Journal of Oceanography
https://doi.org/10.1007/s10872-023-00702-8

ORIGINAL ARTICLE

Seasonal variation in the current field and development of bottom
cold water in Harima‑Nada
Siraporn Tong‑u‑dom1· Akihiko Morimoto2 · Qian Leng1 · Xinyu Guo2

Received: 16 February 2023 / Revised: 6 July 2023 / Accepted: 17 August 2023
© The Author(s), under exclusive licence to The Oceanographic Society of Japan 2023

Abstract
We investigated the seasonal variation in the current field in Harima-Nada using a high-resolution three-dimensional numerical model. The model showed sufficiently good performance at recreating its spatial and seasonal variation. Additionally, themodel successfully reproduced the observed temperature and salinity patterns and values, as well as the observed surface
current fields. The seasonal variation was consistent with previous studies, showing downwind circulation in winter induced
by northwesterly winds and cyclonic circulation in summer induced by density-driven circulation. The water was well-mixed
during winter and stratified in summer. During summer, a bottom cold water (BCW) dome develops beneath the thermocline
in the central basin, where a surface cyclonic eddy occurs. Cold water from the previous winter is trapped at the bottom in
topographic depressions after the onset of spring, forming BCW in the Harima-Nada (HNBCW). Meanwhile, pressure gradients associated with the density difference across the BCW drive geostrophic flow and form a cyclonic eddy at the surface
above the HNBCW. HNBCW experiences a temperature increase of approximately 12.8 °C from spring to summer, which is
associated with vertical diffusion and horizontal advection processes. Air–sea heat flux is the main factor influencing watertemperature and its changes in the HNBCW. In addition, topographic features and river discharge factors affected water
circulations as well as the formation and variation in the HNBCW. Harima-Nada is a small, shallow semi-enclosed coastalsea, and therefore any small change in these dynamic factors can affect water characteristics.
Keywords Hydrodynamic model · Seasonal variation · Bottom cold water · Cyclonic eddy · Harima-Nada · Seto Inland Sea

1 Introduction
Harima-Nada is a basin of the Seto Inland Sea (SIS) thatis connected to Hiuchi-Nada, Osaka Bay, and Kii Channel
through narrow straits named the Bisan, Akashi, and Naruto
Straits, respectively (Fig. 1). Harima-Nada is surrounded by
Honshu and Shikoku Islands, which are intensively urbanized and industrialized. Its area and average water depth are3400 ­km−2 and 26 m, respectively (Yanagi 2008), and thebasin contains numerous islands in its northern and western parts. These complex geographic features are essential
to the physical processes and biogeochemical activities ofthe basin. Several rivers supply freshwater and nutrients* Siraporn Tong‑u‑dom
aommy_se7en@hotmail.com
1

Graduate School of Science and Engineering, Ehime
University, Matsuyama, Japan

2

Center for Marine Environmental Studies (CMES), Ehime
University, Matsuyama, Japan

to Harima-Nada, supporting an abundant system that is amajor fishing ground and aquaculture site for fish, oysters,
and seaweed (Nishikawa et al. 2011). With the increase in
human activities associated with rapid economic growth in
the 1960s–1970s, Harima-Nada became one of the areas of
the SIS that was most seriously impacted by eutrophication(Yamamoto 2003). To alleviate this problem, the Interim
Measures Law for Conservation of the Environment of
the SIS (later designated the Special Measures Law) was
enacted to control and limit total allowable pollutant loads
to the environment from industrial and urban sources. As
a result, phosphorus and nitrogen loads into the SIS werereduced by 55% and 45%, respectively, between 1979 and2009 (Boesch 2019), and some areas of the SIS graduallybecame oligotrophic coastal systems. In recent years, oligotrophication has become a problem, driven by nutrient
depletion. The change in nutrient concentrations is associated with decreases in fisheries production affecting small
pelagic fish, shellfish, and cultivated nori (Pyropia) (Aboand Yamamoto 2019).

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S. Tong‑u‑dom et al.

Fig. 1  The locations of the SIS and the Harima-Nada (a). Locations of tide gauge and monthly observation stations (b). Bathymetry(unit: meters) and model domain for the Harima-Nada (c). In b, thered dots with lowercase letters (a–r) represent the tide gauge, while
the blue dots and triangles denote the monthly observation stations.
The number 1 to 5 denote the selected stations used to validate themodel results for the vertical profile of temperature in Fig. 6. In c,
the dotted lines in Hiuchi-Nada (OB1) and Kii channel (OB2) repre-

sent the open boundaries of the hydrodynamic model. The black solid
circles with lowercase letters (a–t) in c are the locations of the rivers. The bold solid lines with upper case letters (A–C) represent thenarrow straits that are connected to other bays (e.g., A: Bisan Strait,
B: Akashi Strait, and C: Naruto Strait). Line A′B′ denotes the section
along with hydrographic fields presented in Figs. 9, 13, 14, and 15g–i(color figure online)

Numerical model studies in the SIS have been conducted by many researchers (e.g., Kobayashi et al. 2006;
Chang et al. 2009; Yu et al. 2016; Yu and Guo 2018; Wanget al. 2019; Zhu et al. 2019). These studies have reported
that the circulation pattern in the SIS shows strong seasonal variation and differs among basins due to the complex geography of this region. Kobayashi et al. (2006)
suggested that tidal currents and tidal energy dissipation
are strong in and around the straits, and relatively weakin basins, particularly Harima-Nada. Chang et al. (2009)
investigated the seasonal variation in circulation throughout the SIS using a three-dimensional model and revealed

that northwesterly winds play an important role in theoverall circulation of the SIS during the winter season,
driving surface downwind and near-bottom upwind circulation patterns. By contrast, density-driven circulation isdominant in summer due to weak winds and strong stratification, generating cyclonic eddies in several basins including Iyo-Nada, Suo-Nada, and Harima-Nada. Such cycloniceddies are associated with surface warm pool and bottom
cold dome structures (Guo et al. 2004; Chang et al. 2009;
Yu et al. 2016; Yu and Guo 2018; Zhu et al. 2022). However, no previous studies have focused on Harima-Nada.

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Seasonal variation in the current field and development of bottom cold water in Harima‑Nada﻿	

Bottom cold water (BCW), also known as a bottom colddome, generally forms in spring, is well-developed in summer, and disappears in autumn. It has lower temperatures
than surrounding waters and has been widely observed inseveral shelf seas, including the Irish Sea (Horsburgh andHill 2003; Holt and Proctor 2003), Yellow Sea (Xia et al.
2006; Yuan et al. 2013; Zhu et al. 2018), Korean Strait(Cho and Kim 1998; Johnson and Teague 2002; Kim et al.
2006), and Bungo Channel (Takeoka et al. 2000; Kaneda
et al. 2002). Moreover, this phenomenon has been reported
in small-scale areas such as the SIS (Guo et al. 2004; Kobayashi et al. 2006; Kasai et al. 2007; Yu et al. 2016; Yu andGuo 2018; Zhu et al. 2022). The formation of BCW depends
on geographic features, and has two main formation mechanisms: cold water from the previous winter is trapped in
topographic depressions after the onset of the spring season(e.g., cold water masses in the Irish Sea, Yellow Sea, andSIS), which is the most commonly described process, andcold water mass intrusion from adjacent seas (e.g., Bungo
Channel bottom layer intrusion and Korean Strait BCW).
The presence of BCW in Harima-Nada (hereafter, HNBCW)
has been demonstrated through hydrographic observation(Kobayashi et al. 2006) and recreated in a three-dimensional
numerical ocean models (Chang et al. 2009; Yu and Guo2018).
The BCW and associated cyclonic eddy play importantroles in heat transport, water exchange, and biogeochemical activities. For example, a cyclonic eddy in the easternpart of Hiuchi-Nada, which is located on the western side ofHarima-Nada, prevents water exchange between the centerand outer edges of the eddy; in addition, a bottom cold dome
is present, with oxygen-deficient waters formed in the central
part of the eddy (Ochi and Takeoka 1986; Takeoka et al.
1986; Guo et al. 2004; Kasai et al. 2007). Furthermore,
Abe et al. (2015) suggested that nutrient concentrations andapparent oxygen utilization increase in summer in association with the formation of BCW in Suo-Nada. Yoshie et al.
(2011) suggested that breakdown of the BCW in autumn
likely supplies nutrients to the surface layer, supporting theautumn diatom bloom in Iyo-Nada. As noted above, BCW
is associated with a cyclonic eddy that influences coastal
environments and ecosystems throughout the wide basin,
and thus may influence fluctuations of nutrients and the ecosystem of Harima-Nada.
As BCW plays significant roles in heat transport, waterexchange, nutrient cycling, and biogeochemical processes,
clarification of the mechanisms, controlling factors, andintensification of the HNBCW would be useful. Therefore,
we focused on spatial and temporal variation in circulationand the development of BCW using a high-resolution, threedimensional numerical model and examined the generation
mechanism and driving factors of BCW and cyclonic eddy
formation in Harima-Nada.

2 Model description
2.1 Hydrodynamic model and data input
The hydrodynamic model used is based on the Princeton Ocean Model (POM) (Blumberg and Mellor 1987), a
three-dimensional, sigma-coordinate model with a primitive equation. The momentum turbulent closure scheme(Mellor and Yamada 1982) and Smagorinsky formulation(Smagorinsky 1963) are used to calculate vertical and horizontal turbulence mixing, respectively. The model domain
covers the eastern part of Hiuchi-Nada, Harima-Nada,
Osaka Bay, and part of the Kii Channel from 133.34° E to135.48° E and 33.95° N to 34.82° N (Fig. 1c). The bottom
topography for the model was obtained from a nauticalchart with 250 m resolution. The model resolution was set
to approximately 500 m in the horizontal directions (1/220
degree in the meridional direction and 1/180 degree in thezonal direction) and 11 vertical sigma levels. The domain
has two open boundaries, namely, the western boundary
in Hiuchi-Nada (OB1) and the southern boundary at Kii
channel (OB2). To characterize the typical seasonal variation in circulation and BCW formation, climatological
data were used in the hydrodynamic model. The model
was continually repeated for 3 years to achieve a stationary state and the results were saved at an hourly interval
during the last year.
Daily atmospheric data (e.g., wind stress and air–sea
heat flux) were considered a major forcing factor in thesimulation of the hydrodynamic model, detailed descriptions of which were provided by Chang et al. (2009). Daily
river discharge data from multiple years (2000–2019)obtained from the Ministry of Land, Infrastructure, Transport, and Tourism were also used in this calculation. The
model includes 11 major rivers and 9 secondary rivers,
the locations of which are shown in Fig. 1c. The monthly
salinity, water temperature, and velocities obtained fromprognostic modeling across the whole SIS (Chang et al.
2009), as well as the amplitude and phase of the tide andtidal currents based on the M­ 2, ­S2, ­O1, and K­ 1 constituents
obtained from the two-dimensional Harima-Nada model
were applied as boundary conditions at the two open
boundaries.
The Harima-Nada was characterized by four seasons:spring (March–May), summer (June–August), autumn(September–November), and winter (December–February). The monthly variation in wind stress, air–sea heat
flux, and river discharge are presented in Fig. 2. During
the spring season, wind stress is relatively weak, and no
dominant direction is apparent. In the summer and autumn
seasons, the stress remains weak, but southeasterly andnortheasterly winds are dominant. In winter, strong

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S. Tong‑u‑dom et al.

July are used as representative months for winter and summer, respectively. The locations of observation points areshown in Fig. 1b, in which blue dots and triangles represent
the observation points of Hyogo and Kagawa Prefecture,
respectively. In addition, mooring observation data of currents obtained from the Japan Oceanographic Data Center(https://​jdoss1.​jodc.​go.​jp/​vpage/​moor.​html) were used forcomparison with the modeled currents.

3 Results and discussion
3.1 Validation of the model
To assess model performance, the model results were validated against observational data. First, we compared theamplitude and phase of tidal constituents with observations.
Then we compared the spatial distributions of simulated
temperature and salinity with monthly observations collected around Harima-Nada. High-resolution data in vertical along stations 1–5 in Fig. 1b were utilized for comparing
the vertical profiles of temperature. Finally, we presented
the results of observed current fields in the Harima-Nada.
Fig. 2  Monthly averaged climatological mean of a wind stress, b
air–sea heat flux, and c river discharge used in the calculation of thehydrodynamic model in Harima-Nada. The positive u- and v-component of wind stress in a are eastward and northward, respectively.
Positive heat flux in b indicates that the ocean gains heat

northwesterly wind stress is dominant. The net air–sea
heat flux is negative in winter and late autumn, whichmeans that the sea surface loses heat and water temperature decreases. By contrast, net air–sea heat flux is positive, which means that the sea surface gains heat and watertemperatures increases during the spring and summer seasons. In general, river discharge is low throughout the year
except during summer. Total river discharge reaches its
maximum (2242 ­m3 ­s−1) in July and minimum (363 ­m3 ­s−1)
in December, with a mean value of 716 ­m3 ­s−1.

2.2 Observation data
Tidal harmonic constants along the coastline calculated by
the Hydrographic and Oceanographic Department, Japan
Coast Guard (https://j​ doss1.j​ odc.g​ o.j​ p/v​ page/t​ ide.h​ tml) wereused to validate model results, as were monthly water temperature and salinity. Data from 19 stations were observedby Hyogo Prefectural Fisheries Department over 20 years(2000–2020), and those from 7 stations were observedby Kagawa Prefectural Fisheries Department over 9 years(2011–2019). The latter data were collected at a standard
depth interval of 5 m and of 0.1 m for Hyogo and Kagawa
Prefectural Fisheries Department, respectively. January and13

3.1.1 Tidal constituent components
The dominant tidal constituents in Harima-Nada are M­ 2, ­S2,­K1, and O­ 1, among which M­ 2 is dominant (Yanagi and Higuchi 1981). We compared these four modeled tidal constituents with observations from 18 tide gauges. Figure 3 shows
the tidal amplitude and phase lag calculated from model
results and observations (see Fig. 1b for the location of thetide gauges). The comparisons of amplitude and phase lag
showed satisfactory agreement for the four tidal constituents
between the model and observations. Although the model
simulated the observed amplitude and phase lag quite well,
weak comparability was found at a few sites for the ­M2 and­S2 tidal constituents (Fig. 3a, b). The modeled amplitudes of­M2 around the Akashi Strait were larger than observations,while the simulated phase lags of M
­ 2 and S­ 2 in HarimaNada were faster than the observed. These sites are locatedin areas of complex topography, such as around narrowstraits and between islands, that the model could not realistically represent. Nevertheless, comparison of area-averaged
values across the model domain for the four tidal constituents included in the model with observations revealed goodprediction results for all four tidal constituents in terms ofboth amplitude and phase lag (Table 1). The coefficients ofdetermination (R2) for the four tidal constituents in terms ofamplitude and phase lag between observations and model
results were 0.96 and 0.95, respectively. In addition, the root
mean square error (RMSE) was less than 10 cm and 20° for
amplitude and phase lag, respectively.

Seasonal variation in the current field and development of bottom cold water in Harima‑Nada﻿	Fig. 3  Comparison of tidal amplitude (left axis) and phase lag (right axis) between observation (triangles) and model simulation (dots). Locationof tide gauges is shown in Fig. 1b. The comparison of tidal constituent of M2 tide (a), S2 tide (b), K1 tide (c), and O1 tide (d)Table 1  Comparison ofharmonic constants of four
tidal constituents between
observation and model results

Tidal constituent
M2
S2
O1
K1

Amplitude (cm)Phase lag (deg.)
2

RMSE

Obs.

Mod.

R2

RMSE

6.14
3.09
0.82
1.06

273.37228.77
197.86220.62263.44224.12
194.06215.78

0.93
0.99
0.93
0.95

17.43
13.95
4.16
3.30

Obs.

Mod.

R

48.41
18.52
20.44
27.59

49.14
20.54
20.97
27.24

0.96
0.95
0.97
0.95

Amplitude and phase lag are area-averaged ones over the model domain

3.1.2 Temperature and salinity
Figures 4 and 5 show the spatial distributions of observed
and simulated water temperature and salinity at the nearsurface and near-bottom layers in January (winter) and July(summer). During winter, the simulated temperature accurately represents the observed temperature pattern in both
surface and bottom layers, showing lower values along thecoastline compared to the interior of the basin, although thesimulated temperatures are approximately 1 °C higher thanobserved temperatures. On the other hand, the simulation
results represent the observed salinity well in both distribution and value, at approximately 32 throughout HarimaNada, except around river mouths, where it falls to around31.0–31.5 in both surface and bottom layers. In summer,
the simulation results successfully reproduce the observed

temperature and salinity patterns in both surface and bottom
layers, although the values were lower than observations
by about 1 °C and 0.5, respectively. Both the observed andmodeled results indicate the presence of isolated cold waterat the near-bottom layer in the central part of Harima-Nada(Fig. 5c, d). Although the BCW in the model is situated in
the central basin of the Harima-Nada and extends to deep
basin as indicated by 19 °C isotherm, the observed BCW is
located slightly northward and spreads in a northeast–southwest direction. These discrepancies of intensity and positionof the BCW between model and observation might be due
to differences of resolutions; coarse resolution of observed
data and high-resolution of model.
We select specific stations corresponding to the BCW
region indicated by the 19 °C isotherm to validate vertical structure of the BCW in the model. The comparison

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S. Tong‑u‑dom et al.
Fig. 4  Spatial distributions ofobserved and simulation nearsurface temperature (a–d) andsalinity (e–h) in January andJuly in Harima-Nada. The contour interval is 1 °C and 0.5 fortemperature and salinity, respectively (color figure online)of vertical temperature profiles between modeled andobserved data in July at stations 1–5 is shown in Fig. 6.
The observed temperature profiles indicate strong stratification in most stations, except in station 3. The large
standard deviation mostly occurred below the depth 30 m,
suggesting the inter-annual variability of the BCW. The
results clearly show that the model successfully reproduces observed temperature profiles at stations 1, 2, and5. However, at stations 3 and 4, the model exhibits similar temperatures near the surface layer, gradually large inthe deeper layers, which suggests that the model establishes an intensified BCW in those areas compared to theobservation. Although the BCW in the model tends to beintensified, the model effectively reproduces the observed

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temperature and salinity patterns and values in the studyarea.
3.1.3 Surface current fields
The mooring surface current velocity data were collected
at various times between 1972 and 1992 during the monthsof April and June to September. The duration of mooring period was from 2 weeks to a month, and observed
intervals were from 5 to 60 min. As process the data, a25-h running mean is applied to remove tidal signals andthen averaged during mooring period. The results of themooring data analysis are presented in Fig. 7, showing
current field in April and June to September, representingSeasonal variation in the current field and development of bottom cold water in Harima‑Nada﻿	Fig. 5  The same as Fig. 4, but
for near-bottom. The contour
interval is 1 °C and 0.5 fortemperature and salinity, respectively (color figure online)

the spring and summer seasons. In spring, the appearanceof anticyclonic eddy-like patterns near the Akashi Strait
is observed, which is also reflected in the modeled results
shown in Fig. 8a. The magnitude of the surface currents inthe observations is in the range 0.09-0.11 m ­s−1, which is alittle stronger than the modeled results (0.04–0.07 m ­s−1).
In summer, the observations reveal the presence of
cyclonic eddy in the central basin of the Harima-Nada,
as well as the southwestward currents near the Akashi
Strait. The modeled results successfully reproduce thesefeatures as shown in Fig. 8a. The magnitude of the surface
current near the Akashi Strait in the model (0.15 m ­s−1)
is constituent with that in the observations (approximately 0.17 m ­s −1). As for the magnitude of cyclonic

eddy, modeled currents (0.2 m ­s−1) are stronger than theobserved current (0.06–0.13 m ­s−1). The coastal currents
along the northwestern and northern coast of the HarimaNada predominantly flow in a northeastward direction
with an average magnitude of 0.9 m ­s−1 in the observations. However, the modeled results exhibit northeastward
currents along the northwestern coast and southwestward
currents along the northern coast. The magnitude of themodeled currents is relatively stronger near the northerncoast compared to the observations. These inconsistencies in patterns and magnitudes between the modeled andobserved results may be attributed to the difference inthe observation period (year-by-year) compared to thelong-term averaged data used in the model simulations.

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S. Tong‑u‑dom et al.

Fig. 6  The vertical profiles of temperature in July, comparing the model results (black lines with dots) and long-term observations (blue lines).
The shaded areas indicate the standard deviations of observation data (see Fig. 1b for the location of stations 1 to 5) (color figure online)

Fig. 7  Mooring observation current data at near-surface layer during 1972–1992. The left panel shows the moored data during April and theright panel shows the moored data during June to September (color figure online)

Nevertheless, the model generally performs well in capturing the observed surface currents in the Harima-Nada.

3.2 Seasonal variation in the hydrographic field
In this section, we describe the seasonal variation in
the surface and bottom current fields and the horizontal
and vertical distributions of temperature and salinity. To
remove high-frequency signals such as tidal currents, atide-killer filter was applied to the model results, and theresulting values were averaged monthly.

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3.2.1 Spatial and seasonal variation in current fields
Seasonal variation in the near-surface and near-bottom current fields is shown in Fig. 8, in which January, April, July,and October are defined as the representative months for
winter, spring, summer, and autumn, respectively. In January, southeastward currents are dominant at the surface
across the entire Harima-Nada, which might be related to
the winter monsoon wind. Water flows into Harima-Nada
from Osaka Bay through Akashi Strait, and a cyclonic eddy
was present west of the strait. Meanwhile, water flowed
out to Kii Channel through Naruto Strait. Current speeds

Seasonal variation in the current field and development of bottom cold water in Harima‑Nada﻿	Fig. 8  Monthly average ofsimulated surface (a) and nearbottom (b) current distributionsin January, April, July, andOctober. The arrow represents
current vectors and color represents current magnitude (unit:m ­s−1) (color figure online)

were relatively weak (0.05–0.10 m ­s−1) in the central part ofHarima-Nada. In April, westward coastal currents appearedalong the northern coast, while strong southward and southeastward currents were found along the eastern coast of Shodoshima Island and in the southern part of Harima-Nada,
respectively. The current patterns around Akashi and Naruto
Straits were similar to those in the winter season. Cyclonic
and anticyclonic eddy-like patterns are likely present in
the basin and northern part of Harima-Nada, respectively.
In July, a cyclonic eddy was well-developed in the central
part of the basin, with a maximum speed of 0.25 m ­s−1. A
strong westward coastal current occurred along the northern coast, and the current exhibited counter-clockwise circulation in the northern part of Harima-Nada. In October,southeastward current was present in the central basin, alongwith southwestward currents in the northeastern part of thebasin and southward currents along the eastern coast of
Shodoshima Island. In addition, a well-developed cycloniceddy was found in the southern part of Akashi Strait in thisseason.
Figure 8b shows the horizontal distributions of near-bottom currents in January, April, July, and October. In January, upwind currents (northwestward currents) were clearlypresent throughout the study area, and were stronger in the
deeper region than in the shallower region. In Akashi Strait,
the current flowed into Harima-Nada, similar to the nearsurface current. Moreover, an anticyclonic eddy-like pattern was present in the northeastern part of Harima-Nada. In
April, the near-bottom current was relatively weak comparedto other seasons and no distinct circulation patterns were13

S. Tong‑u‑dom et al.

noted. Divergent currents appeared in the northern part ofthe basin in this season. The near-bottom current was similar
in July to the spring season, except that divergent currents
were present in the central basin, where a cyclonic eddy
occurred in the surface layer. In October, current speeds
were relatively strong compared to other seasons. Downwind currents appeared in the southern part of the basin,
while upwind currents were found in the northern part ofthe basin. An anticyclonic eddy-like pattern with a speed of
0.03 m ­s−1 was apparent in the northeastern part of HarimaNada. In addition, a cyclonic eddy appeared south of Akashi
Strait, where a cyclonic eddy also occurred at the surface.

difference between surface and bottom water temperaturesof approximately 3.8 °C.

3.2.2 Seasonal variation in water temperature and salinity

Figure 10 shows the time series of observed and modeled
temperature in the BCW region. Stratification began inspring due to sea surface heating, became well-stratified insummer due to intensified surface heating and weak winds,
and then decayed in early autumn due to surface cooling.
Based on the observation data, the water temperature at thesurface increased from 11.2 to 26.7 °C, and from 10.4 to
21.4 °C at the bottom. Hence, there was surface temperature increase of 15.5 °C, and a bottom temperature increaseof 11.0 °C. The temperature difference between the surface
and bottom layers reached 5.2 °C in mid-August (Fig. 10a).
The rate of temperature increase during the summer season was approximately 3.9 °C ­month−1 at the sea surface
and 2.8 °C ­month−1 at the bottom. On the other hand, thewater temperature derived from the model results, revealed
that at the surface, (bottom) increased from 10.2 (9.4) °C
in early April to 25.3 (22.2) °C in August; increase of surface and bottom water temperature is 15.1 °C and 12.8 °C,
respectively. The difference in water temperature between
the surface and bottom layers reached 3.2 °C in mid-August.
The rate of change in water temperature from mid-autumn
to early spring is similar between the surface and bottom layer, but differs from the rate in mid-spring to early
autumn. In spring, the rate of increase in water temperature
is 0.10–0.20 °C ­day−1 at the surface and 0.05–0.10 °C ­day−1
at the bottom, leading to the development of stratification.
Conversely, the rate rapidly decreases (by approximately
0.10–0.20 °C ­day−1) in the surface layer from late summer
to early autumn. Meanwhile, the rate in the bottom layer
increases (by approximately 0.6 °C ­day−1) in late summer
and decreases during early autumn, causing stratification todisappear. Accordingly, the rate of increase in the surface
layer is accelerated in spring, while the bottom layer does
not show this trend.
We selected July to represent the HNBCW in summer
because the difference in water temperature between thesurface and bottom is relatively constant than in August.
Moreover, we defined the boundary of the HNBCW as
the 19 °C isotherm to isolate the BCW mass from theIn general, spatial differences in water temperature at thesurface were small across Harima-Nada regardless of seasonal changes. On the other hand, salinity varied both seasonally and spatially. Water temperature was lowest during
winter (8 °C), gradually increased during spring, and washighest in summer (27 °C). On the other hand, salinity was
highest in winter (32), gradually decreased during spring,
and was lowest in summer (30.5). Thus, cool and saline
waters were present in winter due to cooling of the sea surface and low river discharge. On the other hand, in summer,
the sea surface gained heat from the atmosphere and higher
river discharge was supplied, causing a warm and less saline
water mass to form.
Water temperature and salinity around the straits were
well-mixed throughout the year due to strong tidal mixing.
On the other hand, the vertical structure of water masses inthe basin showed seasonal variation. We plotted the vertical distribution of temperature, salinity, and density alongsection A′–B′ (shown in Fig. 1c) in January, April, July, andOctober (Fig. 9). In winter (January), the vertical distributions show well-mixed structures of temperature, salinity,and density. Cool (12 °C) and saline water (32) results inhigh density (1024.5 kg ­m−3) in the basin. During spring(April), slight vertical gradients of temperature, salinity,and density form, which become pronounced in summer.
In summer (July), the water is strongly stratified and a cold
dome is present at the bottom of the basin. The temperature
ranges from 17.8 to 21.6 °C, and the salinity ranges from
31.6 to 31.9, from the bottom to the surface. The verticalgradients of salinity are relatively weak compared to thoseof temperature, and thus the vertical gradient of density islargely driven by temperature. In autumn (October), watertemperature rises to 25 °C and the vertical gradient of temperature nearly disappears. On the other hand, salinity isrelatively stratified, and therefore salinity is reflected in thevertical density gradient. Overall, the surface warm pool andbottom cold dome are well established in summer due to the13

3.3 Formation of HNBCW and a cyclonic eddy
in central Harima‑Nada
The summer features described in the previous section demonstrate that the HNBCW was present in the lower layer
and a cyclonic eddy occurred in the surface layer above it.
Therefore, we explore the occurrence of the HNBCW and its
relationship with the cyclonic eddy in this section.
3.3.1 Formation of HNBCW and structures

Seasonal variation in the current field and development of bottom cold water in Harima‑Nada﻿	Fig. 9  Vertical distributions of simulated temperature (a), salinity (b),and Sigma-T (c) along a section A′–B′ (see Fig. 1c for the location ofsection A′–B′) in January, April, July, and October. The blue line of

the 19 °C isotherm in ′ is used to define the Harima-Nada bottom cold
water (color figure online)

surrounding water. The area of the HNBCW is approximately 21 km × 30 km in the zonal and meridional directions, respectively (Fig. 5d), with a maximum (average)
thickness of around 21.5 (10.5) m (July in Fig. 9). The

HNBCW is located in the central deep portion of the basin
below 15 m. The temperature increasing rate during thesummer season is approximately 3.8 °C ­month−1 at the sea
surface and 3.2 °C ­month−1 at the bottom.

13

S. Tong‑u‑dom et al.
Fig. 10  a Time series ofmonthly-average observed
temperature from stations 1 to
2, and b daily-average modeled
temperature in the HNBCW
region. Red solid lines represent
the surface temperature, and theblue solid lines represent thebottom temperature. In b, rightaxis shows the temperature (T)change rate (°C d­ ay−1) for thesurface (red dashed line) andbottom (blue dashed line) layersof the HNBCW (color figure
online)3.3.2 Mechanism of HNBCW formation and its relationshipwith cyclonic eddy

Fig. 11  Time series of daily-average vertical temperature gradient(a), vertical diffusivity coefficient above the HNBCW (b), and relative vorticity at the surface layer (c). The lines are 7-days moving
averaged (color figure online)

13

Figure 11 shows the time series of daily averaged vertical temperature gradient, vertical diffusivity coefficient,and relative vorticity. The vertical temperature gradient isnearly 0 °C ­m−1 from late autumn to early spring, gradually
increases to about 0.10 °C ­m−1 in summer, and then rapidly
decreases to nearly 0 °C ­m−1 in early autumn (Fig. 11a).
The vertical diffusivity coefficient (Kh) above the HNBCW(approximately 15 m in depth) shows an apparent responseto the well-mixed and stratified seasonal patterns, with large
values in winter (2 × ­10−2 ­m2 ­s−1) that gradually decreasein spring to summer and then increase again in autumn.
The vertical diffusivity coefficient in summer ranges from2 × ­10−9 to 10 × ­10−9 ­m2 ­s−1 (Fig. 11b). Meanwhile, relative vorticity showed the similar pattern to the vertical temperature gradient, when the vertical temperature gradientreached its peak (Fig. 11c). Strong stratification prevents
downward heat transport from the sea surface to the bottom layer, which results in small vertical diffusion above the
HNBCW. The relationship between the vertical temperature
gradient and vertical diffusivity suggests that the HNBCWis controlled by the vertical diffusion process.
In general, heat transport in water is governed by the processes of advection and diffusion. Water temperature differs
between the BCW and the surrounding water. To clarify

Seasonal variation in the current field and development of bottom cold water in Harima‑Nada﻿	the processes driving heat transport inside the HNBCW, we
calculated the contribution of each process to the change
in water temperature. The temporal change in water temperature in the hydrodynamic model is calculated with thefollowing equation:

𝜕T= AdvT + VdfT + HdfT,𝜕t(1)

where 𝜕T
is the temporal change in water temperature in the𝜕t
BCW, AdvT is the sum of the advection term, VdfT is thevertical diffusion term, and HdfT is the horizontal diffusion
term. A tide-killer filter was applied to the hourly results foreach term of Eq. (1) and other parameters, and integration
was performed over 24 h.
Figure 12 shows daily averaged heat transport processes
at the center of HNBCW from January to December basedon Eq. (1). Note that the horizontal diffusion term is relatively small compared to the advection and vertical diffusion
terms, and thus is not shown here. Increase of water temperature (°C ­day−1) is quite small in winter and relatively large
in summer. In summer, the rate of increase in water temperature between the surface and 30 m depth is larger than that
below 30 m depth. Moreover, variation in the increase rateof water temperature corresponds to the spring–neap tidal
cycle (Fig. 12a). Advection term at depths of 15–30 m ispositive and accelerates from July to September, indicatingthat the advection process transfers heat to the upper part of
HNBCW (Fig. 12b). The vertical diffusion term is consistently positive during the summer season. From the surface to
15 m in depth, vertical diffusion is greater than below 15 m,
suggesting that downward heat transport from the sea surface to the HNBCW is limited by the thermocline (Fig. 12c).
As noted in the previous section, the HNBCW is associated with an overlying surface cyclonic eddy, and the vertical temperature gradient has a relationship with relative vorticity. Here, we investigated the generation of this cycloniceddy and its relationship with the HNBCW. As stratification
begins in spring and ceases in autumn, the monthly mean
normal velocity was illustrated along with water temperaturefrom April to September (Fig. 13). Stratification formed in
April and accelerated toward summer due to both surface
heating and increased river discharge, which induces a large
horizontal pressure gradient between areas to the north andsouth of Harima-Nada. To maintain quasi-stable flow, thishorizontal pressure gradient force is balanced by the Coriolis force. Consequently, a cyclonic eddy is generated in thesurface layer that isolates a dome of cold bottom water fromthe previous winter. This generation mechanism is similar tothat of the anticlockwise eddy in the eastern part of HiuchiNada described by Guo et al. (2004) and also explains theformation of a cyclonic gyre in the western Irish Sea (Hillet al. 1997). Warming accelerates toward summer (July toAugust), causing the surface layer to become warmer thanthe bottom layer due to limited heat transport at the thermocline. In consequence, the cyclonic eddy becomes stronger at
the surface layer and the dome of cold bottom water becomes
sharper (Hill 1993). The cyclonic eddy is sustained throughthe summer season and gradually changes in response to sea
surface cooling and well-mixed water during autumn.

3.4 Sensitivity analysis for the HNBCW and cycloniceddy
3.4.1 Influences of heat flux and river discharge

Fig. 12  Daily-integrated of each term from Eq. (1). a Daily increasein water temperature (°C), b sum of the advection term (°C d­ ay−1)
and c vertical diffusion term (°C ­day−1) (color figure online)

HNBCW developed in summer and was controlled by heattransport through the processes of advection and vertical diffusion. To investigate the response of the HNBCW
to dynamic factors, we conducted numerical sensitivity

13

S. Tong‑u‑dom et al.

Fig. 13  Monthly mean cross-section distributions of normal velocity(m ­s−1) along a section A′–B′ (see Fig. 1c for the location of section
A′–B′) from April to September (color with black contour). Addi-

Table 2  Sensitivity experiments
and conditions

Experiments

Conditions

Case 1Case 2
Case 3
Case 4
Case 5
Case 6

River discharge increased by 30%
River discharge decreased by 30%
The surface heat loss in the previous winter increased by 20%
The surface heat loss in the previous winter decreased by 20%
The surface heat gain in spring increased by 10%
The surface heat gain in spring decreased by 10%

experiments (Table 2). We investigated only the influencesof river discharge and air–sea heat flux, not local winds. Discharge reached its peak in summer and played an importantrole in density-driven circulation. Meanwhile, air–sea heat
flux generally plays a significant role in circulation in coastal
sea areas and responds to the formation of a BCW mass.
However, local wind stress is relatively weak and might not
influence circulation in summer.
In general, the sea surface loses heat in winter and gains
heat in spring and summer. To determine the effects of
air–sea heat flux on the HNBCW under diverse conditions,
we increased and decreased air–sea heat flux over HarimaNada in winter (December to February) and spring (April toJune). In addition, to determine the effects of river discharge,
we increased and decreased the discharge of each river from
May to July. Percentages given in Table 2 for each sensitivity experiment are based on the long-term variation in each13

tionally, water temperature contours are shown by red lines with redlabels (color figure online)

factor and season. The model was run for 3 years as control
case and then apply each conditions as shown in Table 2.
The results were saved at an hourly for 4th year. Before further analysis, a 25 h running mean was applied to the results
to remove tidal signals.
To quantify the response of HNBCW, we used the percentage sensitivity coefficient (% coefficient), which can becalculated with the following equation:][
Xcase − Xcontrol
× 100,% coefficient =(2)
Xcontrolwhere subscript case and control represent the average values from one of the sensitivity experiments and the climatology simulation, respectively, and x is the variable for watertemperature, thickness, or the area of HNBCW enclosed bya specific isothermal (19 °C, July in Fig. 9).

Seasonal variation in the current field and development of bottom cold water in Harima‑Nada﻿	
Table 3  Percent of sensitivity coefficient for each variable in the sensitivity experiments
Experiments

Case 1Case 2
Case 3
Case 4
Case 5
Case 6

Sensitivity coefficient (%)
TemperatureThicknessArea+ 0.03− 0.04− 0.57+ 0.49+ 0.26− 0.32− 2.31+ 2.88+ 8.06− 7.17− 5.83+ 7.53+ 1.10− 0.58+ 13.87− 19.65− 14.86+ 13.06

Table 3 shows the percentage sensitivity coefficient foreach experiment in terms of water temperature, thickness,
and area of the HNBCW. Positive values indicate that thevalue for the sensitivity experiment is greater than for thecontrol case and negative values indicate that it is below thecontrol case value. The sensitivity coefficient in terms ofwater temperature was most prominent in Case 3 and Case4, followed by Case 6 and Case 5. This suggests that air–sea
heat flux during winter plays a significant role in determining HNBCW water temperature. In terms of thickness, thesensitivity coefficient was relatively high in cases involving air–sea heat flux, indicating that both spring and winterair–sea heat fluxes have equally important and influences
on HNBCW thickness. The sensitivity coefficient for thickness in river discharge cases was comparable but lower thanthose in air–sea heat flux cases. Regarding HNBCW area,
Case 4 had the highest sensitivity coefficient, followed byCase 5, Case 3, and Case 6. This implies that air–sea heat
flux has a greater impact on HNBCW area compared to riverdischarge. Conversely, the sensitivity coefficients in alteredriver discharge cases (Case 1 and Case 2) were lower thanin other cases, indicating that river discharge does not havea direct impact on the HNBCW.
Cold water from the previous winter was trapped in thebottom layer after the onset of the warming season. Thus,
air–sea heat flux change in winter is the most significant
factor controlling the water temperature of the HNBCW.
These changes also had a substantial impact on the thickness and area of HNBCW. Similarly, air–sea heat flux during
spring has a comparable effect on the thickness and area of
HNBCW as in winter. The warming season initiates in April,leading to an increase in water temperature facilitated byvertical diffusion and advection processes. As Harima-Nada
is a shallow coastal sea, there is substantial heat diffusionfrom the sea surface into the HNBCW through downward
heat transport. Therefore, variations in the air–sea heat flux
during spring are crucial in driving changes in the watertemperature of the HNBCW. Although air–sea heat fluxes
in winter and spring play different roles in the formation of

HNBCW, no significant difference in the cyclonic circulation above the HNBCW was observed.
River discharge is another factor influencing circulationin the summer season. The balance between the horizontal pressure gradient and the Coriolis force generates geostrophic flow. Therefore, changes in river discharge affectcirculation associated with the HNBCW below the cycloniceddy. Figure 14 shows the vertical distributions of water temperature (a) and normal velocity (b) in July for the control
case, as well as cases of increased (Case 1), and decreased(Case 2) river discharge. Additionally, the red contour line
shown in Case 1 and Case 2 is the contour of the Control
Case. An increase in river discharge strengthens densitydriven currents, causing a relatively strong horizontal current that can transport heat from surrounding warm water tothe HNBCW, which increases water temperature within the
HNBCW. Moreover, the thermocline above the HNBCW
shifted downward due to the strong cyclonic eddy at thesurface layer; the thickness of HNBCW is smaller and its
area is larger than in the control case. The case of decreased
river discharge showed the opposite results as the case ofincreased discharge, with a weaker density-driven current
resulting in weak horizontal advection of heat transport.
Consequently, cooler water temperature within the HNBCW,
which is of greater thickness and smaller area comparedto the control case, is predicted. However, the influencesof river discharge minimally contributed to the HNBCW
because the boundary of 19 °C isotherm was deeper thanthe effect of cyclonic eddy, changes in river discharge playsmall rule in HNBCW.
3.4.2 Influences of topography
Generally, stratification develops during the warming season
in areas where the tidal current is weak and the water is relatively deep, e.g., basin and shelf areas. The transition frommixed to stratified regimes is associated with tidal fronts.
Tidal fronts occur along the critical contour line of ­log10(H/U3), where H is the water depth and U is the amplitude ofthe ­M2 tidal current, with a critical value of 2.5–3 in the
SIS (Yanagi 2003). The BCW becomes trapped after the
onset of stratification beneath the thermocline in topographic
depressions. In addition, the complex topographic featuresof Harima-Nada affect the BCW mass and cyclonic eddy.
Therefore, we conducted two numerical experiments withvariation in bottom topography. First, we artificially modified the bottom topography to remove Shodoshima Island(Case 7), and second, we set a fixed depth of about 30 m
across the entire calculation domain (Case 8). The hydrodynamic model was run again with the same forcing as thecontrol case, changing only the bottom topography. The
results are shown in Fig. 15.

13

S. Tong‑u‑dom et al.

Fig. 14  Cross-section distributions of temperature (°C) (a) and normal velocity (m ­s−1) (b) along a section A′–B′ (see Fig. 1c for thelocation of section A′–B′) for the control case, increased river dis-charge (Case 1) and decreased river discharge (Case 2) in July. The
red contour lines in Case 1 and Case 2 represent the contour line of
the Control Case (color figure online)

The distribution of the surface current field shows that
Case 7 is similar to the control case, with a cyclonic eddy
at the center of the bay and counter-clockwise circulation in
the northern part of the bay. However, the cyclonic eddy isrelatively large compared to the control case, occupying theentire basin (Fig. 15b). On the other hand, the current fieldin Case 8 shows a markedly different pattern, in which thecyclonic eddy in the central part is unclear and the counter-clockwise circulation in the northern part is extended(Fig. 15c). Cyclonic eddy variation might be related to thechange in l­ og10(H/U3) and position of the tidal front, as thecyclonic eddy occurs around the contour of 3–3.5 (Fig. 15d).
Without Shodoshima Island (Case 7), the tidal front shifted
westward toward Bisan-Seto, indicating that stratification
was enhanced, and as a result, the cyclonic eddy was relatively large (Fig. 15e). Flat topography (Case 8) affects theresidual currents and water exchange among bays. As thewater depth at the straits becomes shallower, tidal currents
around the straits in Case 8 become stronger than in thecontrol case. Thus, no geostrophic flow is generated and no
cyclonic eddy forms, although the distribution of l­og10(H/U3) is quite similar to the control case (Fig. 15f). In conclusion, topographic features play an important role in generating the circulation pattern of Harima-Nada.
The BCW mass in Case 7 is relatively large and cold compared to the control case and is associated with the shape ofthe cyclonic eddy above it (Fig. 15h). By contrast, the BCW
mass in Case 8 is warmer than in the control case (Fig. 15i).
As noted above, a cyclonic eddy is associated with the tidal
fronts and occurs with the BCW. Furthermore, heat transport
via advection is another important factor affecting the BCW;
heat transport from surrounding warm water weakens under
weak tidal current regimes. Heat transport via advection isgreater in the case with flat topography due to the strong
tidal current, and therefore the water temperature is relatively high in that case.

13

3.5 Comparison of BCW with other coastal areas
BCW masses have been widely reported in shelf and coastal
sea areas where tidal mixing is relatively weak. Therefore,
we compared the characteristics of several BCW masses, as
outlined in Table 4. BCW masses in shelf seas such as the
Yellow Sea show small increases in water temperatures (Yuand Guo 2018; Zhu et al. 2018). On the other hand, BCW incoastal seas experiences large temperature increases, including in the Irish Sea (Holt and Proctor 2003; Horsburgh andHill 2003) and the SIS (Yu and Guo 2018; Zhu et al. 2022).
The temperature increase in BCW is mainly controlled bylimited heat transport through the thermocline. In the Yellow Sea, where the horizontal extent of BCW is large, thetemperature increase is mainly driven by downward heatSeasonal variation in the current field and development of bottom cold water in Harima‑Nada﻿	Fig. 15  Distribution of monthly surface current (upper panels),­log10(H/U3) (middle panels) and cross-section distributions of temperature (lower panels) along a section A′–B′ (see Fig. 1c for loca-

tion of section A′–B′) in July. Control case is presented in a, d, andg. Without Shodoshima Island (Case 7) presented in b, e, and h. Flat
topography (Case 8) presented in c, f, and i (color figure online)

Table 4  Comparison of the BCW with other coastal seas
Temperature increase(°C)

Horizontal size of Factor of the temAverage thickReferences
ness of the BCW BCW mass (­ km2) perature increase in the(m)
BCWHarima-Nada 35
Hiuchi-Nada 20

12.8 (Apr–Aug)
4–6 (Jun–Aug)

10.5
10

21 km × 30 km
16 km × 28 km

Diffusion, advection
Diffusion, advection

Iyo-Nada
Irish Sea

60
100

8–10 (Apr–Jul)
4 (Apr–Aug)

30
50

40 km × 30 km
100 km × 100 km

Diffusion, advection
Diffusion, advection

Yellow Sea

70

1 (Apr–Aug)

40

300 km × 300 km

Diffusion

Coastal seas

Water
depth
(m)

transport through vertical diffusion of heat around the thermocline, causing a temperature increase of approximately
1 °C from spring to summer. By contrast, in a coastal sea
such as the Irish Sea, where the horizontal area is smaller

This study
Kasai et al. (2007), Yu andGuo (2018)
Yu and Guo (2018)
Holt and Proctor (2003),
Horsburgh and Hill
(2003)
Zhu et al. (2018), Yu andGuo (2018)

due to the small area between tidal fronts, the temperature
increase is driven by both advection and vertical diffusionfrom surrounding regions, and therefore the BCW temperature increase is large (4 °C).

13

S. Tong‑u‑dom et al.

In the SIS, the presence of BCW masses has been confirmed in several wide basins, including Iyo-Nada (Kobayashi et al. 2006; Chang et al. 2009; Yu et al. 2016; Yu andGuo 2018), Suo-Nada (Chang et al. 2009; Yu et al. 2016; Yu
and Guo 2018), Harima-Nada (Kobayashi et al. 2006; Changet al. 2009; Yu et al. 2016; Yu and Guo 2018), and HiuchiNada (Ochi and Takeoka 1986; Takeoka et al. 1986; Kasai
et al. 2007; Guo et al. 2004; Yu and Guo 2018). These basins
have different geographic features, and thus the horizontal
and vertical scales of their BCW masses differ. Consequently, these BCW masses have different characteristics. In
Iyo-Nada, which is a wide area with deep water, the largest
BCW mass in the SIS occurs, which undergoes a temperature increase of about 8–10 °C from spring to summer. The
temperature increase in this area is driven by advection fromsurrounding warm water, which transports heat to the BCW
at twice the rate of vertical diffusion (Yu and Guo 2018).
Meanwhile, Hiuchi-Nada has the smallest BCW mass in the
SIS. This area is a shallow, small region and the tidal current
is relatively weak; consequently, the temperature increaseis mainly controlled by downward heat transport throughvertical diffusion (Yu and Guo 2018). In Harima-Nada, the
HNBCW is surrounded by areas of relatively strong tidal
mixing around the straits, and thus heat transport from surrounding warm water is relatively large. In addition, HarimaNada is relatively shallow, and thus downward heat transport
through vertical diffusion and redistribution of heat within
the HNBCW play significant roles in the rate of increasein water temperature. Accordingly, advection and vertical
diffusion play comparable roles in warming the HNBCW.

4 Conclusion
Physical processes in Harima-Nada were investigated basedon a high-resolution, three-dimensional numerical model.
Seasonal variations in currents and hydrographic fields were
examined in this study. Summer features, e.g., BCW andcyclonic eddy, were explored in terms of their mechanisms
and controlling factors. The model accurately reproduces
long-term observed hydrographic fields, and the simulated
current fields were consistent with the surface observed
currents and a previous numerical study in the SIS (Changet al. 2009). Moreover, observed water temperature in summer revealed the existence of a BCW mass in the basin ofHarima-Nada (the HNBCW). Therefore, this model has sufficiently good performance for assessing the temporal andseasonal variation in currents and hydrographic fields in
Harima-Nada.
The current field shows seasonal variation in both thesurface and near-bottom layers in terms of the circulation
pattern and magnitude. In winter, winds play an important role in driving circulation, which is downwind in the13

surface layer and upwind in the near-bottom layer. On theother hand, density-driven circulation plays a significant
role in summer circulation, associated with weak winds andstratification. In addition, a cyclonic eddy is generated in thesurface layer of the central Harima-Nada in summer. During transitional seasons (spring and autumn), no dominantpattern is observed due to relatively weak winds. The hydrographic fields show distinct winter and summer structures. In
winter, vertically well-mixed water is present throughout the
study area due to strong northwesterly winds and sea surface
cooling. By contrast, in summer, water is strongly stratified
in the basin due to relatively weak winds but is well-mixed
at the straits due to strong tidal mixing. Stratification begins
in spring due to sea surface heating, accelerates toward summer, and then is destroyed in autumn. The BCW mass develops in summer beneath the thermocline layer, above which
the cyclonic eddy occurs.
Cold water from the previous winter becomes trappedin the bottom layer after the onset of the warming season,
leading to HNBCW generation in the central HarimaNada. The pressure gradient in spring drives geostrophic
flow, which develops into a cyclonic eddy in the surface
layer above the BCW mass. The HNBCW experiences atemperature increase from early spring to summer of about
12.8 °C, while the increase at the surface is about 15.1 °C.
These large increases in temperature are compatible withthe temperature increase measured in Iyo-Nada (Yu andGuo 2018). Heat transport via advection and vertical diffusion is responsible for the large temperature increase within
the HNBCW. The vertical diffusion of heat is limited by
the thermocline, resulting in an increase in the temperature
within the HNBCW due to redistribution of heat inside thiswater mass. In addition, advection transports warm waterfrom the surrounding area to the HNBCW in association
with the tidal cycle.
Air–sea heat flux is the main factor influencing water temperature and its changes in the HNBCW. Water temperaturein the previous winter controls the intensity of the BCW
mass. However, variation in the air–sea heat flux in spring
affects the HNBCW through the processes of advection andvertical diffusion. Furthermore, topographic features affectthe circulation and control the formation of HNBCW. River
discharge is another factor affecting water circulation, andthus influencing variation in the HNBCW. Harima-Nada isa small, shallow semi-enclosed coastal sea, and therefore
any small change in these dynamic factors can affect water
characteristics.
Acknowledgements This research was performed by the Environment
Research and Technology Development Fund (JPMEERF20205005) of
the Environmental Restoration and Conservation Agency Provided by
the Ministry of Environment of Japan. The authors thank Drs. Kuninao Tada, Hitomi Yamaguchi, and Masatoshi Nakakuni of Kagawa
University for their research collaboration. Hydrographic data for theSeasonal variation in the current field and development of bottom cold water in Harima‑Nada﻿	whole Harima-Nada were supported by Hyogo Prefectural Fisheries
Department and Kagawa Prefectural Fisheries Department. Data of
tidal constituent were supported by Hydrographic and Oceanographic
Department. Mooring observation data of currents were provided by
the Japan Oceanographic Data Center.
Data availability The datasets generated during the course of this study
are accessible upon reasonable request from the collabrorative effortsof the Hyogo Prefectural Fisheries Department and the Kagawa Prefectural Fisheries Department.

Declarations
Conflict of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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