Centennial-Millennial Climate Variability in the Makassar ...202 Marfasran Hendrizan et al. 3. METHODS 3.1. Age model AMS 14C records of Core SO217-18517 used in this study are obtained

International Journal of Oceans and Oceanography

ISSN 0973-2667 Volume 14, Number 2 (2020), pp. 197-220

© Research India Publications

https://dx.doi.org/

Centennial-Millennial Climate Variability in the

Makassar Strait during Early Holocene until the End

of the Last Deglaciation

Marfasran Hendrizan1,3*, Nining S. Ningsih2, Sri Y. Cahyarini3, Mutiara R.

Putri2, Bambang Setiadi4, Iwan P. Anwar1,2, Dwi A. Utami3, Vera C. Agusta3

1 Earth Sciences Study Program, Faculty of Earth Sciences and Technology,

Bandung Institute of Technology, Labtek XI, Jl. Ganeca No. 10, Bandung 40132, Indonesia.

E-mail: m_hendrizan@yahoo,com (MH); [email protected] (IPA)

2 Research Group of Oceanography, Faculty of Earth Sciences and Technology,

Bandung Institute of Technology, Labtek XI, Jl. Ganeca No.10, Bandung 40132,Indonesia.

E-mail:[email protected] (NSN), [email protected] (MRP)

3Paleoclimate and Paleoenvironment Research Group, Research Center for Geotechnology,

Indonesian Institute of Sciences, Jl. Sangkuriang Bandung 40135, Indonesia.

E-mail:[email protected] (SYC), [email protected] (DAU),

[email protected] (VCA)

4Geoinformatics and Computations Research Group, Research Center for Geotechnology,

Indonesian Institute of Sciences, Jl. Sangkuriang Bandung 40135, Indonesia.

E-mail: [email protected]

*Correspondence: [email protected]

Abstract

Indonesian archipelago establishes an essential region for considering

relationships between climate and human activities in the region. However;

large uncertainties remain in understanding Indonesian hydroclimate under

varying timescales. Here we present reanalyzed data of high-resolution proxy

from high sedimentation rate (120-170 cm/kyrs) marine sediment core SO217-

18517 from 9 to 14 kyrs in the offshore Mahakam Delta. Our dataset reveals

high-frequency variations at centennial and millennial time scales during the

period between 9 and 14 kyrs based on multi-proxies data (δ18Osw; Sea Surface

Temperature/SST; and δ18O). Early Holocene to the end of last deglaciation

period in the Makassar Strait was characterized by mixture forcing between

mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]

198 Marfasran Hendrizan et al.

deep ocean and solar radiation with ~1100 and ~1000-years periodicity in

altering millennial-scale variability on δ18Osw and δ18O records. On centennial

timescale; the Makassar Strait climate variability was dominated by ~500-years

periodicity recorded for Sea Surface Temperature (SST) at our core site location

which is more influenced by deep ocean circulation.

Keywords: Centennial; Millennial; Mixture Forcing; Deep Ocean, Solar

Radiation; Makassar Strait

1. INTRODUCTION

Climate variability in the Indonesian archipelago may have played a confidence role on

the intensity of rainfall patterns and tropical convections in the highly populated region

related to global warming impact in the future. Precipitation patterns in the Indonesian

archipelago are strongly governed by island topography and/or ocean-atmosphere

interactions. The phase five of Coupled Model Intercomparison Project (CMIP5)

climate model predicts Southern Hemisphere monsoon including Indonesia will get less

precipitation in the future (Lee & Wang, 2014). However, large uncertainties remain in

understanding Indonesian hydroclimate under different timescales in the past.

Therefore, it is crucial to study hydrologic variability in the Indonesian archipelago and

dynamic process on a wide range spatial and temporal timescales.

Holocene climate archived have been identified centennial to millennial-scale in

tropical region (Khider et al., 2014). It is also challenging to look further those

centennial to millennial-scale climate into the last deglacial period in the tropical

region. Examples of millennial-scale variability such as the Heinrich Stadial 1 (HS1),

Bølling-Allerød (B-A) and the Younger Dryas (YD) exist in the Indonesian region

which is associated with precipitation changes in the region (Hendrizan et al., 2017;

Kuhnt et al., 2015). However, centennial to millennial-scale variability of Indonesian

hydroclimate since the last deglaciation until the early Holocene might be controlled by

more than single forcing on tropical rain belt changes (Hendrizan et al., 2017).

Southward swings of the Intertropical Convergence Zone (ITCZ) (Hendrizan et al.,

2017; Kuhnt et al., 2015; Muller et al., 2008), El Niño Southern Oscillation (ENSO)

changes (Levi et al., 2007; Stott et al., 2004), and sea level (Griffiths et al., 2009; Partin

et al., 2007) are likely mechanisms in controlling precipitation changes at Indonesian

region. The questions will be appeared, do centennial to millennial-scale climate

variability occur in the Indonesian region during the last deglaciation and the Holocene?

What is the main forcing on precipitation changes in the Indonesian region? we will

extend the strength of the Atlantic Meridional Overturning Circulation (AMOC)

proposed by previous study (Khider et al., 2014) which may influence the

ocean/atmosphere system on centennial-millennial timescales in the Indonesian region.

Centennial-Millennial Climate Variability in the Makassar Strait… 199

In addition, solar forcing is also identified in the Holocene period as an external forcing

(Bond et al., 2001; Debret et al., 2009). However, recent study mentions Holocene

centennial to millennial-scale variability might be controlled by deep water circulation

in the western Pacific region (Khider et al., 2014) or ocean-ice sheet interaction (Bakker

et al., 2017) as an internal forcing. Both external and internal forcing could trigger heat

transfer in the Indonesian region which can be traced in the longer period until the last

deglacial period in the region. Several marine sediment cores in the Indonesian region

record a long temporal resolution until the last deglaciation in understanding the

influence of Sea Surface Temperature (SST) with regional climate in the region

(Mohtadi et al., 2011, 2017; Schroder et al., 2016; Schröder et al., 2018; Visser et al.,

2003). Core SO217-18517 (Hendrizan et al., 2017) is more challenging to be reanalyzed

due to the influence of river runoff and the ITF intensity in the core site. In addition,

the core provides the highest resolution timescales until < 7 years during the last

deglacial period. δ18Osw records in the Makassar Strait (Fan et al., 2013) interpreted

millennial-scale variability during Holocene controlled by ENSO variability. Other

revealed deep sea circulation is the main forcing of millennial-scale variability in the

West Pacific Warm Pool (WPWP) during Holocene (Khider et al., 2014). Different

forcing on millennial-scale variability in the WPWP especially central Indonesia is still

open question related to complex influences of δ18Osw in the central Indonesia

(Schröder et al., 2018). One of the most important is local river input which local river

input is known to be an important factor in controlling δ18Osw – salinity variability in

the WPWP (Katz et al., 2010; Morimoto et al., 2002). Therefore, Core SO217-18517

closes to the Mahakam River is suitable to understand high resolution climate signal in

the Makassar Strait.

Here we present high-resolution proxy data from high sedimentation rate (120-170

cm/kyr) marine sediment core SO217-18517 from 9 to 14 kyr in the offshore Mahakam

Delta ((Hendrizan et al., 2017); Figure 1). The previous study (6) in Core SO217-18517

has not explained whether similar or not the Younger Dryas climate mechanisms in the

Makassar Strait with the early Holocene period. Previously, uneven time series of Core

SO217-18517 based on multi-proxies analysis was reported in (Hendrizan et al., 2017).

In this study we have improved the evenness of the time series to 10 years/sample

resolution, and concentrated on the time period 9 to 14 kyr. We present multi-proxies

(δ18O, SST, δ18Osw) wavelet analysis of Core SO217-18517 to characterize centennial

and millennial climate variability spanning from early Holocene and the end of the last

deglaciation in the Makassar Strait. We compare our multi-proxies data with other

hydroclimate records in the central Indonesia particularly Kalimantan and Sulawesi

region.


Figure 1. a. Location of core SO217-18517 (1°32.198’S, 117°33.756’E; 698 m water

depth), off Mahakam Delta, East Borneo (modificafion Figure from Supp. Figure 1 in

(Hendrizan et al., 2017)). Red stars indicates core locations from other studies, marine

sediment cores SO217-18519 and TGS-931 (Schröder et al., 2018), SO217-18515

(Schroder et al., 2016), Lake sediment from Towuti (Konecky et al., 2016), and Gunung

Buda speleothem (Partin et al., 2007) in a bathymetric map from ETOPO 1

(http://maps.ngdc.gov/viewer/bathimetry); b. Marine sediment photograph of Core

SO217-18517 in-depth scale.

2. REGIONAL CLIMATE AND OCEANOGRAPHY

Marine sediment core SO217-18517 (1°32.198’S, 117°33.756’E; 698 m water depth)

is situated in the offshore Mahakam Delta, East Borneo (Hendrizan et al., 2017) which

extends for about ~90 km from the coastal line (Figure 1). The core was collected as a

part of the SO217 (Makassar-Java/MAJA) cruise using R/V Sonne. The core site is

connected to the southeast distributary channel of the Mahakam River. However, the

core site is not only influenced by Mahakam river runoff but also controlled by lower

thermocline Indonesian Throughflow (ITF) ((Hendrizan et al., 2017); Figure 1). During

boreal summer, the changes in wind direction shift towards Asia due as the Intertropical

Convergence Zone (ITCZ) moves northward, leading to reduced precipitation in

eastern Borneo, and increased SST follows the peak sun radiation (Figure 2). Saline

http://maps.ngdc.gov/viewer/bathimetry


surface water during boreal summer indicates a reduced freshwater input related to the

monsoonal wind shift ((Gordon, 2005); Figure 2). During boreal winter, wind direction

moves along the Indonesian archipelago, dipping into northern Australia. Both

increased precipitation in the eastern Borneo and decreased the SST also cause a

reduced salinity in the Makassar Strait (Figure 2). The core site is situated in the

Makassar Strait which is the inflow pathways of the ITF (Hendrizan et al., 2017).

Recent study found the ITF changes during decadal time scales, the ITF strengthened

when the Pacific Decadal Oscillation (PDO) positive and weakened when the PDO

negative (Sprintall et al., 2019).

Figure 2. Monthly climatology in the offshore Mahakam river (a) average salinity

(World Ocean Atlas 2009), (b) average SST (World Ocean Atlas 2013) (Locarnini et

al., 2013), (d) average wind velocities (NCEP reanalysis data at

http://www.esrl.noaa.gov/psd/), (d) CMAP Estimated precipitation from NOAA NCEP

CPC Merged Analysis over the 1979-2011 period (Xie & Arkin, 1997).

http://www.esrl.noaa.gov/psd/


3. METHODS

3.1. Age model

AMS 14C records of Core SO217-18517 used in this study are obtained by the previous

study in the similar core (Hendrizan et al., 2017). Summary of previous study

(Hendrizan et al., 2017), approximately 6 mg of well-preserved pteropod shells were

picked from the >355 µm size fractions and mixed planktonic foraminifera were picked

from the size fractions 250-315 µm for accelerator mass spectrometry (AMS) 14C

dating. AMS14C analysis was performed at the Leibniz Laboratory, Christian-

Albrechts-University, Kiel. The age model was constrained by 8 AMS 14C dates based

on planktonic foraminifers and pteropods. An interpolated curve was fitted through the

8 AMS 14C tie points using a Stineman function (smooth function in Kaleidagraph).

3.2. Data

We used reanalysis data of Mg/Ca derived SST, δ18O, and δ18Osw from core SO217-

18517 that was published in (Hendrizan et al., 2017). In addition, a detailed explanation

of the analytical technique for Mg/Ca and δ18O is shown in (Hendrizan et al., 2017) and

summarized below. For δ18O analysis, approximately 10 tests of G. ruber were picked

from the size fraction 315-250 µm at 2 cm interval from 14 to 9 ka. δ18O was measured

with a Finnigan MAT 253 mass spectrometer (Carbo-Kiel Device (Type IV) for

automated CO2 preparation from carbonate samples for stable isotopic analysis) at the

Leibniz Laboratory, Christian-Albrechts-University, Kiel. For Mg/Ca measurement,

thirty well-preserved tests of G. ruber were selected from the size fraction 315-250 µm.

The samples were measured using a radial viewing simultaneous ICP-OES (Spectro

Ciros SOP CCD, Spectro Analytical Instruments, Germany) at the Institute of

Geosciences, Christian-Albrechts-University Kiel. Foraminifera Mg/Ca were

converted into temperature equation (Anand et al., 2003).

Mg/Ca=0.38 exp 0.09 T for Globigerinoides ruber

δ18Osw reconstruction was calculated based on paired Mg/Ca and δ18O measurements

of G. ruber using equation (Bemis et al., 1998).

δ18Osw = 0.27 + (T (°C) – 16.5 + 4.8 × δ18O (V – PDB))/4.8

δ18Osw Core SO217-18517 indicates paleosalinity indicator in the Makassar Strait,

which is assumed similar with relationship between δ18Osw-salinity in the Western

Pacific Warm Pool (Morimoto et al., 2002).


A length of “uneven dataset” (~5000 years), original dataset obtained from geochemical

measurements with different time spacing (δt), between 9 and 14 kyrs is prepared to

analyze further for wavelet analysis. Before wavelet analysis applied, unevenly dataset

at Core SO217-18517 from previous study (Hendrizan et al., 2017) should be

interpolated to acquire equal time spacing (δt) in the entire timeseries between 9 and 14

kyrs for reanalysis data in this paper. Interpolated data with equal time spacing (δt) of

10 years in this study will be identified as “evenly dataset”. We applied linear

interpolation in this study by (Lepot et al., 2017; Mathworks, 2019). Linear

interpolation of our dataset will obtain a straight line passed through the end point χa

and χb of original dataset including SST, δ18O, and δ18Osw (Hendrizan et al., 2017).

Equivalent equation for the method shown below

𝑋𝑖 =𝜒𝑎 − 𝜒𝑏

𝑎 − 𝑏(𝑖 − 𝑏) + 𝜒𝑏

Interpolated data are bound between xA and xB, and true values are, in average,

underestimated: this affirmation is strongly dependent on the distribution of data and

should be verified for each data set (Lepot et al., 2017). A Number of dataset before

interpolated or original dataset are 208 data of SST, 232 data of δ18O, and 229 data of

δ18Osw with various time spacing (δt) between 10 and 150 years. After interpolation

applied, our interpolated data increase to be 484 data of SST, 481 data of δ18O, and 482

data of δ18Osw with 10 years’ time spacing (δt) data.

3.3. Wavelet Analysis

Before wavelet analysis performed, interpolated data in this study have removed their

trends using equation of linear detrending. Removing a trend from our dataset help us

to focus on the fluctuations of the data. We applied linear detrending using (Mathworks,

2019). The mean in linear detrending is given by the linear regression line Xt=St + I

over the period T (=Ni∆𝑡), the regression slope S and intercept I shown as below

(Rannik & Vesala, 1999)

𝑆 =𝑁𝑖 ∑ 𝑡𝑋𝑡 − ∑ 𝑡 ∑ 𝑋𝑡

𝑁𝑖 ∑ 𝑡2 − (∑ 𝑡)2

𝐼 =∑ 𝑋𝑡 − 𝑆 ∑ 𝑡

𝑁𝑖

Where t=1∆t and the summation is made of i=1,……., Ni. Detrending data has a

mean = 0 and standard deviation = 1.


Wavelet analysis is useful for analyzing localized variations of power within time series

records. We analyze our multiproxy records (Mg/Ca, δ18O, and δ18Osw) using a

modified script by (Torrence & Compo, 1997). Evenly datasets (~5000 years) between

9 and 14 kyrs in our multiproxy (Mg/Ca derived SST, δ18O, and δ18Osw) are prepared

to obtain several millennial and centennial signal in the records with equal time spacing

(δt) with 10 years periodicity. Wavelet transform is a band-pass filter which consists of

convoluting the signal with scaled and translated forms of a highly time-localized wave

function (the filter), the so-called “mother wavelet”. Morlet transform consists of a

Gaussian plane wave as shown below:

ѱ0(𝜂) = 𝜋−1/4𝑒𝑖𝜔0𝜂𝑒−𝜂

2/2

Where ѱ0(𝜂) is wavelet function that depends on a nondimensional “time” parameter

𝜂 and 𝜔0 is the nondimensional frequency. Normalization is applied to ensure the

wavelet transforms at each scale are directly comparable to each other and to the

transforms of additional time series. Confidence levels refer to the range of confidence

value in a given time series, we use the 95% confidence level to measure the mean

power spectrum at Core SO17-18517. Global wavelet spectrum is the time-averaged

wavelet spectrum of a vertical slice over a local wavelet spectrum plot as shown at the

formula below,

𝑊𝑛2(s)=

1

𝑛𝑎∑ |𝑊𝑛(𝑠)|

𝑛2𝑛=𝑛1

2

Explanation of the formula indicates n is the midpoint of n1 and n2, and na=n2-n1+1 is

the average number of points.

4. RESULTS

4.1. Distribution of Datasets

The box plot of our δ18O, SST, and δ18Osw which can be seen in Figure 3 indicates a

number summary of critical information in Core SO217-18517 datasets. We see from

the box plot (Figure 3), several SST distribution exceeds the upper whisker compare to

other δ18O, and δ18Osw in a core location. Exceeding the upper whisker of SST could be

as ‘outlier’ observations, we see the SST with the value of maximum box plot (~29.5°C)

could be ignored. We make a limitation of the upper whisker in the SST based on

maximum calcification temperature based on foraminiferal Mg/Ca is more less 29.5°C

(Anand et al., 2003; Regenberg et al., 2009). Therefore, outliers are lied more than

upper whisker as a maximum calcification temperature should be ignored. The


summary of our datasets in Core SO217-18517 is shown in table 1. Statistical summary

in Core SO217-18517 shows 25th and 75th percentile range (blue box), median (red

lines), and outliers (red cross) in Figure 3; Table 1 to approximately 99.5% the data

range (blue ‘whiskers’) which are normally distributed (Suppl. Figure 1).

Table 1. Critical information of statistical summary in Core SO217-18517 datasets.

Datasets Mean Median Upper

Quartile

Lower

Quartile

Maximum Minimum

δ18O -0.1086 -0.1060 0.0594 -0.3 0.5764 -0.6729

SST 27.8621 27.8191 28.3 27.75 29.5 26.3858

δ18Osw -2.2764 -2.3335 -1.8 -2.7 -1.13 -3.275

Figure 3. multi-proxies box plot of Core SO217-18517. a. δ18O, b. Sea Surface

Temperature, c. δ18Osw. By reducing the outlier’s effect in SST, our multi-proxies

reconstruction in Core SO217-18517 is more considerable.

4.2. Normalized Datasets

Uneven records of core SO217-18517 are interpolated into evenly datasets with time

resolution of 0.01 kyrs (Figure 4). It shows that linear interpolation between original

and interpolated data intersects with each other. Coefficient correlation (r value)

between original and interpolated data about 41.2% of δ18Osw, 29.7% of SST, and 73%

of δ18O (Suppl. Figure 2). Depleted δ18Osw records at our core site occur in the periods

of the 11-10 kyrs and 12-13 kyrs and. The amplitude of δ18Osw shows higher salinity

value at the Younger Dryas (12-13 kyrs) compare to other salinity records at 10-11 kyrs


Figure 4. Composite multi-proxies Core SO217-18517 between original and

interpolated data with time resolution of 0.01 kyrs. a. Composite δ18Osw, b. Composite

SST, c. Composite δ18O. These records present a significant high-resolution paired

Mg/Ca-δ18O with average sampling interval ~10 years during the last deglacial until

early Holocene in maritime continent providing hydrological changes during the past

14,000 years.

4.3. Wavelet Power Spectrum

Three multi-proxies of core SO217-18517 including δ18Osw, SST, and δ18O show high-

frequency variations at centennial and millennial timescale. These multi-proxies have

been interpolated and normalized to evenly space data with time resolution of 0.01 kyrs

(Figures 5a, 6a, 7a). These multi-proxies will be explained in each section below:

4.3.1. δ18Osw reconstruction

Wavelet power spectrum of δ18Osw reveals a number of centennial from 9 to 14 kyrs.

Result of wavelet analysis shows that ~ 1.1-kyrs or 1100-years oscillation of δ18Osw

core SO217-18517 is the most stable and dominant among periodicities between 9 and


14 kyrs (Figure 5b). Although, low-power global wavelet spectrum on centennial and

millennial-climate variability (Figure 5c) but those climate variability can be traced on

wavelet power spectrum in a range of 95% confidence level (Figure 5b). An increase

in (heavy) δ18Osw during 10-11 kyrs and 12-13 kyrs associated with an increase in δ18Osw

average variance between 0.01-0.04 ‰ using bandpass filter output of 0.1-1 kyrs

(Figure 5d). In contrast, light δ18Osw have slightly constant average variance during 9-

10 kyrs, 11-12 kyrs, and 13-14 kyrs. Occurrences of several centennial-scale variability

including 300 years, 150 years, and 63 years is getting stronger on periods of heavy

δ18Osw at 10-11 kyrs and 12-13 kyrs (Figures 5b-c).

Figure 5. a. δ18Osw reconstruction of core SO217-18517 after interpolation to evenly

spaced data with time resolution of 0.01 kyrs; b. Wavelet power spectrum δ18Osw core

SO217-18517 (High power is indicated by red whereas low power is indicated by blue),

areas cycles by black solid lines represent the confidence level greater than 95 %; c.

Global wavelet spectrum using mean power spectrum δ18Osw signal from 9 to 14 kyrs

1, 0.3, and 0.15 kyrs periodicities; orange dotted lines indicate confidence level greater

than 95 %; d. Average variance with band pass filter skala ±0.05 -0.03 kyrs. It shows

increasing δ18Osw variance during 10-11 kyrs and 12-13 kyrs. Significant power

spectrum shown at millennial timescale of 1.1 kyrs or 1100 years-periodicity.

4.3.2. Sea surface temperature (SST)

Wavelet power spectrum of SST reveals a number of centennial-timescale in periodicity

of 125, 230 and 500-years (Figure 6b). A dominant climate signal of centennial-scale

on 500-years periodicity is the most stable and dominant during 9-14 kyrs


(Figures 6b-c). Bandpass filter output (after the 0.1-1 kyrs bandpass filter) of SST

reconstructions shows SST variance between 0.03-0.17 °C (Figure 6D). 230 years

periodicity is the second dominant signal during 11-14 kyrs and followed by 125 years

periodicity during 9-11 kyrs. A trend of 500-years periodicity in our SST records

strengthened from 10-14 kyrs and reduced after 10 kyrs (Figure 6b).

Figure 6. a. SST reconstruction of core SO217-18517 after interpolation to evenly

spaced data with time resolution of 0.01 kyrs; b. Wavelet power spectrum SST core

SO217-18517 (High power is indicated by red whereas low power is indicated by blue),

areas cycles by black solid lines represent the confidence level greater than 95 %; c.

Global wavelet spectrum using mean power spectrum SST signal from 9 to 14 kyrs

with dominant signal 125, 230, and 500-years periodicities; orange dotted lines indicate

confidence level greater than 95 %; d. Average variance with band pass filter

skala ±0.1 -1 kyrs. Significant power spectrum occurs at centennial timescale

of 0.5 kyrs.

4.3.3. δ18O reconstruction

Wavelet power spectrum of δ18O core SO217-18517 reveals little variance signals

(Figures 7b, d). The result shows a statistically confidence above 95% level centennial

periodicity centered at 375 and 1000-years periodicity (Figures 7b, c). The result of

wavelet analysis shows that ~ 1000-years periodicity of δ18O at core SO217-18517 are

the most stable and dominant among periodicities of 9 to 14 kyrs (Figure 7b). Bandpass

filter output (after the 0.05-1 kyrs bandpass filter) of δ18O reconstructions shows

variance between 0.01-0.13‰


5. DISCUSSION

The ~1100-years or 1.1-kyrs and 1000-years periodicities are detected in planktonic

foraminifera δ18Osw and δ18O records of SO217-18517 between 9 and 14 kyrs timeseries

(Figures 5b & 7b). These millennial-scale variabilities of Core SO217-18517 confirm

similar millennial-scale in Holocene planktonic records in the North Atlantic and the

North Pacific (Khider et al., 2014; Lüning & Vahrenholt, 2016; Oppo et al., 2009;

Wanner et al., 2008) which extended to the last deglaciation in the Makassar Strait.

However, SST records SO217-18517 represent centennial-scale variabilities (Figure

6b) which is contrast to millennial-scale Holocene SST records in the North Pacific

(Khider et al., 2014). In the next sections, we will explain this centennial to millennial-

scale climate variabilities in the Makassar Strait. We will also compare our records with

other records in the central Indonesian region to see how the salinity changes response

to precipitation particularly in the period of 10-11 kyrs and 12-13 kyrs.

Figure 7. a. δ18O reconstruction of core SO217-18517 after interpolation to evenly

spaced data with time resolution of 0.01 kyrs; b. Wavelet power spectrum SST core

SO217-18517 (High power is indicated by orange whereas low power is indicated by

blue), areas cycles by black solid lines represent the confidence level greater than 95

%; orange dotted lines indicate confidence level greater than 95 %; c. Global wavelet

spectrum using mean power spectrum SST signal from 9 to 14 kyrs with dominant

signal 375 and 1000-years periodicities; d. Average variance with band pass filter skala

±0.05 -1 kyrs. Significant power spectrum occurs at millennial timescale of 1000 years.


5.1. Centennial-Millennial-scale variability since the last deglaciation

The δ18Osw and δ18O records on G. ruber of Core SO217-18517 are characterized by

millennial-scale variability with 1100-years and 1000-years periodicity between 9 and

14 kyrs (Figures 5 and 7). Wavelet power spectrum indicates a period of millennial-

scale variability is the most stable event in the entire δ18Osw and δ18O records between

9 and 14 kyrs (Figures 5b & 7b), even though this millennial power occurs below 95 %

confidence level (Figure 5c & 5d). We see δ18Osw trends are strong on millennial-scale

variability in the Makassar Strait shown by the wavelet power spectrum (Figure 5b).

This millennial-scale variability is robust based on age from the previous study

(Hendrizan et al., 2017), analytical, and calibration uncertainties (Figures 3 and 4). In

addition, a dominant signal of 1100-years periodicity from δ18Osw Core SO217-18517

can be found as well at Mindanao marine sediment core MD81 (Khider et al., 2014).

Signal of 1100 years periodicity at Mindanao during Holocene probably extend to last

deglacial period in the Makassar Strait as shown in Figure 5b. We propose mixture

forcing between the deep ocean and solar radiation could be an amplifier for forcing

and altering millennial-scale variability from 9 to 14 kyrs at our core location.

The most prominent δ18Osw maximum occurs at 10-11 kyrs and 12-13 kyrs, coincides

with the Early Holocene and Younger Dryas interval (Figure 4). We interpret the peak

of δ18Osw at 10-11 kyrs and 12-13 kyrs as a response to a decreased in precipitation and

a reduced in Mahakam River input into the Mahakam Strait. In those period at 10-11

kyrs and 12-13 kyrs, several centennial-scale variability including 300 years, 150 years,

and 63 years are stronger than other periods at 9-10 kyrs, 11-12 kyrs, and 13-14 kyrs,

which indicate strengthening centennial-scale periodicity (Figure 5b). Those

centennial-scale variability can be related to strengthening of solar radiative forcing

(Liu et al., 2009). It would affect intensified precipitation in tropical region (Novello et

al., 2016) particularly regions influenced by Australia-Indonesia Monsoon (Mohtadi et

al., 2016). This mechanism probably could explain an increase in δ18Osw during 10-11

kyrs and 12-13 kyrs with existing several centennial-scale variability in our core

SO217-18517 (Figure 5b).

5.2. Mixture forcing of climate variability

Wavelet analysis of our SST time series (Fig. 6) reveals a confidence period of ~500-

years periodicity. A common periodicity of ~500 years is found in global ocean from

North Atlantic to the East Asia region (H. Cheng et al., 2015; Zielhofer et al., 2019). A

reduced in North Atlantic Deepwater (NADW), cooling of the ocean surface and high-

latitude continent around North Atlantic and North Pacific, weakening of the Asian

monsoon (H. Cheng et al., 2015; Hai Cheng et al., 2012) could be mechanisms in

controlling 500-years periodicity at SST records Core SO217-18517 (Figure 6b). To

explain deep water circulation on our SST records, we see on log (Zr/Rb) as proxy of


bottom current intensity in the ITF region from Core SO217-18517 (Hendrizan et al.,

2017). Intriguing finding show the ITF intensity based on log (Zr/Rb) (Figure 8g; left

panel) associated with replacement of the ITCZ from 10 to 14 kyrs (Figure 8). This

evidence indicates likely the ITF transfer heat to our Core SO217-18517 site during 10-

14 kyrs which is reflected by 500-years periodicity in our SST records (Figure 5b). We

also looked furher on solar radiation forcing from Jun-August local insolation records

near Core SO217-18517 (Figure 8g: right panel). When the the ITCZ shifted northward

during 11-12 kyrs and 13-14 kyrs, light δ18Osw (Figure 8a) associated with both increase

in solar radiation forcing and stronger ITF intensity (Figure 8g). In contrast, southward

movement of the ITCZ reflects heavy δ18Osw associated with opposite pattern between

solar radiation forcing and the ITF intensity during 10-11 kyrs and 12-13 kyrs (Figure

8). Here we suppose the deep ocean is not the main forcing in driving SST and δ18Osw

in this core-site, other external forcing from solar radiation is the second forcing to

change climate proxy of Core SO217-18517.

5.3 Comparison hydroclimate proxy records

Today, precipitation patterns over Kalimantan and Sulawesi are associated with the

ITCZ movement along these region (Hendrizan et al., 2017; Konecky et al., 2016).

Precipitation pattern in Kalimantan shows the ITCZ position shifts twice which cause

rain falls along the year with two precipitation peaks on May and October (Dubois et

al., 2014). Precipitation pattern in Sulawesi indicates the ITCZ shifts to the south during

December-January with maximum precipitation and minimum precipitation when

reverse movement of the ITCZ to the north during June-August (Dubois et al., 2014).

Multi-factors in controlling δ18Osw reconstruction include sea level, current circulation,

and river discharge (Schröder et al., 2018) need to be considered when interpreting

fluctuation of precipitation changes in the past. δ18Osw from marine sediment cores of

the northwest Banda Sea (TGS-931) and Makassar Strait (SO217-18517, 18519, and

18515) reflects seasonality of rainfall in Kalimantan and Sulawesi (Schröder et al.,

2018). Those records will be compared with δ18O Gunung Buda speleothem records

(Cobb et al., 2007) and δDprecip (Konecky et al., 2016) as proxy of precipitation to more

comprehend interpretation of Kalimantan and Sulawesi precipitation pattern during the

last deglacial until early Holocene period.

Temporal evolution of proxy records occurred in the central Indonesia (Fig. 8),

indicating a decrease in δ18Osw particularly during 10-11 ka and 12-13 ka in the

Makassar Strait. It is also associated with reduced precipitation in Kalimantan (Fig. 8e)

but the changes is uncertain in Sulawesi (Figs. 8b-d). An increase δ18Osw is represented


as reduced in Mahakam River runoff in Core SO217-18517 and 18519 (Figure 8).

Similar changes of δ18Osw especially during 10-11 ka corresponding to our core sites

also found in marine core MD98-2178 at Celebes Sea (Fan et al., 2013). However,

records in Sulawesi show more complex mechanisms during 10-11 ka and 12-13 ka

(Figure 8). During 12-13 ka, marine sediment cores TGS-931 and SO217-18515 from

Sulawesi has same pattern of an increase in δ18Osw with marine sediment cores off

Mahakam Delta. Those records also associated with reduced precipitation based on

δDprecip from Lake Towuti (Figure 8). In contrast, light δ18Osw reflected more fresh water

supplied to the marine sediment cores from Sulawesi region which are consistent with

increase in precipitation at Lake Towuti during 10-11 ka. We interpret difference

between Kalimantan and Sulawesi during 10-11 kyrs due to movement of the ITCZ to

the south but Sulawesi has received more rainfall and Kalimantan is still drying.

A proposed mechanism in driving precipitation pattern at Kalimantan and Sulawesi

could be related to the ITCZ position changes during the end of the last deglacial period

until the early Holocene. During the period of 12-13 ka which was coincided with the

YD, the ITCZ shifted further to the south (Figure 8). Therefore, it will reduce the

Australian-Indonesian Summer Monsoon in almost entire region of Indonesia,

including Kalimantan and Sulawesi. Enhanced precipation in the Flores and Australia

during the YD (Ayliffe et al., 2013; Griffiths et al., 2009; Kuhnt et al., 2015). The

influence of ocean circulation via AMOC during the last deglaciation (Henry et al.,

2016) to atmospheric variability in the central Indonesia could be terminated at 10 kyrs

as both the ITF and solar radiation weakened but light δ18Osw which indicates the ITCZ

shifted to the north (Figure 8). Centennial-scale variability of SST with 500-years

periodicity show coherency of stronger centennial-scale from 10 to 14 kyrs (Figure 6).

However, this interpretation still need to be examined in the Holocene records in the

future. We suppose centennial and millennial-scale variability of AMOC intensity

associated with the ITF contribute to climate variability in the central Indonesia until

10 kyrs ago.


Figure 8. Comparison of hydroclimate proxies between Kalimantan and Sulawesi. a)

Interpolated δ18Osw data Core SO217-18517 offshore Mahakam Delta with smoothing

trend in red line, b,f) δ18Osw Core TGS-931 in the northwest Banda Sea and δ18Osw Core

SO217-18519 in the offshore Mahakam Delta (Schröder et al., 2018) c) δ18Osw Core

SO217-18515 in the Mandar Bay, Offshore Sulawesi (Schroder et al., 2016), d) δDprecip

records from Lake Towuti (Konecky et al., 2016), e) δ18O stalagmite records from


Gunung Buda, Kalimantan (Partin et al., 2007), g) Left panel: Log (Zr/Rb) based on X-

ray fluorescence (XRF) measurements at 1 cm intervals from Core SO217-18517

(Hendrizan et al., 2017), right panel: mean summer (21 June to 21 September)

insolation at 0°S (Laskar et al., 2004). Green shaded colors indicate heavy δ18Osw on

10-11 kyrs and 12-13 kyrs as reduced precipitation in Kalimantan during those periods.

6. CONCLUSION

Marine Sediment core SO217-18517 records the Makassar Strait climate variability on

a wide range between early Holocene and the end of the last deglaciation. During the

period between 9 and 14 kyrs, multi-proxies data (δ18Osw, SST, and δ18O) show high-

frequency variations at centennial and millennial timescale. δ18Osw and δ18O records

show the confidence power spectrum occurs at millennial time scales of ~1100-years

and 1000-years periodicity. However, the confidence power spectrum with ~500 years

periodicity (centennial) of SST is more stable than millennial time scales. Our results

find peaks of δ18Osw at 10-11 kyrs and 12-13 kyrs as a response to a decrease in

precipitation and a reduced in Mahakam River input into the Mahakam Strait. In those

period at 10-11 kyrs and 12-13 kyrs, several centennial-scale variability including 300

years, 150 years, and 63 years are stronger than other periods at 9-10 kyrs, 11-12 kyrs,

and 13-14 kyrs, which indicate strengthening centennial-scale periodicity. A proposed

mechanism in driving precipitation pattern at Kalimantan and Sulawesi could be related

to the ITCZ position changes during the end of the last deglacial period until the early

Holocene. The influence of ocean circulation via AMOC to atmospheric variability in

the central Indonesia could be terminated at 10 kyrs as both the ITF and solar radiation

weakened but light δ18Osw which indicates the ITCZ shifted to the north.

Author Contributions: All the authors are the main contributors to this manuscript.

MH wrote the manuscript and analyzed the data; NSN, SYC, and MRP wrote and

reviewed the manuscript; BS and IPA analyzed the data using wavelet analysis, DAU

and VCA drew the map, analyzed regional oceanography the Makassar Strait.

Acknowledgments: We gratefully acknowledge the Deutsche Forschungsgemeinchaft

(grant KU649/29-1 to Wolfgang Kuhnt) for funding this geochemical analysis in this

research and the Germany Ministry for Education and Science (BMBF, grant SO-217,

and MAJA, 03G0217A to Wolfgang Kuhnt) for funding the Sonne-217 Cruise. We

thank Beasiswa Saintek Kemenristek/BRIN for funding the publication fee.


Conflicts of Interest: The authors declare no conflict of interest

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Supplementary Figure 1. Histogram of interpolated SO217-18517 dataset. a.

Normal distribution of sea surface temperature (SST), b. Normal distribution of

δ18Osw, c. Normal distribution of δ18O

Supplementary Figure 2. Coefficient correlation between original and interpolated

SO217-18517 dataset. a. Sea surface temperature (SST), b. δ18Osw, c. δ18O

Documents

Centennial-Millennial Climate Variability in the Makassar ...202 Marfasran Hendrizan et al. 3. METHODS 3.1. Age model AMS 14C records of Core SO217-18517 used in this study are obtained