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A composite sea surface temperature record of the northern South China
Sea for the past 2500 years: A unique look into seasonality and seasonal
climate changes during warm and cold periods
Hong Yan
a,
⁎, Willie Soon
b
,YuhongWang
c
a
State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710075, China
b
Harvard-Smithsonian Center for Astrophysics,Cambridge, MA 02138, USA
c
Department of Chemistry and Laser Chemistry Institute, Fudan University, Shanghai 200433, China
abstractarticle info
Article history:
Received 4 July 2014
Accepted 7 December 2014
Available online 13 December 2014
Keywords:
South China Sea
Coral
Tridacna gigas
Sea surface temperature
Seasonal climate
Late Holocene
High-resolution late Holocene climate records that can resolve seasonality are essential for confirming past cli-
matic dynamics, understanding the late 20th century global warming and predicting future climate. Here a
new compositerecord of the sea surfacetemperature, SST, variation in the northern South China Sea (SCS)during
the late Holocene is constructed by combining seven seasonally-resolved coral and Tridacna gigas Sr/Ca-based
SST time-windows with the instrumental SST record from modern interval between 1990 and 2000. This com-
posite multi-proxy marine record, together with the reconstructions from mainland China and tropical Western
Pacific, indicates that the late Holocene warm periods, the Roman Warm Period (RWP) and Medieval Warm Pe-
riod (MWP),were prominently imprinted and documented in the climatic and environmental history of the East
Asia–Western Pacific region. Meanwhile,substantial and significant SST seasonality variations duringthe late Ho-
locene were observed inthe composite record. The observedincrease in seasonality (or amplitude of seasonal cy-
cles) during the cold periods around our study area was probably caused by the different amplitudes between
winter versus summer SST variations in northern SCS, with much larger SST variation during winters than during
summers for the late Holocene. In addition, the distinctive warm, cold and neutral climatic episodes identified in
our northern SCS composite SST record correspond well with other paleo reconstructions from mainland China
and especially well with the Northern Hemisphere-wide composites by Moberg et al. (2005) and Ljungqvist
(2010). The overall agreement however also calls for more information and insights on how seasonal tempera-
tures and their ranges vary on decadal–centennial timescales.
© 2014 Elsevier B.V. All rights reserved.
Contents
1. Introduction.............................................................. 123
2. Materialandmethods ......................................................... 123
2.1. Regionalsetting ......................................................... 123
2.2. Datasources .......................................................... 124
2.3. Themethodofcompositing ................................................... 126
3. Resultsanddiscussion ......................................................... 126
3.1. Acompositeproxy-SSTrecordinthenorthernSCSduringthelateHolocene ............................. 126
3.2. Intercomparison with other SST proxies from tropical Western Pacific ................................ 126
3.3. Distribution of RWP and MWP in the Asia-Pacificregionwithacomparisontootherregions ...................... 127
3.4. VariationoftheSSTseasonalityintheSCSduringthelateHoloceneanditsrelationshipwiththemeanclimatestate ........... 128
3.5. DifferentamplitudesofsummerandwinterSSTvariationsduringthelateHolocene .......................... 130
3.6. MechanismforthedifferentvariationamplitudesofthesummerandwinterSSTduringthelateHolocene................ 131
4. Conclusions .............................................................. 133
Acknowledgment .............................................................. 134
References ................................................................. 134
Earth-Science Reviews 141 (2015) 122–135
⁎Corresponding author.
E-mail address: yanhong@ieecas.cn (H. Yan).
http://dx.doi.org/10.1016/j.earscirev.2014.12.003
0012-8252/© 2014 Elsevier B.V. All rights reserved.
Contents lists available at ScienceDirect
Earth-Science Reviews
journal homepage: www.elsevier.com/locate/earscirev
1. Introduction
High-resolution climate reconstructions during the late Holocene,
especially during the past 2000 years, can provide a timely opportunity
to place the current global warming in a long-term context and help un-
derstand the importance of natural and anthropogenic forcings on past
and future climate changes. Many recent works have focused on the cli-
matic changes during this time period, but the complete characteristic
of the seasonal climate during the late Holocene, aswell as the historical
status of the late 20th century global warming, remain debated (IPCC,
2001; Esper et al., 2002; Ge et al., 2003; Soon et al., 2003; IPCC, 2007;
Wang et al., 2007). The insufficiencies of the currently available proxy
data for the late Holocene are the major cause of ongoing debates and
controversies. For example, although more than 1200 proxy reconstruc-
tions were used in the compilation of Mann et al. (2008), only 25 re-
cords cover the last 2000 years. Meanwhile, most of the proxy records
are derived from the mid and high latitudes of the Northern Hemi-
sphere, and the temperature reconstructions from the Southern Hemi-
sphere and tropics are less common (IPCC, 2007; Mann et al., 2008,
2009). Furthermore, while tree-ring-proxy records during the late Holo-
cene have been built for the vast terrestrial area over the last 20 years,
high-resolution proxy ocean temperature records of the late Holocene
are still very limited. Thus a more concerted study on proxy records of
the late Holocene for the past 2000–3000 years, in particular high-
resolution, seasonally-resolved, ocean temperature records from South-
ern Hemisphere and tropics, are needed.
In addition to the variations of mean climatic state [see e.g., two early
papers for discussion on the inadequacy of the current definition and
framework basing on the statistical 30-year averages (Landsberg,
1972; Guttman, 1989)], the seasonal and sub-seasonal changes of cli-
mate conditions are the primary component and physical descriptor of
Earth's climate system (Kukla and Gavin, 2004; Denton et al., 2005;
Soon, 2009). The information of past seasonal and sub-seasonal changes
in different weather regimes and climatic states is the key for a compre-
hensive understanding of past climatic dynamics and for predicting fu-
ture climate. However, except the coral recordsin tropical area, most of
proxy-based climate records have temporal resolution insufficient for
quantifying temperature seasonality.
The fast-growing marine biogenic carbonates, such as corals and
mollusks, are sensitive to surrounding environmental changes in most
aquatic settings, and they have the potential to sample the full seasonal
range of past sea surface temperature (SST) and were used extensively
to provide high-resolution seasonal/monthly climate records from tro-
pics to high latitudes for the past 30 years (Williams et al., 1982; Cole
et al., 1993; Gagan et al., 1994; McCulloch et al., 1994; Schöne et al.,
2004a,b; Watanabe et al., 2004; Schöne et al., 2005; Wanamaker et al.,
2008; Aubert et al., 2009; Elliot et al., 2009; Maier and Titschack,
2010; Batenburg et al., 2011; Wanamaker et al., 2011). These seasonal
and sub-seasonal proxy-climate records, together with lower resolution
marine sediment records, have greatly improved our understanding of
the past climate changes in global oceanduring the late Holocene. How-
ever, the time spans of themarine biogenic carbonate records, typically
less than 200 years for most of the reported records, are too short to
cover the whole late Holocene, and thus limiting the use of high resolu-
tion marine carbonate records to reconstruct the climatic history of late
Holocene and assess the past climatic dynamics.
In order to overcome the short time-duration limit of the bio-
carbonate records, several recent studies have tried to concatenate
some short bio-carbonate archives together in order to produce longer
composite climate records (Cobb et al., 2003; Yu et al., 2005; Patterson
et al., 2010; Wanamaker et al., 2011; Giry et al., 2013). For example,
Cobb et al. (2003) reconstructed the El Niño-Southern Oscillation
(ENSO) variability covering the past millennium using several coral
δ
18
O time windows from mid-Pacific(Cobb et al., 2003). Yu et al.
(2005) discussed the mid-to-late Holocene monsoonal climate in
South China Sea based on the Sr/Ca chemical ratio and δ
18
O of several
coral records. Recently, the North Atlantic seawater temperature sea-
sonality variations during the past two millennia, concatenated from
about 26 time windows, were investigated using some bivalve shell ar-
chives (Patterson et al., 2010; Wanamaker et al., 2011). These studies
highlighted the potential of compositing bio-carbonate records in
order to reconstruct high-resolution climate history of the world
ocean and for providing the most important historical and geological
context for judging the current climatic changes. We followed similar
approach in producing our composite SST record for northern SCS cov-
ering the past 2500 years.
South China Sea, SCS, is the largest marginal sea of thewestern trop-
ical Pacific(Fig. 1). The seasonal climate variation in the SCS is largely
controlled by the East Asian Monsoon; but on inter-annual timescales,
it is probably dominated by tropical Pacific ENSO conditions (Yan
et al., 2010, 2011). Climate records from SCS are thus important for in-
vestigating the interactions between tropical climate and the Northern
Hemisphere high latitudes. However, climate characteristics of the SCS
during the late Holocene are still somewhat unclear because there are
insufficient numbers and types of paleoclimate proxies available.
The coral Sr/Ca-based SST reconstructions in SCS have been system-
atically developed in recent decades and a series of paleo-SST records is
reported to reflect high-time-resolution Holocene climate history (Wei
et al., 2004a,b; Yu et al., 2004, 2005; Wei et al., 2007; Deng et al., 2009).
In addition to the coral records, Tridacna gigas, the biggest marine bi-
valves in the SCS region,was also used to reconstruct thehigh resolution
climate history in the South China Sea. T. gigas shell is the largest bivalve
species in global ocean; it can grow to over 1 m in length and live up to
100 years (Rosewater, 1965). T. gigas has hard and dense aragonite
shells with daily growth lines and its growth rate is usually higher
than 1 mm per year. The microdrill sampling method can provide
monthly resolution δ
18
O and Sr/Ca profiles easily (Watanabe and Oba,
1999; Watanabe et al., 2004; Elliot et al., 2009; Yan et al., 2013, 2014a,
b,c). The calibrations between modern T. gigas Sr/Ca and instrumental
SST confirmed that the T. gigas Sr/Ca can be used as a high resolution
(resolving time changes, at least, on a month-to-month basis) SST
proxy comparable to the coral Sr/Ca measure (Yan et al., 2013, 2014a)
and indeed several T. gigas Sr/Ca-based Holocene proxy-SST records
were recently reported (Yan et al., 2014b). These high resolution bicar-
bonate SST records, although each covering only specifictimeintervals
for certain warm and cold periods, offer a new opportunity in gaining a
broader overall knowledge and detailed insight by coming up with a
high-resolution composite SST series in the South China Sea during
the late Holocene.
In this study, we will combine seven high-resolution, seasonally-
resolved, coral and T. gigas proxy-SST records together with the instru-
mental SST record from 1990 to 2000 interval to provide a 2500-year
long documentation and view of the climatic variations in the northern
SCS during the late Holocene. The changes of temperature seasonality
and the climatic dynamics in the northern SCS during the warm and
cold periods of the late Holocene will also be highlighted.
2. Material and methods
2.1. Regional setting
The SCS is located in the far western tropical Pacific, it is a semi-
enclosed marginal sea with an area of ~ 3.6 million km
2
(Fig. 1). SCS con-
sists of hundreds of islands, coral reefs, atolls, and shoals. The largest is-
land is Hainan Island. Most of the others are much smaller and divided
into four archipelagos: Nansha Islands (Spratly Islands), Xisha Islands
(Paracel Islands), Zhongsha Islands (Macclesfield Islands), and Dongsha
Islands (Pratas Islands).
The coral and T. gigas records used in this study are from the Leizhou
Peninsula (20°15′N, 109°56′E), Yongxing Island (16°50′N, 112°20′E),
Shidao Island (16°50′, 112°20′) and Dongdao Island (16°40′N, 112°44′
E). The Leizhou Peninsula is located in the north of Hainan Island and
123H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
the coral reef in Leizhou Peninsula is the only developed and well-
preserved coral fringing reef on the Mainland China (Yu et al., 2005)
(Fig. 1). The Yongxing Island, Shidao Island and Dongdao Island are lo-
cated in the Xisha Islands, and they are elliptical tropic reef islands
with a land area of 2.13 km
2
,0.08km
2
and 1.55 km
2
, respectively.
The seasonal climate of SCS is dominated by East Asia Monsoon
(EAM). EAM is characterized by southwesterly winds (warm and wet)
in boreal summer and northeasterlywinds (cool and dry) in boreal win-
ter. The monthly SST of the Leizhou Peninsula and Xisha Islands are
shown in Fig. 2 and the average annual-mean SST (AD 1982–2011)
are 25.41 and 27.59 °C, respectively. The monthly time series of SST
and SST anomalies in Leizhou Peninsula and Xisha Islands are shown
in Fig. 3.AsseeninFigs. 2 and 3, the summer SSTs in Leizhou Peninsula
and Xisha Islands are similar, but the winter SSTs in Leizhou Peninsula
are substantially colder than those in Xisha Islands, leading to a larger
seasonality of SST in Leizhou Peninsula than in Xisha Islands. The
SST data are obtained from the NOAA-NCEP-EMC-CMB GLOBAL
Reyn_SmithOIv2 database (a global weekly SST data starting from
1982 with a spatial resolution of 1° × 1°); the grid cells of the NOAA
SST data used were selected to include Leizhou Peninsula and Xisha
Islands, respectively.
2.2. Data sources
The Sr/Ca ratios of coral skeletons have long been known to robustly
yield a high-resolution SST proxy and have been extensively utilized in
high-resolution paleo-temperature reconstructions in the tropical
oceans (Beck et al., 1992; McCulloch et al., 1994, 1996; Alibert and
McCulloch, 1997). The coral Sr/Ca-based SST reconstructions in the
SCS have also been developed and reported in recent decades. For ex-
ample, three high-resolution late Holocene paleo-SST records, around
~535 BC, ~495 AD and ~1464 AD, were reported in northern SCS from
Leizhou Peninsula, Hainan Island and Xisha Islands, respectively (Wei
et al., 2004a,b). Yu et al. (2005) reported five mid-late Holocene month-
ly resolution Porites corals Sr/Ca based SST records from Leizhou Penin-
sula (~4789 BC, ~3906 BC, ~3011 BC, ~541 BC, ~487 AD), each covering
a growth history of 9–13 years (Yu et al., 2005). The coral Sr/Ca-based
SST records, covering mid-Holocene time interval, were also reported
from Leizhou Peninsula, Hainan Island and Xisha Island (Wei et al.,
2004a; Yu et al., 2004; Wei et al., 2007; Deng et al., 2009).
In the meantime, the Sr/Ca ratios of marine bivalve, such as Tridacna
species, have also been investigated in the northern SCS. The study on
Sr/Ca of modern T. gigas specimen from SCS showed that the high-
resolution Sr/Ca ratio profiles determined by the inductively coupled
plasma-optical emission spectrometer (ICP-OES) had clear annual cy-
cles, correlating with thelocal SST variations, and were highly reproduc-
ible across the shells regardless of the physiological effects (Yan et al.,
2013, 2014a). Thus the Sr/Ca ratio of T. gigas from South China Sea, pri-
marily controlled by water temperature, is a useful paleo-temperature
proxy that promises to tell us past summer and winter temperatures
(Yan et al., 2013, 2014a). Based on these new insights, the high resolu-
tion Sr/Ca data of two late Holocene T. gigas specimens were analyzed to
reconstruct paleo-SST around ~50 AD and ~ 990 AD (Yan et al., 2014b).
In this study, a total of seven coral and T. gigas Sr/Ca-based SST time
windows as well as modern instrumental SST in northern SCS were
0° 10°N 20°N
110°E
30°N 40°N
90°E 130°E
Xisha Islands
Leizhou Peninsula
3
5
4
7
6
North
Porites lutea coral
Tridacna gigas shell
(a)
(b)
(c) (d)
1
2
Fig. 1. Thelocations of the study sites.(a): map of the East Asia from northwest China to tropical Western Pacific.The locations of the reported temperature records are marked: 1 (Wang
et al., 1999; Shintani et al., 2011), 2 (Wu et al., 2012), 3 (Oppo et al., 2009), 4 (He et al., 2013), 5 (Liuetal.,2009), 6 (Tan et al., 2003), and 7 (Ge et al., 2003). (b): Locations of the Xisha
Islands and the Leizhou Peninsula. (c) and (d): the pictures of Porites lutea coral and Tridacna gigas shell from the northern SCS.
20
22
24
26
28
30
02468
SST (°C)
Month
1210
Fig. 2. Monthly mean sea surfacetemperatures(SST) in Xisha Islands(circles connectedby
red line) and Leizhou Peninsula(triangles connected by purple line)constructed from the
averages over the 1982 to 2008 interval. The source of the SST data is the NOAA NCDC
ERSST ver.2 data, a global monthly SST data from January 1854 with a spatial resolution
of 2° × 2°. (For interpretation of the references to color in this figure legend, the reader
is referred to the web version of this article.)
124 H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
assembled here to produce a proxy-SST record over the last 2500 years.
Coral and T. gigas records meeting the following conditions were includ-
ed in this assembly work. First, the coral and T. gigas records are from
the northern SCS. Second, the time windows of coral and T.gigas records
must cover the late Holocene of the last 3000 years or so. Third, the time
resolutions of the coral and T. gigas records are higher than one month.
Based on these three stringent conditions, one coral record from Xisha
Islands (Wei et al., 2004a), four coral records from the Leizhou Peninsu-
la (Weietal.,2004a,b;Yuetal.,2005), and two T. gigas Sr/Ca based SST
time series from Xisha Islands (Yan et al., 2014b) were selected (see all
the individual records in Fig. 4). Thedetails and statisticsof the coral and
T. gigas proxy-SST for the seven time windows of the late Holocene and
18
20
22
24
26
28
30
32
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
Year
SST (°C)SST anomaly (°C)
r=0.54, p<0.001
r=0.91, p<0.001
a
b
1982 1987 1992 1997 2002 2007 2012
1982 1987 1992 1997 2002 2007 2012
Fig. 3. SST and SST anomaly series from 1982 to 2012 in Xisha Islands (red curve)and Leizhou Peninsula (purple curve). A significantcorrelation between SST anomalies in Xisha Islands
and Leizhou Peninsula is observed (r = 0.54, p b0.001). The source of the SST data isthe NOAA NCDCERSST ver.2 data, a global monthly SST data from January 1854 with a spatial res-
olution of 2° × 2°. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
-12
-8
-4
0
4
8
-6
-4
-2
0
2
4
6AD 990±40AD 50±40
SST (°C) SST (°C)
AD 1455±51
AD 487±22
BC 541±24 AD 489±22
BC 530±24
Leizhou, Coral Leizhou, C o ral Leizhou, C o ral Leizhou, C o ral
Xisha, T. gigas Xisha, T. gigas Xisha, Coral
Fig. 4. All sevencoral and T. gigas Sr/Ca-based SST time seriesused in this study. One coralrecord from Xisha Islands (Wei et al., 20 04a),four coral recordsfrom the Leizhou Peninsula (Wei
et al., 2004a,b; Yu et al., 2005), and two T. gigas records from Xisha Islands (Yan et al., 2014b) were selected for our study.
125H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
the instrumental SST data are summarized in Table 1. Our method of
compositing explicitly assumed that each of the time window, though
relatively short in the full extent of their actual time coverages, can be
representative of the major climatic warm, cold and neutral periods
studied here. We believe that this assumption is reasonable since the
dating accuracy of the coral and T. gigas samples is relatively accurate
so there can be no doubt that our coral and bivalve samples actually
sampled and recorded the SST conditions during the historical time
windows when they were alive.
2.3. The method of compositing
In this study, the time resolution of all coral and T. gigas Sr/Ca series
was homogenously resampled to one month using linear interpolation
from original raw data records. For each series,the proxy-SST was calcu-
lated from Sr/Ca ratio using the calibration equations between instru-
mental SST and modern coral/T. gigas Sr/Ca ratios (Wei et al., 2004a,b;
Yu et al., 2005; Yan et al., 2013). For each proxy-SST time series, the win-
ter SST value was calculated using the average of annual SST minima
and the summer SST was calculated using the average of annual SST
maxima. The SST seasonality of each time windows was defined as the
difference between winter and summer SST values. Then, the average
of the winter SST and summer SST values was re-calculated and
employed as the annual-mean SST of each time windows. We note
that the use of such arithmetic means will minimize the impact of ana-
lytical errors, growth rate and other shorter-term variability on the final
longer term SST estimates (Yu et al., 2005; Yan et al., 2013).
As noted, the modern SSTs in Xisha Islands and Leizhou Peninsula
are different (27.59 vs. 25.41 °C), thus making the combination difficult
if using the reconstructed SST data directly. Therefore, we have chosen
to use SST anomalies to combine the seven proxy-SST records and in-
strumental SST record. We first calculated the instrumental winter,
summer and mean SST in Xisha Islands and Leizhou Peninsula during
the 1990–2000 using the same method of the paleo-SST. The anomalies
were calculated by subtracting the winter, summer and annual-mean
SSTs of each paleo time windows from the individual values of instru-
mental winter, summer and annual-mean SSTs (Table 1).
Because thevariation range of the modern climate in Leizhou Penin-
sula is much larger than that in Xisha Islands; the relative change rate,
therefore, was used to further normalize our data. The relative change
rate is defined as the percentage of the paleo SST anomalies to the mod-
ern instrumental SSTs. For example, the reconstructed annual-mean SST
in Xisha Islands around AD 990 is 28.54 °C, the instrumental annual-
mean SST in Xisha Islands during the 1990–2000 is 27.65 °C, the mean
SST anomaly is 0.89 °C (28.54–27.65 = 0.89), and the relative change
rate is thus calculated to be 3.2% (0.89/27.65 = 0.032). All relative
change rates are also given in Table 1.
3. Results and discussion
3.1. A composite proxy-SST record in the northern SCS during the late
Holocene
Both SST anomalies and relative change rates of the composite SST
record, including winter, summer and annual-mean SSTs, in northern
SCS during the late Holocene are plotted in Fig. 5. Both plots cover a
total of 8 time windows (see summary in Table 1 and Fig. 5), including
5 coral-based time windows around BC 541, BC 535, AD 487, AD 495
and AD 1464, two T. gigas-based time windows around AD 50 and AD
990, and the instrumental SST time window covering AD 1990–2000.
The annual-mean SST anomalies for the 8 time windows are ranging
from −2.2 °C (−8.6%) to 1.55 °C (5.6%) during the last 3000 years
(Fig. 5). The SSTs of warm period time-windows around AD 990 ± 40,
AD 50 ± 40 and BC 535 ± 24 are 0.89 °C (3.2%), 1.55 °C (5.6%) and 0.1
°C (0.4%), higher than that during modern instrumental period of AD
1990–2000 (Fig. 5). The SSTs of cold period time-windows around AD
1464 ± 51, AD 495 ± 22, AD 487 ± 22 and BC 541 ± 24 are 1.08 °C
(−3.9%), 2 °C (−7.8%) and 2.2 °C (−8.6%) and 0.4 °C (−1.6%), lower
than that of the modern instrumental SST decade (Fig. 5). It is worthwhile
to note that the warmer SSTs in northern SCS around AD 990 ± 40 (3.2%)
and AD 50 ± 40 (5.6%) occurred within the notable warm episodes of
Medieval Warm Period (MWP, ≈AD 800–1300
1
)andRomanWarmPe-
riod (RWP, ≈BC 400–AD 200), respectively. Conversely, the cooler SSTs
around AD 1464 ± 51, AD 495 ± 22 and AD 487 ± 22 are consistent
with the European cold periods of Little Ice Age (LIA, ≈AD 1400–1850)
and Dark Age Cold Period (DACP, ≈AD 400–800).
3.2. Intercomparison with other SST proxies from tropical Western Pacific
Although the high resolution temperature reconstructions in north-
ern SCS are scarce, the nearby low resolution marine sediment SST
1
Please seepp. 235–239 of Soon et al. (2003) for a detailed discussion on the appropri-
ate use of the terminology “Medieval Warm Period”. We also proposehere that the timing
of 1300 AD for the transition between MWP andLIA may be not entirely arbitrary nor ac-
cidental but instead has a physical root and link to the timing of 1246 AD being the last
time in which the perihelion of the Sun–earth orbit coincided with Northern Hemisphere
winter solstice (see e.g., Kukla and Gavin, 2004).
Table 1
Detailedinformation of coraland T. gi gas Sr/Ca-based SST timewindows in northern SCSduring the late Holocene. The calculatedSST anomalies and relative change ratesin SST were also
presented. Please see Section 2.3 for the methodology for the assembly of our composite SST recordcombining the seven coral and T. gigas records with the instrumental SST records.
Locations Materials References Dating
(BC/AD)
Length
(years)
SST anomalies SST relative change rates
Annual SST (°C) Winter SST
(°C)
Summer SST
(°C)
SST
seasonality
(°C)
Annual
SST
(in %)
Winter
SST
(in %)
Summer
SST
(in %)
SST
seasonality
(in %)
Northern SCS Instrumental
data
Xisha
Leizhou
AD 1990–2000 11 0 ± 0.37 0 ± 0.56 0 ± 0.32 0 ± 0.50 0 0 0 0
0 ± 0.35 0 ± 0.89 0 ± 0.38 0 ± 1.01
Xisha Island Coral Wei et al.
(2004a)
AD 1405 ± 51 3 −1.08 ± 0.36 −0.8 ± 1.00 −1.45 ± 0.14 −0.65 ± 0.89 −3.9 −3.2 −4.9 −13.3
Xisha Island T. gigas Yan et al.
(2014b)
AD 990 ± 40 11 0.89 ± 0.65 1.39 ± 0.64 0.3 ± 0.97 −1.09 ± 1.02 3.2 5.6 1.0 −22.2
Leizhou
Peninsula
Coral Wei et al.
(2004b)
AD 495 ± 22 11 −2 ± 1.58 −2.9 ± 2.46 −1 ± 1.03 1.9 ± 1.01 −7.8 −14.1 −3.4 21.1
Leizhou
Peninsula
Coral Yu et al.
(2005)
AD 487 ± 22 13 −2.2 ± 1.59 −3.8 ± 2.48 −0.7 ± 1.01 3.1 ± 1.18 −8.6 −18.4 −2.4 34.5
Xisha Island T. gigas Yan et al.
(2014b)
AD 50 ± 40 15 1.55 ± 0.64 1.88 ± 0.73 1.13 ± 0.76 −0.75 ± 0.79 5.6 7.6 3.8 −15.3
Leizhou
Peninsula
Coral Wei et al.
(2004b)
BC 535 ± 24 9 0.1 ± 1.53 0.4 ± 2.48 −0.2 ± 1.32 −0.6 ± 1.21 0.4 1.9 −0.7 −6.7
Leizhou
Peninsula
Coral Yu et al.
(2005)
BC 541 ± 24 11 −0.4 ± 1.54 −0.8 ± 2.49 −0.1 ± 1.31 0.7 ± 1.26 −1.6 −3.9 −0.3 7.8
126 H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
records (Wang et al., 1999; Shintani et al., 2011), which yield similar
variation pattern with our composite SST record, provide some support
to our composite 8 time windows SST record (Fig. 6). First to note is the
larger variability of winter SST relative to summer SST, which is clearly
shown in ourcomposite high resolution SST record (Fig. 5), was also ob-
served in the marine sediment SST record (Fig. 6)(Wang et al., 1999;
Shintani et al., 2011). The SST reconstruction of Indonesia derived
from the Mg/Ca of planktonic foraminifera (Oppo et al., 2009; Steinke
et al., 2014) and SST record of southern Okinawa Trough derived from
TEX
86
(Wu et al., 2012) also showed similar time variation pattern
with our composite SST record during the late Holocene (Fig. 6). These
marine sediment SST records that are more continuous in time coverage
largely supported the reliability of our composite SST record in northern
SCS that was constructed from seven proxy-SST and the instrumental
SST time windows. It may be important to note that the relative
agreement of our Sr/Ca-based SST proxies with the SST deduced from
differentproxies and methodologies in Fig. 6 serve as a very good inde-
pendent check of our Northern SCS seasonal SST records.
3.3. Distribution of RWP and MWP in theAsia-Pacific region wit h a compar-
ison to other regions
The composite proxy-SST record gives us an important overview and
scientific context for the climate changes in northern SCS during the late
Holocene (Fig. 5). As seen in Fig. 5, the reconstructed SST record re-
vealed six climatically recognizable periods: two warm periods around
AD 990 and AD 50 corresponding to the MWP and RWP, two cold pe-
riods around AD 1464 ± 51, AD 495 ± 22 and AD 487 ± 22 correspond-
ing to the LIA and DACP, and two “normal”periods around BC 541 ± 24,
BC 535 ± 24 and AD 1990–2000.
The RWP has been proposed as a period of unusually warm weather
in Europe and the North Atlantic (Lamb, 1977). The time span for RWP
is generally considered to cover broadly between 2500 and 1600 BP, al-
though the exact time period varies in different regions and stated to be
so by different authors: 2700–1600 BP in southwest Greenland
(Seidenkrantz et al., 2007), 2400–1600 BP in the North Sea (Hass,
1996) and 2600–1600 BP in southern Spain (Martín-Puertas et al.,
2009). It is still unclear if the warm climate during the Roman times oc-
curred globally but it is clear from the literatures, even within dating im-
precision, the warm period probably did not occurred or initiated
synchronously all across the globe. From the perspective of multi-
century scale variation of glacier mass fluctuations, Joerin et al.
(2006), for example, through the accurate dating of wood and peat frag-
ments, suggested a warm and major glacier recession in the Swiss Alps
centered around the 300-year long period from 2150 to 1850 BP. Al-
though many paleoclimate reconstructions from the Eurasia–Atlantic
regions revealed an obvious warm climate around AD 0, there were
also some temperature records from the Northern and Southern Hemi-
spheres (Cook et al., 2000; Hantemirov and Shiyatov, 2002)aswellas
Antarctica (Masson et al., 2000), that showed no significant warm con-
dition during the RWP 2000 years ago. Similarly, there were some ef-
forts to synthesize various records from different regions to produce a
wider areal, if not hemispheric, averages, but the results were also con-
troversial. For example, one early multi-proxy compilation of Northern
Hemisphere did not find the obvious warm period during the Roman
times (Moberg et al., 2005), but a more recent synthesis of extratropical
Northern Hemisphere temperature showed the obvious warm climate
around AD 0 (Ljungqvist, 2010)(seeFig. 7).
The annual-mean proxy-SST for the time window during the RWP
(around AD 50 ± 40) is the warmest one among the eight time win-
dows of our northern SCS composite record, with 1.55 °C warmer than
that of recent de cades (Fig. 4). The warm climate in northern SCS during
the RWP is consistent with the nearby SST reconstruction surrounding
marine-continental region of Indonesia (Fig. 6)(Oppo et al., 2009)and
in China (Fig. 7a) (Yang et al., 2002). However, the warm RWP does
not seem to be uniformly warm for the whole East Asian Monsoon af-
fected domain. The historical documentary and stalagmite reconstruc-
tions from the mid-east (Fig. 7b) and north China (Fig. 7c) suggested a
relatively warm period (Ge et al., 2003; Tan et al., 2003), but the tree
ring (Fig. 7d) and lake sediment records (Fig. 7e) from the northwest
China indicated either neutral or even a cold period during the Roman
times (Liu et al., 2009; He et al., 2013). The regional difference, the er-
rors of age models and nonlinear proxy transfer functions or relative in-
sensitivity of certain proxies could all provide some explanations for the
discrepancy. Overall, we find that although the presence of warm cli-
mate in northwest China during the Roman times remains to be
substantiated, the relatively prominent and geographically wide distri-
bution of the Roman warm period in the Eastern margin of China and
the western tropical Pacific region is well established.
In contrast to RWP, there are more comprehensive proxy records
that support the MWP, a warm period during AD 800–1300, and the ex-
istence of MWP is demonstrated by climate data from not only in north-
ern SCS and northern Europe but also in many parts of the world
(Hughes and Diaz, 1994; Soon et al., 2003; Mann et al., 2008, 2009;
Esper and Frank, 2009; Ljungqvist, 2010; Graham et al., 2011). The aver-
aged SST of the time window during the MWP (around AD 990 ± 40)
was higher than that during the DACP and the LIA (Fig. 5 and Table 1),
confirming the existence of a warm period during the MWP in the
northern SCS. The warm medieval times was also found in the
Indonesian record, as well as some records from China (Figs. 6 and 7).
Although there are also some difference in the timingand the tempera-
ture change amplitude in these diverse types of proxy records, but a
warm climate during the MWP seems to be certain in Asia-Pacific re-
gion, covering broad geographical areas from Northwest China to the
Western Pacific.
Our composite proxy-SST record also reveals two cold periods, one is
between RWP and MWP corresponding to the European DACP well
noted in historical documents and the other is between MWP and cur-
rent warm period corresponding to the relatively better-studied LIA in-
terval (Matthes, 1939, 1940; Grove, 1988). The cold climate during the
-4
-2
0
2
SST anomaly
in Northern SCS (°C)
Annual
Summer
Winter
BC/AD
BC/AD
-20
-15
-10
-5
0
5
10
0
SST anomaly
in Northern SCS (%)
Annual
Summer
Winter
a
b
AD 990±40AD 50±40
AD 1455±51
AD 487±22
BC 541±24
AD 489±22BC 530±24
-1000 -500 500 1000 1500 2000
0-1000 -500 500 1000 1500 2000
Fig. 5. Thecomposite proxy-SSTrecords. Winter(triangles connected by pink curve),sum-
mer (triangles connected by blue curve) and annual-mean (diamonds connected by red
curve) SSTs,in northern SCS during the late Holocene are indicated. Both the SST anoma-
lies (a) andSST relative changerates (b) are shown.The composite SST records consist of 8
time windows (see summaryin Table S1), including 5 coral time-windows aroundBC 541,
BC 535, AD 487, AD 495 and AD 1464, two T. gigas time-windows around AD 50 and AD
990, and a instrumental SST time-window covering AD 1990–2000. (For interpretation
of the references to color in this figure legend, the reader is referred to the web version
of this article.)
127H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
Dark Age was pointed out specifically by Hubert Lamb (Lamb, 1977).
Later studies further confirmedacoldandwetperiodinEuropeduring
the DACP. The cold climate duringthe DACP was also clearly recorded in
various proxies from the Western Pacific to the Northwestern China
(Figs. 6 and 7), such as the marine sediment record (Oppo et al.,
2009), the ancient Chinese literature record (Ge et al., 2003), the cave
stalagmite record (Tan et al., 2003) and the lake sediment record (He
et al., 2013), confirming that the cold climate during the DACP was in-
deed widely distributed all over the East Asia–Western Pacific region.
Despite the relatively more stringent requirements for persistency of
meteorological and climatic forcings and finite time for the growth of
glacier ice mass, the clear imprints of the DACP can also be found in
the glacial record of Sheridan Glacier, around the Copper River Delta,
coastal South-Central Alaska which has its peaked phase of advance
centered at around 530 to 640 AD (Barclay et al., 2013). In addition,
the recent syntheses work of Northern Hemisphere temperature varia-
tions also demonstrated an obvious cold climate during the DACP
(Fig. 7)(Moberg et al., 2005; Ljungqvist, 2010). The anomalous weather
regimes and climatic conditions during the LIA have been heavily stud-
ied in recent decades and the results suggested a cold climate with a
substantial accumulation of land ice covering most high-elevation
areas of the Earth. The relatively low temperature anomaly of 1.08 °C
during the LIA in our composite proxy-SST record was clearly consistent
with the other reconstructions from the East Asia–Western Pacific re-
gion (Figs. 6 and 7).
Overall, the variation pattern of our northern SCS SST record
was similar to that of other temperature reconstructions from East
Asia–Western Pacific regions and two syntheses of the Northern
Hemisphere-wide temperature records during the late Holocene with
some divergences in details especially for the RWP (Fig. 7). These results
demonstrated convincingly that the climate oscillations in northern SCS
were in step with other regional and perhaps even the global climate
changes during the late Holocene.
3.4. Variation of the SSTseasonality in the SCS during the late Holocene and
its relationship with the mean climate state
Temperature seasonality, the difference between summer and win-
ter temperatures, is an important aspect of Earth's climate and has sig-
nificant influences on local, regional and global terrestrial and marine
27
28
29
24
25
26
27
28
0
25
26
27
28
21
24
27
30
West Pacific Warm Pool
SST (°C)
17940-Northern SCS
Annual mean SST (°C)
17940-Northern SCS
Summer/Winter mean SST (°C)
c
a
b
MWP
RWP
BC/AD
Southern Okinawa Trough
SST (°C)
d
Summer SST, SD= 0.28 °C
Winter SST, SD= 1.19 °C
Annual SST, SD= 0.64 °C
-1000 -500 500 1000 1500 2000
Fig. 6. The comparison betweencomposite SST series in northern SCS (triangles connected byred line) and other marine sediment-basedtemperature recordsfrom northern S CS (Wang
et al., 1999; Shintani et al., 2011), Indonesia (Oppo et al., 2009) and southern Okinawa Trough (Wu et al., 2012). (For interpretation of the references to color in this figure legend, the
reader is referred to the web version of this article.)
128 H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
environments and ecosystems. However, most of the current proxy-
based climate recordsare not sufficient to quantify the temperature sea-
sonality due to the limits of the temporal resolution inherent in those
individual paleoclimate proxies. In this study, our high-resolution SST
record gives us an exciting opportunity to examine the seasonality var-
iation in northern SCS during the late Holocene that are known to cover
several warm and cold weather regimes and climatic periods. We em-
phasize that the current climate understanding and theory are still
-1.0
-0.5
0.0
0.5
1.0
1.5
-1.5
-1
-0.5
0
0.5
-0.8
-0.6
-0.4
-0.2
0
0.2
-1.0
-0.5
0.0
0.5
1.0
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
20
21
22
23
24
Temperature variation
in China (°C)
Winter half-year temperature
in mid-east China (°C)
Warm season temperature in Beijing
Northern China (°C)
Temperature variaion
in mid-east Tebet Platea
North-west China (°C)
Northern Hemisphere
Temperature (°C)
a
b
c
d
f
MWP
RWP
BC/AD
10
12
14
16
18
Temperature in Gahai
North-West China (°C)
e
Northern Hemisphere
extratropical Temperature (°C)
g
0 1000-1000 -500 500 1500 2000
Fig. 7. The comparison betweencomposite SST seriesin northern SCS (trianglesconnected by red curve)and other temperaturerecords from mainlandChina (a) (Yang et al., 2002), mid-
east China (b) (Ge et al., 2003), northern China (c) (Tan et al., 2003), north-west China (d, e) (Liu et al., 2009; He et al., 2013), Northern Hemisphere (f) (Moberg et al., 2005), and
extratropical region of Northern Hemisphere (g) (Ljungqvist, 2010). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this
article.)
129H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
simply not mature enough (Essex, 2011, 2013)toanswersuchadirect
question,so we will have to rely on empirical knowledge systematically
built from such a paleoclimatic study.
The changes in SST seasonality derived from the differences between
winter and summer SST anomalies were shown in Fig.8.Boththeincon-
stant nature of and the large variation in the amplitude of seasonality for
locations like Northern SCS are the major findings in this study. The SST
seasonality anomalies of eight time windows during the late Holocene
varied substantially from −1.09 to 3.1 °C and the relative change rates
of SST seasonality varied from −22.2% to 34.5% (Table 1 and Fig. 8).
We compare the annual-mean SST anomalies with the SST seasonal-
ity anomalies and find a strong and statistically significant negative cor-
relation (r
2
=0.69,pb0.001, Fig. 8). The seasonality decreased when
the mean SSTs were warmer, such as the time windows centered at
around RWP (SST seasonality anomaly was −0.75 °C) and MWP (SST
seasonality anomaly was −1.09 °C). The result of decreased seasonality
under warmer climateis consistent withthe previous composite bivalve
shell records (i.e., also concatenated from several time windows) from
the Gulf of Maine, North Atlantic, which revealed increased seasonality
with climatic cooling (Wanamaker et al., 2011). This empirical fact
concerning the inverse relation between amplitude of seasonality and
mean climatic condition is also supported by some marine sediment re-
cords. For example, the nearby marine sediment core SCS90-36
(17°59.70′N, 111°29.64′E) record presents an obvious decrease of sea-
sonality in northern SCS during the Holocene than during the last glacial
period (Huang et al., 1997). The new and independent results, both in
terms of area of study and methodology, from western Arabian Sea
also found, from analyses of δ
18
O in individual shells of planktic forami-
nifera samples from their Ocean Drilling Program Site 723A, that the
seasonality amplitude of SST around western Arabian Sea for the rela-
tively colder time during LIA (ca. 0.5 ka for their samples) is about
four times larger than the seasonal SST amplitude during the warmer
period around RWP (ca. 2.07 ka) (Naidu et al., 2014). Our result can fur-
ther directly verify such an observation for northern SCS where the larg-
est amplitude variation for the seasonality occurs during the cold period
of DACP. We have also checked the relationship between the SST sea-
sonality and the SST anomalies in winter and summer, respectively.
The results suggested that the SST seasonality anomalies were highly
correlated with the winter SST anomalies (r
2
= 0.86, p b0.001, Fig. 8),
but not with the summer SST anomalies (r
2
= 0.19, p = 0.29, Fig. 8),
probably indicating that the changes of SST seasonality in northern
SCS mainly depend on the variations of winter climate which is sugges-
tive of the more prevalent effects on seasonality by the land–sea con-
trast of the monsoon-controlled climate regions like East Asia (Ding
et al., 2014).
Similar statistical correlations and physical tendencies can also be
found in instrumental SST data for modern period from 1982 to 2012.
Both the observations from Xisha Island and Leizhou Peninsula revealed
stronger correlations between SST seasonality and winterSST, and weak
ones between SST seasonality and summer SST (Fig. 9). The coefficients
of the correlations between SST seasonality and annual-mean, summer
and winter SST in Xisha Islands were −0.5 (r
2
= 0.25, p b0.01), 0.1
(r
2
= 0.01, p = 0.58) and −0.82 (r
2
= 0.68, p b0.001), respectively
(Fig. 9 top panels). The coefficients of the correlations between SST sea-
sonality and annual-mean, summer and winter SST in Leizhou Peninsu-
la were −0.58 (r
2
= 0.34, p b0.001), 0.45 (r
2
= 0.21, p = 0.01) and
−0.92 (r
2
= 0.85, p b0.001), respectively (Fig. 9 bottom panels).
Such an observed reality from instrumental data clearly provides a
good physical grounding for our interpretation of the paleo-SST results.
3.5. Different amplitudes of summer and winter SST variations during the
late Holocene
Meanwhile, the variation of the winter SST anomaly amplitude in
our composite record was much larger than that of summer SST anom-
aly during the late Holocene (Fig. 5). The winter SST anomalies for the
eight time-windows changed from −3.8 °C to 1.88 °C and the summer
values varied from −1.45 °C to 1.13 °C. The regression between annual-
mean SST anomalies and winter SST anomalies of eight time windows
yielded the equation (Fig. 10): winter-SST (°C) = 1.45 × annual-
y = -0.93x - 0.03
r2 = 0.69
-4
-3
-2
-1
0
1
2
3
4
-5
-4
-3
-2
-1
0
1
2
3
4
BC/AD
SST anomaly
in Northern SCS (°C)
Summer
Winter
Seasonality
SST seasonality anomaly
in Northern SCS (°C)
Annual SST (°C)
y = -0.80x + 0.12
r2 = 0.19
-4
-3
-2
-1
0
1
2
3
4
Summer SST (°C)
y = -0.70x - 0.08
r2 = 0.86
-4
-3
-2
-1
0
1
2
3
4
012
0
0 1 012
Winter SST (°C)
SST seasonality anomaly
in Northern SCS (°C)
SST seasonality anomaly
in Northern SCS (°C)
ab
cd
-2 -1.5 -1 -0.5 0.5 1.5 -4 -3 -2 -1
-3 -2 -1
-1000 -500 500 1000 1500 2000
Fig. 8. The SST seasonality in northern SCS during the lateHolocene (a). The linearregressions of SST seasonality versusannual-mean SST anomaly (b), SST seasonality versus summerSST
anomaly (c) and SST seasonality versus winter SST anomaly (d) are also shown.
130 H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
mean-SST (°C) −0.026 (r
2
= 0.96, p b0.001, n = 8). The regression
between mean SSTs and summer SSTs yielded the equation: summer-
SST (°C) = 0.52 × annual-mean-SST (°C) −0.05 (r
2
= 0.74, p b0.01,
n = 8). This empirical result suggests that an increase of annual-mean
SST of 1 °C corresponds to a winter SST increase of 1.45°C and a summer
SST increase of only 0.52 °C (Fig. 10).
This large difference in the variability of the winter SST and summer
SST has also been detected in two previously published coral δ
18
Otime
series from northern SCS (Peng et al., 2003; Sun et al., 2005). For exam-
ple, Sun et al. (2005) found that the interannual variability of winter
coral δ
18
O in Hainan Island of northern SCS was dominated by theinter-
annual variation of the winter SST, but the interannual variability of
summer coral δ
18
O was primary controlled by the summer rainfall
with little impact from the summer SST variation. This independent re-
sult and interpretation confirm the small interannual variability of sum-
mer SST relative to winter SST variability. Peng et al. (2003) reported a
significant correlation between the interannual variation of coral δ
18
O
from Hainan Island and the winter monsoon index/winter SST, also im-
plying a larger variability of winter SST.
The large difference in the variability of the winter SST and summer
SST in northern SCS was also observed in the instrumental SST record
(Fig. 11). The direct instrumental SST data for the most recent
50 years in northern SCS suggest that an annual-mean SST increase of
1 °C corresponds to a winter SST increase of 1.64 °C and a summer SST
increase of 0.62 °C (Fig. 11), similar to the calculated results from the
paleo-SST records during the late Holocene even in a quantitative
sense. This fact adds confidence to our paleoclimate study of seasonality
contrasting the sharp differences between climate warm and cold pe-
riods of the past 2500 years.
Thus, we conclude that the larger amplitude in SST variation during
winters than during summers in northern SCS during the late Holocene
and instrumental era could explain the negative correlation between
the SST seasonality and the mean climate state in Figs. 8 and 9. When
northern SCS climate turned warm, the summer SST increased less
and the winter SST increased disproportionately more, resulting in a re-
duction of the amplitude of seasonality. When northern SCS climate was
undergoing cooling tendencies, the summer SST decreased less and
winter SST decreased more, resulting in a larger seasonality. The stron-
ger correlation between the winter SST and seasonality than that be-
tween summer SST and seasonality could be similarly explained by
the relative dominance of the winter season for northern SCS monsoon-
al climate region.
3.6. Mechanism for the different variation amplitudes of the summer and
winter SST during the late Holocene
Seasonal and sub-seasonal changes are important components of
Earth's multi-scale and multi-component climate system. The mecha-
nism for the different variation amplitudes in winter and summer SST
is, therefore, essential both for clarifying and understanding the climatic
dynamics in the northern SCS. The SST maps in the tropical Western Pa-
cific (including SCS) for the winter (i.e., January, 2000) and summer
(i.e., July, 2000), respectively, are shown in Fig. 12. The SCS was covered
by the West Pacific Warm-Fresh Pool (WPWFP; consider iso-
temperature zones with SST N28.5 °C (Cravatte et al., 2009)) during
y = -0.67x + 23.56
R2 = 0.25
3
4
5
6
7
y = 0.16x + 0.15
R2 = 0.01
y = -0.73x + 23.07
R2 = 0.68
y = -1.65x + 51.32
R2 = 0.34
7
8
9
10
11
12
3
4
5
6
7
7
8
9
10
11
12
3
4
5
6
7
7
8
9
10
11
12
y = 1.18x - 25.70
R2 = 0.21 y = -1.03x + 30.3
R2 = 0.85
30.5 25.5
SST seasonality (oC)SST seasonality (oC)
Annual SST (oC) Summer SST (oC)
ahsiXahsiX Xisha
Leizhou Leizhou Leizhou
abc
ba c
24.5 25 25.5 26 26.5 28.5 29 29.5 30 30.5 18.5 19.5 20.5 21.5 22.5
27.527 28 28.5 29 28.5 3029.529 23.5 24.5 26.5
Annual SST (oC) Summer SST (oC) Winter SST (oC)
Winter SST (oC)
Fig. 9. The linear regressions of instrumental SST seasonality versus annual-meanSST (a), SST seasonality versussummer SST (b) and SSTseasonality versus winter SST(c) in Xisha Islands
(red triangles and line)and Leizhou Peninsula (purpletriangles andline) from 1982 to 2012. The sourceof the SST data is the NOAANCDC ERSST ver.2data, a global monthly SST data from
January 1854 with a spatial resolution of 2° × 2°. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
y = 0.5216x - 0. 0543
R
2
= 0.7393
y = 1.4539x - 0. 0262
R
2
= 0.9545
-4
-3
-2
-1
0
1
2
Winter SST (pink) and Summer SST
(blue) (°C)
-2.5 -1.5 -0.5 0.5 1.5
SST (mean, °C)
Fig. 10. Thelinear regressions of winter SST versus annual-mean SST anomalies (pink tri-
angles and line) and summer SST versus annual-mean SST anomalies (blue circles and
line) in northern SCS during the late Holocene. (For interpretation of the references to
color in this figure legend, the reader is referred to the web version of this article.)
131H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
summer when the WPWFP migrated north (right panel in Fig. 12). The
summer SST in northern SCS was, therefore, consistent with the SST of
WPWFP. As a result, the changes of summer SST in northern SCS were
closely controlled by and connected to the climate conditions of the
WPWFP. However, the situation was quite different during winter
when the WPWFP migrated south (left panel in Fig. 12). The SCS now
seemed to be free from the predominance of the WPWFP and an obvi-
ous “cold tongue”lied on the northern SCS (Fig. 12). The “cold tongue”
was formed by the southward migration of the cold water along the
northwest coast of the northern SCS driven by the strong East Asian
Winter Monsoonal circulation (EAWM). The “cold tongue”makes the
SST in northern SCS about 3–5 °C lower than the SST in the eastern
part of the Philippines under the same latitude.
The summer and winter SSTs in northern SCS are controlled by
oceanographic conditions of the WPWFP and the strength of the
EAWM atmospheric circulation, respectively. In modern meteorological
observation, the impacts of EAWM on the northern SCS are manifested
through the pulse type of cold waves. The winter temperature around
the region could drop significantly by more than five degrees rather
abruptly when a cold wave sets in from the Siberian High, and the sea
surface temperature also could recover quickly after the cold waves dis-
sipated (Ding et al., 2014). In contrast, the WPWFP oceanographic
y = 0.0192x - 11.324
R2 = 0.4645
25
26
27
28
29
y = 0.6219x + 12.644
R2 = 0.341
28.4
28.8
29.2
29.6
30
30.4
y = 1.6415x - 20.797
R2 = 0.6499
20
21
22
23
24
25
26
y = 0.0109x + 7.6391
R2 = 0.1323
27
28
29
30
31 y = 0.0315x - 39.344
R2 = 0.3015
21
22
23
24
25
Year Year Year
Annual mean temperature (°C)
Winter temperature (°C)
Summer temperature (°C)
Annual mean temperature (°C)
Temperature (°C)
Annual mean Summer Winter
b
e
SD=0.39
SD=0.41 SD=0.79
25.5 26 26.5 27 27.5 28
1955 1975 1995 1955 1975 1995 1955 1975 1995
25.5 2826 26.5 27 27.5
a
d
c
Fig. 11.The variation trendsof annual-mean (a),summer (b) and winter(c) SST in Xisha Islandsfrom 1958 to 2005.The linear regressionsof summer SST versusannual-mean SST(d) and
winter SST versus annual-mean SST (e) from 1958 to 2005 are also shown.
30N
0
10N
20N
10S 95E 115E 125E105E 135E85E 105E 135E95E 115E 125E85E
January 2000 July 2000 29.5
28.5
27.5
26.5
25.5
24.5
23.5
22.5
21.5
20.5
19.5
18.5
Fig. 12. The spatial distributions of SST in SCS in January 2000 (left) and July 2000 (right). The source of the SST data is the NOAA NCDC ERSST ver.2 data, a global monthly SST data from
January 1854 with a spatial resolution of 2° × 2°.
132 H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
conditioning during summers is usually kept more stable with less var-
iability. That is why theinstrumental SSThas a relatively larger variation
amplitude during winters than during summers (see Fig. 11).
From a broader and even hemispheric view, the pulse-type cold
wave is likely one major cause for the larger variability of winter tem-
peratures (Ding et al., 2014). For example, in regions like East Asia and
the east coast of North America, which are strongly influenced by the
winter pulse-type cold waves, hence winter temperature variability
was much larger than summer one (Fig. 13). Dinget al. (2014) recently
provided a comprehensive description and summary of the multi-scale
and multi-modal natures of the EAWM. These authors explained that
EAWM is modulated on timescale of several decades while being repre-
sented by at least three major meteorological modes that are concur-
rently operating and competing. On the prominent multidecadal
timescale, Ding et al. (2014)'s illuminating discussion of physical pro-
cesses covered not only ENSO but also the co-workings of AO, PDO
and AMO phenomena that are not necessarily local to East Asia or
South China Sea.
The modern instrumental data could provide us some additional
clues about the seasonal variations of our composite SST record during
the late Holocene. The similar patterns of winter and summer SST vari-
ations in northern SCS probably hinted at a close inverse relation be-
tween the EAWM and WPWFP conditions during the late Holocene,
with a weak EAWM corresponding to a warm WPWFP. This coupling
between EAWM and tropical Pacific has also been reported by many
previous studies using instrumental data and observations (Lau and Li,
1984; Masumoto and Yamagata, 1991; Li and Mu, 2000; Wang et al.,
2000).
The larger variability of atmosphere-controlled EAWM than ocean-
controlled WPWFP conditions derived from the instrumental data ex-
plains the relatively larger variation amplitude of winter SST than that
of summer SST in northern SCS during the late Holocene. We compare
our composite record with the SST reconstruction from the Indonesian
region of WPWFP. The variability of the winter proxy-SST in our com-
posite record was much larger than that of the proxy-SST record from
the Indonesia region of WPWFP, but the amplitude of the summer SST
variations in both our northern SCS and Indonesian WPWFP records
were comparable. This fact suggests the existence of different mecha-
nisms for the summer and winter SST variations innorthern SCS during
the late Holocene.
The large differences in the amplitude of summer and winter SST
variations found in our study imply a potentially serious problem for
other syntheses of multi-proxy paleoclimate records. In many of the
current synthesis works (IPCC, 2001, 2007; Mann et al., 2008, 2009),
most of the proxy records considered and adopted have a time-
resolution too low to take seasonal effect into consideration and these
proxy records tend to reflect the climate of a particular season. For ex-
ample, most tree ring growth and increment in Northern Hemisphere
occur during boreal springs and summers and the tree ring width
index is basically recording summer-climate information (Briffa et al.,
1990; Büntgen et al., 2005). The climate information derived from the
phenological records and historical winter snow-day records in East
Asia region mainly reflect the early-spring and winter temperatures, re-
spectively (Ge et al., 2003; Aono and Kazui, 2008). Another example is
recently pointed out by Ekaykin et al. (2014) where these authors con-
vincingly demonstrated that their stacked δD isotopic proxy record for
the past three centuries from Vostok station in East Antarctica best rep-
resented summer temperature variations and that summer-sensitive
proxy behavior is distinctly different from variations in annual-mean
temperature (Ekaykin et al., 2014). The synthesis of these climate re-
cords may result in substantial uncertainty if the seasonal cycle ampli-
tude is large (i.e., especially over mid-to-high latitude regions;
including even highly sensitive tropical regions like northern SCS de-
scribed above) and that seasonal bias is a significant factor for the
proxies.
4. Conclusions
In this study, a composite multi-proxy record of the SST variation in
the northern SCS during the late Holocene is constructed by the combi-
nation of seven high-resolution coral and T. gigas Sr/Ca-based SST time
windows and the instrumental SST from 1990 to 2000 interval. The
60E 180 0
120W
120E0 60W
60N
EQ
0.25 10.33
0.2 0.5 2
20S
60S
40N
20N
40S
45
3710
Fig. 13. A comparison of the temperature variability during wintersversus during summers. Thered zones indicate areas withlarger winter temperature variability. The values were cal-
culated from the ratio of the standarddeviation of January temperatures to the standard deviation of July temperatures from 1982 to 2012.The source of the SST data is the NOAA NCDC
ERSST ver.2data, a global monthly SST datafrom January 1854 with a spatial resolution of 2° ×2°. (For interpretation of the references to colorin this figure legend, the readeris referred to
the web version of this article.)
133H. Yan et al. / Earth-Science Reviews 141 (2015) 122–135
variation pattern and characteristic of the composite SST record is con-
sistent with other reconstructions from Eastern to Northwestern China
and tropical Western Pacific; they all indicate a prominent high-
amplitude and geographically wide distribution of the warm climate
during the RWP and MWP in the East Asian–Western Pacificregion.
Meanwhile, we also observe the substantial difference in seasonal SST
variations in northern SCS during the late Holocene, with much larger
SST amplitude during winters than during summers, and the climatic
seasonality of northernSCS over the last 2500 years appears to be signif-
icantly impacted by East Asian Winter Monsoon. The importance of sea-
sonality for past climate states and climatic variations highlights the
potential uncertainty in other current synthesis works that adopted cli-
mate proxies that cannot resolve seasonal SST.
Acknowledgment
Financial support for this research was provided by the
Natural Science Foundation of China (NSFC) (41403018), Major
State Basic Research Development Program of China (973 Program)
(2013CB955900), the West Light Foundation of The Chinese Acade-
my of Sciences (29Y42909101) and the Key Programs of the Chinese
Academy of Sciences (55ZZBS1304101). We are grateful to Professor
Kefu Yu and Gangjian Wei for the constructive comments on earlier
versions of the manuscript, as well as useful comments from the ed-
itor and three anonymous reviewers.
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