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East Asian monsoon variations in the loess–desert transitional zone (northern China) during the past 14 ka and their comparison with TraCE21K simulation results

Published online by Cambridge University Press:  08 February 2024

Yao Gu ,
Huayu Lu Open the ORCID record for Huayu Lu [Opens in a new window] ,
Jingjing Wang ,
Hongyan Zhang ,
Wenchao Zhang ,
Chenghong Liang  and
Jiang Wu
Yao Gu
Affiliation:
School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Huayu Lu*
Affiliation:
School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Jingjing Wang
Affiliation:
School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Hongyan Zhang
Affiliation:
School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Wenchao Zhang
Affiliation:
School of Earth Sciences and Resources, China University of Geosciences (Beijing), Beijing 100083, China
Chenghong Liang
Affiliation:
School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Jiang Wu
Affiliation:
School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China School of Geography, Nanjing Normal University, Nanjing 210023, China
*
Corresponding author: Huayu Lu; Email: huayulu@nju.edu.cn
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Abstract

The Holocene is a critical period for understanding the East Asian monsoon system (EAM) over long timescales, but high-precision dating and high-resolution records from the Holocene epoch at monsoonal margins of East Asia are lacking. Here, on the basis of closely spaced radiocarbon and optically stimulated luminescence dating results obtained from a typical loess–paleosol sequence on the northern Chinese Loess Plateau (CLP), we provide an independent age-based, high-resolution depositional record of East Asian summer (EASM) and winter monsoons (EAWM) variations over the past ~14 ka. We find that both the EASM and EAWM simultaneously strengthened sometime during the Holocene optimum (~7–5 ka BP), with greater seasonality, and weakened during the Late Holocene. These findings are counterintuitive to our understanding of the EAM variations based on loess records at suborbital scales during interglacial periods, providing an alternative scenario of the monsoon system evolution. We postulate that high-latitude forcing and surface feedbacks, such as vegetation change, have modulated the EAM variations during the Holocene warmth.

Keywords

East Asian monsoonRadiocarbon datingHoloceneLoessTraCE21K

Information

Type
Research Article
Information
Quaternary Research , Volume 120: Loess Environments: Generation, Transport, and Deposition , July 2024 , pp. 53 - 61
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Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press on behalf of Quaternary Research Center

INTRODUCTION

The Holocene has experienced considerable climate variability (Bond et al., Reference Bond, Kromer, Beer, Muscheler, Evans, Showers, Hoffmann, Lotti-Bond, Hajdas and Bonani2001; Cai et al., Reference Cai, Cheng, Ma, Mao, Breitenbach, Zhang, Xue, Cheng, Edwards and An2021), and these climatic changes have been reported from all latitudes (Routson et al., Reference Routson, Mckay, Kaufman, Erb, Goosse, Shuman, Rodysill and Ault2019; Walczak et al., Reference Walczak, Mix, Cowan, Fallon, Fifield, Alder and Du2020; Bova et al., Reference Bova, Rosenthal, Liu, Godad and Yan2021; Cai et al., Reference Cai, Cheng, Ma, Mao, Breitenbach, Zhang, Xue, Cheng, Edwards and An2021; Liang et al., Reference Liang, Lu, Gu, Zhao, Liu, Zhang and Zhang2022). It is also recognized that there is regional diversity in Holocene climate variations in East Asia influenced by the East Asian monsoon system (EAM) circulation. However, the phase relationship between the East Asian summer (EASM) and winter monsoons (EAWM) (e.g., Wen, X.Y. et al., Reference Wen, Liu, Wang, Cheng and Zhu2016) and their seasonal evolution have not yet been determined. Loess deposits on the Chinese Loess Plateau (CLP) constitute an excellent proxy record of the EASM and EAWM variations at multiple timescales, and provide an opportunity to address these questions. The loess deposits were originally transported by the EAWM (Li et al., Reference Li, Feng and Tang1988; An, Reference An2000; Lu et al., Reference Lu, Wang, Wang, Zhang and Markovi2022), their grain size and dust sedimentation rate (DSR) are proxy indicators of the EAWM strength (Lu and Sun, Reference Lu and Sun2000; Lu et al., Reference Lu, Wang, Wang, Zhang and Markovi2022). Meanwhile, magnetic susceptibility, organic matter content, and carbon and hydrogen isotopic compositions of loess deposits are direct proxies of the EASM intensity, indicated by precipitation (Wang et al., Reference Wang, Biasutti, Byrne, Castro, Chang, Cook and Fu2021; Liang et al., Reference Liang, Lu, Gu, Zhao, Liu, Zhang and Zhang2022; Lu et al., Reference Lu, Wang, Wang, Zhang and Markovi2022). Hence, the loess deposits provide one of the best records for reconstructing the variability in the EASM and EAWM at high resolution concurrently, avoiding the problems that the EASM and EAWM variations cannot be compared under a similar timescale.

The loess–desert transitional zone in northern China has long been thought to be sensitive to climate change and human influences. Small changes in vegetation, climate, or land use in this region will drive major changes in surrounding sand dunes and transportation and deposition of aeolian dust (Wang et al., Reference Wang, Lu, Zhang, Yi, Gu and Liang2019; Xu et al., Reference Xu, Mason, Xu, Yi, Bathiany, Yizhaq, Zhou, Cheng, Holmgren and Lu2020). In this region, the widespread aeolian deposits have recorded the history of environmental change under the influence of the EAM circulation and global climate change (Lu et al., Reference Lu, Miao, Zhou, Mason, Swinehart, Zhang, Zhou and Yi2005, Reference Lu, Mason, Stevens, Zhou, Yi and Miao2011). In this study, on the basis of a loess–paleosol record in the loess–desert transitional zone in northern China (Fig. 1), a high-resolution record of the EASM and EAWM variations since ~14 ka is obtained. The results reveal novel behaviours of the EAM seasonal variability during a warm period.

Figure 1.

Climatological mean wind conditions in boreal summer (June–July–August) and winter (December–January–February) and sampling site at Zhenbeitai (ZBT). (a) Summer mean 850 hPa streamline based on NCEP reanalysis data from 1980 to 2010 (Kanamitsu et al., Reference Kanamitsu, Ebisuzaki, Woollen, Yang, Hnilo, Fiorino and Potter2002). The red rectangle is the area shown in c (107–114°E, 33–41°N). (b) Winter mean 1000 hPa streamline based on NCEP reanalysis data from 1980 to 2010 (Kanamitsu et al., Reference Kanamitsu, Ebisuzaki, Woollen, Yang, Hnilo, Fiorino and Potter2002). (c) Sampling site at ZBT and some other records in the loess–desert transitional zone.

MATERIALS AND METHODS

Geographic setting

The Zhenbeitai (ZBT) section (38°19′41.9″N, 109°43′51.4″E; 1187 m above sea level) is located in the transitional zone between monsoon humid and Asian interior arid regions: the CLP and the Mu Us sand fields. The mean annual temperature at this site is ~8.0°C, and the mean annual precipitation is ~400 mm. Most precipitation falls in the summer season, in a typical monsoon climate (Wang et al., Reference Wang, Lu, Zhang, Yi, Gu and Liang2019; Liang et al., Reference Liang, Lu, Gu, Zhao, Liu, Zhang and Zhang2022).

The exposed studied section has a thickness of 16.8 m. The upper 0–0.6 m is a light yellow-brown sandy loam soil with some modern plant roots. A dark yellow-brown paleosol layer from 0.6 to 2.9 m underlies the upper unit. Below this is a dark brown, sandy soil layer from 2.9 to 3.3 m and a sand layer from 3.3 to 5.1 m that overlies a thick loess layer that extends to the bottom of the section.

After 30–50 cm of surface sediments were excavated to avoid contamination, a total of 44 loess samples were collected from the upper 5.1 m of the section at intervals of 10 cm above 3.3 m and 20 cm below 3.3 m for accelerator mass spectrometry (AMS) radiocarbon dating.

Radiocarbon dating

The humin fraction of the loess samples was extracted following the acid–alkaline–acid method for AMS radiocarbon dating (Hajdas, Reference Hajdas2008). All samples were dried thoroughly at room temperature; visible plant remains were removed with tweezers. HCl (2 N) was used for at least 4 hours at room temperature to completely remove carbonates. After samples were rinsed with ultrapure Milli-Q deionized water to a pH of ~6, a series of 0.5% NaOH washes was added to remove the base-soluble fraction (i.e., humic acids) based on the concentration of humic acids. NaOH washes were conducted until the solution became clear, and the remainder was rinsed with deionized water three times. Then, 1 N HCl was added, and after acid washing, the samples were rinsed with deionized water to neutral pH and dried at 60°C.

All samples were combusted in an online combustion system in a mixture of O2 and He gas atmosphere at 920°C. Then, water was eliminated, and the extracted CO2 was converted to graphite in the reaction CO2 + H2 → C + H2O with ~5 mg of iron catalyst at a temperature of 550°C. All 14C measurements were undertaken on graphitized samples at the Laboratory of AMS Dating and the Environment at Nanjing University using a compact radiocarbon AMS dating system (MICADAS; Synal et al. Reference Synal, Stocker and Suter2007). Conventional radiocarbon ages were converted to calendar ages using OxCal online v. 4.4 (Ramsey, Reference Ramsey2009) and the IntCal20 calibration curve (Reimer et al., Reference Reimer, Austin, Bard, Bayliss, Blackwell, Ramsey and Butzin2020), except for the 0.1 m sample, for which the post-bomb atmospheric NH zone 2 curve was used (Hua et al., Reference Hua, Barbetti and Rakowski2013).

Age–depth modelling

Bayesian age–depth modelling was performed using the Bacon code (Blaauw and Christen, Reference Blaauw and Christen2011) based on 44 radiocarbon ages and 20 OSL ages for the ZBT site (Wu et al., Reference Wu, Lu, Yi, Xu, Gu, Liang, Cui and Sun2019). We first performed modelling with the default prior information: sedimentation (sed.) shape = 1.5 and acc. mean = 20 for the gamma distribution; and memory (mem.) mean = 0.7 and mem. strength = 4 for the beta distribution, describing the memory effects of the DSR. Then, based on the first modelling results, we adjusted the parameters and reran the model to obtain our age–depth results. The final prior information used in this case was as follows: acc. shape = 1.5 and acc. mean = 20 for the gamma distribution; and mem. mean = 0.4 and mem. strength = 25 for the beta distribution. The IntCal20 calibration curve was used to convert the conventional radiocarbon ages input to calendar ages, and age modelling was run to achieve a 1 cm final resolution (Fig. 2). The ages were expressed in years before present (BP), where “present” is defined as 1950 CE.

Figure 2.

Age–depth model for Zhenbeitai (ZBT) loess–paleosol sequence based on 44 radiocarbon ages (this study) and 20 optically stimulated luminescence (OSL) ages (Wu et al., Reference Wu, Lu, Yi, Xu, Gu, Liang, Cui and Sun2019). Blue denotes the 14C ages, and green denotes OSL ages.

DSR

DSR was calculated using the age–depth model as follows:

$${\rm DSR\ } \! = ( {d_2-d_1} ) /( {a_2-a_1} ) $$

where d 1 and d 2 are consecutive depths and a 1 and a 2 are weighted mean model ages in the profile.

Numerical simulations

TraCE21K is a transient simulation of global climate evolution in the last 21,000 yr in the fully coupled Community Climate System v. 3 (CCSM3) (Liu et al., Reference Liu, Otto-Bliesner, He, Brady, Tomas, Clark and Carlson2009; He and Clark, Reference He and Clark2022). This simulation outputs a set of 4D model data sets to allow investigations of coupled atmosphere–ocean–sea ice–land surface mechanisms and terrestrial ecosystem feedbacks. We selected boreal summer (June–July–August) precipitation as an index of the EASM and boreal winter (December–January–February) wind at 1000 hPa level as an index of the EAWM over the CLP (107–114°E, 33–41°N, as shown in the range of Fig. 1c) to obtain simulation records of EAM variations over the past 14 ka in TraCE21K (Wen X.Y. et al., Reference Wen, Liu, Wang, Cheng and Zhu2016; Wang et al., Reference Wang, Lu, Cheng and Zhao2023).

The outputs of TraCE21K show that all forcings (ALL), insolation forcing (Orbit), greenhouse gases (CO2), meltwater flux forcing (MWF), and ice-sheet forcing (Ice Sheet) separately modulated EASM and EAWM variations during the Holocene optimum (Liu et al., Reference Liu, Otto-Bliesner, He, Brady, Tomas, Clark and Carlson2009; Otto-Bliesner et al., Reference Otto-Bliesner, Russell, Clark, Liu, Overpeck, Konecky, deMenocal, Nicholson, He and Lu2014; Wen X.Y. et al., Reference Wen, Liu, Wang, Cheng and Zhu2016; Wang et al., Reference Wang, Lu, Cheng and Zhao2023; Supplementary Figs. S1–S3).

RESULTS AND DISCUSSION

Enhanced EAM seasonality during the Holocene optimum

Forty-four samples were obtained from ZBT for AMS radiocarbon dating (Fig. 2, Supplementary Table S1). An additional 20 optically stimulated luminescence (OSL) dating ages from the ZBT section were collected previously (Wu et al., Reference Wu, Lu, Yi, Xu, Gu, Liang, Cui and Sun2019). Combining these two sets of data, we built an independent timescale for ZBT loess–paleosol deposits over the past 14 ka (Fig. 2). Along with this timescale, magnetic susceptibility at ZBT section, total organic carbon, and leaf wax n-alkane δD values of C29 at ZBT section are used as proxies for EASM strength (Liang et al., Reference Liang, Lu, Gu, Zhao, Liu, Zhang and Zhang2022), while the DSR distribution is a proxy of EAWM strength (Lu and Sun, Reference Lu and Sun2000; Lu et al., Reference Lu, Wang, Wang, Zhang and Markovi2022).

The DSR shows remarkable variations during the Holocene (ranging from 9 to 147 cm/ka with an average of 39.91 cm/ka) (Fig. 3e and f), presenting the first evidence that the EAWM strengthened during the Holocene optimum, a warm and humid period in East Asia (Lu et al., Reference Lu, Miao, Zhou, Mason, Swinehart, Zhang, Zhou and Yi2005, 2013a; Chen et al., Reference Chen, Xu, Chen, Birks, Liu, Zhang and Jin2015). In contrast, grain-size variations do not necessarily coincide with DSR variations (Fig. 3d), which is similar to what was observed in a European high-resolution 14C-dated loess record (Ujvari et al., Reference Ujvari, Stevens, Molnar, Demeny, Lambert, Varga, Jull, Pall-Gergely, Buylaert and Kovacs2017). These disagreements between grain size and DSR are likely due to grain size being impacted by complex processes at short timescales (Ujvari et al., Reference Ujvari, Kok, Varga and Kovacs2016).

Figure 3.

Synchronous strengthening of East Asian summer (EASM) and winter monsoons (EAWM) during the Holocene optimum. (a) Annual temperature anomaly trends from pollen-based reconstructions over the Northern Hemisphere landmass. The temperature anomaly is calculated against the recent 1 ka average annual temperature (Zhang et al., Reference Zhang, Wu, Cheng, Geng, Li, Sun, Yu, Lu and Guo2022). (b) Total organic carbon content (green line) (Lu et al., Reference Lu, Yi, Liu, Mason, Jiang, Cheng and Stevens2013a) and magnetic susceptibility (blue line) in the Zhenbeitai (ZBT) section. (c) Leaf wax n-alkane δD values of C29 in the ZBT section. Positive trend of δD values since the Mid-Holocene indicates both weakening of EASM and decrease in regional precipitation (Liang et al., Reference Liang, Lu, Gu, Zhao, Liu, Zhang and Zhang2022). (d) Grain size > 63 μm in the ZBT section in this study (grey line) and percentage of stabilized dune sites in northern China (bottle-green line) (Xu et al., Reference Xu, Mason, Xu, Yi, Bathiany, Yizhaq, Zhou, Cheng, Holmgren and Lu2020). (e) Dust sedimentation rate (DSR) of ZBT. Dots under line e are 44 calibrated 14C ages for ZBT, with an uncertainty interval of 2σ for 14C ages. (f) Average DSR of ZBT. The average DSR was calculated for low-DSR Late Holocene period, high-DSR Mid-Holocene period, low-DSR Early Holocene period, and sand layer unit. (g) Other EAWM records in the loess–desert transitional zone (Wen X.H. et al., Reference Wen, Li, Zheng, Yang, Niu and Shu2016; Gong et al., Reference Gong, Wang, Yang, Dong, Song, Guo and Chen2021). The locations of the records are shown in Fig. 1c. The green bar represents the period in which the EASM and EAWM synchronously strengthened.

Grain size is a result of combined effects of local/regional atmospheric circulation and environmental settings, including factors such as topography (Mason et al., Reference Mason, Nater, Zanner and Bell1999), source distance (Ding et al., Reference Ding, Derbyshire, Yang, Sun and Liu2005; Yang and Ding, Reference Yang and Ding2008; Yang et al., Reference Yang, Ding, Li, Wang, Jiang and Huang2015), aridity of source and sink, and vegetation cover (Pye, Reference Pye1995). Taking the example of ZBT, which is close to the Mu Us Desert dune fields, grain size is highly affected by the expansion and retreat of the dune fields, and large expansion and retreat in the Mu Us dune field has occurred since the last glacial maximum (Lu et al., Reference Lu, Miao, Zhou, Mason, Swinehart, Zhang, Zhou and Yi2005, 2013b). It is well known that the EASM was strong in the warm and humid climate of the Mid-Holocene (Lu et al., Reference Lu, Miao, Zhou, Mason, Swinehart, Zhang, Zhou and Yi2005, 2013a; Chen et al., Reference Chen, Xu, Chen, Birks, Liu, Zhang and Jin2015), as is further evidenced by the new proxies presented in this study (Fig. 3b–d). Stabilization of sand dunes in proximal dune fields is associated with strengthened EASM circulation; therefore, the maximum stabilization of dune fields occurred in the Mid-Holocene (Lu et al., Reference Lu, Miao, Zhou, Mason, Swinehart, Zhang, Zhou and Yi2005, 2013b; Xu et al., Reference Xu, Mason, Xu, Yi, Bathiany, Yizhaq, Zhou, Cheng, Holmgren and Lu2020; Fig. 3d, bottle-green line). An increased distance from the dust source would have led to an apparent decrease in grain size at the ZBT site. Thus, the grain-size variations were closely associated with sand dune changes, which are controlled by EASM precipitation. A fine particle size indicates a wetter climate in the transition zone between the loess and desert regions.

The DSR reflects only the number of particles deposited per unit time and area, which is determined by atmospheric loading, local trapping, and preservation conditions (Ujvari et al., Reference Ujvari, Stevens, Molnar, Demeny, Lambert, Varga, Jull, Pall-Gergely, Buylaert and Kovacs2017). The ZBT section is currently located at the margin of Mu Us dune fields. Surface sediments of the Mu Us dune field have dominated coarse silt and fine sand deposition, and the sediment accumulation rate is closely associated with dune field surface processes. Meanwhile, EAWM circulation, which determines the Mu Us dune field surface processes and atmospheric loading in winter, has varied significantly during the Holocene, forced by boreal winter insolation (Wen X.Y. et al., Reference Wen, Liu, Wang, Cheng and Zhu2016). At glacial–interglacial timescales, variations in vegetation can affect dust trapping and preservation, thus accounting for some portion of the DSR variations in the dune field marginal areas (Lu et al., Reference Lu, Yi, Xu, Zhou, Zeng, Zhu and Feng2013b). However, vegetation has not changed significantly during the Holocene on the CLP, as grasslands or grasslands with sparse trees have dominated this region throughout, leading to a nonsignificant change in vegetation (Jiang et al., Reference Jiang, Cheng, Yang, Yang and Wan2013). Therefore, DSR is a direct and sensitive proxy index of EAWM strength, and a high DSR during the Holocene optimum corresponds to strengthened EAWM circulation. Some other records in the loess–desert transitional zone also indicate increased aeolian dust activities during the Holocene optimum (Wen X.H. et al., Reference Wen, Li, Zheng, Yang, Niu and Shu2016; Gong et al., Reference Gong, Wang, Yang, Dong, Song, Guo and Chen2021; Fig. 3g), revealing a strengthened EAWM in this region.

Proxies of EASM intensity, such as magnetic susceptibility, total organic carbon, and leaf wax n-alkane δD values from the ZBT section (Liang et al., Reference Liang, Lu, Gu, Zhao, Liu, Zhang and Zhang2022; Fig. 3b and c), indicate increased EASM precipitation in the Holocene optimum, thus providing direct evidence of the simultaneous strengthening of the EASM and EAWM (Fig. 3). This finding is counterintuitive to our understanding of EASM and EAWM variations in a warm period, as previously understood from Chinese loess records, in which a stronger EASM is associated with a weakened EAWM, and vice versa. However, our findings provide the first proxy-based evidence that the EASM and EAWM are concurrently strengthened.

Variations in EASM and EAWM in the past 14 ka are generally driven by solar radiation, high-latitude ice sheets, atmospheric CO2, surface feedbacks such as vegetation changes, the El Niño–Southern Oscillation (ENSO), and the Atlantic Meridional Overturning Circulation (AMOC) (He et al., Reference He, Liu, Otto-Bliesner, Brady, Zhu, Tomas and Clark2021). A strengthened EASM during some part of the Holocene optimum has been demonstrated by several types of proxies, such as lacustrine records (Chen et al., Reference Chen, Xu, Chen, Birks, Liu, Zhang and Jin2015), stalagmites (Wang et al., Reference Wang, Cheng, Edwards, He, Kong, An, Wu, Kelly, Dykoski and Li2005; Cai et al., Reference Cai, Cheng, Ma, Mao, Breitenbach, Zhang, Xue, Cheng, Edwards and An2021), loess sediments (Lu et al., Reference Lu, Yi, Liu, Mason, Jiang, Cheng and Stevens2013a), and dune field change records (Lu et al., Reference Lu, Yi, Xu, Zhou, Zeng, Zhu and Feng2013b; Xu et al., Reference Xu, Mason, Xu, Yi, Bathiany, Yizhaq, Zhou, Cheng, Holmgren and Lu2020). Numerical simulation results have indicated that a strengthened atmospheric pressure gradient between the East Asian continent and adjacent ocean resulted in strengthened southerly winds (Wen X.Y. et al., Reference Wen, Liu, Wang, Cheng and Zhu2016) and increased precipitation (Sun et al., Reference Sun, Liu, Wan, Ning and Yan2020), indicating a strong EASM during the Holocene optimum.

Although EASM variations generally track the insolation curve, there exists an ~3 ka delayed response to the summer insolation peak (Lu et al., Reference Lu, Miao, Zhou, Mason, Swinehart, Zhang, Zhou and Yi2005; Fig. 4a). This delay of the EASM peak relative to insolation forcing is thought to result from the impact of relict ice sheets (Lu et al., Reference Lu, Miao, Zhou, Mason, Swinehart, Zhang, Zhou and Yi2005) and atmospheric CO2 forcing (Lu et al., Reference Lu, Yi, Liu, Mason, Jiang, Cheng and Stevens2013a). From the Early to Mid-Holocene, reduction of the residual Laurentide Ice Sheet (Lu et al., Reference Lu, Miao, Zhou, Mason, Swinehart, Zhang, Zhou and Yi2005, 2013a) could have enhanced EASM precipitation over northern China via atmospheric teleconnection. This enhancement cancelled out the insolation-induced precipitation decline and led to an enhanced EASM in the Mid-Holocene.

Figure 4.

East Asian summer (EASM) and winter monsoon (EAWM) variations at millennial scales and the possible forcing mechanisms. (a) The 30°N summer (June–July–August) and winter (December–January–February) insolation (Laskar et al., Reference Laskar, Robutel, Joutel, Gastineau, Correia and Levrard2004). (b) Numerically simulated EASM evolution as indicated by the average summer (June–July–August) precipitation over the Chinese Loess Plateau (CLP) (pink line) in TraCE21K and simulated EAWM evolution as indicated by the average winter (December–January–February) wind speed over the CLP (blue line). The model domain for the CLP is 107–114°E, 33–41°N. (c) Magnetic susceptibility of the Zhenbeitai (ZBT) section. (d) North Atlantic drift-ice records (Bond et al., Reference Bond, Kromer, Beer, Muscheler, Evans, Showers, Hoffmann, Lotti-Bond, Hajdas and Bonani2001). (e) Dust sedimentation rate (DSR) of the ZBT section. Numbers above d and e represent Bond events 1–8, and the grey bars indicate high-DSR events correlated with North Atlantic cold events. The dashed lines indicate the Holocene optimum–strengthened EASM and EAWM.

Similar to the EASM, the EAWM was also strengthened during some part of the Holocene optimum (Figs. 3 and 4), and this synchronous strengthening in the EASM and EAWM suggests that these two were separately forced. Sedimentary diatom assemblages and biogeochemical records from lacustrine sediments in southern China (Wang et al., Reference Wang, Li, Lu, Gu, Rioual, Hao and Mackay2012; Jia et al., Reference Jia, Bai, Yang, Xie, Wei, Ouyang, Chu, Liu and Peng2015) and a record of vertical thermal structure changes from the southern China Sea (Steinke et al., Reference Steinke, Glatz, Mohtadi, Groeneveld, Li and Jian2011), as well as some grain-size proxies in the loess–desert transition zone (Wen X.H. et al., Reference Wen, Li, Zheng, Yang, Niu and Shu2016; Gong et al., Reference Gong, Wang, Yang, Dong, Song, Guo and Chen2021; Fig. 3g), indicate an intensified EAWM sometime during the Holocene optimum. However, the EAWM as reconstructed based on grain size of loess in the central and south CLP is weak during the Mid-Holocene (Kang et al., Reference Kang, Du, Wang, Dong and Song2020), which is different from our DSR record. This mismatch is likely due to grain size being a much more complex parameter that is affected by multiple factors; stochastic processes often have modulated grain-size distribution in specific regions (Ujvari et al., Reference Ujvari, Kok, Varga and Kovacs2016). In our DSR record, the EAWM in the Early Holocene was not as intense as it was during the Holocene optimum, representing a delayed response of several thousand years relative to the winter insolation minimum (Fig. 4a). Perihelion shifts from boreal summer to winter from the Early to Late Holocene, as insolation was still relatively low in the Northern Hemisphere in winter during the Holocene optimum (~2–4% higher insolation than in the Early Holocene but ~4–7% lower compared with the present; Fig. 4a), may have resulted in low temperatures across the East Asian continent and thus enhanced land‒sea temperature differences and winter monsoon circulation. However, this winter insolation forcing cannot explain the enhanced EAWM strength in the Holocene optimum compared with that in the Early Holocene, and other factors, such as high-latitude forcing and regional surface feedbacks, may be responsible for the strengthened EAWM circulation.

Our findings are in contrast to the hypothesis that the EASM and EAWM exhibit antiphase variations during this warm period. We interpret this discovery as having two implications: (1) Both the EASM and EAWM synchronously strengthened during some period of the Holocene optimum, suggesting that climate seasonality is enhanced during warming periods, with the dry season becoming drier and the wet season becoming wetter in a warming world. (2) The long-term EAM climate variations cannot be solely dominated by seasonal insolation changes, and high-latitude temperatures, atmospheric CO2, regional vegetation, and AMOC may play roles in modulating long-term EAM variations.

Forcing mechanisms of EASM and EAWM variations

Our newly obtained records show that several short, strengthened EAWM events have occurred during the Holocene (Fig. 4e). These events were probably forced by cold events that occurred in the North Atlantic region (Bond et al., Reference Bond, Kromer, Beer, Muscheler, Evans, Showers, Hoffmann, Lotti-Bond, Hajdas and Bonani2001; Menviel et al., Reference Menviel, Skinner, Tarasov and Tzedakis2020; Walczak et al., Reference Walczak, Mix, Cowan, Fallon, Fifield, Alder and Du2020; Zhang et al., Reference Zhang, Barker, Knorr, Lohmann, Drysdale, Sun, Hodell and Chen2021). It is clear that increased DSR events are tightly linked to high-latitude cold events in the North Atlantic region (Bond et al., Reference Bond, Kromer, Beer, Muscheler, Evans, Showers, Hoffmann, Lotti-Bond, Hajdas and Bonani2001; Otto-Bliesner et al., Reference Otto-Bliesner, Russell, Clark, Liu, Overpeck, Konecky, deMenocal, Nicholson, He and Lu2014), especially during the 12–5 ka period (Fig. 4d and e). Bond events 4 to 8 were found to be well correlated with our DSR records within dating errors, showing that EAWM variations are highly sensitive to high-latitude forcing. However, Bond event 3 was not observed in the ZBT record after 5 ka, and this may have resulted from fewer cold events occurring in the North Atlantic region or from the low-resolution record of the surface loess deposit. The synchrony of the EAM climate and North Atlantic variations has also partly been indicated by previous isotopic records and aeolian sediments along the arid to semiarid transition zone of north-central China (Porter and Zhou, Reference Porter and Zhou2006; Wang et al., Reference Wang, Si, Li, Niu, Li, Wen and Yang2022).

In addition, our findings of a strong EAWM during some part of the Holocene optimum are more surprising, as it was postulated in many previous works that a warm world might reduce the winter monsoon circulation (Ljungqvist et al., Reference Ljungqvist, Krusic, Sundqvist, Zorita, Brattstrom and Frank2016), and the warm temperatures and humid climate of the Holocene optimum could be coupled with a weakened EAWM. Because winter insolation, which increased during the Early to Middle Holocene, cannot have affected the strengthened EAWM during the Holocene optimum (Fig. 4a and e), we suggest surface conditions such as relict ice sheets, sea level, and vegetation could have enhanced the seasonality of EAM variations during the Holocene optimum (Fig. 5b, Supplementary Fig. S4b). One interpretation is that cold Bond events at high latitudes have directly facilitated the occurrence of Holocene EAWM events at the Holocene optimum (Fig. 4). Over the optimum period, Bond events 4 and 5, within uncertainty of dating, may have forced increased EAWM events (Fig. 4) through atmospheric bridges such as the westerlies in the Northern Hemisphere (Porter and An, Reference Porter and An1995; Zhang et al., Reference Zhang, Barker, Knorr, Lohmann, Drysdale, Sun, Hodell and Chen2021). In addition, enhanced EASM circulation has brought more rainfall to this semiarid and arid region, through which surface runoff is strengthened and more sand/silt particle materials are deposited in dust source region, and grass grows during summertime. These processes may have resulted in more surface sediment accumulation on one hand, and vegetation development along with higher temperatures induced evaporation/transpiration on the other hand. Together, these processes caused regional drying and enhanced dust deposition as recorded in high DSR at our site. In addition, from the Early to Middle Holocene, an increase of sea ice in high-latitude led to enhanced albedo, together with a strengthening of Siberian High and a southward migration of the East Asian trough, inducing cooling in midlatitude Asia and strengthening the EAWM (Kaboth-Bahr et al., Reference Kaboth-Bahr, Bahr, Zeeden, Yamoah, Lone, Chuang, Lowemark and Wei2021). Our interpretation is that enhanced seasonality in the EAM determined EASM and EAWM variations during this warm period. Therefore, we suggest that the EASM and EAWM, a regional climatic circulation system in middle latitudes, were modulated by both high-latitude temperature variations and surface feedbacks under a background of insolation variations during the Holocene optimum.

Figure 5.

Holocene optimum (7–5 ka) summer (a) and winter (b) surface air temperature (SAT) minus the preindustrial period simulated by TraCE21K, with all forcing (Full), insolation forcing (Orbit), greenhouse gas forcing (GHG), meltwater flux forcing (MWF), and ice-sheet forcing (Ice Sheet). Insolation-forced SAT changes lead to both an increased temperature gradient from land to sea and from high latitudes to low latitudes during summer; thus, both indicate a strengthened East Asian summer monsoon (EASM), while the effects of other forcings are less than those of orbital forcing. During winter, orbital forcing increases the land-to-sea temperature gradient. However, high-latitude temperature exhibits a significant increase, leading to a decreased latitudinal temperature gradient. High-latitude forcing, such as ice-sheet forcing and the effect of the greenhouse gas forcing compensate for high-latitude temperature increase and play an important role in strengthening the East Asian summer winter monsoon (EAWM).

Using boreal summer (June–July–August) precipitation as an index of EASM and boreal winter (December–January–February) wind at 1000 hPa as an EAWM index, the simulated EAM variations over the past 14 ka by the full-forcing TraCE21K model are presented in Figure 4b (Liu et al., Reference Liu, Otto-Bliesner, He, Brady, Tomas, Clark and Carlson2009). The TraCE21K simulation results show that EASM and EAWM peaked synchronously in the Early Holocene (Fig. 4b, Supplementary Fig. S2, Full), revealing direct insolation forcing. Both EASM precipitation and EAWM wind at 1000 hPa changes during the entire Holocene are dominantly forced by decreasing boreal summer insolation and weakly increasing winter insolation, respectively (Supplementary Fig. S2). However, variations of atmospheric CO2 forcing, meltwater flux forcing (MWF), and ice-sheet forcing are slight. During the Holocene optimum, EASM responses to low-latitude orbital forcing result from summer temperature increases and enhanced sea-level pressure gradients between the East Asian continent and adjacent oceans (Fig. 5a, Supplementary Fig. S4a). However, variations in winter temperature and sea-level pressure gradient highlight both high- and low-latitude forcings (Fig. 5b, Supplementary Fig. S4b). The mismatch between our proxy record and the modelling results in East Asia reveals that the simulation is based on limited boundary conditions and thus needs further improvement. This is also supported by a recent broadscale pollen assemblage analysis conducted in the Northern Hemisphere, which also revealed widespread model–data contrast (Zhang et al., Reference Zhang, Wu, Cheng, Geng, Li, Sun, Yu, Lu and Guo2022).

CONCLUSIONS

We find that the EASM and EAWM strengthened simultaneously sometime during the Holocene optimum, with increased seasonality. In addition, the increased DSR events observed in our records are tightly linked to high-latitude cold events in the Northern Atlantic region, indicating high-latitude modulation of the EAWM. The TraCE21K simulation results show that EASM responses to low-latitude orbital forcing resulted from summer temperature increases and enhanced sea-level pressure gradients, while variations in winter temperature and sea-level pressure gradient highlight both high- and low-latitude forcing. The synchronously strengthened EASM and EAWM during the Holocene optimum demonstrate enhanced seasonality in the EAM during a warm period under the modulation of the high-latitude temperature, low-latitude insolation and regional feedbacks, revealing that the EAM may also exhibit new features under forcing conditions of future global warming by increasing anthropogenic greenhouse gasses.

Supplementary Material

The supplementary material for this article can be found at https://doi.org/10.1017/qua.2023.76

Acknowledgments

This research is supported by the National Natural Science Foundation of China (Grant Nos. 42021001, 41920104005, 41971103). All authors declare no conflict of interests relevant to this study.

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Figure 0

Figure 1. Climatological mean wind conditions in boreal summer (June–July–August) and winter (December–January–February) and sampling site at Zhenbeitai (ZBT). (a) Summer mean 850 hPa streamline based on NCEP reanalysis data from 1980 to 2010 (Kanamitsu et al., 2002). The red rectangle is the area shown in c (107–114°E, 33–41°N). (b) Winter mean 1000 hPa streamline based on NCEP reanalysis data from 1980 to 2010 (Kanamitsu et al., 2002). (c) Sampling site at ZBT and some other records in the loess–desert transitional zone.

Figure 1

Figure 2. Age–depth model for Zhenbeitai (ZBT) loess–paleosol sequence based on 44 radiocarbon ages (this study) and 20 optically stimulated luminescence (OSL) ages (Wu et al., 2019). Blue denotes the 14C ages, and green denotes OSL ages.

Figure 2

Figure 3. Synchronous strengthening of East Asian summer (EASM) and winter monsoons (EAWM) during the Holocene optimum. (a) Annual temperature anomaly trends from pollen-based reconstructions over the Northern Hemisphere landmass. The temperature anomaly is calculated against the recent 1 ka average annual temperature (Zhang et al., 2022). (b) Total organic carbon content (green line) (Lu et al., 2013a) and magnetic susceptibility (blue line) in the Zhenbeitai (ZBT) section. (c) Leaf wax n-alkane δD values of C29 in the ZBT section. Positive trend of δD values since the Mid-Holocene indicates both weakening of EASM and decrease in regional precipitation (Liang et al., 2022). (d) Grain size > 63 μm in the ZBT section in this study (grey line) and percentage of stabilized dune sites in northern China (bottle-green line) (Xu et al., 2020). (e) Dust sedimentation rate (DSR) of ZBT. Dots under line e are 44 calibrated 14C ages for ZBT, with an uncertainty interval of 2σ for 14C ages. (f) Average DSR of ZBT. The average DSR was calculated for low-DSR Late Holocene period, high-DSR Mid-Holocene period, low-DSR Early Holocene period, and sand layer unit. (g) Other EAWM records in the loess–desert transitional zone (Wen X.H. et al., 2016; Gong et al., 2021). The locations of the records are shown in Fig. 1c. The green bar represents the period in which the EASM and EAWM synchronously strengthened.

Figure 3

Figure 4. East Asian summer (EASM) and winter monsoon (EAWM) variations at millennial scales and the possible forcing mechanisms. (a) The 30°N summer (June–July–August) and winter (December–January–February) insolation (Laskar et al., 2004). (b) Numerically simulated EASM evolution as indicated by the average summer (June–July–August) precipitation over the Chinese Loess Plateau (CLP) (pink line) in TraCE21K and simulated EAWM evolution as indicated by the average winter (December–January–February) wind speed over the CLP (blue line). The model domain for the CLP is 107–114°E, 33–41°N. (c) Magnetic susceptibility of the Zhenbeitai (ZBT) section. (d) North Atlantic drift-ice records (Bond et al., 2001). (e) Dust sedimentation rate (DSR) of the ZBT section. Numbers above d and e represent Bond events 1–8, and the grey bars indicate high-DSR events correlated with North Atlantic cold events. The dashed lines indicate the Holocene optimum–strengthened EASM and EAWM.

Figure 4

Figure 5. Holocene optimum (7–5 ka) summer (a) and winter (b) surface air temperature (SAT) minus the preindustrial period simulated by TraCE21K, with all forcing (Full), insolation forcing (Orbit), greenhouse gas forcing (GHG), meltwater flux forcing (MWF), and ice-sheet forcing (Ice Sheet). Insolation-forced SAT changes lead to both an increased temperature gradient from land to sea and from high latitudes to low latitudes during summer; thus, both indicate a strengthened East Asian summer monsoon (EASM), while the effects of other forcings are less than those of orbital forcing. During winter, orbital forcing increases the land-to-sea temperature gradient. However, high-latitude temperature exhibits a significant increase, leading to a decreased latitudinal temperature gradient. High-latitude forcing, such as ice-sheet forcing and the effect of the greenhouse gas forcing compensate for high-latitude temperature increase and play an important role in strengthening the East Asian summer winter monsoon (EAWM).

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