bq/Bp∣ is given [Kara et al.,
2008]. R ≈ 1 explains that the buoyancy appears to be
equally affected by thermal and haline effects. The buoyancy
is due mostly to the net heat flux at the sea surface when
R 1, and the buoyancy is due mostly to net freshwater flux
at the sea surface when R 1. The spatially and temporally
varying R values in Figure 9 demonstrate that the thermal
buoyancy flux is one order larger than the haline buoyancy
flux in most of the study on the climatological time scale.
However, the buoyancy due to freshwater exceeds that due
to heat flux (R < 1) in the tropical NWP and central SCS
during November and January, and in the BS and east of the
YS in September. These sporadically Bp forcing regions are
associated with the near-zero thermal buoyancy (Figure 8a).
The buoyancy ratio is extraordinary larger (R > 100) in the
coastal areas of the BS, YS, and ECS during January and
May and around 25°N from May to September, associated
with the near-zero haline buoyancy (Figure 8b).
4.2. M-O Length and Depth Ratio (d)
[29] Figure 10 shows the M-O depth ratio and wind
stress. The M-O depth ratio is calculated using wind stress,
total buoyancy flux, and thermocline depth, based on
equation (3). The main characteristic of the wind data is
the seasonal variation of the monsoon wind. In winter
(November to March), strong northerly to northwesterly
winds prevail north of 20°N and northerly to northeasterly
winds prevail south of 20°N, with the largest wind stress
of the year (on the order of 101 kg m1 s2). However,
the wind stress is relatively smaller south of the islands of
Japan. In July, a weak southeasterly wind prevails. May
and September are the summer and winter monsoon transition periods, respectively. The wind stress is small (on
the order of 102 kg m1 s2) over the study areas during
these periods, especially in May. The thermocline depth is
dominated by the surface buoyancy flux and wind stirring
when d > 10 and d < 1, respectively.
[30] The most interesting feature of the depth ratio distribution is the large d (>10) along the Kuroshio area from
November to May (heat lost from November to March),
especially near the Ryukyu Islands. At the same time, the
thermocline depth is at its deepest, and the occurrence frequency is <10% south of the islands of Japan from January
to March (Figure 4), associated with the large buoyant loss
(Figure 8c, 2 107 m2 s3) and the relatively small wind
stress there (Figure 10b). The effect of the wind perhaps is
mainly related to the anticyclonic wind curl and the resulting
subduction. It is noteworthy that d is the largest in May (the
summer monsoon transition period) when the wind stress is
the smallest of the year. However, d is smaller along the
Kuroshio in summer owing to smaller amplitude of buoyancy gain (0.6 107 m2 s3) compared with that of
buoyancy loss in winter. Opposite to that along the Kuroshio, large d appears in the YS from May to July and the
tropical NWP from May to September (heat gain). During
this period, the thermocline is shallow and strongly influenced by a large buoyant gain. The wind stress-dominated
areas (d < 1) are located at the waters shallower than 200 m
from September through March, and another area is located
south of 20°N during the winter monsoon. It is obvious that
the wind stress-dominated period is consistent with the
winter monsoon when the wind stress is one order larger
than that of the summer monsoon. It is worth pointing out
9 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
C02022
Figure 10. (a) M-O depth ratio (d), and (b) wind stress (t, kg m1 s2; contours) and wind speed (m/s).
Small dots mark the grid cells with actual observations.
that d is <10 in the ECS and northern SCS throughout
the year, even during the large buoyant gain period, when
the wind stress is the smallest. It is mainly influenced by the
shallowest thermocline in summer, resulting from the combined impact of coastal freshwater and upwelling introduced
by the southerly wind there.
4.3. Zonally Averaged Thermocline
[31] Figure 11 shows the zonally averaged thermocline, its
associated SST and SML temperature (SML temperature is
the vertically averaged temperature of the SML), total
buoyancy flux, buoyancy ratio, wind stress, and M-O depth
ratio in the study area (excluding the JS). It suggests significantly different variations of the thermocline on a shelf
(north of 30°N), on a slope (20–30°N), and over an open
ocean (south of 20°N). The temperature profiles during
different periods in various types of regions are shown in
Figures 3a–3d.
4.3.1. Open Ocean
[32] Figure 11 shows there is little seasonal variation in
the thermocline south of 20°N. The strength and occurrence frequency of the permanent thermocline are 0.5°C/m–
1.0°C/m and >90%, respectively, all year-round (Figure 11a),
associated with little variation in the SST and SML temperature (Figure 11c). The buoyancy flux shows obvious seasonal variations not only in the subtropical regions but also in
the tropical areas with large negative values (ocean gains
buoyancy) in summer (Figure 11d). However, it does not
result in dramatic increases in the SST and SML temperature
north of 30°N, perhaps owing to the relatively larger thermocline depths in the tropical areas. The heat gain at the sea
surface warms a large volume of water, causing slow changes
in the SST and SML temperature. This feature also can be
10 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
C02022
Figure 11. Zonally averaged (a) thermocline strength (°C/m) and occurrence frequency (%), (b) thermocline thickness and depth (m), (c) SST and SML temperature (°C), (d) total buoyancy flux (108 m2 s3)
and buoyancy ratio, and (e) wind stress (kg m1 s2) and M-O depth ratio. Shaded contours indicate
frequency, depth, SML temperature, buoyancy ratio, and M-O depth ratio, respectively. The Japan Sea
(north of 30°N and east of 127°E) is not included in the study area.
seen from the coincidence of larger (smaller) temporal variations of the SST and SML temperature with the shallower
(deeper) thermocline in summer (winter) at high latitudes
(Figure 11c). The thermocline is a little deeper and thinner in
winter and spring with an average amplitude of about 20 m
(Figure 11b), influenced by the annual cycle of the buoyancy
flux (dominate during the monsoon transition period, d > 10)
and wind stress (dominating during the winter monsoon,
d < 1). The profiles in the open ocean in Figure 3d also
show that a permanent thermocline exists there all year
round, with a little deeper SML during winter and spring.
The buoyancy ratio is quite a bit smaller than that north of
20°N, indicating the combined impact of the thermal and
saline buoyancy fluxes on the total buoyancy flux.
4.3.2. Slope
[33] There exists seasonal variations of the thermocline
north of 20°N, especially on a shelf. Generally, the SST,
SML temperature, and the strength and occurrence frequency of the thermocline reach their peaks (troughs) in
August (February), while the thermocline is the shallowest
(deepest) in June (February) and the thickest (thinnest) in
September (April). The variation of the thermocline is
mainly controlled by the life cycle of the seasonal thermocline and its merging with the subsurface semipermanent
thermocline (Figure 3c).
[34] During the winter monsoon (December–February),
the SST and SML temperature are lower (Figure 11c)
because of increasing wind stirring and convective mixing,
which result in the deepest thermocline depth in February
(usually reaching the bottom layer) as in Figure 3c. Meanwhile, the thermocline strength and occurrence frequency
are also at their lowest. From March to May, the vertical
thermal structure is in its restratification period, and a shallow seasonal thermocline is formed. With increasing buoyancy gain, the seasonal thermocline is shallow and thin
(thinnest in April) in early spring.
[35] During the onset of the summer monsoon (June–
August), the SST increases rapidly from April through July
with a large buoyancy gain (dominance factor, d > 10),
resulting in a shallower (shallowest in June) and relatively
thicker seasonal thermocline than that in early spring. In
August, when the summer monsoon prevails, the seasonal
thermocline is mature and strongly affected by the sustaining
heat gain, while the thermocline is relatively deep, influenced by a larger wind stress than that in June (Figure 11e).
From July to September, the seasonal thermocline depth and
thickness are both increasing. This process can be seen from
the temperature profiles on the slope in Figure 3c. It shows
that the thermocline has been deepened with the strengthening wind and buoyancy loss, resulting in the merging of
the seasonal thermocline with the subsurface permanent
thermocline, and accordingly the thermocline thickness
increases. From September, the beginning of the transition
back to winter conditions, the seasonal thermocline begins to
deepen and even disappears in winter, caused by a large
buoyancy loss and a dramatic increase in wind strength.
4.3.3. Shelf
[36] The seasonal variation of the thermocline on the shelf
is similar to that on the slope. The seasonal cycle amplitudes
of the thermocline strength, depth, and thickness show
opposite phases between the thermocline on shelf and that
on slope. The averaged seasonal amplitude of the thermocline strength is about 0.5°C/m on the shelf, which is much
larger than that on slope (about 0.05°C/m) (Figure 11a),
while the averaged seasonal amplitude of the thermocline
depth and thickness on slope (about 80 and 45 m, respectively) are larger than those on shelf (about 30 and 10 m,
respectively) (Figure 11b). For the latter, the water depth
over most of the shelf area is less than 75 m (Figure 1),
which limits the amplitudes of the thermocline depth and
thickness there. For the thermocline strength, the upper layer
mixing process on the shelf is enhanced by the large
11 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
seasonal cycle amplitudes of buoyancy flux and wind stress,
which can also be found from the more obvious dominating
characteristics on the shelf (Figure 11e).
[37] In fact, tide mixing is another important factor in
controlling the thermocline on the shelf. The summer temperature profiles in Figures 3a and 3c show that although the
SST and SML temperature on the slope are higher because
of the larger net surface heat flux than that on the shelf, the
well-developed BML is absent on the slope because of a
weak tidal current. When the tidal waves propagate from
open ocean onto the Chinese shelf, the strengthened tidal
currents produce a high vertical shearing strain of velocity
through an interaction with the bottom topography, which
enhances the turbulent mixing [Lee and Beardsley, 1999].
The tidal mixing leads to a well-generated BML on the shelf,
and pushes the thermocline upward. Therefore, the thermocline on the shelf becomes shallow and strong. Qiao et a1.
[2004] suggested that within 30 m from the bottom, a vertical structure of temperature is mainly controlled by tidal
mixing in the YS. Based on a two-layer model, the variations
of thermocline depth can be expressed as functions of the
upward and downward entrainment velocities, ∂h/∂t = We1
3
1
We2 = f(U3s h1
1 , Q) f(Ub, h2 ) [Stigebrandt, 1981],
where Us and Ub are the velocities at sea surface and bottom,
respectively, Q is the net heat flux, and h1 and h2 are the
distances from the surface and bottom to the thermocline,
respectively. The effects of We1 and its components (thermal
buoyancy flux Bq and wind stress t), which play important
roles in upper layer mixing processes, have already been
discussed in sections 4.1 and 4.2. We2 is mainly related to the
tidal mixing that is generated from the bottom and pushes
the thermocline upward, indicating that a larger Ub and small
h2 (shallow bottom water) lead to a shallower thermocline.
Therefore, the seasonal cycle amplitudes of the thermocline
characters and their spatial distributions are mainly controlled by tidal mixing and topography, which also can be
seen from the topography-following distributions of the
thermocline depth and thickness (Figures 6 and 7). The
thermal stratification on the shelf is enhanced by the bottom
mixing process, and the resulting sharp thermocline in
summer leads to a larger amplitude of the thermocline
strength.
5. Conclusions
[38] We have investigated the thermocline in the China
Seas and NWP (10°N–40°N, 110°E–140°E) using the historical temperature data from 1930 through 2001, and we
have explored its seasonality and plausible causes on and off
the shelf. The depth ratio (the ratio of the thermocline depth
to the Monin-Obukhov length) was estimated for diagnosing
dominant driving mechanisms of the thermocline in different
seasons and regions: convection regimes with d > 10, wind
forcing regimes with d < 1, and combined forcing regimes
with 1 < d < 10. The results indicate the significantly different variations of the thermocline and dominant driving
mechanisms between seasons and between the shelf and offshelf regions.
[39] A thermocline exists in the study area south of 20°N
all year round. The strength and occurrence frequency of the
permanent thermocline are 0.5°C/m–1.0°C/m and >90%,
respectively. These are associated with a few variations in
C02022
the SST and SML temperature (Figure 11c). The thermocline is a little deeper and thinner in winter and spring,
influenced by the annual cycle of the buoyancy flux (dominant during the monsoon transition period, d > 10) and wind
stress (dominant during the winter monsoon, d < 1). The
buoyancy appears to be equally affected by temperature and
salinity effects (1 < R < 10) south of 20°N throughout almost
the whole year, with a larger effect due to heat flux (R > 100)
in May and a larger effect due to salinity (R < 1) in winter.
The thermocline strength in the northern SCS is similar to
that in the NWP. The 0.1°C/m contour line extends westward from the NWP through the Luzon Strait to about 117°E
in July, to 114.5°E in November, and to 110°E in January
and March, perhaps mainly being associated with the transition from a southerly wind in summer to a northerly wind
in winter (Figure 10b), and perhaps also indicating that the
Kuroshio can easily intrude on the SCS when the northeast
monsoon prevails [Wyrtki, 1961]. The thermocline depth in
the SCS decreases from northwest to southeast in winter and
increases in summer because of the surface Ekman transport
by the monsoon.
[40] The thermocline presents obvious seasonal variations
in the study area north of 20°N. The thermocline occurrence
frequency is the highest in summer and the lowest in winter.
The frequency is <10% in the BS, YS, and ECS from
December to March because of the influence of surface
cooling and wind mixing, and in some areas south of the
islands of Japan from January to March when the subduction
occurs. There are some low occurrence frequency zones
along the shallow areas of the western and eastern YS, near
the Yangtze River Estuary, and in the vicinity of the Taiwan
Strait, where the water depth is <25 m all year round and
tidal mixing is strong. The thermocline is basically shallower
and stronger in summer and deeper and weaker in winter as
it is influenced by surface cooling and wind stirring. However, the thermocline is thinner in spring owing to the
emerging but separated seasonal thermocline, while thicker
in autumn resulting from the decreasing SST, relaxing
summer monsoon, and the merging of the seasonal and
permanent thermoclines.
[41] Seasonal variations of the thermocline strength are
generally enhanced on the shelf, with an average seasonal
amplitude of about 0.5°C/m, which is much larger than that
on the slope (about 0.05°C/m). This is affected by the
intensification of surface buoyancy flux, wind stirring, and
tidal mixing in the shelf area. There are three strong centers
of the thermocline strength in summer, associated with the
YSCWM and ECSCE where the stratification is strengthened. The amplitudes of seasonal variations of the thermocline depth and thickness are larger on the slope than on the
shelf, owing to the difference of water depth. The topography-following distributions of the thermocline depth and
thickness on the shelf are mainly influenced by tidal mixing.
[42] The distribution of the M-O depth ratio (d) indicates
that the thermocline depth is dominated by the surface
buoyancy flux (d > 10) near and east of the Ryukyu Islands
from November through March, influenced by a large surface buoyancy loss and a relatively small wind stress. d is
<10 in the ECS and northern SCS throughout the year, and is
<1 (wind mixing dominated) during the winter monsoon
period. However, the dominant characteristic in the BS and
YS is more obvious, suggesting thermal stratification is
12 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
enhanced by surface buoyancy flux in summer and
destroyed by wind stirring in winter. The buoyancy ratio (R)
demonstrates that the surface buoyancy is mainly controlled
by the thermal buoyancy flux, especially in the coastal areas
of the BS and YS from January to May and the areas along
25°N from July to September.
[43] Acknowledgments. The authors would like to thank Zuojun Yu
from the International Pacific Research Center, University of Hawaii, for
her valuable suggestions. This study is funded by the National Natural Science Foundation of China (41106026) and the Chinese Academy of
Sciences through grants KZCX1-YW-12 and KZCX2-YW-Q11-02. We
are also very thankful to two anonymous reviewers for their constructive
comments on the original manuscript.
References
Akima, H. (1970), A new method of interpolation and smooth curve fitting
based on local procedures, J. Assoc. Comput. Mech., 17(4), 589–602.
Boyer, T., and S. Levitus (1994), Quality control and processing of historical oceanographic temperature, salinity, and oxygen data, NOAA Tech.
Rep., NESDIS 81, 72 pp., U.S. Dep. of Commer., Washington, D. C.
Chen, X., W. Y. Sha, and Y. Li (2001), The elementary analysis for the
distribution character of thermocline in the area of South China Sea [in
Chinese with English abstract], Mar. Forecasts, 8(4), 9–17.
Chen, Y. L., D. X. Hu, and F. Wang (2004), Long-term variabilities of thermodynamic structure of the East China Sea cold eddy in summer, Chin. J.
Oceanology Limnol., 22(3), 224–230, doi:10.1007/BF02842552.
Chu, P. C., C. R. Fralick Jr., S. D. Haeger, and M. J. Carron (1997), A parametric model for the Yellow Sea thermal variability, J. Geophys. Res.,
102(C5), 10,499–10,507, doi:10.1029/97JC00444.
Chu, P. C., C. W. Fan, C. J. Lozano, and J. Kerling (1998), An airborne
expandable bathythermograph survey of the South China Sea, May
1995, J. Geophys. Res., 103(C10), 21,637–21,652, doi:10.1029/
98JC02096.
Chu, P. C., N. L. Edmons, and C. W. Fan (1999), Dynamical mechanisms
for the South China Sea seasonal circulation and thermohaline variabilities, J. Phys. Oceanogr., 29, 2971–2989, doi:10.1175/1520-0485(1999)
029<2971:DMFTSC>2.0.CO;2.
Conkright, M. E., et al. (2002), World Ocean Database 2001, vol. 1, Introduction, NOAA Atlas NESDIS, vol. 42, edited by S. Levitus, 167 pp.,
U.S. Gov. Print. Off., Washington, D. C.
da Silva, A. M., C. C. Young, and S. Levitus (1994), Atlas of surface
marine data 1994, in Algorithms and Procedures, Tech. Rep. 6, U.S.
Dep. of Commer., NOAA, Silver Spring, Md.
Ding, Z. X. (1994), A preliminary analysis of vertical structure types of
temperature and salinity and its causes of formation of inverse phenomena in the Yellow Sea and East China Sea in autumn [in Chinese with
English abstract], Mar. Sci., 2, 47–51.
Ding, Z. X., and S. F. Lan (1995), A preliminary analysis of the distribution
of the inverse types of temperature and its formation causes in the southern Yellow Sea and the East China Sea in spring and winter [in Chinese
with English abstract], Mar. Sci., 1, 35–39.
Fofonoff, P., and R. C. Millard Jr. (1983), Algorithms for computation of
fundamental properties of seawater, UNESCO Tech. Pap. Mar. Sci., 44,
1–53.
Ge, R. F., F. L. Qiao, F. Yu, Z. X. Jiang, and J. S. Guo (2003), A
method for calculating thermocline characteristic elements in shelf sea
area–Quasi-step function approximation method [in Chinese with English
abstract], Adv. Mar. Sci., 21(4), 394–400.
Ge, R. F., J. S. Guo, F. Yu, and B. H. Guo (2006), Classification of vertical
temperature structure and thermocline analysis in the Yellow Sea and
East China Sea shelf sea areas [in Chinese with English abstract], Adv.
Mar. Sci., 24(4), 424–435.
Guan, B. X. (1983), A sketch of the current structure and eddy characteristics in the East China Sea [in Chinese], in Proceedings of Symposium on
Sedimentation on the Continental Shelf, with Special Reference to the
East China Sea, edited by L. R. Yu, pp. 52–73, China Ocean Press,
Beijing, China.
Guan, B. X. (1999), Phenomenon of the inversion thermocline in winter in
the coastal waters of the west of East China Sea and its relation to circulation [in Chinese with English abstract], J. Oceanogr. Huanghai Bohai
Seas, 17(2), 1–7.
Guan, B. X. (2000), Inversion thermocline in coastal region north and east
of Shandong Peninsula in winter and its relation to deep-bottom counter
current [in Chinese with English abstract], J. Oceanogr. Huanghai Bohai
Seas, 18(3), 1–6.
C02022
Hao, J. J., Y. L. Chen, and F. Wang (2008), A study of thermocline calculations in the China Sea [in Chinese with English abstract], Mar. Sci.,
32(12), 17–24.
Hao, J. J., Y. L. Chen, and F. Wang (2010), Temperature inversion in China
Seas, J. Geophys. Res., 115, C12025, doi:10.1029/2010JC006297.
Hu, D. X. (1994), Some striking features of circulation in Huanghai Sea and
East China Sea, in Oceanology of China Seas, vol. 1, edited by D. Zhou,
Y. B. Liang, and C. K. Zeng, pp. 27–38, Kluwer Acad., Norwell, Mass.
Kara, A. B., A. J. Wallcraft, H. E. Hurlburt, and E. V. Stanev (2008),
Air-sea fluxes and river discharges in the Black Sea with a focus on
the Danube and Bosphorus, J. Mar. Syst., 74, 74–95, doi:10.1016/j.
jmarsys.2007.11.010.
Kobashi, F., H. Mitsudera, and S.-P. Xie (2006), Three subtropical fronts in
the North Pacific: Observational evidence for mode water-induced
subsurface frontogenesis, J. Geophys. Res., 111, C09033, doi:10.1029/
2006JC003479.
Lan, S. F. (1997), Study on temperature and salinity inversion in the northern East China Sea shelf [in Chinese with English abstract], Stud. Mar.
Sin., 38, 17–30.
Lan, S. F., C. C. Gu, and B. Z. Fu (1985), Statistical Analysis of vertical
structure of water temperature in the Bohai Sea, Yellow Sea and East
China Sea (in Chinese with English abstract), Stud. Mar. Sin., 25, 11–25.
Lan, S. F., C. C. Gu, and B. Z. Fu (1993), Inversion phenomenon of temperature and salinity in the continental shelf region of East China Sea [in
Chinese with English abstract], Trans. Oceanol. Limnol., 3, 28–34.
Lee, S. H., and R. C. Beardsley (1999), Influence of stratification on
residual tidal currents in the Yellow Sea, J. Geophys. Res., 104(C7),
15,679–15,701, doi:10.1029/1999JC900108.
Li, H. Q., and Y. L. Yuan (1992), On the formation and maintenance
mechanisms of the cold water mass of the Yellow Sea, Chin. J. Oceanol.
Limnol., 10(2), 97–106, doi:10.1007/BF02844741.
Liu, Q. Y., H. J. Yang, and Q. Wang (2000), Dynamic characteristics of
seasonal thermocline in the deep sea region of the South China Sea, Chin.
J. Oceanol. Limnol., 18(2), 104–109, doi:10.1007/BF02842568.
Liu, Q. Y., Y. L. Jia, P. H. Liu, and Q. Wang (2001), Seasonal and intraseasonal thermocline variability in the central South China Sea, Geophys.
Res. Lett., 28(23), 4467–4470, doi:10.1029/2001GL013185.
Lombardo, C. P., and M. C. Gregg (1989), Similarity scaling of viscous and
thermal dissipation in a convecting surface boundary layer, J. Geophys.
Res., 94, 6273–6284, doi:10.1029/JC094iC05p06273.
Lozovatsky, I., M. Figueroa, E. Roget, H. J. S. Fernando, and S. Shapovalov
(2005), Observations and scaling of the upper mixed layer in the North
Atlantic, J. Geophys. Res., 110, C05013, doi:10.1029/2004JC002708.
Mao, H. L., and D. L. Qiu (1964), National Oceanic Comprehensive Survey
Report: Thermocline, Halocline, Pycnocline Phenomena in China
Coastal Waters [in Chinese] 116 pp., Science Press, Beijing, China.
Marshall, J., and F. Schott (1999), Open-ocean convection: Observations, theory, and models, Rev. Geophys., 37(1), 1–64, doi:10.1029/
98RG02739.
McDougall, T. J. (1987), Neutral surfaces, J. Phys. Oceanogr., 17,
1950–1964, doi:10.1175/1520-0485(1987)017<1950:NS>2.0.CO;2.
McGregor, S., N. J. Holbrook, and S. B. Power (2004), On the dynamics of
interdecadal thermocline depth and sea surface temperature variability in
the low to mid-latitude Pacific Ocean, Geophys. Res. Lett., 31, L24201,
doi:10.1029/2004GL021241.
Pan, A. J., X. G. Guo, J. D. Xu, X. F. Wan, and R. S. Wu (2006), Discussion of criteria for determining thermocline, halocline and sound-cline in
continental shelf break zone of northeastern South China Sea [in Chinese
with English abstract], J. Trop. Oceanogr., 25(5), 8–12.
Park, S., and P. C. Chu (2007), Synoptic distributions of thermal surface
mixed layer and thermocline in the southern yellow and East China Seas,
J. Oceanogr., 63, 1021–1028, doi:10.1007/s10872-007-0085-7.
Qiao, F. L., J. Ma, and Y. Z. Yang (2004), Simulation of the temperature
and salinity along 36°N in the Yellow Sea with a wave current coupled
mode, J. Korean Soc. 0ceanogr., 39(1), 35–45.
Stigebrandt, A. (1981), Cross thermocline flow on continental shelves
and the locations of shelf fronts, Elsevier Oceanogr. Ser., 32, 51–65,
doi:10.1016/S0422-9894(08)70403-3.
Tang, X. H., F. Wang, Y. L. Chen, and M. K. Li (2009), Warm trend in
northern East China Sea in recent four decades, Chin. J. Oceanol. Limnol.,
27(2), 185–191, doi:10.1007/s00343-009-9238-4.
Tu, J. Z. (1992), Variation and distribution of thermocline layers in Bohai
Sea and Yellow Sea [in Chinese with English abstract], Mar. Sci. Bull.,
11(4), 27–32.
Wang, B., R. Wu, and R. Lukas (2000), Annual adjustment of the thermocline in the tropical Pacific Ocean, J. Clim., 13, 596–616, doi:10.1175/
1520-0442(2000)013<0596:AAOTTI>2.0.CO;2.
13 of 14
C02022
HAO ET AL.: SEASONAL THERMOCLINE IN CHINA SEAS
Wang, C. Z., Z. Y. Song, F. L. Qiao, and S. F. Dong (2009), What signals
are removed and retained by using an anomaly field in climatic research?,
Int. J. Oceanogr., 2009, 329754, doi:10.1155/2009/329754.
Wang, F., C. Xu, and L. Dai (2004), International ocean database management system in the China and adjacent seas (IODBMS) [in Chinese with
English abstract], in Proceedings on Scientific Database and Informative
Technology, vol. 7, pp. 66–72, edited by the Office of Scientific Database, Chinese Academy of Sciences, China Environ. Sci. Press, Beijing,
China.
Wang, Y. B., B. Huang, R. Zhang, J. Teng, Z. J. Dong, and H. Z. Wang
(2008), Distribution characteristics of world oceanic thermocline based
on Argo data [in Chinese with English abstract], Adv. Mar. Sci., 26(4),
428–435.
Wang, Z. S., B. C. Xu, M. B. Jin, E. M. Zou, and F. H. Li (1998), A
numerical prediction model of strong thermocline in the Bohai and
the Huanghai Seas, Acta Oceanol. Sin., 17(2), 141–154.
Wyrtki, K. (1961), Physical oceanography of the Southeast Asian waters,
NAGA Rep. 2, 195 pp., Scripps Inst. of Oceanogr., La Jolla, Calif.
Xu, X. Z., Z. Qiu, and X. M. Long (1993), The radical characteristics and
the one-dimensional calculated pattern of the South China Sea thermocline [in Chinese with English abstract], Oceanol. Limnol. Sin., 24(5),
494–502.
Yu, H. H. (1988), Analysis of thermocline feature in the East China Sea
[in Chinese with English abstract], Donghai Mar. Sci., 6(1), 1–11.
C02022
Zhang, R. H., A. J. Busalacchi, and Y. Xue (2007), Decadal change in the
relationship between the oceanic entrainment temperature and thermocline depth in the far western tropical Pacific, Geophys. Res. Lett., 34,
L23612, doi:10.1029/2007GL032119.
Zhang, X., Y. Gehang, S. J. Zhang, and F. L. Huang (2009), The distribution characteristics and seasonal variabilities of thermocline in the Philippine Sea [in Chinese with English abstract], Mar. Sci. Bull., 28(4), 17–26.
Zhao, B. R. (1989), Basic characteristics and forming mechanism of the
sharp thermocline in the Bohai Sea, Huanghai Sea and northern East
China sea, Acta Oceanol. Sin., 8, 497–510.
Zhou, Y. X., B. L. Li, Y. J. Zhang, and L. C. Ba (2002), World oceanic thermocline characteristics in winter and summer [in Chinese with English
abstract], Mar. Sci. Bull., 21(1), 16–22.
Zou, E. M., X. J. Xiong, B. H. Guo, and K. Lin (2001), Characteristics and
seasonal variations of the thermocline and halocline in the Huanghai Sea
and East China Sea [in Chinese with English abstract], J. Oceanogr.
Huanghai Bohai Seas, 19(3), 8–18.
Y. Chen, J. Hao, and F. Wang, Key Laboratory of Ocean Circulation and
Waves, Institute of Oceanology, Chinese Academic of Sciences, 7 Nanhai
Rd., Qingdao, Shandong 266071, China. ([email protected])
P. Lin, State Key Laboratory of Numerical Modeling for Atmospheric
Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric
Physics, Chinese Academy of Sciences, Beijing 100029, China.
14 of 14