RESEARCH ARTICLE
10.1029/2022PA004486
Key Points:• V olume transport through the
Tsushima Strait reduces non-linearly
when the sea level reduces linearly• Sea surface salinity of the Japan Sea
reached its minimum value (20.2) at
20 kyr BP• Volume transport through the
Tsushima Strait dominates the value
and timing of the minimum salinity,
and P-E can modify the former
Supporting Information:

Supporting Information may be found in
the online version of this article.
Correspondence to:

X. Guo,guoxinyu@sci.ehime-u.ac.jp
Citation:

Zheng, J., Guo, X., Yang, H., Du, K.,
Mao, X., Jiang, W., et al. (2023). Low
sea surface salinity event of the JapanSea during the Last Glacial Maximum.
Paleoceanography and Paleoclimatology,
38, e2022PA004486. https://doi.
org/10.1029/2022PA004486
Received 24 MAY 2022
Accepted 26 DEC 2022

Low Sea Surface Salinity Event of the Japan Sea During theLast Glacial Maximum
Junyong Zheng1,2,3 , Xinyu Guo3,4 , Haiyan Yang5, Kailun Du6, Xinyan Mao1,2 ,Wensheng Jiang6 , Takuya Sagawa7 , Yasumasa Miyazawa4 , Sergey M. Varlamov4,
Ayako Abe-Ouchi8 , and Wing-Le Chan8,9
Key Laboratory of Physical Oceanography, Ministry of Education, Ocean University of China, Qingdao, China, 2College of
Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China, 3Center for Marine Environmental Studies,
Ehime University, Matsuyama, Japan, 4Application Laboratory, Japan Agency for Marine-Earth Science and Technology,
Yokohama, Japan, 5Graduate School of Science and Engineering, Ehime University, Matsuyama, Japan, 6Key Laboratory ofMarine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao, China, 7Institute of Scienceand Engineering, Kanazawa University, Kanazawa, Japan, 8Atmosphere and Ocean Research Institute, University of Tokyo,
Tokyo, Japan, 9Now at Research Center for Environmental Modeling and Application, Japan Agency for Marine-Earth
Science and Technology, Yokohama, Japan
1

Abstract Abnormal lightening of the oxygen isotope ratio (δ 18O) of planktonic foraminifera during the Last
Glacial Maximum (LGM, ∼21 kyr BP) suggests that the Japan Sea had experienced a low sea surface salinity
event at that time. However, the exact value and timing of minimum salinity have been controversial so far.
To address this issue, we adopt a simple box model and reconstruct the sea surface salinity in the Japan Sea(SJP) over the past 35 kyr with a focus on the LGM period. In particular, as input data for the box model, theinflow transport through the Tsushima Strait (Q) is converted from sea level evolution using a newly defined
relationship, in which Q reduces non-linearly with the sea level reduction through a dynamically-constrained
realistic ocean model. Meanwhile, another input data of the box model, sea surface freshwater flux
(precipitation minus evaporation (P-E) evolution), is obtained by averaging multi-paleoclimate models(PMIP3 and MIROC4m models) results. The reconstructed SJP using the box model reached its minimum
value (20.2) at 20 kyr BP with a high coefficient of determination (R 2) for δ 18O (0.81, p << 0.01). Further
analysis demonstrates that the above non-linear relationship, determined by h 3/2 (h is the strait depth), promisesa more reasonable reconstruction of the SJP evolution. It is also concluded that both the value and timing of
the minimum SJP depend on the Q evolution, and the P-E evolution can modify the former. Therefore, thecombination of Q and P-E determines the exact value and timing of minimum salinity.

Plain Language Summary Twenty one thousand years ago, as a large volume of water froze
over land at the Last Glacial Maximum (LGM), the global sea level was depressed by about 130 m. Somesemi-enclosed marginal seas with shallow entrances, like the Japan Sea, became completely or almost
isolated. Limited communication with the surrounding seas and continuous freshwater input led to a low
surface salinity event in the Japan Sea. With two refinements on prior reconstructions of surface salinity, we
configure a simple box model to obtain its minimum value (20.2) at 20 kyr BP. Among two refinements, one
is a nonlinear-constrained evolution of the inflow transport through the Tsushima Strait; the other is a morereasonable evolution of freshwater flux from multi-paleoclimate models. The reduction of surface salinity could
enhance the density stratification and severely restrict the deep convection, leaving a poorly-ventilated, anoxic,and sulfidic deep water, which has been suggested for the environment in the Japan Sea during the LGM. It isnoted that such box models can be applied to other semi-enclosed marginal seas.
1. Introduction© 2023. American Geophysical Union.
All Rights Reserved.

ZHENG ET AL.

The Last Glacial Maximum (LGM, ∼21 kyr BP) is the most recent interval marked by a maximum expansionof continental ice sheets associated with a global sea level lowstand (Clark et al., 2009; Spötl et al., 2021). It
has been suggested that the sea level was ∼130 m lower during the LGM than at present (e.g., Fairbanks, 1989;
Gowan et al., 2021; Stiller et al., 2021; Yokoyama & Purcell, 2021; Yokoyama et al., 2000, 2019). With a decrease
in sea level of ∼130 m, it is easy to imagine that many shallow shelf seas or bays at present were land during the

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Figure 1. (a) Model domain of the realistic numerical model and its bathymetry (unit: m) under the present sea level (0 m).
(b) Enlarged view of the black box in (a) around the Japan Sea area. Light and dense gray areas indicate land under Last
Glacial Maximum (−130 m) and present sea level, respectively. Red arrows indicate three branches of the Tsushima Warmcurrent (the East Korea Warm Branch, Offshore Branch, and Nearshore Branch from west to east). Blue arrow indicatesthe Liman Cold Current. (c) Evolution of oxygen isotopic ratio (δ 18O) in planktonic foraminifera adapted from Sagawa
et al. (2018).

LGM. Some semi-enclosed marginal seas or fjords with shallow entrances have become completely or almost
isolated (E. Lee, Kim, & Nam, 2008).
A typical example is the Japan Sea in the Northwest Pacific (Figures 1a and 1b). The Japan Sea is a deep(∼1,500 m in depth) but semi-enclosed marginal sea surrounded by the Eurasian Continent and Japanese Archipelago (Kida et al., 2016). It is connected with the surrounding seas through four shallow and narrow straits:
the Tsushima Strait (∼130 m) connecting to the East China Sea, the Tsugaru Strait (∼130 m) to the Northwest
Pacific, and the Soya and Tartar Straits (∼55 and ∼12 m, respectively) to the Sea of Okhotsk (E. Lee, Kim, &Nam, 2008; Oba & Irino, 2012). With present-day sea level (dense gray area in Figure 1b), the water exchange
between the Japan Sea and surrounding seas involves warmer and saltier inflow through the Tsushima Strait(2.64 Sv, Shin et al., 2022, 1 Sv ≡ 10 6 m 3 s −1), and colder and fresher outflow through the Tsugaru and Soya
Straits (1.5 and 0.91 Sv, respectively, Japan Sea Throughflows). Transport through the Tartar Strait (<0.05 Sv) is
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negligible compared to transport through the other straits (Tsujino et al., 2008; Yanagi, 2002). The upper 200-m
layer of the Japan Sea, which is above the permanent pycnocline, is profoundly affected by the throughflows(Isobe, 2020; Oba & Irino, 2012; Yanagi, 2002). Coupled with the air-sea heat flux and freshwater input, thethroughflows maintain the heat and salinity budget balance of the upper Japan Sea (Dong et al., 2020; Kida
et al., 2016; Wu et al., 2020). As partial original water source, the inflow through the Tsushima Strait was alsosuggested to contribute to the formations of the intermediate and deep water masses (Gamo et al., 2014; S.
Kim et al., 2021; J. Park & Lim, 2018). With a decrease in sea level of ∼130 m, shelves of these four straits
were exposed and the Japan Sea was either completely or almost isolated from adjacent seas during the LGM(light gray area in Figure 1b; Isobe, 2020; Oba & Irino, 2012; Wu et al., 2020; Yokoyama et al., 2007). Water
exchange with the throughflows was extremely limited and drastic regulation of oceanographic conditions naturally occurred in the upper Japan Sea (E. Lee & Nam, 2004). In this study, we focus on the influence of thisisolation event on the surface salinity in the Japan Sea (SJP).
The recovery of this drastic regulation event of SJP during the LGM has been diligently examined in many studies(K. E. Lee, 2007; Sagawa et al., 2018; Wu et al., 2020). The oxygen isotope ratio (δ 18O) of planktonic foraminifera in the sediments, as a recorder of paleoenvironmental conditions in the Japan Sea, could faithfully explain
this regulation story. It has been suggested that δ 18O ratio experienced a sharp reduction from ∼30 kyr BP, witha minimum value around the LGM (Figure 1c; Matsui et al., 1998; Oba et al., 1991; Sagawa et al., 2018; Wu
et al., 2020; Yokoyama et al., 2007). A minimum δ 18O generally corresponds to highest temperature or lowest
salinity at the sea surface (Ravelo & Hillaire-Marcel, 2007; Yokoyama et al., 2007).
Over the past several decades, the alkenone thermometry has been applied to reconstruct sea surface tempera′ture (SST) of the Japan Sea. Ishiwatari et al. (2001) reported a high alkenone-based(UK37 ) SST as 18°C–19°C𝐴𝐴during the LGM, 2°C–3°C higher than that during Holocene, which was probably caused by thermal energyof solar radiation trapped in the stable stratified surface seawater. This high SST was also identified by Fujine′
et al. (2009), Liu et al. (2014), and Wu et al. (2020). However, unusually𝐴𝐴high UK37 -SSTs was not found in K. E.
Lee, Bahk, and Choi (2008) and Y. H. Park and Khim (2022). Yokoyama et al. (2007) suggested that the alke′
none content was dramatically low during the LGM, and thus difficult to calculate𝐴𝐴
UK37 -SST. Fujine et al. (2009)
further indicated that low salinity may have an ecological or physiological influence on the alkenone proxy, andthereby regarded the high SST as anomalous. Furthermore, the warm LGM SST was not supported by micropaleontological studies (Yokoyama et al., 2007). Records from diatom, benthic and planktonic foraminifera, andradiolarian species revealed that SST during the LGM was much lower than that of today (Hyun et al., 2013; Itaki
et al., 2007; Koizumi & Yamamoto, 2011; Matsui et al., 1998; Nakagawa et al., 2003; Oba & Tanimura, 2012).
Although the SST of the Japan Sea during the LGM remains controversial, we assumed that, supported by theabove descriptions, the SST during the LGM was not higher than that in other periods. Following this assumption, the abnormal reduction in δ 18O there strongly suggests a low SJP event (S. Gorbarenko et al., 2021; E. Lee,
Kim, & Nam, 2008; Matsui et al., 1998). However, partly because of the unclear relationship between δ 18O andSJP, previous studies leave the exact value of minimum SJP during the LGM as disputable (28, Oba et al., 1991;
20, Tada, 1999; 29.8, S. A. Gorbarenko & Southon, 2000; 26–29, Oba & Tanimura, 2012).
The box model, based on water and salinity budget balance in the Japan Sea, has been employed to resolve thiscontroversy. Matsui et al. (1998) adopted a salinity-balance box model for the upper Japan Sea to reconstruct
SJP evolution over the past 35 kyr. They obtained a minimum SJP of 20 during 20–15 kyr BP. Similarly, Ikeda
et al. (1999) employed two boxes to represent the northern and southern parts of the upper 300 m in the Japan
Sea, and estimated that the SJP in the two boxes reached their minimum values (28.83, 29.59) during 17–15 kyr
BP. Despite the minimum SJP (value and timing) differences, the box model provides an alternative and feasible
method to quantify low-salinity event.
The calculated minimum SJP depends strongly on the inflow transport through the Tsushima Strait (Q) and theprecipitation minus evaporation (P-E) evolution for the box model. However, it is challenging to estimate continuously and precisely through a direct methodology. As a compromise, Matsui et al. (1998) assumed a linear relationship between Q and the Tsushima Strait depth (sea level), and used it to convert the sea level evolution into
Q evolution, but without verifying this relationship. Ikeda et al. (1999) simply specified an idealistic Q evolution(linearly decreased from 1.0 to 0.01 Sv between 25 and 17 kyr BP, remained at 0.01 Sv over 17–15 kyr BP, linearly increased to 1.5 Sv from 15 to 10 kyr BP and remained at 1.5 Sv until present day). An idealistic P-E evolution was also specified and remained as a time-independent constant (0.3 m y −1 ≈ 0.82 mm d −1) both in Matsui
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et al. (1998) and Ikeda et al. (1999). Apparently, the Q and P-E evolutions
used in the above studies are not supported by paleoceanographic evidence
nor do they have dynamical constraints, and therefore more careful examinations and refinements for a reasonable SJP reconstruction are needed.
In this study, we also design a box model to reconstruct the SJP evolution
over the past 35 kyr with a focus on the low SJP event at the LGM. As an
improvement over Matsui et al. (1998) and Ikeda et al. (1999), we refine the
Q and P-E evolutions to obtain a more precise value and timing for minimum
SJP. For the Q evolution, we will first quantify the relationship between Q andsea level through a basin-scale realistic hydrodynamic model. This realistic
model, constrained by dynamical equations, could provide a more reasonable relationship than that assumed by Matsui et al. (1998). Investigation ofthis relationship is meaningful for the study of regional paleoenvironmental
Figure 2. Schematic of the box model for SJP reconstruction. This box modelchanges around the Japan Sea. More importantly, such an investigation could
focuses on the upper 200-m Japan Sea and its total volume is defined as W0.
capture local effects exerted by remote forcing from the open sea during theWater mass conservation is among inflow through the Tsushima Strait Q,
last deglaciation (Nishida & Ikehara, 2013; Oba et al., 1991). This is because
freshwater flux F, and outflow through the Tsugaru and Soya Straits Q + F.
local sea level difference (high in south of the Tsushima Strait and low in
The freshwater flux here comprises precipitation over evaporation P-E, andriver discharge R. The conservation of salinity is between inflow salinity QS0,
east of the Tsugaru and Soya Straits), which dominates the mean value of Q,
and outflow salinity (Q + F)SJP.
was remotely controlled by the basin-scale wind stress over the North Pacific(Minato & Kimura, 1980; Ohshima, 1994; Tsujino et al., 2008). Assisted bythis dynamically-constrained relationship, the Q evolution can be converted
from sea level evolution provided by previous studies (e.g., Yokoyama et al., 2018). Meanwhile, multi-model
simulation results from the third phase of the Paleoclimate Modeling Intercomparison Project (PMIP3) andModel for Interdisciplinary Research on Climate 4m (MIROC4m) are also involved, which offer an excellent
opportunity to refine the P-E evolution more comprehensively and quantitatively.
The remainder of this paper is organized as follows. Details of the box model and methods used to refine the Q
and P-E evolutions are introduced in Section 2. Section 3 shows the relation between the Q and sea level and theQ, P-E, and reconstructed SJP evolutions over the past 35 kyr. Section 4 includes further discussions and Section 5
presents the summary.

2. Materials and Methods
A simple box model for SJP reconstruction is laid out in this section. Methods to refine its input data (Q and P-E
evolutions) are given in detail.
2.1. Box Model
Similar to previous studies (e.g., Matsui et al., 1998; Topper et al., 2011), conservation of water mass and balanceof salt budget provide the framework for this box model. In this model, the following four points are considered.
(a) Only the upper 200 m of the Japan Sea is considered in this box model and its total volume W0 is assumed
as a constant (1.5 × 10 14 m 3, Yanagi, 2002). A sensitivity experiment and analysis in the Text S1 in Supporting Information S1 suggest the acceptability of this assumption; (b) Freshwater flux (F), inflow, and outflow
through straits are taken into consideration, while the vertical water exchange between the upper 200 m and thelayer below is neglected. F here contains P-E and river discharge (R); (c) Response of SJP to external influences
mentioned above is instantaneous, that is, the box is always well mixed; and (d) The salinity of adjacent seasaround the Japan Sea does not change over time. Based on these considerations, we establish a salt-balance box
model (Figure 2), which can be formulated as:
𝑄𝑄(𝑡𝑡)𝑆𝑆0 − [𝑄𝑄(𝑡𝑡) + 𝐹𝐹 (𝑡𝑡)]𝑆𝑆JP (𝑡𝑡)d𝑆𝑆JP (𝑡𝑡)
=
(1)
d𝑡𝑡
𝑊𝑊0
𝐹𝐹 (𝑡𝑡) = 𝑃𝑃 (𝑡𝑡) − 𝐸𝐸(𝑡𝑡) + 𝑅𝑅(𝑡𝑡)(2)The meanings of each symbol in these two equations are listed in Table 1. The salt input through the Tsushima
Strait is calculated by multiplying its volume transport Q(t) with salinity S0, that is, Q(t)S0. Correspondingly, salt
output through the Tsugaru and Soya Straits is [Q(t) + F(t)]SJP(t). The salt through the Tartar Strait is negligible
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Table 1
Variables and Parameters Related to the Box Model
Variable or parameter

Meaning

Method or value

Reference

Q(t)Inflow transportThis study

–

P(t)

Precipitation over Japan Sea

PMIP3, MIROC4m

–

E(t)

Evaporation over Japan Sea

PMIP3, MIROC4m

–

F(t)

Freshwater flux

P(t)-E(t) + R

Yanagi (2002)

R(t)River discharge

Linearly proportional to P(t)–S0Inflow salinity

33

Matsui et al. (1998)

W0

Volume of upper Japan Sea

1.5 × 10 14 m 3

Yanagi (2002)

SJP(t)

Salinity of upper Japan Sea

To be resolved–

because its volume transport is much smaller than that through the other three straits, as described in the Introduction. The difference between salt input and output for the upper 200 m of the Japan Sea (W0) determines theevolution of SJP(t). The calculation method and value of input variables and parameters in the two equations arealso presented in Table 1, where unknown variables are marked in bold. Notably, we assume that R(t) is linearly
proportional to P(t) as R(t) = αP(t), where α is a constant coefficient calculated as the ratio of river discharge
and precipitation rate under presented day. With the specified Q and P-E evolutions, the temporal variation of SJP
during the evolution period can be calculated using Equation 1. Methods to determine Q and P-E evolutions are
introduced in the following section.
2.2. Methods to Refine the Q and P-E Evolutions
2.2.1. Refinement to the Q Evolution
As a first step, we introduce and develop a basin-scale realistic numerical model to examine the relationshipbetween Q and sea level. Second, sea level evolution from previous studies is also described. Under this newly
defined relationship, sea level evolution can be converted into Q evolution.
2.2.1.1. Experiments Using the Realistic Numerical Model
A basin-scale numerical model incorporating realistic bathymetry and meteorological forcing (wind stresses, heat
fluxes, and salt fluxes) over the North Pacific and Japan Sea is involved here. The source codes come from theStony Brook Parallel Ocean Model (sbPOM, Jordi & Wang, 2012). The model domain covers the entire North
Pacific and the Japan Sea (30°S–62°N, 100°E−70°W, Figure 1a) with a horizontal resolution of 1/4° and 21
terrain-following vertical layers. Detailed configurations of this realistic numerical model could be found in the
Text S2 in Supporting Information S1.
The calculation for realistic model (R-CTRL) is set under the present sea level (0 m) and the model is evaluatedby judging whether it can capture the basic features of the annual mean Q. To reveal the regression relationshipbetween the Q and sea level, 13 sensitivity experiments (R-SENS) are conducted by modifying the sea level in
R-CTRL. In these experiments (R-SENS), the sea level decreases linearly from 0 m to −130 m at intervals 10 m.
This is the only change from the R-CTRL. After fixing the new water depth of each grid point in R-SENS, theinitial and boundary conditions for R-SENS are obtained in the same way as R-CTRL. All the experiments arestarted from an equilibrated ocean and run continuously for 40 years. We treat the first 35 years as the spin-up
phase and use the annual mean model results from the final 5 years for analysis.
2.2.1.2. Sea Level Evolution
Apart from this regression relationship derived from the realistic model, another variable for refining the Q evolution is the change in global mean sea level, which is adapted from Yokoyama et al. (2018; Figure 3a). The sea
level change was derived from fossil coral reef material obtained from the Great Barrier Reef in Australia during
the Integrated Ocean Drilling Program (IODP) Expedition 325, combined with data through glacio-isostatic
modeling. Figure 3a shows a rapid fall (∼45 m) in sea level from 32 to 29 kyr BP after an initial gentle fall (∼5 m)from 35 to 32 kyr BP. A relatively constant sea level was construed at 28–22 kyr BP. Subsequently, the sea level
reached its lowest value (<−125 m) within a short period (∼2 kyr) around 20 kyr BP. From then on, the sea level
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Figure 3. The sea level and Q evolutions. Solid lines in (a), (c), and (e) represent the sea level evolutions adapted from
Yokoyama et al. (2018), Arz et al. (2007), and Saito et al. (1998), respectively. The solid lines in (b), (d), and (f) are Q
evolutions derived from (a), (c), and (e) under the non-linear regression relationship, respectively. The dashed line in (b) is thesame as the solid one but under the linear regression relationship. Width of the curves represents analytical uncertainties fromsea level. The dotted lines denote the sea level at −130 m for (a), (c), and (e), and transport at zero for (b), (d), and (f).

exhibited an increasing trend until present with several rapid melting events. The width of the curve in Figure 3a
represents the analytical uncertainties at the sea level.
To explore the influence of Q evolution on SJP reconstruction, especially on the value and timing of minimum SJP,
the sea level changes reported by Arz et al. (2007) and Saito et al. (1998) are also used to calculate the Q evolutions for the box model. These two kinds of sea level evolutions (Figures 3c and 3e) were reproduced from benthic
δ 18O in the northern Red Sea and radiocarbon dating of shells in the East China Sea, respectively. Althoughdetailed features among these three types of sea level evolutions are different, the values of the lowest sea level
were all smaller than −120 m and occurred around 20 kyr BP.
Overall, the sea level has gone through a series of changes over the past 35 kyr. A drastic Q evolution is expected
and will be obtained with the new regression relationship with the sea level mentioned above.
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Table 2
Basic Information About the PMIP3 and MIROC4m Models
Model
CCSM4
CNRM-CM5
FGOALS-g2
IPSL-CM5A-LR
MIROC-ESM
MPI-ESM-P
MRI-CGCM3
MIROC4m

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2.2.2. Refinement to the P-E Evolution

We use simulation results from the PMIP3 and MIROC4m models to refine
the P-E evolution over the past 35 kyr. The PMIP was first established in
Referencethe early 1990s to provide a framework for coordinating paleoclimate modeling, paleo-data syntheses, and evolution to analyze and understand climate
1.25° × ∼0.90°
Gent et al. (2011)change and its feedbacks (Braconnot et al., 2012; Harrison et al., 2015). The∼1.40° × ∼1.40°
Voldoire et al. (2013)
PMIP coordinated experiments, conducted by multiple modeling groups,∼2.80° × ∼3–6°
L. Li et al. (2013)
reproduced features of several key historical periods by imposing suitable∼3.75° × ∼1.90°
Dufresne et al. (2013)changes in the boundary conditions. Detailed information regarding these∼2.80° × ∼2.80°
Watanabe et al. (2011)
experiments is provided at https://esgf-node.ipsl.upmc.fr/search/esgf-ipsl/.
∼1.87° × ∼1.87°
Giorgetta et al. (2013)
Here, monthly simulation results of the LGM, Mid-Holocene (MH, 6 kyrBP), and Pre-industrial (PI, 0 kyr BP) experiments from the CCSM4,∼1.12° × ∼1.12°
Yukimoto et al. (2012)
CNRM-CM5, FGOALS-g2, IPSL-CM5A-LR, MIROC-ESM, MPI-ESM-P,∼2.80° × ∼2.80°
Chan et al. (2011)
and MRI-CGCM3 models within the framework of PMIP3 (Table 2) areused to quantify the P-E evolution. Pre-processing is performed on the above
results by calculating the temporal mean at these three periods, and averaging spatially over the Japan Sea area (35°N–52°N, 128°E−142°E). Moreover, MIROC4m simulation results are
employed to provide data for these three periods and two extra historical regimes (35 and 30 kyr BP) with thesame pre-processing. MIROC4m is a coupled atmosphere-ocean general circulation model, where m stands for
mid-resolution (horizontal resolution of the atmospheric model is ∼2.8°; Table 2). This model has been widelyused to simulate paleoclimatic changes (e.g., Sherriff-Tadano et al., 2021).

Atmosphere resolution(Latitude × Longitude)

The P-E evolution is refined by averaging these multi-model simulation results for 35 and 30 kyr BP, LGM, MH,
and PI, which is considered to be a means of reducing the uncertainty from each of the models. Additionally,
simulation result from each model is also employed to quantify the impact of P-E evolution on the minimum SJP.

3. Results
In this section, the regression relationship between Q and sea level is derived from the realistic ocean model
result. With this relationship, the sea level evolution over the past 35 kyr is converted to the Q evolution. The box
model thereafter is used to demonstrate the SJP evolution and its minimum value with a combination of this Q
evolution and the averaged P-E evolution.
3.1. Q Evolution
3.1.1. Variations in the Flow Field Around the Japan Sea
Before presenting the regression relationship, it is worth describing mean elevation, and velocity patterns averaged over the final 5 years of the realistic model results to demonstrate how the flow field around the Japan Sea
varies with decreasing sea levels. The horizontal distribution of the mean elevation and sea surface velocity
around the Japan Sea, simulated by R-CTRL and R-SENS, are shown in Figures 4 and 5, respectively. Among theresults from R-SENS, only those with sea level decreasing to −30, −60, −90, and −130 m are provided, which
are sufficient to address the response of the flow field to sea level change.
For the mean elevation patterns (Figure 4), the −0.2 m contour line in each pattern is marked as white for a betterview. The mean elevation from the R-CTRL simulation is characterized by a decrease from south to north withthe −0.2 m contour line in the middle of the Japan Sea (Figure 4a). The highest magnitude (≥0.50 m) is locatedsouth of the Japanese Archipelago, where the Kuroshio alternates between a straight and meandering path. The
lowest magnitude (≤−0.50 m) is located along the coasts of Siberia and North Korea, where a distinctive current,
named the Liman Cold Current, flows southward (Figure 1b). Among the R-SENS patterns (Figures 4b–4e), oneof the most evident features, compared with R-CTRL, is that the elevation inside the Japan Sea tends to decreaseas the sea level decreases. The −0.2 m contour line moves southward gradually and out of the Japan Sea when thesea level is at −90 and −130 m (Figures 4d and 4e).
The mean sea surface velocity patterns for the same domain and experiments are shown in Figure 5. Arrows
indicate the current direction in the areas with velocity magnitude exceeding 0.1 m s −1. For the R-CTRL pattern(Figure 5a), it is clear that the Kuroshio flows along the southern coast of Japan after passing through the Tokara
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Figure 4. Annual mean elevation (shadings, unit: m) of R-CTRL and R-SENS (−30, −60, −90, and −130 m) around the Japan Sea. White solid lines indicate contourof −0.2 m.

Figure 5. Annual mean sea surface speed (shadings, unit: m s −1) of R-CTRL and R-SENS (−30, −60, −90, and −130 m) around the Japan Sea. Arrows indicate current
direction in the area with a speed over 0.1 m s −1. Red line in (a) indicate section for calculating the Tsushima Strait transport.

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Figure 6. Relationship between Q and sea level. Solid line (non-linear
relationship) presents the Q estimated from the R-CTRL (horizontal tick label
is 0 m) and R-SENS (horizontal tick label varies from −10 to −130 m) results.
Dashed line (linear relationship) links the transport under the sea level at 0 and−130 m as a liner trend reference.

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Strait, leaves Honshu Island, and enters the Northwest Pacific as the Kuroshio Extension. With sea level reduction, the Kuroshio is strengthened invelocity and the affected area (extending to the east coast of Honshu Island,
Figures 5b–5e). The Tsushima Warm Current, shown in Figures 1b and 5a,
is separated into three current branches after entering the Japan Sea. (a) The
East Korea Warm Branch flows northward along the eastern coast of the
Korean Peninsula and returns to the south, rejoining the Tsushima Warm
Current; (b) The Nearshore Branch flows northeastward along the western
coast of Kyushu and Honshu Islands and reaches the vicinity of the Tsugaru
Strait; and (c) A weak Offshore Branch flows northward between the othertwo branches, meanders after touching the subpolar front, and organizes itself
into the Nearshore Branch. These three branches agree well with previous
studies (Chang et al., 2016). In R-SENS results, these current branches likely
weaken as the sea level decreased and almost disappear at −130 m sea level
due to the cutoff of the Tsushima Strait (Figure 5e). In the northwesternpart of the Japan Sea, the Liman Cold Current, flowing along the Siberian
coast southward to Vladivostok, is too weak (<0.1 m s −1) to be identified
in the R-CTRL pattern. As the sea level decreases, the Liman Cold Current
strengthens, and a cyclonic gyre emerges in the northern part of the Japan
Sea (Figures 5b–5e), which is related to the wind stress curl there (D. Kim
et al., 2020).

In these sensitivity experiments, the dropping sea level leads a reduction inmean elevation and a variation in the surface circulation pattern in the Japan
Sea. The Japan Sea, as a semi-enclosed sea, receives external forcing fromthe sea surface and lateral boundaries and its hydrodynamic characteristics therefore are determined by the above
two factors. Since the sea surface forcing is unchanged, the only change from the R-CTRL is the eustatic sea levelin the sensitivity experiments. The dropping sea level restricts not only the volume transport but also the momentum and heat/salt flux through the Tsushima Strait. As a result, the lateral boundaries contribute less kinetic andbuoyancy energy to the formation of the hydrodynamic pattern than the sea surface forcing does. Through thesesensitivity experiments, we capture how the eustatic sea level affects the local hydrological conditions.
3.1.2. Non-Linear Regression Relationship Between the Q and Sea Level
The annual mean Q under the present sea level (0 m) in R-CTRL is presented in Figure 6 as a starting point for
the reduction of Q with the drop in sea level, and the section used for transport estimation is shown in Figure 5a
as a red line. For a quick comparison, the mean transports obtained from long-term in-situ observations are
summa rized in Table 3. It is known that annual mean Q from R-CTRL (2.78 Sv) is close to the value from thein-situ observations (2.3–2.7 Sv). Therefore, the realistic model can reproduce the mean-state Q under the present
sea level, which allows us to use this model to further examine the relationship between Q and sea level.

Figure 6 also shows the response of Q to sea level reduction (solid line) from −10 to −130 m obtained from the
R-SENS results. As a reference, we also plot a dashed line linking Q with sea levels at 0 and −130 m, representing a linear downward trend with sea level reduction, that is, the linear regression relationship used by Matsui
et al. (1998). The R-SENS results (solid line in Figure 6) demonstrate a steeper downward trend in Q from asea level of 0 to −100 m, and a gentler downward trend from a sea level of −110 to −130 m as compared to thelinear downward trend (dashed line). Hereinafter, we call the reduction of Q
with sea level reduction from the realistic model as the non-linear regression
Table 3
relationship. The potential mechanism for this non-linear relationship will be
Mean-State Transport Through the Tsushima Strait Obtained From In-Situ
discussed in Section 4.2.
Observations in Previous Studies
Time periods
1999.05–2000.03

Mean transport/Sv

Reference∼2.3 (northeastern section)

Teague et al. (2002)∼2.7 (southwestern section)
1997.02–2002.08∼2.64

Takikawa et al. (2005)

1997.02–2007.02∼2.65

Fukudome et al. (2010)

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3.1.3. Evolution of Q
Under this non-linear regression relationship between Q and sea level, we canfurther convert the sea level evolution proposed by Yokoyama et al. (2018)
into Q evolution. The conversion process relies on the tripartite relationshipbetween sea level, Q, and time. The relationship between sea level and Q isthe above non-linear regression relationship (solid line in Figure 6). Between
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sea level and time is referred to sea level evolution by Yokoyama et al. (2018;
Figure 3a). By coupling these two relationships, the relationship between Q
and time, that is, the Q evolution, is obtained (solid line in Figure 3b). The
main features of the Q evolution are as follows: (a) 35–32 kyr BP, transport
decreases slightly from about 1.15 to 1.0 Sv; (b) 31–29 kyr BP, the rate of
reduction becomes greater from about 1.0 to 0.1 Sv; (c) 28–16 kyr BP, thetransport is smaller than 0.1 Sv with a fairly small fluctuation. The Tsushima
Strait is almost closed around the LGM period when transport is close tozero; (d) 15–3 kyr BP, the Tsushima Strait reopens with sea level rising andthe transport increases rapidly to about 2.76 Sv; and (e) 2 kyr BP-Present,
the transport remains at about 2.78 Sv. The width of the curve in Figure 3b
represents analytical uncertainties from sea level.
With the same process, the Q evolution can also be converted from sea level
evolutions in Saito et al. (1998) and Arz et al. (2007) (Figures 3d and 3f,
respectively). It is found that from 35 to 25 kyr BP, the features from thesethree Q evolutions are quite different: a general downward trend for thatbased on Yokoyama et al. (2018) and Arz et al. (2007), but a roughly upward
and then downward trend for that based on Saito et al. (1998). Subsequently,
these three Q evolutions exhibit similar features, remaining at almost zerothroughout 25–15 kyr BP and increasing after 15 kyr BP.
Figure 7. The precipitation (P) and river discharge (R), evaporation (E), andprecipitation minus evaporation (P-E) evolutions. (a), (b), and (c) exhibit P
and R, E, and P-E over the Japan Sea, respectively. A positive value of P-E
indicates freshwater flux into the Japan Sea through the air-sea interface.
In each panel, the filled dots with the same color represent the value of avariable (left vertical axis) at PI, MH, LGM, 30, and 35 kyr BP. Different
colors indicate different model results from PMIP3 and MIROC4m, and thecorresponding relationship between color and model name can be found in
the right legend. The solid orange lines represent the average value over these
multi-model results.

We apply the Q evolution converted from Yokoyama et al. (2018) sea level
data to reconstruct SJP over the past 35 kyr, and those from Saito et al. (1998)
and Arz et al. (2007) to discuss the influence of Q on the minimum SJP.
3.2. P-E Evolution

The evolutions of precipitation and evaporation obtained from multi-model
simulation results are shown in Figures 7a and 7b, respectively. At 35 and30 kyr BP, only the results from the MIROC4m model are available, and boththe precipitation (∼3.4 mm d −1) and evaporation (∼3.4 mm d −1) remained
stable at these two periods. From the LGM to the PI, the PMIP3 model results
are also available, and all the models suggest an increasing trend in precipitation and evaporation. It should be noted that the specific values of precipitation and evaporation vary from model
to model. The mean precipitation and evaporation, calculated from the available model results for each period, areshown using solid orange lines in Figures 7a and 7b, respectively. Both the mean precipitation and evaporation areminimal (2.52, 1.90 mm d −1) during the LGM with a roughly downward (upward) trend before (after) the LGM,
which is related to the reduction of air temperature and weakening of solar radiation.

Figure 7c shows the P-E evolutions from the multi-model simulation results with their averaged values (a positive
value indicates freshwater entering the Japan Sea through the air-sea interface). An upward trend in P-E is foundfrom 35 kyr BP to the LGM. As for the period from the LGM to the PI, the mean P-E exhibits a downward trend
until it stabilizes after the MH. The mean P-E has its maximum value (0.62 mm d −1) at the LGM, which is smaller
than that (0.82 mm d −1) in Matsui et al. (1998) and Ikeda et al. (1999).
To minimize model uncertainties, the P-E evolution averaged over the multi-model simulation results is used toforce the box model. The P-E evolution from each model is employed individually to explore the influence of
P-E on the minimum SJP.
As we assumed that R(t) is linearly proportional to P(t), the variation of river discharge is similar to that of
precipitation as shown in Figure 7a. Here, α is 0.0013 Sv mm −1 d calculated as the ratio of presented-day riverdischarge (0.0044 Sv, Yanagi, 2002) and precipitation (3.46 mm d −1, averaged over the PMIP3 and MIROC
simulations for PI).
3.3. SJP Evolution
The Q evolution converted from sea level in Yokoyama et al. (2018) under the non-linear regression relationship,
and P-E evolution averaged from multi-model simulation results, are employed to drive the box model. The
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Figure 8. SJP evolution reconstructed from the box model. The solid (dashed) line in (a) is the result forced by Q evolution
under the non-linear (linear) relationship, and averaged P-E evolution. The sea level evolution used here is adapted from
Yokoyama et al. (2018). The solid red (pink) line in (b) is the result forced by the P-E evolution obtained from MIROCESM (MIROC4m) model, and Q evolution converted from sea level in Yokoyama et al. (2018) under the non-linear
relationship. The solid/dashed lines in (c) and (d) are the same as that in (a), but the sea level evolutions used here are adaptedfrom Arz et al. (2007) and Saito et al. (1998), respectively. Width of the curve represents typical uncertainties from sea level.

reconstructed SJP evolution over the past 35 kyr using Equation 1 is shown in Figure 8a as a solid line. During
the period of 35–31 kyr BP, the reconstructed SJP maintains its initial value (32.8) with slight fluctuations (<0.2)
because of stable inflow transport and weak freshwater flux. From 31 kyr BP until the timing of minimum SJP(20 kyr BP), there are three distinct stages of SJP decline: falling abruptly from 32.8 to 30 during 31–29 kyr BP,
decreasing gently from 30 to 28.6 during 29–22 kyr BP, and dropping sharply from 28.6 to the minimum SJP(20.2) during 22–20 kyr BP. As shown in Section 4.3, it is the combined effect of weaker inflow transport andheavier freshwater flux that leads to minimum SJP (20.2) around 20 kyr BP. Meanwhile, a robust halocline is
expected at 20 kyr BP, and this separates the seawater of the Japan Sea into two main layers with a less saline
upper layer and a more saline lower layer (Isobe, 2020). From then on, SJP begins to rise gradually with thereopening of the Tsushima and Tsugaru Straits and a reduction of freshwater flux. SJP recovers its initial value at
13 kyr BP and this persists until the present. Overall, the reconstructed SJP reaches its minimum value of 20.2 at
20 kyr BP, which is close to that estimated by Matsui et al. (1998) (20 at 20–15 kyr BP).
Additionally, linear regression analysis is conducted to explore the relationship between δ 18O and the reconstructed SJP (Figure 9a), and the coefficient of determination (R 2) is used to evaluate the correlation between
them. The δ 18O evolution used here is adapted from Sagawa et al. (2018), as shown in Figures 1c and is estimatedfrom Globigerina bulloide of the KR07-12 PC3 core located in the southern Japan Sea. It is found that the slope
and intercept for the linear relationship between reconstructed SJP and δ 18O are 0.22 and −4.50, respectively. A
high value of R 2 (0.81, p << 0.01) indicates that the reconstructed SJP is significant correlated with δ 18O anddescribes the low SJP event in the Japan Sea reasonably well.

4. Discussion
In this section, the necessity of the non-linear regression relationship for SJP reconstruction is clarified and themechanism behind this non-linear relationship is explored. Next, we reveal the cause of the minimum SJP and theinfluence of Q and P-E evolutions on it. At last, the implications of changing in Q and SJP on the Japan Sea are
discussed.
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Figure 9. Linear regression of δ 18O and reconstructed SJP evolution. The dots in (a) exhibit the relationship between theδ 18O and reconstructed SJP evolution. Here, SJP evolution is reconstructed with the Q evolution converted from Yokoyama
et al. (2018) sea level under the non-linear relationship, and averaged P-E evolution. The solid line is a linear regression ofthese dots, and dashed lines represent typical uncertainties from sea level. (b) exhibits the relationship between the δ 18O andreconstructed SJP evolution, but the Q evolution is converted under the linear regression relationship. (c) and (d) exhibit therelationship between the δ 18O and reconstructed SJP evolution, but the Q evolution is converted from Arz et al. (2007) andSaito et al. (1998) sea level, respectively.

4.1. Necessity of the Non-Linear Regression RelationshipBy coupling the Q evolution converted under a non-linear relationship and P-E evolution averaged over themulti-model simulation results, the SJP evolution has been reconstructed using the box model and its R 2 for δ 18O
is estimated to be 0.81 (p << 0.01). Here, we demonstrate that a non-linear relationship promises such a precise
result.
To clarify the necessity of this non-linear relationship, we reconstruct the SJP evolution again with the samesetting, but convert the Q evolution under the linear relationship (dashed line in Figure 6) assumed by Matsui
et al. (1998). Similarly, the sea level evolution used here is also adapted from Yokoyama et al. (2018). The Q
evolution converted under the linear relationship is shown in Figure 3b using the dashed line, and its values are
generally much larger than those under the non-linear relationship, except for the period from 10 kyr BP to thepresent.
Figure 8a presents the SJP evolution forced by this “linear” Q evolution in the dashed line. It exhibits muchhigher values and less variation than that forced by the “non-linear” Q evolution (solid line in Figure 8a).
This new SJP evolution reaches its minimum value (27.7), which is larger than the previous value (20.2), but
occurs at the same time, 20 kyr BP. Further linear regression analysis suggests that the value of R 2 (0.64,
p << 0.01; Figure 9b) for this new SJP evolution is smaller than the previous one (0.81, p << 0.01; Figure 9a),which indicates that the former, forced by the “linear” Q evolution, cannot describe the variability in δ 18O as
sufficiently as the latter. Additionally, the sea level elevations from Arz et al. (2007) and Saito et al. (1998)
are also employed to carry out the same experiments, and the results (not shown here) also lead to the sameconclusions. In this sense, the non-linear regression relationship is more suitable for SJP reconstruction thanlinear. It is necessary to refine Q evolution using this non-linear regression relationship when dealing with thepaleo Japan Sea.

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4.2. Cause for the Non-Linear Regression RelationshipWe have employed realistic bathymetry and meteorological forcing to investigate Q and its non-linear mapping relationship with sea level. An interestingquestion is why there is a non-linear response for Q to sea level change rather
than a linear one as assumed in Matsui et al. (1998)? Generally, if the Tsushima Strait is regarded as a channel with uniform depth h, length L, and width
B connecting two large basins, then its mean-state transport can be derived
from the along-strait (x-direction) momentum balance, as follows:
𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡−B

Figure 10. Variations of term-A, B, and C split from Equation 3 with sea level
dropping.

𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡−A ⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞⏞ term−C)1∕2 ⏞⏞⏞
⏞⏞⏞(
(3)
𝜕𝜕𝜕𝜕
3∕2
𝑄𝑄 = 𝐵𝐵𝐵𝐵𝐵a = 𝐵𝐵 ℎ−𝑔𝑔
𝐶𝐶d −1∕2𝜕𝜕𝜕𝜕where ua is the depth-averaged velocity component in the along-strait direction, g is gravitational acceleration, η is surface elevation, and Cd is thebottom friction coefficient. The derivation of Equation 3 is given in the Text
S3 in Supporting Information S1.
Equation 3 depicts a non-linear relationship between Q and sea level (strait depth h) assuming that other terms
vary little with water depth. With output data from the realistic model, we can estimate each term in Equation 3
and diagnose these effects on the non-linearity. However, multiple spatial-scale variations are contained in boththe topographical and regional meteorological forcings. The hotchpotch of multiscale variations may sometimes
blur the dominant dynamical processes (Yang & Pratt, 2013) and, as a result, complicate the diagnosis of Equation 3. Therefore, we build a simple but more general finite-depth idealized numerical model to bring insight
into why Q responds non-linearly to the sea level change. The configurations of this finite-depth idealized model
can be found in the Text S4 in Supporting Information S1. Text S5 suggests that a similar non-linear relationshipcould be mirrored by the results from this idealized model and is formulated by Equation 3, which increases
our confidence in diagnosing Equation 3 with the output from this idealized model.
The changes in each term in Equation 3 with sea level reduction are shownin Figure 10. Term-A, which represents the strait depth to the power of 3/2,
exhibits a non-linear downward trend, similar to the transport response to
sea level reduction. However, term-B, representing the elevation difference
across the strait, shows an irregular behavior with slight fluctuations. TermC, representing Cd to the power of −1/2, shows a non-linear and downward
trend because Cd is inversely proportional to the sea level. However, the variation range of term-C is much smaller than that of term-A. Therefore, it is thevariation in term-A that contributes to the majority of the non-linear downward variation, and it can be concluded that term-A, h 3/2, plays a dominantrole in determining the non-linear regression relationship.
4.3. Cause of the Minimum SJP in 20 kyr BP

Figure 11. (a) The differences between salt input and output over the past
35 kyr. The dashed line denotes the zero line for reference. Width of the curve
represents typical uncertainties from sea level. (b) and (c) are the same as(a) but for time-integrated salt differences and ratio of freshwater flux andTsushima Strait transport (F/Q), respectively.

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In the box model for salinity, the differences between salt input and output
regulate the salinity inside the box and the time-cumulative differences determine the salinity evolution. For the Japan Sea, the transport though the Tsushima Strait provides salt into the Japan Sea. Meanwhile, the transport throughthe Tsugaru and Soya Straits together with the freshwater flux serves as themain salt output. To specifically explain the appearance of the minimum SJP(20.2) at 20 kyr BP, we plot the difference between salt input and output, its
time-integrated value, and the ratio of freshwater flux and transport throughthe Tsushima Strait (F/Q) over the past 35 kyr (Figure 11).
From 35 to 20 kyr BP, the difference between salt input and output is less thanor equal to zero (Figure 11a), which suggests the salt input from the Tsushima Strait is in short supply to the salt output through the Tsugaru and Soya
Straits. Over this period, the transport through the Tsushima Strait decreased
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to almost zero and in contrast, the freshwater flux increased to a peak value, which together led to a decreasing
SJP. The descending time-integrated difference also indicates a continued salt loss until 20 kyr BP (Figure 11b).
Around 20 kyr BP, the transport through the Tsushima Strait decreased to almost the same amount of freshwater
flux but then recovered back quickly (Figure 11c), leading the difference between the salt input and output tochange suddenly from a negative value to a positive value (Figure 11a).
After the 20 kyr BP, the difference was greater than or equal to zero (Figure 11a), which runs a salt budget surplus
with the increasing of transport through the Tsushima Strait and decreasing of freshwater flux. The SJP thereby
increases with time. The time-integrated difference changed from decreasing to increasing, which suggests asalt gain after 20 kyr BP (Figure 11b). The minimum SJP therefore occurs at the break-even point when the F/Q
reached a maximum value, that is, 20 kyr BP (Figure 11c). It is concluded that the combination of the volumetransport through the Tsushima Strait and the freshwater input determines the exact value and timing of minimum
salinity.
4.4. Impact of Q Evolution on the Minimum SJP
Under the non-linear regression relationship, the Q evolution has been determined by the sea level evolution in
Yokoyama et al. (2018) and further applied to reconstruct the SJP evolution. To further analyze the effect of the Q
evolution on the minimum SJP, we also convert the sea level evolutions in Arz et al. (2007) and Saito et al. (1998)
into Q evolution and rerun the box model with the averaged P-E evolution. The corresponding results of the
SJP evolution are shown in Figures 8c and 8d, respectively. Combining the results forced by Q evolution under
Yokoyama et al. (2018) sea level (solid line in Figure 8a), it is found that these three types of SJP evolutions are allroughly axisymmetric over the past 35 kyr, that is, a downward (upward) trend before (after) ∼20 kyr BP with aminimum value around this period. Notably, the exact value and timing of minimum SJP for these three evolutions
are different: a minimum value of ∼20.2, ∼26.4, and 28.4 at 20, 17, and 19 kyr BP for Q evolution converted
from Yokoyama et al. (2018), Arz et al. (2007), and Saito et al. (1998) sea level, respectively, which indicatesthat Q evolution plays a crucial role in determining both the value and timing of the minimum SJP. These timings
correspond to the moments when the F/Q reaches a maximum value, suggesting again the combined effect offreshwater flux and transport through the Tsushima Strait on the appearance of minimum SJP.
Linear regression analysis for δ 18O and SJP evolution, corresponding to Q evolutions converted from Arz
et al. (2007) and Saito et al. (1998) sea level, are shown in Figures 9c and 9d, respectively. The value of R 2 forthese two SJP evolutions (0.69, 0.60; p << 0.01) are both smaller than that shown in Figure 9a (0.81, p << 0.01),
which means that the Q evolution converted from Yokoyama et al. (2018) sea level is the most suitable for SJP
reconstruction. This also reminds us that it is still valuable and desirable to explore an accurate sea level evolution.
4.5. Impact of P-E Evolution on the Minimum SJP
We would also like to discuss the influence of P-E evolution on the value and timing of the minimum SJP. Here,the Q evolution is converted from the Yokoyama et al. (2018) sea level under the non-linear regression relationship, and the P-E evolution is obtained from each PMIP3 and MIROC4m simulation result, one by one. Therefore, eight types of P-E evolutions are used to drive the box model with the same Q evolution.
It is found that each type of reconstructed SJP suggests a similar evolution feature to that forced by the averaged
P-E evolution, that is, a minimum SJP around ∼20 kyr BP with a considerable descending and rising process
before and after, respectively. Thus, only the SJP evolutions corresponding to the MIROC-ESM and MIROC4m
simulations are selected and shown in Figure 8b as red and pink lines, respectively. Results corresponding tothe other six models lie somewhere between these two and are omitted here. Notably, the P-E evolution data for
35–30 kyr BP from the PMIP3 models are not available, and those from the MIROC4m model replace them. As
a result, the reconstructed SJP evolutions from 35 to 30 kyr BP are the same as that in Figure 8a. All the reconstructed SJP under P-E evolutions from CCSM4, CNRM-CM5, FGOALS-g2, IPSL-CM5A-LR, MIROC-ESM,
MPI-ESM-P, MRI-CGCM3, and MIROC4m models produce their minimum values (19.21, 19.53, 21.52, 22.08,
15.45, 18.71, 23.49, and 25.17, respectively) around 20 kyr BP, which means that the P-E evolution can modify
only the value of minimum SJP but not the timing. In other words, the Q evolution, adjusted by the eustatic sea
level, determines the amount of saline water entering the Japan Sea and mostly determines the value and timingof the minimum SJP. Meanwhile, the P-E evolution provides a continuous freshwater supply to modify the valueof minimum SJP.
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4.6. Implications of the Changes in Q and SJP on the Japan Sea
In the present configuration, the inflow through the shallow Tsushima Strait brings warm and saline water into
the Japan Sea, which significantly affects the hydrography of the upper layer water (Dong et al., 2021). The deep
layer is occupied by a water mass called the Japan Sea Proper Water, which is formed by deep convection due tosurface cooling under the winter East Asian Monsoon in the northern Japan Sea (Senjyu, 2022). The semi-isolationand self-contained thermohaline circulation system including deep water formation make the Japan Sea uniqueamong the various marginal seas in the western North Pacific (Kida et al., 2016; Wu et al., 2020).
Over the past 35 kyr BP, the eustatic sea level would have regulated the inflow through the Tsushima Strait andthereby the surface salinity of the Japan Sea (Dong et al., 2020; Tada et al., 2018). During the glacial period,
especially during the LGM, the inflow through the Tsushima Strait, restricted by the dropping sea level, wasin short supply of the salt input to the Japan Sea. Moreover, the occurrence of dropstones and ice-rafted debris
indicates active sea ice formation in the northern Japan Sea during this interval (Ikehara, 2003). Together withthe continuous freshwater water supply, a lower-salinity sea surface is formed. Since the deep water is formed by
the surface cooling and deep convection, the lower salinity surface water could enhance the density stratificationof the water column and severely limit the occurrence of deep convection as well as the formation of deep water.
The benthic foraminiferal barren zone accompanied by high concentrations of sedimentary molybdenum suggests
the existence of a poorly ventilated deep-water in the Japan Sea (Domitsu & Oda, 2006; Dong et al., 2021). The
dissolved oxygen would be consumed up through oxidation of organic material, and the anoxic and sulfidic
bottom conditions have been developed in the deep water (Ishiwatari et al., 2001; Keigwin & Gorbarenko, 1992),
which has been indicated by the presence of well-laminated sediment (Watanabe et al., 2007) and peak values of
total sulfur/organic carbon (TS/TOC) (Zou et al., 2012). The sea level rise since the LGM leads to the reopeningof the Tsushima and Tsugaru Straits. The stratification in the Japan Sea then weakened and the ventilation became
possible again. The reemergence of microfossils in the marine sediment cores indicates that the benthic fauna
have recovered with the oxygen supply from the upper water to the deep water (Itaki et al., 2004). In addition, thepresent-day Japan Sea is a net sink for atmospheric CO2 (M. Kim et al., 2022) and the hypoxic deep/bottom waters
in the glacial period have been considered as a potential carbon source to the atmosphere (Dong et al., 2021; D.
Li et al., 2019). With the re-ventilation since the LGM, the changing role of the Japan Sea in the carbon cycle
deserves further study.

5. Summary
Using a simple box model, the low sea surface salinity event of the Japan Sea during the LGM is investigatedthrough two indicators: the value and timing of the minimum SJP. As a cornerstone, the relationship between Q
and sea level is quantified. A non-linear regression relationship, rather than the linear one assumed in Matsui
et al. (1998), is confirmed through a dynamically-constrained realistic numerical model and experiments withdifferent sea levels. Assisted by this non-linear regression relationship, the sea level evolution reported in previous studies can be converted into Q evolution to force the box model. We also refine the P-E evolution withsimulation results from seven PMIP3 models and from MIROC4m.
Forced by the Q evolution converted from Yokoyama et al. (2018) sea level under the above non-linear relationship and P-E evolution averaged over these multi-model simulation results, the SJP evolution is reconstructed withthe box model, and a minimum value (20.2) is reached 20 kyr BP (solid line in Figure 8a). A high value of R 2(0.81, p << 0.01) for δ 18O evolution suggests a high degree of reliability for this SJP evolution.
A comparison experiment is conducted by converting the Q evolution under the linear regression relationship,
and a smaller R 2 (0.64, p << 0.01) demonstrates that the non-linear relationship is essential for SJP reconstruction.
Analysis through Equation 3 and an idealized numerical model reveal that the dependence of Q on h 3/2 is thecause of this non-linear relationship.
The combined effect of Q and P-E determines the occurrence of minimum SJP. Furthermore, we discuss theimpact of Q and P-E evolutions on the minimum SJP. Under the averaged P-E evolution, the reconstructed SJP
evolutions, forced by Q evolution converted from sea level in Yokoyama et al. (2018), Arz et al. (2007), andSaito et al. (1998), reached minimum values of ∼20.2, ∼26.4, and 28.4 at 20, 17, and 19 kyr BP, respectively.
Meanwhile, under the Q evolution converted from Yokoyama et al. (2018) sea level, all of the reconstructed
SJP evolutions forced by P-E evolution from different models exhibited their minimum SJP at 20 kyr BP, but the
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minimum values are quite different. The Q evolution likely dominates both the value and timing of the minimum
SJP, whereas P-E evolution modifies its value.
In summary, the refinement of Q and P-E evolutions by using the box model deepens our knowledge of the low
sea surface salinity event of the Japan Sea. With innovations in theoretical methodology, developments of paleoclimate numerical models, and enrichments of proxy data, a more comprehensive and profound understanding of
the paleo Japan Sea is expected in the future.

Data Availability Statement
Configurations of the box model, the realistic numerical model, and the finite-depth idealized numerical model
are available in Miyazawa et al. (2009), Jordi and Wang (2012) and Yang et al. (2022). Evolution of oxygenisotopic ratio in planktonic foraminifera is adapted from Sagawa et al. (2018). Evolutions of sea level are adaptedfrom Yokoyama et al. (2018), Arz et al. (2007), and Saito et al. (1998). The basic information about the PMIP3
and MIROC4m models is listed in Table 2. Simulation results from the PMIP3 models can access by searchingin https://esgf-node.ipsl.upmc.fr/search/esgf-ipsl/. The MIROC4m data used in this study are available at Zheng
et al. (2022).
Acknowledgments
This work was supported by JSPS
KAKENHI Grants 17H02959, 17H06104,
and 17H06323. Junyong Zheng thanks thefinancial support from China ScholarshipCouncil (CSC, No. 202006330055) for
supporting his stay in Japan.

ZHENG ET AL.

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