CPClimate of the PastCPClim. Past1814-9332Copernicus GmbHGöttingen, Germany10.5194/cp-11-1067-2015Multiscale monsoon variability during the last two climatic cycles
revealed by spectral signals in Chinese loess and speleothem recordsLiY.liying@ieecas.cnSuN.LiangL.MaL.YanY.https://orcid.org/0000-0003-0091-3857SunY.State Key Laboratory of Loess and Quaternary Geology, Institute of
Earth Environment, Chinese Academy of Sciences, Xi'an, Shaanxi 710061, ChinaCollege of Science, Technology and Engineering, James Cook University,
Cairns, Queensland 4870, AustraliaSchool of Mathematics and System Science, Shenyang Normal University,
Shenyang, Liaoning 110034, ChinaY. Li (liying@ieecas.cn)25August20151181067107524October201420December20147August201511August2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://cp.copernicus.org/articles/11/1067/2015/cp-11-1067-2015.htmlThe full text article is available as a PDF file from https://cp.copernicus.org/articles/11/1067/2015/cp-11-1067-2015.pdf
The East Asian Monsoon (EAM) exhibits a significant variability on timescales
ranging from tectonic to centennial as inferred from loess, speleothem and
marine records. However, the relative contributions and plausible driving
forces of the monsoon variability at different timescales remain
controversial. Here, we spectrally explore time series of loess grain size
and speleothem δ18O records and decompose the two proxies into
intrinsic components using the empirical mode decomposition method. Spectral
results of these two proxies display clear glacial and orbital periodicities
corresponding to ice volume and solar cycles, and evident millennial signals
which are in pace with Heinrich rhythm and Dansgaard–Oeschger (DO) cycles.
Five intrinsic components are parsed out from loess grain size and six
intrinsic components from speleothem δ18O records. Combined signals
are correlated further with possible driving factors including the ice
volume, insolation and North Atlantic cooling from a linear point of view.
The relative contributions of components differ significantly between loess
grain size and speleothem δ18O records. Coexistence of glacial and
orbital components in the loess grain size implies that both ice volume and
insolation have distinctive impacts on the winter monsoon variability, in
contrast to the predominant precessional impact on the speleothem
δ18O variability. Moreover, the millennial components are evident
in loess grain size and speleothem δ18O records with variances of
13 and 17 %, respectively. A comparison of the millennial-scale signals
of these two proxies reveals that abrupt changes in the winter and summer
monsoons over the last 260 kyr share common features and similar driving
forces linked to high-latitude Northern Hemisphere climate.
Introduction
The East Asian Monsoon (EAM), as a significant part of Asian monsoon
circulation, plays an important role in driving the palaeoenvironmental
changes in East Asia (An, 2000). The EAM fluctuations can be quantified at
different time intervals ranging from thousands of years to intraseasonal
periodicities, and the primary driving force of the monsoon variability on
each timescale is not unique (An et al., 2015). Multiscale monsoon
variability has been inferred from numerous proxies generated from deep-sea
sediments (e.g. Wang et al., 1999, 2005), eolian deposits (e.g. An, 2000;
Sun et al., 2012), and speleothem records (e.g. Wang et al., 2001, 2008),
which provide valuable insights into the changing processes and potential
driving forces of the EAM variability. In particular, Chinese loess has been
investigated intensively as a direct and complete preserver of the EAM
changes, with great effort spent on deciphering the EAM variability at both
orbital and millennial scales (e.g. An et al., 1990; Ding et al., 1994,
2002; Porter and An, 1995; Guo et al., 1996; Chen et al., 1997; Liu and Ding,
1998; Liu et al., 1999; An, 2000; Chen et al., 2006).
On the orbital timescale, the EAM variation recorded by Chinese
loess–paleosol sequences was characterized by an alternation between the
dry–cold winter monsoon and the wet–warm summer monsoon (Liu and Ding, 1998;
An, 2000). A strong 100 kyr periodicity was detected in the Chinese loess
particle size record, implying an important impact of glacial boundary
conditions on the EAM evolution (Ding et al., 1995). Obliquity and
precession signals were also clear in loess-based proxies (Liu et al., 1999;
Ding et al., 2002; Sun et al., 2006). In addition to these dominant
periodicities, some harmonic periodicities related to orbital parameters
were also found in the EAM records, such as the ∼ 75,
∼ 55, and ∼ 30 ka spectral peaks (Lu et al.,
2003; Sun et al., 2006; Yang et al., 2011). In contrast, absolute-dated
speleothem δ18O records revealed an evident 23 kyr cycle,
implying a dominant role of summer insolation in driving the summer monsoon
variability (Wang et al., 2008; Cheng et al., 2009). Different variances of
obliquity and precession signals in monsoonal proxies suggest that the
responses of the winter and summer monsoons to the orbital forcing were
dissimilar (Shi et al., 2011). The various patterns of orbital-scale monsoon
fluctuations between the loess proxies and speleothem δ18O
records most likely reflected the sensitivity of various archives and
proxies to the EAM variability (Clemens et al., 2010; Cheng et al., 2012;
Sun et al., 2015; Cai et al., 2015).
On the millennial timescale, the
rapid monsoon oscillations inferred from Chinese loess were not only
persistent during the last two glacial cycles (Porter and An, 1995; Guo et
al., 1996; An and Porter, 1997; Chen et al., 1997; Ding et al., 1999; Sun et
al., 2010; Yang and Ding, 2014), they were also evident during early glacial
extreme climatic conditions (Lu et al., 1999). The millennial-scale monsoon
variability during the last glacial period was strongly coupled to climate
changes recorded in the Greenland ice core and North Atlantic sediments,
indicating a dynamic connection between the EAM variability and the
high-latitude Northern Hemisphere climate (Porter and An, 1995; Guo et al.,
1996; Chen et al., 1997; Fang et al., 1999). Recently, a combination of
proxies from Chinese loess, speleothem, and Greenland ice core with modelling
results indicated that the Atlantic meridional overturning circulation might
have played an important role in driving the rapid monsoon changes in East
Asia during the last glaciation (Sun et al., 2012).
Although previous studies have revealed that past EAM variability
principally comprise a mixture of forcing signals from ice volume, solar
radiation, and North Atlantic climate, the relative contributions of
glacial, orbital and millennial forcing to the EAM variability remain
unclear. In this study, we conducted a comprehensive investigation of
multiscale EAM variability over the last 260 kyr by analysing the mean grain
size (MGS) record from a Gulang loess sequence (a proxy indicator of the
East Asian winter monsoon intensity) and speleothem δ18O record
of Hulu and Sanbao caves (a debatable indicator of the summer monsoon
intensity). Our objectives are to evaluate the relative contributions of
glacial–interglacial- to millennial-scale signals registered in these two
widely used monsoon proxies, and to emphasise the glacial–interglacial
discrepancy and millennial similarity between loess and speleothem records
during the last two glacial cycles.
Data and methods
The data for the loess sequence was collected at a section in Gulang, Gansu
Province, China (37.49∘ N, 102.88∘ E, 2400 m a.s.l.), which is situated in the northwestern part of the Chinese Loess
Plateau. It is about 10 km to the southwest, on the margin of the Tengger Desert
(Fig. 1). In this region, the average annual precipitation and temperature
over the last 20 years are 350 mm and 5.7 ∘C.
About 70 m of loess accumulated at Gulang during the last two climate
cycles. A high sedimentation rate and weak pedogenesis in this region made
the Gulang loess sequence very sensitive to orbital and millennial monsoon
changes (Sun et al., 2012, 2015).
Map showing the loess distribution and locations of the Gulang
loess section, Sanbao, and Hulu caves. Dotted lines indicate the
precipitation isohyets (PI).
The samples used in this study were collected at 2 cm intervals,
corresponding to 50–100-year resolution for the loess–paleosol sequence.
The grain size data of the upper 20 m were from a 20 m pit near Gulang (Sun
et al., 2012), and the lower part spanning the last two glacial cycles were
from another 50 m section (for the full grain size data, see Supplement Table S1). The mean grain size data of the
composite 70 m section have been employed for a chronological reconstruction
(for a detailed description, see Sun et al., 2015). The Gulang chronology was
evaluated by comparison with a 249 kyr Chinese loess millennial-scale
oscillation stack (CHILOMOS) record in the northern Loess Plateau (Yang and
Ding, 2014) (Fig. 2); the close matches between these two records indicate a
high reliability of our Gulang age construction. Unlike previous studies (Sun
et al., 2012, 2015), here we performed spectral and decomposing analysis on
the mean grain size time series in order to decipher multiscale variability
and dynamics of the winter monsoon.
Comparison of Gulang MGS (blue; Sun et al., 2015) and CHILOMOS
stack median grain size (Md, green; Yang and Ding, 2014) with the benthic
δ18O (black; Lisiecki and Raymo, 2005) and Sanbao/Hulu
speleothem δ18O (magenta; Wang et al., 2008; Cheng et al.,
2009) records. The red and black dashed lines denote tie points derived from
optically stimulated luminescence (OSL) dating and benthic δ18O
correlation, respectively.
The absolute-dated speleothem δ18O records from Sanbao/Hulu caves
(0–224 ka, Wang et al., 2008) and the Sanbao cave (224–260 ka, Cheng et
al., 2009) (Fig. 1; Supplement Table S2) were selected to infer the summer
monsoon variability spanning the last two glacial–interglacial cycles.
Compatible with the analysis by Wang et al. (2008), we plotted the Hulu
δ18O data 1.6 ‰ more negative than that from the Sanbao
cave (Fig. 2). Interpretation of the Chinese speleothem δ18O
records remains debatable as a direct indicator of the summer monsoon
intensity since various factors like seasonal changes in precipitation
amount, moisture sources, and circulation patterns would influence the
speleothem δ18O composition (e.g. Yuan et al., 2004; Wang et al.,
2001, 2008; Cheng et al., 2009; Clemens et al., 2010; Dayem et al., 2010;
Pausata et al., 2011; Maher and Thompson, 2012; Caley et al., 2014).
Nevertheless, the high similarity between millennial events in Chinese
speleothem and Greenland ice core revealed that speleothem δ18O is
a reliable indicator of seasonal monsoon change (Wang et al., 2001; Clemens
et al., 2010). More recently, a model–data comparison suggested that Chinese
speleothem δ18O can be regarded as a monsoon proxy to reflect the
southerly wind intensity rather than the precipitation change (Liu et al.,
2014). Thus, spectral and decomposed results of the composite speleothem
δ18O record time series were used in this study to address
multiscale variability and dynamics of the summer monsoon.
To detect the presence of glacial–millennial periodicities, we performed
spectral analysis on the 260 ka records of Gulang MGS and speleothem
δ18O using both the Multitaper (MTM, implemented in the SSA
toolkit, Vautard et al., 1992) (http://www.atmos.ucla.edu/tcd/ssa/) and
REDFIT (Schulz and Mudelsee, 2002) methods, which are related to the
empirical orthogonal function and Lomb–Scargle Fourier transform,
respectively. The MTM method has the advantages of quantified and optimized
trade-off between the spectral leakage reduction and variance reduction, and
is suitable for time series affected by high-noise levels (Lu et al.,
1999), but MTM requires equally spaced data and therefore an interpolation
is needed. The REDFIT program estimates the first-order autoregressive (AR1)
parameter from unevenly sampled time series without interpolation, which
avoids a too “red” spectrum (Schulz and Stattegger, 1997), but uses the
weighted overlapped segment averaging (WOSA) method for the spectral leakage
reduction and variance reduction, which makes the trade-off not
quantifiable. The similar spectral periodicities derived from both REDFIT
and MTM methods were regarded as dominant frequencies at
glacial–millennial bands.
The decomposed components of loess MGS and speleothem δ18O records
were parsed out using the technique of empirical mode decomposition (EMD; Huang et al., 1998) (for the MATLAB code of EMD method, see the code in the Supplement). EMD directly
extracts energy which is associated with intrinsic timescales in nonlinear
fluctuations, and iteratively decomposes the raw complex signal with several
characteristic timescales coexisting into a series of elementary intrinsic
model function (IMF) components, avoiding any arbitrariness in the choices of
frequency bands in this multiscale study. The EMD method has been widely
applied to various palaeoclimate databases such as ice cover (Gloersen and
Huang, 2003), North Atlantic oscillation (Hu and Wu, 2004), solar insolation
(Lin and Wang, 2006), and temperature under global warming (Molla et al.,
2006). This approach has also been used to decipher the multiscale variations
of Indian monsoon (Cai et al., 2015). However, the application of the EMD
method on the loess record remains poorly investigated with limited
understanding of decomposed components at glacial and orbital timescales due
to the low-resolution proxy variations (Yang et al., 2011, 2008). In this
study, we applied EMD on linearly interpolated loess and speleothem data with
a 100-year interval to quantify the relative contributions of both orbital
and millennial components.
Multiscale monsoon variability
The highly comparable spectral results between REDFIT and MTM methods showed
that apparent periods identified in the MGS spectrum are at ∼ 100,
∼ 41, ∼ 23, ∼ 15, ∼ 7, ∼ 5, ∼ 4, and
∼ 3–1 kyr, for REDFIT and MTM methods, over the 80 and 90 %
confidence levels, respectively (Fig. 3). It is shown that the potential
forcing of the glacial–interglacial and orbital EAM variability is part of
external (e.g. the orbital-induced summer insolation; An, 1991; Wang et
al., 2008) and the internal factors (e.g. the changes in the ice volume and
CO2 concentrations; Ding et al., 1995; Lu et al., 2013; Sun et al.,
2015). The coexistence of the ∼ 100, ∼ 41, and ∼ 23 kyr
periods in the Gulang MGS record confirms the dynamic linkage of the winter
monsoon variability to glacial and orbital forcing. Based on the spectral
results, many millennial frequencies are detected, which can be mainly
divided into two groups, namely, ∼ 7–4 and ∼ 3–1 kyr, which
possibly correspond to the Heinrich (∼ 6 kyr) rhythm and the DO
(∼ 1.5 kyr) cycles recorded in the North Atlantic sediments and
Greenland ice core (Bond et al., 1993; Dansgaard et al., 1993; Heinrich,
1988). Taking into account the sampling resolution and surface mixing effect
at Gulang, the residual component (< 1 kyr) might contain both
centennial and noisy signals, which was excluded for further discussion in
this study.
Spectra of Gulang MGS
(a) and Sanbao/Hulu speleothem δ18O (b) (Wang et
al., 2008; Cheng et al., 2009) records using REDFIT (lower) and MTM (higher)
methods. The red, green and black dotted lines represent the 80, 90 and
95 % confidence levels. Periodicities are shown above the spectral
curves. (for REDFIT: nsim = 1000, mctest = T, ofac = 4.0,
hifac = 1, rhopre =-99.0, n50 = 1, iwin = 2; for MTM:
sampling interval = 0.1, MTM parameters = default value, computation
of tapers window = default value, median smoothing window
width = 0.1).
Compared to the MGS spectral results, the speleothem δ18O
spectrum shares similar peaks at the precession (∼ 23 kyr) and
millennial bands (∼ 5, ∼ 3, ∼ 2.4,
∼ 2, ∼ 1.5, ∼ 1.3, and
∼ 1 kyr), but has a lack of distinct peaks at ∼ 100
kyr and ∼ 41 kyr (Fig. 3). Notably, precession peaks at
∼ 23 and ∼ 19 kyr are more dominant in the
speleothem δ18O than in the loess MGS record. Moreover, the
speleothem spectrum shows a peak over the 80 and 90 % confidence
levels in REDFIT and MTM spectra, respectively, centred at ∼ 10 kyr frequency, which is approximately related to the semi-precession
frequency.
The different oscillation patterns composing loess MGS and speleothem
δ18O time series are separated out using the EMD method as
presented in Figs. 4 and 5. REDFIT spectral analysis is further carried out
on each IMF with dominant periods as shown. Five IMFs are generated for the
Gulang MGS data on the glacial-to-millennial timescale. The variability of
Gulang MGS is dominated by the lowest frequency signal with a variance of
32 % (IMF5). Two periodicities (41 and 23 kyr) in the orbital component
(IMF4) are linked to the obliquity and precession, contributing altogether
40 % to the total variance. The IMF3 component dominated by a 15 kyr
periodicity likely either related to another unknown driver or corresponding to
the second precessional cycle (19 kyr) caused by the chronology uncertainty.
The variances of two millennial components (IMF2 and IMF1) are very close
with variances of 8 and 5 %, respectively, in the Gulang MGS record.
Similarly, six IMFs are decomposed for the speleothem δ18O record
on frequencies less than 1 kyr, and all the glacial-to-orbital
periodicities correspond to parameters in Milankovitch cycles. Compared with
decomposed results of the Gulang MGS record, the glacial (IMF6) and obliquity
(IMF5) components are unclear in the speleothem δ18O record; both
of the variances are 12 %. The precession component (IMF4), however, is
the most dominant signal among the six components, accounting for 59 % of
the variance. Notable millennial components (IMF3, IMF2, and IMF1) are
evident with variances of 8, 6
and 3 %, respectively.
IMFs of Gulang MGS series (a) and corresponding spectra (b).
Numbers in black are dominant periods and dotted lines represent the 90 %
confidence level.
IMFs of speleothem δ18O series (a) and corresponding
spectra (b). Numbers in black are dominant periods and dotted lines
represent the 90 % confidence level.
Dynamics of multiscale EAM variabilityGlacial and orbital forcing of the EAM variability
We combine IMF3, IMF4 and IMF5 of Gulang MGS and IMF4, IMF5 and IMF6 of
speleothem δ18O records as the low-frequency signals
(period > 10 kyr) to reveal the glacial- and orbital-scale variations of the
winter and summer monsoon. The glacial and orbital variations of the loess
and speleothem records represent the total variances of ∼ 87
and ∼ 83 %, respectively. The low-frequency signals of
the loess MGS and speleothem δ18O records are compared with the
changes in the ice volume and solar insolation at 65∘ N (Berger,
1978) to ascertain plausible impacts of glacial and orbital factors on the
EAM variability (Fig. 6).
Comparison of the glacial- and orbital-scale components of Gulang MGS
(blue) and Sanbao/Hulu speleothem δ18O (magenta; Wang et al., 2008;
Cheng et al., 2009) records with summer insolation at 65∘ N (red;
Berger, 1978) and benthic δ18O record (black; Lisiecki and Raymo,
2005). The vertical gray bars represent the interglacial periods.
The low-frequency component of the Gulang MGS record is well correlated to
the global ice volume change inferred from the benthic δ18O
record (Lisiecki and Raymo, 2005) with a correlation coefficient (R2)
of 0.56, reinforcing the strong coupling between the winter monsoon
variation and ice volume changes, particularly in terms of
glacial–interglacial contrast (Ding et al., 1995). However, fine MGS signals
at the precessional scale seem more distinctive than those in the benthic
δ18O stack. For example, the remarkable peaks in the MGS around
85, 110, and 170 ka have no counterpoints in the benthic δ18O
record. By comparing MGS data with the summer insolation record, the overall
∼ 20 kyr periodicity is damped but still visible during both
glacial and interglacial periods except for the insolation maxima around 150
and 220 ka (Fig. 6). The coexistence of the glacial and orbital cycles in
loess MGS indicates that both the ice volume and solar insolation have
affected the winter monsoon variability, and their relative contributions
are 32 and 55 %, respectively, as estimated from variances of the
glacial (IMF5) and orbital (IMF4 and IMF3) components.
The speleothem δ18O record varies quite synchronously with the
July insolation, characterized by a dominant precession frequency (Fig. 6).
This in-phase change is thought to support a dominant role of summer
insolation in the Northern Hemisphere in driving the summer monsoon
variability at the precession period (Wang et al., 2008), given that the
palaeoclimatic interpretation of the speleothem δ18O is quite
controversial (Wang et al., 2001, 2008; Yuan et al., 2004; Hu et al., 2008;
Cheng et al., 2009; Peterse et al., 2011).
The different contributions of glacial and orbital variability in the loess
MGS and speleothem δ18O records indicate that the driving
forces associated with these two proxies are different. The loess grain size
is directly related to the northwesterly wind intensity, reflecting that
atmospheric process is linked to the Siberian–Mongolian High (Porter and An,
1995). The speleothem δ18O might be influenced by multiple
factors such as the isotopic depletion along the vapour transport path
(Pausata et al., 2011), changes in δ18O values of meteoric
precipitation or the amount of summer monsoon precipitation (Wang et al.,
2001, 2008; Cheng et al., 2009), and seasonality in the amount and isotopic
composition of rainfall (Clemens et al., 2010; Dayem et al., 2010; Maher and
Thompson, 2012). Even at the orbital timescale, proxy–model comparison
suggests that the response of the winter and summer monsoon to obliquity and
precession forcing are dissimilar (Shi et al., 2011)
It is quite clear that the EAM is formed by the thermal gradient between the
Asian continent and the Pacific Ocean to the east and southeast (Halley,
1986; Xiao et al., 1995; Lestari and Iwasaki, 2006). In winter, due to a
much larger heat capacity of water in the ocean than that on the land
surface, a higher barometric pressure forms over the colder Asian continent
with a lower pressure over the warmer ocean. This gradient is the driving
force for the flow of cold and dry air out of Asia, forming the winter
monsoon (Gao, 1962). On the glacial–interglacial timescale, the buildup of
the northern high-latitude ice sheets during the glacial periods strengthens
the barometric gradient which results in intense winter monsoons (Ding et
al., 1995; Clark et al., 1999). The contemporaneous falling sea level and
land–ocean pressure gradient further enhances winter monsoon circulation
during glacial times (Xiao et al., 1995). The other factor that influences
the land–ocean differential thermal motion is the orbitally induced changes
in solar radiation. The precession-induced insolation changes can lead to
regional land–ocean thermal gradients whilst obliquity-related insolation
changes can result in meridional thermal gradients, both of which can
substantially alter the evolution of the Siberian and Subtropical Highs and
the EAM variations (Shi et al., 2011).
Impacts of high-latitude cooling on millennial EAM oscillations
The EAM variations are persistently punctuated by apparent millennial-scale
monsoon events (Garidel-Thoron et al., 2001; Wang et al., 2001; Kelly et
al., 2006). The millennial-scale events of the last glacial cycle were
firstly identified in Greenland ice cores (Dansgaard et al., 1993; Meese et
al., 1997). Subsequently, well-dated loess grain size and speleothem δ18O records in China have been found to apparently correspond with
rapid climate oscillations in the North Atlantic (Porter and An, 1995; Guo
et al., 1996; Chen et al., 1997; Ding et al., 1998; Wang et al., 2001). The
most striking evidence is the strong correlation between the loess grain
size, speleothem δ18O and Greenland ice core δ18O
records during the last glaciation (Ding et al., 1998; Wang et al., 2001;
Sun et al., 2012). The findings of these abrupt changes have been extended
to investigate glacial–interglacial cycles using loess and speleothem
records (Ding et al., 1999; Cheng et al., 2006, 2009; Wang et al., 2008;
Yang and Ding, 2014) and North Atlantic sediments (McManus et al., 1999;
Channell et al., 2012).
Unlike previous comparisons based on original proxy variability, here we
combine the IMF1 and IMF2 components of the loess MGS and IMF1, IMF2, and
IMF3 components of speleothem δ18O records as robust
reflections of millennial-scale signals of the winter and summer monsoons,
with variances of 13 and 17 %, respectively. The combination of the
two millennial signals of the loess MGS and speleothem δ18O
records are compared further with the North Atlantic cooling events over the
last two glacial cycles to reveal the dynamic links of abrupt climate
changes in East Asia and the North Atlantic (Fig. 7). The Younger Dryas (YD)
and Heinrich events (H1-H6) are well detected in loess and
speleothem records around 12, 16, 24, 31, 39, 48, 55, and 60 ka. Most of
the millennial-scale events in the loess MGS and speleothem δ18O records are well aligned with comparable timing and duration
during the last two glacial cycles. However, some MGS valleys such as A17,
A23, B17, B18, and B22 are not well matched with the speleothem δ18O minima, possibly due to uncertainties in the loess chronology. The
comparable millennial-scale events between grain size of Gulang and the
CHILOMOS stack (Yang and Ding, 2014) show the nature of replication of
Gulang MGS record within the dating uncertainty, confirming the persistent
millennial-scale winter monsoon variability spanning the last two glacial
cycles (Fig. 7).
Comparison of millennial-scale variations among Gulang MGS (blue),
CHILOMOS stack Md (green; Yang and Ding, 2014) and Sanbao/Hulu speleothem
δ18O (magenta; Wang et al., 2008; Cheng et al., 2009) records
over the last two glacial–interglacial cycles. Cyan dotted lines are the YD
and the Heinrich events identified among the three records and gray bars
indicate interglacial periods. The numbers represent well-correlated Chinese
interstadials identified among the three records.
The millennial-scale monsoon signals over the last two glacial cycles have
been well compared with the cooling events recorded in the North Atlantic
sediments, demonstrating a dynamic link between abrupt climate changes in
East Asia and the North Atlantic. As identified in Chinese speleothem
records, the magnitudes of abrupt climate events are identical between the
last and the penultimate glacial cycles (Wang et al., 2008). However, the
duration and amplitude of these millennial events are quite different
between the glacials and interglacials. The duration of the millennial
monsoon events is relatively shorter and the amplitude larger during glacial
periods, suggesting a plausible glacial modulation of rapid climate changes
(McManus et al., 1999; Wang et al., 2008). The potential driving mechanism
for rapid EAM changes has been attributed to changing climate in the
high-latitude Northern Hemisphere, e.g. the reduction of the North Atlantic
deep water circulation triggered by fresh water inputs from melting icebergs
(Broecker, 1994). The North Atlantic cooling can affect the zonal high
pressure systems, including the Azores–Ural–Siberian–Mongolian high (Palmer
and Sun, 1985; Rodwell et al., 1999; Yuan et al., 2004), which can further
transmit the abrupt cooling effect into East Asia and result in significant
EAM changes (Porter and An, 1995; Wang et al., 2001). Apart from the
geological evidence, numerical modelling also suggests that the Atlantic
meridional overturning circulation might affect abrupt oscillations of the
EAM, while the westerly jet is the important conveyor introducing the North
Atlantic signal into the EAM region (Miao et al., 2004; Zhang and Delworth,
2005; Jin et al., 2007; Sun et al., 2012).
Conclusions
The EAM displays variabilities on timescales ranging from thousands of years to intraseasonal periodicities as inferred from numerous proxy indicators. Multiscale signals were spectrally
detected and naturally decomposed from Chinese loess and speleothem records
over the last two climatic cycles in this study,
permitting an evaluation of the relative contributions of glacial, orbital
and millennial components in the EAM record from a linear point of view. The
spectra of Gulang MGS and speleothem δ18O data show similar
periodicities at glacial-to-orbital and millennial timescales, corresponding
to the rhythms of changing ice volume, orbitally induced insolation, and
North Atlantic cooling (i.e. Heinrich rhythm and Dansgaard–Oeschger cycles).
Amplitude variances of the decomposed components reveal significant glacial
and orbital impacts on the variation in loess grain size and the dominant
precession forcing in the speleothem δ18O variability. The
millennial components are evident in the loess and speleothem proxies with
variances of 13 and 17 %, respectively. Millennial IMFs were combined to
decode the synchronous nature of rapid changes of these two proxies. High
similarity of millennial-scale monsoon events both in terms of the rhythms
and duration between the loess and speleothem proxies implies that the winter
and summer monsoons share common millennial features and similar driving
forces.
The Supplement related to this article is available online at doi:10.5194/cp-11-1067-2015-supplement.
Acknowledgements
Four anonymous reviewers and Dr. Loutre Marie-France are acknowledged for
their insightful comments. This work was supported by the National Basic
Research Program of China (2013CB955904), the Chinese Academy of Sciences
(KZZD-EW25 TZ-03), the National Natural Science Foundation of China
(41472163), and the State Key Laboratory of Loess and Quaternary Geology
(SKLLQG1011).
Edited by: M.-F. Loutre
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