Palaeogeography, Palaeoclimatology, Palaeoecology 410 (2014) 233–243

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Palaeogeography, Palaeoclimatology, Palaeoecology

j ourna l homepage: www.e lsev ie r .com/ locate /pa laeo

Paired Porites coral Sr/Ca and δ18O from the western South China Sea:Proxy calibration of sea surface temperature and precipitation

A. Bolton a,⁎, N.F. Goodkin a, K. Hughen b, D.R. Ostermann c, S.T. Vo d, H.K. Phan d

a Earth Observatory of Singapore, Division of Earth Sciences, 50 Nanyang Avenue, 639798, Singaporeb Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USAc Department of Geological Sciences, Jackson School of Geosciences, University of Texas — Austin, Austin, TX 78712, USAd Institute of Oceanography, Vietnam Academy of Science & Technology, 1 Cau Da Street, Nha Trang City, Vietnam

⁎ Corresponding author at: Earth Observatory of Singap639798, Singapore. Tel.: +65 65923199; fax: +65 67943

E-mail address: annette.b@ntu.edu.sg (A. Bolton).

http://dx.doi.org/10.1016/j.palaeo.2014.05.0470031-0182/© 2014 Elsevier B.V. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 6 January 2014Received in revised form 20 May 2014Accepted 30 May 2014Available online 10 June 2014

Keywords:PoritesSouth China SeaStrontium/calciumStable oxygen isotopesPrecipitationMonsoon

Paired strontium-to-calcium (Sr/Ca) and δ18O measurements for two Porites lutea corals recovered from HonTre Island, Vietnam, are strongly correlated to sea surface temperature (SST) and precipitation at monthly tointerannual time-scales. Least squares linear regression of monthly Sr/Ca to SST shows a strong, significantcorrelation (r2 = 0.77, p b .0001), with root mean square residuals of 0.9 °C. 3-year averaged (binned) Sr/Cafor wet (Sep–Nov) and dry (Jan–Mar) seasons separately captures SST variability at interannual timescales (Sr/Ca RMSR = 0.42 °C and 0.70 °C for wet and dry seasons, respectively). Coral δ18O correlatesweakly to SST at seasonal and interannual time scales for wet and dry seasons, with significant anomalies(δ18O RMSR = 2.4 °C and 1.65 °C, respectively). Correcting the SST influence on coral δ18O using paired Sr/Cavalues provides estimates of δ18O of seawater (δ18Osw). 3-year averaged δ18Osw during the wet season shows asignificant correlation to local precipitation (r2 = 0.54, p = 0.01). These results show that coral Sr/Ca in thislocation accurately reflects SST at a number of timescales, and that seawater δ18O composition in the wet seasonis controlled by local precipitation, largely unmodified by ocean circulation during the winter monsoon. Thisstudy highlights the sensitivity and utility of coral geochemistry in this region for reliably reconstructing SSTand monsoonal precipitation.

© 2014 Elsevier B.V. All rights reserved.

1. Introduction

The South China Sea (SCS) is the largest semi-enclosedmarginal seain the Southeast Asian region (~3.5 × 106 km2), spanning from theequator to 23°N and from 99°E to 121°E (Fig. 1). Two ocean currentsoccur synchronously with seasonally reversing winds associated withthe East Asian Summer Monsoon (EASM) and winter monsoon (WM)systems. The contrasting temperature difference between the westernPacific warm pool (WPWP) and the Asian continent drives the EASMwinds that blow towards the northeast and drives the Hainan currentfrom Vietnam past the China coast and through the Taiwan Strait intothe East China Sea. The stronger, drierWMwinds blow to the southwestoff the Asian continent and initiate the Taiwan Current that flows tothe south along the coast of China towards Sumatra (Guan, 1994;Jilan, 2004). Changes in the location, pathway or speed of theseheat-delivering currents strongly influence the continent and coastalsub-regions surrounding the SCS that are home to approximately270 million people (Morton and Blackmore, 2001).

ore (EOS), 50 Nanyang Avenue,846.

The SCS is a relatively understudied region. Instrumental records ofpast climate variations are sparse, temporally short (30–50 years), andgeographically constrained, limiting our ability to examine long-termclimate fluctuations. In order to resolve and understand past climatevariations, the geochemical and stable isotopic composition of marinecarbonates such as scleractinian corals can be used. It has been shownthat elemental ratios of strontium to calcium (Sr/Ca) in massive Poritescolonies are inversely correlated to sea surface temperature (SST),making this an exceptionally useful paleothermometer (e.g. Weber,1973; Smith et al., 1979; Beck et al., 1992; de Villiers et al., 1994;McCulloch et al., 1994; de Villiers et al., 1995; McCulloch et al., 1996;Alibert and McCulloch, 1997; Beck et al., 1997; Fairbanks et al., 1997).Coral stable oxygen isotopic ratios (δ18O) are also influenced by SST,as well as local net freshwater flux (Epstein et al., 1953; Weber andWoodhead, 1972; Grossman and Ku, 1986; McConnaughey, 1989;Evans et al., 1998). In combination with the Sr/Ca paleothermometer,coral δ18O has been proven useful for reconstructing the oxygen isotopiccomposition of seawater (δ18Osw), and therefore climate parameterssuch as sea surface salinity (SSS) and local precipitation (e.g. McCullochet al., 1994; Gagan et al., 1998; Schmidt, 1999; Delaygue et al., 2000;Wei et al., 2000; Grottoli, 2001; Shen et al., 2005a,b; Yu et al., 2005; Suet al., 2006; Grottoli and Eakin, 2007; Cahyarini et al., 2008; Goodkinet al., 2008). In specific regions such as the SCS, which are strongly

SS

T (°C

)S

SS

South China Sea

Vietnam

China

Borneo

Phillipines

Indonesia

Malaysia

Taiwan

Thailand

KC

NEC South China Sea

Vietnam

China

Borneo

Phillipines

Indonesia

Malaysia

Taiwan

Thailand

KC

NEC

Taiwan Str.

Taiwan Str.

Hainan

a) SST February (dry, NE Monsoon) b) SST October (wet, SW Monsoon)

SS

T (°C

)S

SS

c) SSS February (dry, NE Monsoon) d) SSS October (wet, SW Monsoon)

Fig. 1. Schematic of the South China Seawith generalizedmain surface circulation showing the seasonally alternating, basin-scale cyclonic gyres during (a, c) the dry season and (b, d)wetseason and study location of coral reef at Hon Tre, Nha Trang. All figures are drawn using Ocean Data View (Schlitzer, 2002) using theWorld Ocean Atlas 2009 data (Locarini et al., 2010;Antonov et al., 2010). Surface ocean currents on (a and c) were modified from Wang et al. (2006) and Liu et al. (2002). Black box (a and b) = study site.

234 A. Bolton et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 410 (2014) 233–243

influenced by the Asian monsoon system (Su et al., 2006), multi-proxycoral reconstructions can therefore yield important informationabout past changes in freshwater input, ocean circulation andmonsoonintensity. However, caremust be taken to evaluate and quantify the rel-ative contributions of these different influences with their respectiveproxies.

A common drawback in paleoclimate reconstructions using coralδ18O is that seawater δ18O is rarely measured at the same sites asthe coral. Data that do exist are often infrequent so that the seasonalvariability is unknown. Regional relationships between coral δ18O, SSTand SSS are therefore difficult to quantify and, in many studies, thecoral δ18O variability due to either SST or SSS is assumed to be negligibleand stationary (Quinn and Sampson, 2002) in order to isolate contribu-tions from the other parameters. However, at some sites this assump-tion is not valid (Crowley et al., 1999), requiring knowledge ofseasonal values of δ18Osw. Shen et al. (2005a) demonstrated thatseasonal variations of δ18Osw in Taiwan were closely linked to theannual precipitation cycle, whereas Wei et al. (2000) showed that coralδ18Osw fromHainan Island lagged the precipitationmaximaby 2 months.Although there is no general agreement on the best approach to recon-struct δ18Osw, some studies assume that the seasonal amplitude of theδ18Osw is insignificant when establishing the δ18O to SST relationship(McConnaughey, 1989). Moreover, other work has suggested that

where the seasonal variation is strong, the accuracy of the calibrationmight be compromised (Shen et al., 2005a).

Different slopes and intercepts are often observed when comparingcalibrations of Sr/Ca and δ18O to SST for the same coral genus (Smithet al., 1979; Beck et al., 1992; Shen et al., 1992, 1996; Alibert andMcCulloch, 1997; Gagan et al., 1998, 2000; Sinclair et al., 1998;Marshall and McCulloch, 2002; Corrège, 2006) and even for thesame species in some cases from different geographical areas(de Villiers et al., 1995; Alibert and McCulloch, 1997; Gagan et al.,1998; Swart et al., 2002). However, some studies imply that biologicalor kinetic processes can cause these differences (Evans et al., 1998;Allison and Finch, 2004; Gaetani and Cohen, 2006; McGregor andAbram, 2008; Gagan et al., 2012). Collectively this means that general-ized coral geochemical calibrations cannot be utilized for individualcorals, as they could lead to large offsets in local reconstructions(Yu et al., 2005). Calibrations of modern coral relationships to localenvironmental parameters are therefore required to accuratelyreconstruct local as well as regional climate variability.

In this study, we establish a Sr/Ca to SST calibration for two coralssampled from Hon Tre Island, Vietnam, allowing reconstruction ofmonthly and interannual changes in SST. In addition, we examine theδ18O measurements paired with Sr/Ca from the same samples to showhow precipitation can be directly isolated from the coral record. We

235A. Bolton et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 410 (2014) 233–243

find a strong and significant correlation between δ18Osw and precip-itation at interannual time scales, demonstrating the potential toreconstruct both temperature and hydrological variability in thisregion back through time.

2. Sampling and analytical methods

2.1. Location and climatology of the study site

The study site lies along northeastern Hon Tre Island and sits withinopen water conditions (12°12′49.90″N, 109°18′17.51″E). The site is~12 km from Nha Trang Bay, on the east coast of Central Vietnam inthe western SCS (Fig. 1) and is well-removed from potential runofffrom the river Cai (Dung, 2007). Of the two coral colonies sampled, col-ony “TN” was at 3.6 and colony “BB” at 2.5 m depth.

The area surrounding this region lacks locally measured SST, there-fore we use the gridded instrumental data from HadISST, in a 1° by 1°grid centered at 12.5°N and 109.5°E (HadISST 1.1; Rayner et al., 2003),to calibrate to our coral record. HadISST uses reduced space optimal in-terpolation of data from the Marine Data Bank and The InternationalComprehensive Ocean–Atmosphere Data Set (ICOADS) SSTs through1981 and a combination of in-situ and adjusted satellite SST for 1982onwards (see Rayner et al., 2003). We found that other commonlyused satellite SST records (e.g. AVHRR Pathfinder v.5, Kilpatricket al., 2001) were limited in timescale (1990 to 2009). Nonetheless,data from AVHRR that overlap HadISST show excellent agreement(r = 0.864, p b b0.00001, n = 238, 2-tailed). In addition to theHadISST data, we use a spatially larger (2.5 × 2.5 degree averaged,10–12°N; 107.5–110°E) time series of precipitation from NASA'sGPCP (The Global Precipitation Climatology Project, http://disc2.nascom.nasa.gov/Giovanni/tovas/rain.GPCP.shtml) to provide amerged rainfall analysis for comparison to coral data (1979–2010).We also compare the GPCP data with evaporation and precipitationdata obtained from local meteorological stations from the VietnamInstitute of Meteorology, Hydrology and Environment.

2.2. Coral sampling

In March 2011, two live massive Porites spp. colonies were coredoff the northeastern side of Hon Tre Island (Fig. 1). The coral colonieswere within close proximity (~8 m) and were sampled using an under-water hydraulic drill, producing cores 10 cm in diameter by 4.6 m (TN)and 2.4 m (BB) in length. The uppermost section of the TN sample waslost in transit from the field site to the laboratory, although the entirecore from the BB coral remained intact. All cores were subsequentlycleaned with freshwater and sliced into 1.5 cm thick by 8 cm widesections using a diamond saw along the axis of major growth.

Prior to chemical analysis, each coral slabwas ultra-sonically cleanedin deionized water for 10 min to remove surface contaminants. Thisprocedure was repeated 3 times after which each coral piece wasoven dried at 40 °C for 48 h. The X-ray positives (see SupplementaryFig. 1) were used to determine the drilling direction along the majorgrowth axis to avoid issues with growth effects (McCulloch et al.,1994; Alibert and McCulloch, 1997; DeLong et al., 2011). Sub-annualsamples were drilled using a 1 mm diameter micro-drill at 0.5 mmintervals using a drilling depth of 1 mm. After removing each sample,clean, high-pressure air was used to remove powder residue fromwithin the drilling hole and drill to avoid cross contamination withthe next sample. Each sample produced between 200 and 400 μgof powder.

2.3. Sr/Ca and δ18O geochemical analysis

For Sr/Ca determination, a 200–300 μg fraction from each sub-annual sample was completely dissolved in 2 ml of 5% HNO3 andanalyzed using an inductively coupled plasma-atomic emission

spectrometer (ICP-AES) at the Woods Hole Oceanographic Institution.Solution standards were used to correct for drift and matrix effectsfrom varying Ca concentrations (Schrag, 1999). The trace elementmeasurements of Sr/Ca were calibrated against a bulk coral powderstandard (quantified against international coral standard JCp-1, with aconsensus Sr/Ca value = 0.01932 g/g (Hathorne et al., 2013)). Thisyielded an average value of 0.01935 g/g S.D. = ± 0.00007 g/g (1σ)(RSD = 0.35%, n N 500).

Stable isotopes of oxygen and carbon from the same sample splitswere analyzed at the Bloomsbury Environmental Isotope Facility(BEIF) at the University College of London (UCL), UK, and the AnalyticalLaboratory for Paleoclimate Studies (ALPS) in the Jackson Schoolof Geosciences, University of Texas at Austin, USA. BEIF samples(12 ml exetainers, ~70–100 μg) were acidified by hand in a GasBench II Device using the methodology of Breitenbach andBernasconi (2011). The isotopic ratios of the resulting evolvedclean, dry CO2 were analyzed using a ThermoFisher DeltaPlus XPmass spectrometer. ALPS samples (~50–70 μg) were acidifiedunder vacuum at 70 ºC with 100% H3PO4 in a Kiel IV carbonate prepa-ration device and the resulting CO2 was analyzed using a ThermoFisherMAT253 mass spectrometer. Isotopic measurements were calibrated inboth labs using NBS19 and an internal marble standard (ESTREMOZ,where δ18O = −5.95‰; δ13C = 1.63, Ostermann and Goodkin, 2012).The average values for NBS19 and Estremoz in both labs were as pub-lished, as were the analytical errors for both labs and both standards(δ18O ±0.08‰ and δ13C ±0.04‰ [1σ, total both labs n N 1000]).

2.4. Agemodel development and calibration of paired Sr/Ca and δ18O to SST

Age-depth models for TN and BB were generated with the HadISSTusing the software Analyseries (Paillard et al., 1996). In the Sr/Carecords from TN and BB, a single winter trough (Sr/Ca maximum) andtwo summer peaks (Sr/Ca minima) were observed. Sr/Ca minima,maxima, and inflection points were aligned to the correspondingSST peaks to anchor the age model (Supplementary Fig. 2). For someyears, two Sr/Ca minima were observed over the summer months. Forthose months, Sr/Ca minima were assigned to the SST maxima inorder to optimize agreement with HadISST (DeLong et al., 2011). Inthe latter study, this was considered to result in a small reduction(b0.005 mmol/mol on average) in variability of the conversion and lin-ear interpolation to monthly intervals. If instead, the 2nd Sr/Ca peak isalways correlated to the 2nd SST peak regardless of maxima and mini-ma, there is a small increase in the RMSR from 1.09 to 1.10 °C in BBcoral and 1.06 to 1.13 °C in TN coral. Linear interpolations were madeat monthly intervals to match the resolution of the monthly HadISSTdata. The climatology of the Sr/Ca compared to HadISST shows that onaverage, the Sr/Ca maxima correspond to Jan, and the Sr/Ca minima toMay and June in the HadISST record respectively (Fig. 2). The subse-quent age-depth model was applied to both the Sr/Ca and δ18Odata. The combined X-ray and Sr/Ca age-depthmodel revealed annu-al bands ranging between 3.4 and 18.5 mm. Of those bands, only 5/51contained less than 8 samples per year. The average number of sam-ples per year for the BB and TN coral was 14.7 and 17.7 respectively.

As the uppermost part of the TN coral corewas not available, we cor-related the Sr/Ca in the BB core against the Sr/Ca (and therefore respec-tive δ18O) in the TN core to tie the two records together. By adjusting thestart year in TN, after several iterations,we found that the bestmatch forthe top of TNwas2004.We excluded the year 1981 in the TNwherema-terial was missing at a core break (Section TN2 to TN3), and other years(1992–1987) were excluded from analysis due to the angle of thecorallite being at 90° (i.e. the thecalwall was not visiblewhen examinedunder a microscope and under X-ray, Supplementary Fig. 1). However,where those years are missing in TN, all were available in the BB coral.Therefore, following statistical tests (Section 3.2), we use the compositecoral dataset to derive a calibration for the entire 33-year time interval(1977–2010).

a)

b)

c)

Fig. 2. Monthly climatology from global gridded data compared to composite coralgeochemical data, showing (a) composite Sr/Ca and HadISST (1977–2010), (b) δ18O andthe Global Precipitation Climatology Project (GPCP) precipitation (1979–2010) and(c) monthly (1994–2000) Pnet (precipitation minus evaporation) from Phan Rang stationand monthly GPCP (1979–2010). Gray shaded area and points above the dashedhorizontal line in (c) represent months where precipitation exceeds evaporation.Error bars on climatological data (gray bars) represent the mean standard deviation foreach month over the given time interval. Black error bars indicate the 1 sigma analyticalerror for each geochemical proxy. The gray filled rectangles represent summer andwintermonths as inferred from HadISST respectively, and the gray dotted rectangle representsthe months where precipitation exceeds evaporation (Pnet = SON).

236 A. Bolton et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 410 (2014) 233–243

2.5. Assessment of diagenesis and growth rate effects

Each X-ray was examined for signs of physical alteration as well asexamination of the individual Sr/Ca and δ18O plots. Annual growthrates for each coral were calculated using the distance from each year

(January to the following January) from the Sr/Ca age model and thecorresponding sampling depth. Growth rates from each coral werethen compared to the their respective annual Sr/Ca and δ18O record.

3. Results

3.1. Diagenesis

Close inspection of each X-ray did not reveal any physical evidenceof alteration such as dark high-density patches that would indicatethe presence of calcite (McGregor and Gagan, 2003). In addition,as we have 2 cores from the same location, the reproducibility of theSr/Ca and to some extent the δ18O can be evaluated, improvingconfidence in the overall reconstruction as such tracers usuallyhave a strong response to diagenesis (Müller et al., 2001; McGregorand Gagan, 2003; Corrège, 2006). The trace element and stable isotopedata do not show any abrupt and large magnitude excursionsthat would indicate the presence of secondary aragonite or calcite(McGregor and Gagan, 2003; Quinn and Taylor, 2006). Moreover,diagenesis is more likely to occur in vadose zone corals (McGregorand Gagan, 2003), or towards the oldest part of the coral colony(Nurhati et al., 2011), compared to the youngest material used inthis study.

3.2. Growth rate effects

The longest coral (TN) had the fastest growth rate (8.84 mm/yr−1

compared with 7.35 mm/yr−1 for the BB coral). We assessed therelationship between the annual average growth rate (GR) and boththe annual coral Sr/Ca and δ18O and found no significant correlationbetween either Sr/Ca or δ18O (TN Sr/Ca vs GR, r = 0.228, sig. (2-tailed)p = 0.347, n = 19; TN δ18O vs GR, r = −0.270, sig. (2-tailed) p =0.264, n = 19; BB Sr/Ca vs GR, r = 0.077, sig. (2-tailed) p = 0.675,n = 32; BB δ18O vs GR, r = −0.093, sig. (2-tailed) p = 0.614,n = 32).

3.3. Monthly calibration of Sr/Ca to SST and development ofcomposite records

Least squares linear regressions were used to quantify therelationship between the HadISST and skeletal Sr/Ca in both coralsand are summarized in Eqs. (1) and (2) and Table 1.

Sr=CaBB; 2010−1977ð Þ mmol=molð Þ¼ 10:63 �0:054ð Þ − 0:057 �0:002ð Þ � SST ∘Cð Þ

ðr2 ¼ 0:68; p b 0:0001; std error ¼ 0:06 mmol=mol;cov ¼ 3:793 � 10−6

; RMSR ¼ 1:1 ∘C; n ¼ 403Þ

ð1Þ

Sr=CaTN 2004−1977ð Þ mmol=molð Þ¼ 10:53 � 0:06ð Þ − 0:054 �0:002ð Þ � SST ∘Cð Þ

ðr2 ¼ 0:70; pb0:0001; std error ¼ 0:06 mmol=mol;cov ¼ 5:007 � 10−6

; RMSR ¼ 1:1 ∘C; n ¼ 273Þð2Þ

Inter-colony studies have demonstrated that monthly Sr/Ca ratiosbetween closely located corals of the same species can share statisticallysimilar Sr/Ca ratios (DeLong et al., 2007). Combining inter-colony datafrom the same location is useful as it removes issues related to missingor excluded sections, reduces the noisiness of the proxy records (wherefor example site-specific effects may bias single core reconstructions(Cahyarini et al., 2008)), reduces errors and improves confidence inthe overall reconstruction (Corrège, 2006), and also improves the corre-lation of the proxy record to SST (Cahyarini et al., 2009).

Table 1Least square linear regressions of Sr/Ca and δ18O against HadISST, and δ18Osw against precipitation (GPCP) for each coral (TN) and (BB) and their composites at varioustimescales respectively.

Proxy = m ∗ SST + b

m(slope)

1σ error(m)

b(y-intercept)

1σ error(b)

r2 p RMSR(°C)

stderr cov n

Monthly proxy data Sr/Ca (mmol/mol)BB −0.057 ±0.002 10.630 ±0.054 0.68 b0.0001 1.1 0.06 3.793 ∗ 10−6 403TN −0.054 ±0.002 10.532 ±0.062 0.70 b0.0001 1.1 0.06 5.007 ∗ 10−6 273Composite −0.055 ±0.002 10.573 ±0.430 0.75 b0.0001 0.9 0.05 2.462 ∗ 10−6 407

Monthly proxy data δ18O (per mil)BB −0.151 ±0.014 −1.331 ±0.375 0.24 b0.0001 2.8 0.43 1.836 ∗ 10−4 403TN −0.127 ±0.014 −1.816 ±0.392 0.24 b0.0001 2.1 0.35 2.025 ∗ 10−4 253Composite −0.142 ±0.011 −1.523 ±0.300 0.30 b0.0001 2.4 0.35 1.177 ∗ 10−4 407

Annual proxy data (all months)Composite Sr/Ca (mmol/mol) −0.031 ±0.015 9.905 ±0.413 0.12 0.05 1.1 0.31 2.23 ∗ 10−4 34Composite δ18O (per mil) −0.249 ±0.096 1.441 ±2.640 0.18 0.014 0.8 0.20 0.009 34

Annual proxy data (wet & dry season)Composite Sr/Ca (mmol/mol) −0.052 ±0.003 10.503 ±0.094 0.77 b0.0001 0.7 0.04 1.21 ∗ 10−5 68Composite δ18O (per mil) −0.206 ±0.024 0.158 ±0.625 0.52 b0.0001 1.3 0.28 0.001 68

3-year proxy data (wet & dry season)Composite Sr/Ca (mmol/mol) −0.051 ±0.004 10.472 ±0.097 0.90 b0.0001 0.5 0.02 1.296 ∗ 10−5 24Composite δ18O (per mil) −0.196 ±0.028 −0.106 ±0.759 0.69 b0.0001 0.9 0.19 0.001 24

Proxy = m ∗ precipitation + b

m(slope)

1σ error(m)

b(y-intercept)

1σ error(b)

r2 p RMSR(mm/yr)

stderr cov n

3-year proxy data (wet season only)Composite δ18Osw (per mil) −0.003 ±0.001 −1.008 ±0.305 0.54 0.01 30 0.11 1.147 ∗ 10−6 11

237A. Bolton et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 410 (2014) 233–243

As the BB and TN Sr/Ca data are significantly correlated (r = 0.7,n = 249, p b 0.01, 2-tailed), we compiled a composite record of Sr/Caand δ18O by averaging data from BB and TNwhere they overlapped andfilling in the gaps in either record (see Supplementary Fig. 2). The com-posite records were used to quantify the relationship between proxiesand HadISST using least squares linear regression (LSLR) (Table 1).The monthly composite Sr/Ca correlates strongly and significantly toHadISST while resulting in a decrease of the RMSR by 0.2 °C:

Sr=Cacomposite mmol=molð Þ ¼ 10:573 �0:043ð Þ− 0:055 �0:002ð Þ � SST ∘Cð Þðr2 ¼ 0:75; pb0:0001; std error ¼ 0:05 mmol=mol;

cov ¼ 2:462 � 10−6; RMSR ¼ 0:9 ∘C; n ¼ 407Þ

ð3Þ

where std error is the standard error on Sr/Ca predicted by theregression, RMSR (°C) is the root mean square of the residuals whenthe regression is inverted and used to calculate SST and cov is the co-variance error between the slope and intercept.

The composite Sr/Ca regression slope of −0.055 mmol/mol per °Csits within the range for slope values recorded in other Porites coralsin the SCS (e.g., −0.0424 to −0.06085 (Shen et al., 1996; Wei et al.,2000; Sun et al., 2005; Yu et al., 2005; Mitsuguchi et al., 2008)).

3.4. Relationship of δ18O to HadISST

Similar to the Sr/Ca ratios, the δ18O fromboth corals appear to recordclear annual cycles including a single winter trough and in some yearstwo summer maxima. As both Sr/Ca and δ18O analyses were measuredon the same sample splits, the same tie-points were used to calibrateagainst the HadISST data in Analyseries. The LSLR between the pairedSr/Ca and δ18O yield the following equations:

δ18OBB 2010−1977ð Þ ‰ð Þ ¼ −1:331 �0:328ð Þ – 0:151 �0:014ð Þ � SST ∘Cð Þðr2 ¼ 0:24; p b 0:0001; std error ¼ 0:43 ‰ð Þ; cov ¼ 1:836 � 10−4

;

RMSR ¼ 2:8 ∘C; n ¼ 403Þð4Þ

δ18OTN 2004 – 1977ð Þ ‰ð Þ ¼ −1:816 �0:392ð Þ − 0:127 �0:014ð Þ � SST ∘Cð Þr2 ¼ 0:24; pb0:0001; std error ¼ 0:35 ‰ð Þ; cov ¼ 2:025 � 10−4

; RMSR ¼ 2:1 ∘C; n ¼ 253� �

ð5Þδ18Ocomposite 2010−1977ð Þ ‰ð Þ ¼ −1:523 �0:3ð Þ− 0:142 �0:011ð Þ � SST ∘Cð Þðr2 ¼ 0:30; p b 0:0001; std error ¼ 0:35 ‰ð Þ; cov ¼ 1:177 � 10−4

;

RMSR ¼ 2:4 ∘C; n ¼ 407Þ:ð6Þ

3.5. Climatology of geochemical proxies

Fig. 2a shows that the mean monthly HadISSTs and compositeSr/Ca ratios are well correlated (r = −0.87, sig. (2-tailed) p b 0.001,n = 407), with the highest SSTs reached in May and the coldestSSTs in January. Mean monthly climatology (i.e., all Januarysaveraged from 1979 to 2010, all Februarys, etc.) for instrumental pre-cipitation data from the gridded GPCP dataset and coral δ18O agreestrongly (r = −0.441, sig. (2-tailed) p b 0.0001, n = 383), thoughshowing a slight difference in the timing of onset of the wet season(Fig. 2b). A meteorological station located nearby at Phan Rang (PR)was used to distinguish wet and dry seasons. The station data showthat net precipitation (i.e., Pnet = Precipitation− Evaporation) monthswhere Pnet is positive are in agreement with the wettest months in NhaTrang (wet = SON; dry = JFM), (Fig. 2c). Sea surface salinity (SSS), asinferred from SODA version 2.1.6, 1977–2008 (Carton and Giese,2008), and GPCP are negatively correlated (r = −0.628, sig. (2-tailed)p = 0.01, n = 360), which suggests that variations in SSS are mainlycontrolled by freshwater (precipitation) input, similar to variationsaround Hainan Island in the northern South China Sea but withoutany lag (Deng and Wei, 2014).

3.6. Interannual relationships of Sr/Ca to SST during wet and dry seasons

The slopes and intercepts of monthly proxy versus SST relationshipscan be heavily influenced by the extremes of the seasonal cycle and thuspotentially misleading (Quinn and Sampson, 2002; Goodkin et al.,

SS

T (

°C)Reconstructed SST (wet)

HadISST (dry)

b) Annual SST vs. Sr/Ca(SST)

SS

T (

°C)

c) 3-yr SST vs. Sr/Ca(SST)

WetDry

-9.3

-9.2

-9.1

-9.0

-8.9

24 25 26 27 28 29 30

SST (°C)

r = 0.77, p<0.0001

Sr/

Ca

(mm

ol/m

ol)

a) Sr/Ca vs. SST

wet

dry

Reconstructed SST (dry)

30

28

26

24

22

Sr/Ca (mmol/mol) = 10.503 - 0.052*SST (°C)

HadISST (wet)

RMSR = 0.7°C

RMSR = 0.58 °C

RMSR = 0.81°C

RMSR = 0.39°C

RMSR = 0.45°C

238 A. Bolton et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 410 (2014) 233–243

2005). Therefore, we investigated interannual relationships to evaluatethe robustness of the proxy relationships.

Themonsoon systemexerts an important influence on climate in theSCS, controlling a large amount of interannual variability. To investigatevariability due to the monsoon, the proxy data were separated intomean annual dry (JFM) and wet (SON) seasons based on the monthlyclimatology (Fig. 2). The subsequent data were used to calculate a3-year averaged dataset by binning rather than a moving average.The data show that 1-year and 3-year averaged Sr/Ca (wet and dryseasons only) are statistically and significantly inversely related toHadISST (Eqs. (7) & (8)) (Fig. 3):

Sr=Caannual wet&dry mmol=molð Þ ¼ 10:503 �0:094ð Þ − 0:052 �0:003ð Þ � SST ∘Cð Þðr2 ¼ 0:77; p b 0:0001; std error ¼ 0:039 mmol=mol; cov ¼ 1:21 � 10−5

;

RMSR ¼ 0:7 ∘C; n ¼ 68 Þð7Þ

Sr=Ca3‐year wet&dry mmol=molð Þ ¼ 10:472 �0:097ð Þ − 0:051 �0:004ð Þ � SST ∘Cð Þðr2 ¼ 0:90; pb0:0001; std error ¼ 0:020 mmol=mol; cov ¼ 1:296 � 10−5

;

RMSR ¼ 0:4 ∘C; n ¼ 24Þ:ð8Þ

SST was calculated from Sr/Ca by inverting the regressions inEqs. (2) and (3) to reconstruct wet and dry season SSTs separately,at 1 and 3-year averaged time scales (Fig. 3b and c). Examination ofthe 1 and 3-year average SST reconstructions indicates that the wetseason reflects SST more accurately than the dry season (e.g. RMSRannual wet = 0.58 °C; annual dry = 0.81 °C; 3-year wet = 0.39 °C;3-year dry = 0.45 °C).

3.7. Verification exercise

In order to investigate the fidelity of the Sr/Ca-SST proxy, a quan-titative evaluation was performed by undertaking a verificationprocess (e.g. Fritts et al., 1979; Crowley et al., 1999; Quinn andSampson, 2002). We define the “calibration” interval as the compositeSr/Ca–HadISST overlap for the period 1977–2010. We use thecalibration derived for the wet and dry seasons, (Eq. (7)) to convertthe Sr/Ca data into SST that extends beyond the calibration periodi.e. 1976–1945. The predicted SST is then compared to the early SSTdataset from HadISST for the same period. The RMSR between thepredicted (calibration) and observed (verification) shows an increasefrom 0.7 to 0.9 °C during the wet season and from 0.9 to 1.1 °C duringthe dry season (Fig. 4).

3.8. Estimation of precipitation using the δ18O record

The LSLR between monthly HadISST and δ18O is significant butthe skill in prediction is considerably reduced from Sr/Ca (RMSRSr/Ca = 0.9 °C compared to δ18O = 2.4 °C) (Eq. (4)) (Table 1). Ourcomposite slope of −1.142‰/°C lies close to the lower range ofslopes reported from corals within the SCS (0.174 to −1.137‰/°C)(Shen et al., 1996; He et al., 2002; Shen et al., 2005a; Yu et al., 2005;Su et al., 2006). Our slope is also lower than previously published slopesfrom coral records outside the SCS (0.18 to −0.24‰/°C) (Epsteinet al., 1953; Weber and Woodhead, 1972; Fairbanks and Dodge,1979; McConnaughey, 1989; Shen et al., 1992; Wellington et al.,1996), highlighting important regional differences.

Annual and 3-year averaged correlations of δ18O to HadISST improvethe RMSR of the predicted SST, but still do not achieve the sameprecision in SST reconstructions compared to Sr/Ca (Table 1). Coral δ18O

Fig. 3. (a) Regression of average Sr/Ca and HadISST during the dry (JFM) and wet (SON)seasons for the years 1977–2010, (b) reconstruction of average wet and dry seasonSST from Sr/Ca (solid lines) plotted with HadISST (dashed lines), (c) reconstruction of3-year averagewet and dry season SST from Sr/Ca compared toHadISST (solid anddashedlines as above). RMSR represents the root mean squared residuals of SST (°C).

Observed SSTPredicted SST

ΔS

ST

(°C)

a)

b)

RMSR = 0.7°C RMSR = 0.9°C

RMSR = 0.9°C RMSR = 1.1°C

ΔS

ST

(°C)

WET SEASON

DRY SEASON

SS

T (

°C)

SS

T (

°C)

Fig. 4. Annual observed versus predicted SST for wet and dry season, at Nha Trang, Vietnam. The observed SST record (solid line) is HadISST for the period 1977–1930 and the predictedSST record (dashed line) was derived using the composite annual (wet/dry) Sr/Ca–HadISST relationship for the period 1977–2010 (Eq. (3)). The bar graph underneath the SST values rep-resents the anomaly ΔSST (°C) between the predicted and the observed SST values.

239A. Bolton et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 410 (2014) 233–243

is influenced both by SST and δ18Osw, with δ18Osw reflecting regional andtemporal changes in the hydrological budget. Our record indicates thatSST has a relatively weak relationship in coral δ18O (Table 1). Rainfall isdepleted in 18O relative to seawater, whereas evaporation tends to enrichthe surface ocean in 18O (Epstein and Mayeda, 1953; Friedman et al.,1961; Redfield and Friedman, 1965). High SST and high precipitation

GPCP (mm, 3-year average)

δ18 O

sw (

‰)

R2= 0.54, p= 0.01δ18Osw = 1.008 - 0.004*GPCP

RMSR = 30mm

Fig. 5. Regression of coral δ18O for the years 1977 to 2010 against 3-year averagedδ18Osw from corals versus GPCP precipitation data (wet season only). RMSR represents3-year reconstructed precipitation residuals in mm (1978–2010).

result in more negative seawater, however changes in δ18O in somelocations may partially cancel one another (Cahyarini et al., 2008).Therefore, where δ18Osw and SST are not in phase, this could result insmoothing of proxy signals over annual cycles. Isolation of only themonthswhere isotopically light 16O is expected to increase fromprecip-itation input should therefore be coeval with a decrease in seawaterδ18Osw (i.e., during the SE Asian wet season).

Seawater δ18O measurements by Shen et al. (2005a) showed thatthe monsoon system in the SCS has a demonstrable effect on theisotopic composition of seawater, causing significant changes betweenthe wet and dry seasons. Shen et al. (2005a) calculated the δ18Osw, orresidual δ18O (Δδ18O), by using Sr/Ca to quantify and remove the SSTinfluence on δ18O, and were able to compare their calculated values tomeasured δ18Osw with reasonable agreement.

Here we infer δ18Osw by first regressing coral δ18O against Sr/Cato quantify the SST component within the coral δ18O (Eq. (9)). Wethen calculate the δ18Osw as the anomaly between the measured andSr/Ca-predicted coral δ18O (Eq. (10)).

δ18O3‐yr wet&dry ¼ 3:832 �0:473ð Þ � Sr=Ca3‐yr wet&dry– 40:275 �4:307ð Þr2 ¼ 0:75; p ¼ b0:0001; std error ¼ 0:038 ‰; cov ¼ 0:223; RMSR ¼ 0:17‰; n ¼ 10

� �

ð9Þ

Specifically, Eq. (9) is inverted to calculate the residual Δδ18O, orδ18Osw, by subtracting the Sr/Ca-calculated δ18O (i.e., removal of theSST component) from the coral δ18O (Eq. (10)).

δ18Osw;3‐yr wet&dry ¼ δ18Ocoral; 3‐yr wet&dry− 3:832 � Sr=Ca;3‐yr wet&dry

þ 40:275 ð10ÞThe δ18Osw is then regressed versus local precipitation for wet and

dry seasons. As expected, the 3-year averaged δ18Osw is not strongly

240 A. Bolton et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 410 (2014) 233–243

correlated to precipitation during the dry season. However, during thewet season 3-year averaged δ18Osw shows a significant correlation toprecipitation (Eq. (11), Fig. 5):

δ18Osw 3‐yr wet mmol=molð Þ ¼ −1:008 �0:305ð Þ – 0:0035 �0:001ð Þ�precipitation mm=yrð Þ

ðr2 ¼ 0:54; p ¼ 0:01; std error ¼ 0:11 ‰; cov ¼ 1:147 � 10−6;

RMSR ¼ 30 mm=yr; n ¼ 11Þ:

ð11Þ

Precipitation time series from the GPCP and reconstructed fromcorals show very similar patterns (Fig. 6). The Pearson's correlationcoefficient between GPCP and reconstructed precipitation is r = 0.737,p = 0.01 (2-tailed). The precipitation reconstruction shows an overallincreasing trend towards the present, with the highest values, above300 mm per year, after 2004. Predicted precipitation shows a largedeviation from measured GPCP data for the point from 1999 to

Pre

cipi

tatio

n (m

m/3

yea

r av

erag

e)

a)

b)

c)

SS

S (

SO

DA

)

1978

-198

0

1981

-198

3

1984

-198

6

1987

-198

9

1990

-199

2

1993

-199

5

1996

-199

8

1999

-200

1

2002

-200

4

2005

-200

7

2008

-201

0

Measured Precipitation (GPCP)Coral Reconstructed Precipitation

EN

SO

/IOD

(°C) anom

olies (3-year average)

RMSR = 30 mm

Fig. 6. Reconstruction of a 3-year average precipitation from coral δ18O plotted with(a) precipitation data from GPCP, (b) 3-year average ENSO (gray) and IOD (black), and(c) sea surface salinity (SSS) from SODA. Gray horizontal bar represents largest deviationin the reconstructed precipitation data from the GPCP data, which is coeval with thestrongest negative ENSO (La Niña) anomaly and lowest SSS value over this time interval.RMSR represents 3-year reconstructed precipitation residuals in mm (1978–2010).ENSO data in (b) was obtained from NOAA (see http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_change.shtml) and IOD data was fromJAMSTEC (see http://www.jamstec.go.jp/frcgc/research/d1/iod/e/index.html).

2001, significantly underestimating observed values. This deviationalso coincides with a decrease in sea surface salinity (Fig. 6c).Interestingly, when compared against ENSO (Niño 3.4 SST) and IODindices, this anomalous period of enriched δ18Osw from the coral re-cord (low calculated precipitation) appears to be coeval with the ex-tremely cold and prolonged La Niña years from 1998 to 2001 (Fig. 6b).This suggests that water with enriched δ18Osw resulting from cold, dryLa Niña conditions may have been advected over the coral site duringthose years.

4. Discussion

4.1. Sr/Ca and δ18O as paleotemperature proxies

Both Sr/Ca and δ18O proxies are significantly correlated to HadISSTon monthly timescales, as well as for separate wet and dry seasons atannual and 3-year interannual timescales. However, the relationshipof δ18O to SST was consistently lower in significance compared toSr/Ca for all time series, with the RMSR increasing by 170% higher.This discrepancy likely results from the influence of precipitation onδ18O causing the δ18O to be out of phase with temperature seasonally(Fig. 2).

When examining the individual coral records on an annual basis(i.e. wet/dry seasons only), the two independent coral regressionsshare interesting features. First of all, the annual wet/dry Sr/Ca toHadISST relationships are statistically within error with BB and TNhaving similar slopes of −0.057 (±0.004) and −0.052 (±0.005)respectively. The comparison of δ18O to HadISST for individual coralsis less useful because SST is not strongly influencing the δ18O. This isseen clearly in the seasonal reconstructions where the Sr/Ca minimaand maxima are not always in phase with the δ18O (Supp. Fig. 2). Thissuggests that the δ18O record is more sensitive to another (external)influence, as discussed in Section 4.2.

Differences between the HadISST dataset and the coral proxy re-cords must be considered when evaluating errors in SST reconstruc-tions. HadISST represents a larger integrated area of the surface oceanthan the corals, which are calcifying at one location (Jones et al., 1997,2001; Rayner et al., 2003; Goodkin et al., 2005). The spatially more ex-tensive HadISST dataset may smooth temperature anomalies, whereasmore variable SSTs are likely to be recorded by the corals at a singlepoint. Other potential influences on the coral records include upwelling,where changes in Sr or Ca concentrations in seawatermay occur (Culkinand Cox, 1966; Bernstein et al., 1987; de Villiers, 1999; Shen et al.,2005b). In some oceanic regions including the SCS, anomalies in coralSr/Ca and δ18O have been attributed to upwelling events and/or riv-erine input (de Villiers et al., 1994; Bogdanov and Moroz, 1995;Shen et al., 2005b, 1996). However, the strength of the Sr/Ca–SST re-lationship indicates little to no influence here. Strong upwellingoccurs in the coastal regions of southern Vietnam during May toSeptember (Vo and La, 1997); however, our precipitation recon-struction focuses only on the wet season outside of this upwelling(SON). The nearest river, the Cai, supplies maximum freshwaterand suspended load during the northeastern (SON) monsoon andflows along the eastern edge of the peninsula towards the southernpart of the bay (Ilyash and Matorin, 2007). Given the distance andthe ocean currents, it is unlikely that the river has an influence onseawater at the coral site.

4.2. Relationship of δ18Osw to precipitation

Coral δ18Osw studies in the tropical Pacific are commonly associatedwith changes to δ18O of seawater from advection (Cahyarini et al., 2008;Nurhati, 2011). Reconstructions of δ18Osw focus on seasonal changesand assume a stationary relationship between δ18O and SST thusallowing the removal of the temperature effect. In the SCS, recentwork has shown that monsoon precipitation has a major influence on

241A. Bolton et al. / Palaeogeography, Palaeoclimatology, Palaeoecology 410 (2014) 233–243

temporal changes of δ18Osw (McCulloch et al., 1994; Wei et al., 2000;Shen et al., 2005a; Yu et al., 2005; Su et al., 2006), with δ18Osw used asa proxy to identify changes in the timing of the onset of the monsoon(Deng et al., 2009). In corals from Hon Tre Island, we show that on aninterannual basis, calculated δ18Osw are also strongly influenced bymonsoon precipitation. This only becomes apparent when the timingof precipitation maxima (i.e., the wet season) is specifically targetedat inter-annual timescales. This suggests that in certain months, dueto high increasing rainfall, the δ18Osw can change sufficiently to be de-tected within a coral record. The 3-point binning of the time series ap-pears to suppress some of the higher frequency noise that is apparentat seasonal and annual timescales.

Using the 3-year binned averages of δ18Osw, the correlation withGPCP is statistically significant (Table 1) and indicates the potential toreconstruct hydrological variability at this location over the completelength of the TN coral, which is approximately 450 years. The precipita-tion reconstructions, although unable to accurately predict at 1-yeartimescales, show reasonably good skill at inter-annual timescales, partic-ularly considering the errors associated with precipitation reconstruc-tions from instrumental data and coupled model simulations (Smithet al., 2012; Ren et al., 2013). As one of the main foci of any potentialcoral paleorecord is to reliably reconstruct longer time series (Crowleyet al., 1999), this relationship offers the potential to generate insightinto century long changes in precipitation in a region where changes todistribution and timing of rainfall would have a significant impact formillions of people.

The small misfit in the precipitation reconstruction may be ex-plained by changes in ENSO and subsequent SSS anomalies over thearea that may be linked to changes to the moisture source of precipita-tion. The years 1999–2001 show unusually low salinity (32.25) andwere coeval with 2.5 consecutive years of La Niña conditions. Shenet al. (2005a), in a Taiwan coral study, also noted unusually light seawa-ter Δδ18O in 1991, which they attributed to intrusions of abnormallylow salinity seawater from offshore. In other records from the SCS,both the EAWM and EASM show interannual and interdecadal vari-ability suggesting a weakening ENSO–EAWM relationship since themid-1970s (Wang and He, 2012). However, other coral recordshave shown poor correlation between SCS coral δ18O and NINO3.4SST, compared to corals in the tropical Pacific (Deng and Wei,2014). Given that the wet season occurs just before the peak of thewinter monsoon, when seawater is moving towards the southwest,advection of more isotopically depleted seawater could be responsiblefor the discrepant years between reconstructed and measured precipi-tation. However, the δ18O in precipitation is generally more negativethan seawater, and in tropical areas is weakly affected by temperature(Gat, 1996; Araguas-Araguas et al., 1998), with moisture sources andcirculation patterns thought to be the main control of isotopicsignatures over the region (Aggarwal et al., 2004). Changes in therelationship between coral δ18Osw and precipitation may be reflectingthe dominance of the moisture sources over inter-annual timescalesduring the wet season. Therefore, determination of δ18O meteoric wa-ters would be extremely beneficial to improve our understanding ofthe contribution of δ18O precipitation values into wet season seawater.For example, limitedmeasurements of rainfall from 2 stations in Son La,Vietnam, over July to October in 2002, reveal δ18O values that rangefrom−4.14 to−12.25‰ (Nguyen, 2007). This variable fractionationmay also explain some of the regression error for the calibration ofδ18Osw to precipitation.

5. Conclusion

Coral geochemical proxy calibrations from two Porites lutea coralswere performed to investigate the potential to reconstruct long-termchanges in SST and precipitation in the SCS. Geochemical and climatedata over the last 33 years show that Sr/Ca ratios are an excellentSST proxy, with a RMSR as small as ±0.39 °C for 3-year averaged

reconstructions. This suggests that, although the SCS is a regionwith rel-atively low SST variability on these inter-annual time-scales, coral Sr/Cais able to capture this variability reliably. In addition, δ18Osw in the wetseason calculated from coral δ18O and Sr/Ca values directly reflects var-iability in local precipitation on 3-year averaged timescales. In limitedinstances, deviations in the predicted δ18Oswmay be related to extremeENSO events, although there could be other influences that we have notquantified. Overall, the agreement between coral-based and instrumen-tal precipitation is strong (r2 = 0.54, p = 0.01), indicating that inregions absent of seawater advection processes, coral δ18Osw can beused to evaluate precipitation changes directly.

This calibration study demonstrates the potential for further analysisof the remaining coral skeleton to provide robust records of past SST andprecipitation in the southern SCS over the past 450 years. Such recordswill allow us to investigate the association of inter-decadal trends inSST, precipitation and SSS and improve our understanding of long-term climate variability within this dynamic Asian monsoon system.To confirm the association of the inter-decadal trends of coral δ18Owith the Asian monsoon climate, it is necessary to further analyzethe primary sources responsible for the seawater compositionchanges and to investigate other coral records that are influencedby the monsoon regime. Coral in regions of high seasonal precipitationwould benefit enormously from combined measurements of δ18O inprecipitation and seawater.

Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.palaeo.2014.05.047.

Acknowledgments

The authors would like to thank G. Williams and W. Tak-Cheung(University of Hong Kong) and J. Ossolinski (Woods Hole Oceanograph-ic Institution) for their help collecting specimens in the field. We alsothank B. M. Son (Department of Natural Resources and Environmentof Khanh Hoa province, Vietnam), L. T. Luong (Centre for Hydro-Meteorology of South Central Vietnam), H. T. Tung (Division of Remotesensing and GIS, Vietnam Institute of Meteorology, Hydrology andEnvironment) and Q-T Do (World Bank) for their kind assistance andprovision of the meteorological datasets. The GPCP data used in thisstudy was acquired using the GES-DISC Interactive Online VisualizationANd aNalysis Infrastructure (Giovanni) as part of the NASA's GoddardEarth Sciences (GES) Data and Information Services Center (DISC). Wewish to thank G. J. Huffman (NASA/GSFC, USA) for his useful discussionsand suggestions regarding various precipitation datasets.We thank K. C.Cheung (University of Hong Kong) and V. Lee (Nanyang TechnologicalUniversity) for their assistance in micro-drilling the coral precipationmodels. and also the Centre for Climate Research Singapore for theiruseful discussions onregarding precipitation models. This researchwas financially supported by the National Research FoundationSingapore under its Singapore NRF Fellowship scheme awarded toN. Goodkin (National Research Fellow Award No. NRFF-2012-03) andadministered by Earth Observatory of Singapore, the National ResearchFoundation Singapore and the Singapore Ministry of Education underthe Research Centers of Excellence initiative, the General ResearchFund of HK awarded to N. Goodkin (GRF-HKU702509P) and RinehartAccess to the Sea grant from WHOI (Grant #27500040) awarded toK. Hughen. The stable oxygen isotope analyses from this study werekindly funded by Nu Instruments Ltd.

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