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Journal of Asian Earth Sciences

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Temperature seasonality and ENSO variability in the northern South ChinaSea during the Medieval Climate Anomaly interval derived from the Sr/Caratios of Tridacna shell

Chengcheng Liua,d, Hong Yana,b,c,⁎, Haobai Feia, Xiaolin Maa, Wenchao Zhange, Ge Shia,d,Willie Soonf, John Dodsona,g, Zhisheng Ana

a State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, Chinab CAS Center for Excellence in Quaternary Science and Global Change, Xi’an 710061, ChinacQingdao National Laboratory for Marine Science and Technology, Qingdao, ChinadUniversity of Chinese Academy of Sciences, Beijing 100049, Chinae College of Marine Geosciences, Ocean University of China, Qingdao 266100, ChinafHarvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138, USAg School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong 2500, Australia

A R T I C L E I N F O

Keywords:TridacnaSr/CaSSTSeasonalityENSO

A B S T R A C T

The nature of how the El Niño–Southern Oscillation (ENSO) and its seasonality respond to warmer climate iscritical knowledge to predict future climates under the expected anthropogenic warming scenario. In this study,a sub-fossil Tridacna gigas specimen was collected from the northern SCS and AMS14C dating suggested that theanimal lived around AD 1099, during the Medieval Climate Anomaly (MCA) interval, the most recent naturalwarm period of the late Holocene. Monthly Sr/Ca ratios were determined by the ICP-OES measurements and a30-year long SST record was calculated based on a Sr/Ca-SST calibration equation. The results showed that theSST seasonality for this 30-year window around AD 1099 was about 3.11 °C, which is smaller than the modernwarm period (i.e., about 4.36 °C for AD 1994∼ 2005 interval). This new result is consistent with anotherpublished Tridacna gigas record that was dated around AD 990 from the northern SCS. The signals of ENSOactivity were also extracted from the reconstructed SST record and statistical analyses yielded 9 El Niño eventsand 8 La Niña events within the 30-year record, indicating that the frequency of ENSO activity around AD 1099was similar to the modern instrumental period.

1. Introduction

Bivalve mollusks such as Arctica and Tridacna are reliable, in-siturecorders of the evolution and changes of marine environmental con-ditions. Their layered mineral shells can provide uninterrupted, long,seasonally resolved archives of the paleoclimate and paleoenvironmentas expressed in the form of geochemical variations (Black et al., 2009;Wanamaker et al., 2011; Schöne et al., 2012). For the tropical ocean,Tridacna, the largest and one of the fastest growing bivalves in theworld, has long attracted the attention of palaeoclimatologists (Aharonet al., 1980; Sano et al., 2012; Yan et al., 2013). Tridacna has been aprominent member of Indo-Pacific coral reef communities since theEocene (Yonge, 1936; Rosewater, 1965), and it can grow to more than1m in length and live up to over 100 years (Yonge, 1936; Bonham,

1965). The shell of Tridacna is very hard and forms annual and evendaily growth lines, so it serves as a reliable, high-resolution paleocli-mate archive (Aharon et al., 1980; Romanek and Grossman, 1989; Sanoet al., 2012).

The geochemical research of Tridacna shell began in the 1980s inwhich the oxygen isotope ratios (δ18O) of Tridacna was firstly used toreconstruct relative sea level changes and temperature variations(Aharon et al., 1980; Aharon, 1983). Then, high resolution δ18O mea-surements on Tridacna shell show that the δ18O content of Tridacna iscontrolled by both Sea Surface Temperature (SST) and the δ18O ofambient seawater (Aharon, 1983, 1991; Watanabe and Oba, 1999).Because of the combined influence of SST and seawater on δ18O, it cancause large uncertainties when using δ18O of Tridacna as SST proxy,especially for areas with large Sea Surface Salinity (SSS) variability

https://doi.org/10.1016/j.jseaes.2019.103880Received 1 November 2018; Received in revised form 21 May 2019; Accepted 6 June 2019

⁎ Corresponding author at: State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061,China.

E-mail address: yanhong@ieecas.cn (H. Yan).

Journal of Asian Earth Sciences 180 (2019) 103880

Available online 06 June 20191367-9120/ © 2019 Elsevier Ltd. All rights reserved.

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(Yan et al., 2013). In order to separate the temperature and seawaterδ18O signals, developing other independent or complementary pa-leothermometers are necessary.

In order to support such a practical need, the Sr/Ca ratio has beenwidely used as paleothermometer in coral (Smith et al., 1979;McCulloch et al., 1994) and the relationship between high resolutionSr/Ca ratios of Tridacna and SSTs was critically explored in recentdecades. Some early work suggested that the high resolution TridacnaSr/Ca ratios determined by the Laser Ablation Inductively CoupledPlasma Mass Spectrometry (LA-ICP-MS) presented no clear link withSSTs (Elliot et al., 2009). In contrast, our work in the northern SCSshowed that the monthly resolved Tridacna Sr/Ca ratios, as determinedby the Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES), presented clear annual cycles and was significantly correlatedwith the monthly SSTs. This contradiction indicates that differentanalytical methods for deducing Sr/Ca ratios may lead to significantlydifferent conclusions and that the Tridacna Sr/Ca ratios obtained byICP-OES can be utilized as a SST proxy (Yan et al., 2013). Meanwhile,the Sr/Ca ratios of different modern specimens in the same speciesseemed to yield good reproducibility (Yan et al., 2014). These studieshighlighted the potential of using the Sr/Ca ratio of Tridacna specimensin the SCS to reconstruct high-resolution paleo-temperature variations.

The South China Sea (SCS), located near the margin of the WesternPacific Ocean, is the largest semi-enclosed marginal sea of the WesternPacific Ocean. The modern climate of the SCS is dominated by the EastAsian Monsoon (EAM) which in turn can also be related to the El Niño-Southern Oscillation (ENSO) owing to the close interaction betweenENSO and EAM (Wang et al., 2000; Zhou and Chan, 2010). Therefore,the SCS is an important location for us to better understand both EAMactivity and ENSO variability. Climate records from the SCS are thusimportant for investigating the nature of tropical and sub-tropical cli-mate systems and their dynamic interactions.

The Medieval Climate Anomaly (MCA, AD 800-1300), one of themost recent naturally warm period for most areas of the world (Soonet al., 2003; Loehle and McCulloch, 2008; Lüning et al., 2017, 2019),can be used to test the natural climatic variations with changes inducedby more recent human activity. Therefore, high resolution proxy cli-mate archives during MCA will be very helpful for understanding theinteraction between different regional climate systems in order toprovide some historical context and perspective for the expected an-thropogenic global warming. In this study, a sub-fossil Tridacna gigasspecimen from the northern SCS, that lived around AD 1099 during theMCA, was collected. The monthly resolved Sr/Ca ratios were de-termined by the ICP-OES and a 30-year long SST records were calcu-lated based on the Sr/Ca-SST calibration equation developed by Yanet al. (2013). Further, the signals of ENSO activity were also extractedfrom the reconstructed SST records.

2. Materials and methods

2.1. Study area and sample preparation

One sub-fossil specimen of Tridacna gigas (A25) was collected inApril 2015 in the North Reef, Xisha archipelagos, South China Sea(SCS). The SCS is a semi-enclosed marginal sea on the west boundary ofthe Western Pacific Ocean, and has an area of some 3.6 million km2.The SCS consists of numerous islands, coral reefs, and shoals, and thelargest island is Hainan. The Xisha archipelagos are about 300 km fromHainan Island, and the North Reef (17°05′N, 111°30′E) is located in thenorthern part of the Xisha archipelago (Fig. 1). The climate of Xisha ischaracterized by two distinct seasons: a warm/wet season from May toNovember and a cool/dry season from December to April. The highestmonthly mean air temperature appears in June and the lowest in Jan-uary. The average monthly air temperature range at the Xisha Islands is6.25 °C (1958–2005), which is calculated by the difference betweenmonthly maximum and minimum temperatures within a year (Fig. 2).

The basic characteristics of monthly long term mean SSTs (1982–2014)are similar to air-temperature at Xisha, but the absolute value of SSTs ishigher than air-temperatures (Fig. 2). The highest monthly precipita-tion at Xisha occurs in October (Fig. 2). The precipitation and airtemperature data used in this study were obtained from the meteor-ological observations by the China Meteorological Administration. Themonthly SSTs were obtained from the NOAA NCEP EMC CMB GLOBALReyn_SmithOIv2 dataset, and the data at gird box around 112.5°E,16.5°N were selected. The Southern Oscillation Index (SOI) datasetswere obtained from University Corporation for Atmospheric Research(UCAR) (http://www.cgd.ucar.edu/cas/catalog/climind/soi.html).

The studied sub-fossil specimen A25 was∼35 cm wide and ∼62 cmlong. A slice of approximately 0.5 cm thick was cut from the umbo tothe inner surface and parallel to the axis of maximum growth (Yanet al., 2013, 2014), then the inner and outer shell layers were observedin radial section and annual bands could be observed within the innershell layer (Fig. 1d). The sample slice was soaked in ∼30% hydrogenperoxide to remove any remaining organic matter on its surface andwas then ultrasonically rinsed with deionized water and subsequentlyair-dried (Yu et al., 2005; Goodkin et al., 2005).

A powder sample for accelerator mass spectrometry (AMS) 14Cmeasurement was taken to be about 50mg from the inner surface. Andthe carbonate sub-samples used for Sr/Ca analysis were obtained by acomputer operated micro-milling device along the annual growth in-crements from the youngest to the oldest layer. The grooves are about2mm long and 0.15mm in width (Fig. 1d), then 9–40 subsamples wereobtained from each annual layer and 611 sub-samples were thus ob-tained in total.

2.2. AMS14C dating and Sr/Ca analysis

The radiocarbon age determination was carried out at the Instituteof Earth Environment, Chinese Academy of Sciences. The result was944 a BP (see Table 1). In order to measure the reservoir effect in thesampling site, eleven modern Tridacna samples were also collected fromthe North Reef and AMS 14C dating were performed. The dating resultsshow that there is no obvious “reservoir effect” in the modern Tridacnashells (see Table 1). Therefore, the dating results of specimen A25 wascalibrated by the atmospheric 14C yield model using IntCal13 of CalibRev 7.0.4 for this paper. The conventional radiocarbon age is correctedto be AD 1099 which falls within the MCA period.

Each powder subsample used for Sr/Ca analysis was dissolved in2ml 5% HNO3, then about 1.5ml solution was used for the Sr/Cameasurements. The Sr/Ca ratios were determined by the InductivelyCoupled Plasma Optical Emission Spectrometer (ICP-OES, Agilent5100) with radial plasma observation at the Institute of EarthEnvironment, Chinese Academy of Sciences, and the raw Sr/Ca profilesare shown in Fig. 3a and b (i.e., with identified spectral lines Ca:317.933 nm, Sr: 407.711 nm). In order to monitor the status of the in-strument, we inserted the laboratory standard N1 between every 5subsamples, the average Sr/Ca value of N1 is 2.305 ± 0.010 (1σ)mmol/mol, and the relative standard deviation (RSD) is 0.433%.

2.3. Data resampling, bandpass filtering and spectral analysis

9 to 40 Sr/Ca subsamples were obtained from each layer, whichensured at least 9 points for every year. In order to assess the season-ality of Sr/Ca patterns, we adjusted Sr/Ca data within each year with a9-points cubic spline model using AnalySeries software. The bandpassfiltering of SST, SOI and proxy-SST time series in this study were cal-culated using the Origin 9.1 software. The spectral analysis of SST, SOIand proxy-SST time series were performed using the Past 3 software(Hammer et al., 2001).

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2.4. Chronologies of specimen A25

Seasonal chronologies for Sr/Ca profile of specimen A25 was es-tablished with the method described by Yan et al. (2013). The chron-ologies for seasonal Sr/Ca profile of specimen A25 were establishedusing the arrival times of the winter SST minima at the Xisha Islands.The time for the data point of maximum Sr/Ca ratio was assigned aswinter value (Sr/Ca profile of Tridacna gigas yielded a negative corre-lation with local SST), and the time for the data points between the Sr/Ca ratio maxima were simply allocated using linear interpolation withequal time span (Yan et al., 2013). Then we assumed a relative timeseries as age 1, 2, 3, …, 30 for the annual cycles of Sr/Ca profile shown

in Fig. 3c.

2.5. Calculation of seasonality from Tridacna gigas

The instrumental seasonality is defined as the difference betweensummer SSTs (i.e., the mean of June, July and August) and winter SSTs(i.e., the mean of December, January and February). Likewise, proxySST seasonality could be defined as the difference between summer andwinter SSTs as reconstructed from the Sr/Ca values. In our study, theresampled data points of maximum Sr/Ca value were assigned to winterconditions, and the average of two minimum Sr/Ca values were as-signed to summer conditions.

Fig. 1. (a) Map of the South China Sea; (b) The Xisha Islands; (c) Tridacna shell and (d) the radial section of Tridacna gigas specimen A25.

Fig. 2. Long time-averaged, monthly mean surface air temperature (1958∼ 2005) of the Xisha (filled diamonds), monthly mean precipitation (1958∼ 2005) of theXisha (bar chart), and long time-averaged monthly mean SSTs (1982∼ 2014) of the Xisha (filled circles).

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The relationship between SST and Sr/Ca of Tridacna gigas in thenorthern SCS by Yan et al. (2013) yielded the following linear equation:

° = − ∗ = =SST( C) 64.93 16.60 Sr/Ca(mmol/mol), r 0.95, n 342 (1)

The regression was based on extrema of SST (i.e., January, June,and July data). The proxy-SST seasonality could then be defined as thedifference between SSTs reconstructed from winter and summer Sr/Cavalues (△Sr/Ca), and can be calculated using the following equation:

− ° = ∗proxy SST seasonality( C) 16.60 ΔSr/Ca(mmol/mol) (2)

The proxy seasonality calculated from specimen A25 was comparedwith another sub-fossil Tridacna gigas specimen, SD1 (with a central ageat AD 990) that also lived during the MCA and which was collectedfrom the Shi Dao area (Yan et al., 2014, 2015b) (Fig. 4). In order tocompare seasonality between the modern warm period and the MCA,and to reduce the error between proxy and instrumental records, themodern seasonality was calculated from the modern Tridacna gigasspecimen YX1 which was collected from Yongxing Island (Yan et al.,2013). The 9-points cubic spline method was also applied to specimenYX1, the maximum Sr/Ca were assigned to represent winter conditions,and the average of two minimum Sr/Ca values were assigned to ap-proximate summer conditions, similar to specimen A25 and SD1.

2.6. Extracting the ENSO-related component from Tridacna gigas

In order to further discern the nature of ENSO variability from theSr/Ca-proxy SST, two methods were adopted to extract the ENSO-re-lated component of time variations. The methods include the 3–7 yearsbandpass filtering (Yan et al., 2017) and an event threshold methoddeveloped previously by considering the accumulated 1–10 yearsbandpass percentage of monthly temperature anomalies of the SCS (Liuet al. 2017). The proposed threshold of moderate/ strong El Niño eventsby Liu et al. (2017) is 6%; while the threshold of moderate/ strong LaNiña events is set to be about −7.07%.

3. Results and discussion

3.1. Sr/Ca profile

The Sr/Ca values for specimen A25 range from 1.53 to 1.99mmol/mol, and the average is 1.69 ± 0.003mmol/mol (n=611) (seeFig. 3a, b). A total of 30 annual cycles were identified from the Sr/Caprofile. For the sake of analysis, the Sr/Ca profile was adjusted to 9-points within each year and the full 30 annual cycles were analyzed (seeFig. 3c).

3.2. Seasonality during a 30-year window of the SCS around AD 1099

Even small changes in seasonality may have dramatic impacts onecosystems and human activities (Denton et al., 2005; Ferguson et al.,2011; Zeppel et al., 2014). Assessing past seasonality changes underdifferent climate states is key to understand past climate dynamics andpredict future climate impacts. The instrumental seasonality is calcu-lated by the difference between summer SSTs (i.e., the mean of June,July and August) and winter SSTs (i.e., the mean of December, Januaryand February). The proxy-seasonality of specimen A25, SD1 andmodern YX1 were calculated based on Eq. (2) (see the results shown inFig. 4). The seasonality calculated by instrumental data (i.e., fromAD1982∼ 2014; seasonality is 4.23 °C) is in good agreement with theproxy-seasonality calculated by modern specimen YX1 (i.e., fromAD1994∼ 2005; seasonality is 4.36 °C). The seasonality of specimenA25 (i.e., centered around AD 1099, seasonality is 3.11 °C) was similarto that of another sub-fossil Tridacna gigas specimen SD1 (i.e., centeredaround AD 990, seasonality is 3.55 °C) and both were smaller than thatof modern specimen YX1 (i.e., from AD1994∼ 2005; seasonality is4.36 °C). The two-sample t-test was performed to examine the season-ality differences between each two specimens. The result showed thatthe seasonality difference between medieval shells SD1 and A25 wasnot statistically significant which meant that the seasonality around AD1099 was similar to that during AD 990. But importantly, the differencebetween the modern YX1 and the MCA sub-fossil specimens (A25 andSD1) was significant at p= 0.05 significance level.

The reduced SST seasonality during the MCA is consistent with theprevious seasonality studies published by Yan et al. (2015a, 2015b) andWanamaker et al. (2011), which suggested that seasonality was prob-ably reduced under a warmer climate condition. But there were alsosome opposite situations where seasonality amplitude might be largerduring warmer periods (see Surge and Barrett, 2012; Wang et al.,2012). Some studies suggested that there were probably regional dif-ferences in the response of seasonality to changes of background cli-mate conditions even during the same time period (e.g., Andreassonand Schmitz, 2000). For example, the oxygen isotope profiles of shellsfrom Rocky Branch in Texas and Chickasawhay River in Mississippi,United States, and New Forest in southern England yielded differentresults during the warm early middle Eocene Epoch. The oxygen iso-tope profiles of shells from Rocky Branch in Texas and ChickasawhayRiver in Mississippi showed a seasonality of 8–9 °C, which was lowerthan for the modern period, but the oxygen isotope profiles of shellsfrom southern England showed that the seasonality was similar to thatof the present day, about 10–12 °C (Andreasson and Schmitz, 2000).Seasonality varies with time and location, owing to local and regionalamplification and diminution factors. The SST seasonality of thenorthern SCS is significantly influenced by the East Asian WinterMonsoon and the larger SST amplitude during winters is the key to

Table 1AMS 14C dating results of eleven modern samples and one sub-fossil specimen A25.

Lab number Sample number Material Sample state 14C Age(a BP)

14C Age Error(1σ)

XA14737 XB1 Carbonate powder Alive, modern −371 20XA14738 XB2 Carbonate powder Alive, modern −345 29XA14739 XB3 Carbonate powder Alive, modern −356 23XA14740 XB4 Carbonate powder Alive, modern −367 24XA14741 XB5 Carbonate powder Alive, modern −387 21XA14742 XB6 Carbonate powder Alive, modern −367 30XA14743 XB7 Carbonate powder Alive, modern −386 26XA14744 XB8 Carbonate powder Alive, modern −373 25XA14745 XB9 Carbonate powder Alive, modern −400 21XA14746 XB10 Carbonate powder Alive, modern −389 21XA14747 XB11 Carbonate powder Alive, modern −326 20XA15009 A25 Carbonate powder Dead, sub-fossil 944 22

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explain the larger seasonality during cold intervals and reduced SSTseasonality during warm intervals (Yan et al., 2015a, 2015b). Thewinter temperature will increase comparatively faster than that ofsummer when the background temperature increases, thus the season-ality should reduce or be weakened during warm climate conditions forthe SCS region. In contrast, the winter temperature will decrease fasterthan that of summer when the background temperature decreases, thusthe seasonality should intensify or be enhanced during cold climateconditions.

3.3. ENSO variability around AD 1099

The impacts of ENSO activity on the climate of the South China Sea

have been well documented and the results indicated that the SSTanomaly of the Xisha Islands (1982–2014) was significantly correlatedwith the instrumental ENSO index, with a higher temperature duringthe El Niño events (Liu et al., 2017; Yan et al., 2017). The tele-connections between the Xisha Islands and ENSO events are also sup-ported by shared spectral power in the ENSO regime between the SSTanomaly of the Xisha Islands and ENSO index (i.e., using the SouthernOscillation Index, SOI) (Fig. 5), where a similar principle peaks of SSTanomaly and SOI index are found between 3 and 7 years. The 3–7 yearsbandpass time series for SST anomaly and ENSO index presented a highcorrelation (R=−0.821, p < 0.01) with a SST lag of seven months(Fig. 5e).

In order to investigate the ENSO-like climate variability during the

Fig. 3. Sr/Ca profile of specimen A25. (a), (b) The raw data, with a typical annual/seasonal cycle indicated. The abscissa is the sample number which is numbered bysampling order from the youngest layer to the oldest layer; (c) the raw data (grey) and the 9-point data (red) with arranged chronology. (For interpretation of thereferences to colour in this figure legend, the reader is referred to the web version of this article.)

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Fig. 4. Seasonality reconstruction of specimen SD1 (Yan et al., 2014), specimen YX1 (Yan et al., 2013), specimen A25 and seasonality calculated by instrumentalSST(1982∼ 2014). (a) △Sr/Ca of SD1 (filled circles), A25 (filled diamonds) and YX1 (filled triangles); (b) SST seasonality of SD1 (unfilled bar chart), A25 (filled barchart), YX1 (10% spot-filled bar chart) and instrumental data (crosshatch filled bar chart).

Fig. 5. (a) The spectral analysis of SST (1982∼ 2014) around Xisha; (b) the spectral analysis of SOI index (1982∼ 2014); (c) the spectral analysis of proxy-SST ofspecimen A25; the red dashed line indicated spectral peaks is significant at the 95% confidence level. Significant spectral peaks about ENSO in each panel are marked.(d) SST anomalies of the Xisha (red curve) and ENSO index (black curve); (e) the correlation for the 3-7-yr bandpass filtered time series between the percentage ofmonthly SST anomalies (red) and the SOI series (black) with the adopted Xisha Islands SSTA lag of seven months. (For interpretation of the references to colour in thisfigure legend, the reader is referred to the web version of this article.)

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MCA period, a spectral analysis was performed on proxy-SST anomalyseries, the results showed similar principle peaks between 3 and 7 years(Fig. 5c when compared to 5a and 5b). In order to further discern thenature of ENSO variability around AD 1099, we applied two methods toextract the ENSO-related component from the time series. The methodsinclude 3–7 years bandpass filtering (Yan et al., 2017) and an eventthreshold method developed previously (Liu et al., 2017). Based on the3–7 years bandpass proxy-SST anomaly, 8 El Niño events and 8 La Niñaevents within the 30-year interval around AD 1099 were observed(Fig. 6b). The average frequency of El Niño was estimated to be roughlyonce every 3.75 years, and about the same rate for the occurrence of LaNiña events.

Based on modern observational data of the SCS, an event thresholdwas developed in a previous study by considering the accumulated1–10 years bandpass percentage of monthly temperature anomalies ofthe SCS (Liu et al; 2017). 6% is the proposed threshold of moderate/strong El Niño events and −7.07% is the suggested threshold of mod-erate/ strong La Niña events (Liu et al., 2017). In this case, 9 El Niñoevents and 8 La Niña events were extracted within the 30-year intervalaround AD 1099 (Fig. 7). The frequency of El Niño was roughly onceevery 3.33 years, and the frequency of La Niña was once every3.75 years. This result for the ENSO frequency during the MCA wassimilar to that of the modern warm period which observed a total of 9moderate/strong El Niño events and 10 La Niña events from1983∼ 2012 using the same methods (i.e., El Niño events: once every3.3 years, La Niña events: once every 3 years).

Reconstruction of ENSO variability during natural warm periods ishelpful for us to understand the dynamics of the ENSO and predict itsfuture trends under a global warming scenario (Chen et al., 2007; Diazet al., 2010; Welsh et al., 2011; McGregor et al., 2013). Yan et al.(2017) reconstructed ENSO activity around AD 50, and there were 11 ElNiño events and 12 La Niña events within the 50-year interval of thepaleoclimate data record. This paleo-ENSO frequency is also similar tothose most recent 100 years (Yan et al., 2017). Even in a much warmer

geological epoch like the early Eocene, the ENSO signal and char-acteristics were found to be still similar (or not dissimilar) to that oftoday (Ivany et al., 2011). These results indicate that the frequency ofENSO activity was probably not as sensitive to the changes of thebackground climatic conditions as previously suspected or claimed.

4. Conclusion

In this study, a sub-fossil Tridacna gigas that lived around AD 1099was collected from the SCS. The high-resolution Sr/Ca ratios wereanalyzed and SST seasonality was reconstructed. The seasonality forthis 30-year window around AD 1099 was about 3.11 °C, which in-dicated a smaller difference between summer and winter SST whencompared with the modern period (1982–2014). The variation of ENSOaround AD 1099 was also investigated in this study. Based on the3–7 years bandpass proxy-SST anomaly, 8 El Niño events and 8 La Niñaevents (i.e., once every 3.75 years) were identified within the 30-yearwindow. Based on “threshold” method, 9 El Niño events (i.e., onceevery 3.33 years) and 8 La Niña (i.e., once every 3.75 years) eventsoccurred within the 30-year window. This result indicates that thefrequency of ENSO variability around AD 1099 was similar to that ofthe modern instrumental period.

Declaration of Competing Interest

The author declare no competing financial interests.

Acknowledgements

Financial support for this research was provided by the researchProjects from Chinese Academy of Sciences, China (QYZDB-SSW-DQC001); Pilot National Laboratory for Marine Science and Technology(Qingdao), China (QNLM2016ORP0202); the National Natural ScienceFoundation of China (NSFC), China (41877399); and National Research

Fig. 6. (a) The monthly SST anomalies of specimen A25 plotted in relative percentage units; (b) the corresponding 3–7 years bandpass filtered SST anomalies ofspecimen A25.

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Program for Key Issues in Air Pollution Control Grants, China(DQGG0104, DQGG0105).

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