The East Asian winter monsoon (EAWM) has significant impacts on the weather and climate, and subsequently on the economy and society, in East Asia during boreal winters, and its projection into the future is scientifically and practically significant. However, projections relying on geological EAWM reconstructions, which can compensate for instrumental record limitations, are still lacking and urgently needed. It is more promising to conduct prediction under the background of not only instrumental but also geological changes in the EAWM. We used grain-size records from four high-resolution, chronologically well-defined loess sections on the Chinese Loess Plateau to represent past EAWM intensity and its amplitudes. Our results show that the EAWM is weaker and has lower amplitudes during warm periods than during cold stages at various time scales. Moreover, instrumental records reveal that the EAWM shows a weak level and reduced interannual amplitudes after the mid-1980s under the context of global warming. We propose that the EAWM will experience long-term weakening and reduced (e.g., interannual) amplitudes under 21st century global-warming scenarios.

During boreal winters, the cold-core Siberian High atmospheric-pressure system interacts with the Aleutian Low to its east and the Equatorial Low to its south, forming the meridional East Asian winter monsoon (EAWM) in East Asia (Fig. 1A). The EAWM exerts significant impacts on the weather and climate over China, Korea, Japan, and surrounding regions, and acts as an important bridge for matter and energy cycling between the Northern Hemisphere mid-to high latitudes and the tropics (Chang et al., 2006). An intensified EAWM often causes cold and dry northerly winds, low temperatures, heavy snowfall, freezing, and dust storms in East Asia, as well as heavy convection in Southeast Asia (Chang et al., 2006; Ding et al., 2014). Subsequently, this intensified EAWM leads to severe impacts on the economy and society, particularly over East Asia, where it impacts a highly dense population (~1.6 billion) and concentrated industries. Therefore, it is scientifically and practically crucial to understand EAWM changes at various time scales and to project the EAWM into the future.

Figure 1.

Map showing the circulation system of the East Asian winter monsoon (EAWM) at 850 hPa (A) and locations of studied sites (red circles) on the Chinese Loess Plateau (B), redrawn from An et al. (2015) and Sun et al. (2021). GL—Gulang; JY—Jingyuan; WN2—Weinan; GB—Gaobai.

Figure 1.

Map showing the circulation system of the East Asian winter monsoon (EAWM) at 850 hPa (A) and locations of studied sites (red circles) on the Chinese Loess Plateau (B), redrawn from An et al. (2015) and Sun et al. (2021). GL—Gulang; JY—Jingyuan; WN2—Weinan; GB—Gaobai.

High-quality instrumental EAWM records cover mainly the past ~70 yr and provide valuable insights into changes in the EAWM intensity at decadal, annual, and seasonal scales (Chang et al., 2006; Wang and Lu, 2017; Ma and Chen, 2021). Various observed EAWM indexes support that the EAWM underwent a significant interdecadal weakening between the mid-1980s and the early 2000s; this weakening has been proposed to be mainly related to both global warming and internal climate-system variability (Ding et al., 2014; Ma and Chen, 2021). Moreover, modeling works based on the World Climate Research Programme Coupled Model Intercomparison Project (CMIP) suggest that there will be a long-term weakening of the EAWM under the background of global warming in the 21st century (Xu and Fan, 2021; Zhao et al., 2021). Up to now, projection of the EAWM has relied mainly on instrumental records. However, considering the limitation of instrumental data length, longer-time-scale EAWM records under various climate conditions are urgently needed for a more promising understanding and projection of the EAWM under present and future global-warming scenarios.

Changes in EAWM intensity at geological time scales can be reconstructed from loess, marine sediments, and lake sediments in East Asia (Liu and Ding, 1998; Liu et al., 2009; Huang et al., 2011). The eolian-formed loess on the Chinese Loess Plateau (CLP) is the product of the EAWM and can be used to reconstruct EAWM intensity changes at tectonic, orbital, millennial, and even centennial scales (Lu et al., 2002; Hao et al., 2012; Sun et al., 2012; Yang and Ding, 2014; Nie et al., 2015; Kang et al., 2018; Stevens et al., 2018). Moreover, loess on the CLP shows advantages in revisiting EAWM changes because of its basically continuous nature, relatively precise chronology, and high temporal resolution (Liu and Ding, 1998; An, 2000; Maher, 2016).

In this study, based on four high-resolution, chronologically well-defined loess sections on the CLP, we attempt to understand changes in the EAWM intensity and its amplitudes at various time scales. Combined with observed and projected EAWM data, we conduct logistic predictions of the EAWM changes with respect to long-term trends and amplitudes under 21st century warming scenarios.

Setting, Sections, and Sampling

The CLP is close to the core of the Siberian High (Fig. 1). The climate on the plateau is dominantly influenced by the cold-dry northwesterly EAWM during cold seasons and the warm-humid southeasterly East Asian summer monsoon (EASM) during warm seasons (Liu and Ding, 1998). The development of thick loess-paleosol sequences on the plateau is caused by the accumulation of dust transported by EAWM winds from the deserts and the Gobi in northwestern China and southern Mongolia and by river systems in and around the CLP, and subsequently by pedogenic processes that are closely related to the EASM (Liu and Ding, 1998; An, 2000; Nie et al., 2015; Maher, 2016; Zhang et al., 2021). The loess units indicate climate conditions with a relatively strong EAWM and relatively weak EASM, in contrast to the paleosol units. Loess-paleosol sequences on the CLP have been always regarded as materials that record the alternating dominance between the EAWM and EASM over the past ~2.6 m.y. (An, 2000).

We investigated four high-sedimentation-rate loess records. Located on the southeastern CLP (Fig. 1B), loess sections Gaobai (GB) and Weinan (WN2) were excavated and densely sampled for optically stimulated luminescence (OSL) dating and grain-size measurements (Kang et al., 2018, 2020; Fig. S1 in the Supplemental Material1). Another two loess sections, Gulang (GL) and Jingyuan (JY), are situated at the northwestern margin of the CLP (Fig. 1B) and were drilled or excavated for sampling (Sun et al., 2012, 2021; Fig. S1); the chronology and grain-size data from these two sections have been previously reported and were used for our analysis (Sun et al., 2012, 2021; Fig. 2). Both the GB and JY sections are located on the terraces of the Yellow River, the GL section is close to the southwestern corner of the Tengger Desert, and the WN2 section is situated at the center of a flat tableland with low topography that formed before the Holocene. The four sections' special topographical settings determine their capability of recording paleoclimate changes at high resolution.

Figure 2.

Lithology (orange), mean grain size (MGS; blue), and chronology (red) of sections GL (Gulang) (A; Sun et al., 2021), JY (Jingyuan) (B; Sun et al., 2012), GB (Gaobai) (C; Kang et al., 2020; this study), and WN2 (Weinan) (D; Kang et al., 2018; this study) on the Chinese Loess Plateau (see Fig. 1 for locations). In lithology columns, S and L indicate paleosol and loess units, respectively. In B–D, dashed red curve (weighted mean age) and dashed gray curve (95% confidence interval) indicate Bayesian age-depth models, and gray error bays show uncertainties on OSL ages at ±1σ. Light blue and pink bands indicate relatively cold and warm periods, respectively (MIS—marine isotope stage; LGM—Last Glacial Maximum; HTM—Holocene Thermal Maximum; MWP—Medieval Warm Period; LIA—Little Ice Age), and yellow bands in B and C mark last deglaciation (LD). Original data are provided in the Supplemental Material (see footnote 1).

Figure 2.

Lithology (orange), mean grain size (MGS; blue), and chronology (red) of sections GL (Gulang) (A; Sun et al., 2021), JY (Jingyuan) (B; Sun et al., 2012), GB (Gaobai) (C; Kang et al., 2020; this study), and WN2 (Weinan) (D; Kang et al., 2018; this study) on the Chinese Loess Plateau (see Fig. 1 for locations). In lithology columns, S and L indicate paleosol and loess units, respectively. In B–D, dashed red curve (weighted mean age) and dashed gray curve (95% confidence interval) indicate Bayesian age-depth models, and gray error bays show uncertainties on OSL ages at ±1σ. Light blue and pink bands indicate relatively cold and warm periods, respectively (MIS—marine isotope stage; LGM—Last Glacial Maximum; HTM—Holocene Thermal Maximum; MWP—Medieval Warm Period; LIA—Little Ice Age), and yellow bands in B and C mark last deglaciation (LD). Original data are provided in the Supplemental Material (see footnote 1).

Chronology and Proxy

We applied the single-aliquot regenerative-dose OSL dating protocol (Murray and Wintle, 2000) to fine quartz grains (4–11 μm) from the GB and WN2 sections, the details of which can be found in previous studies (Kang et al., 2018, 2020). The obtained 40 ages (ca. 28.1–3.9 ka; Table S1) at section GB and 10 ages (ca. 1.3–0.2 ka; Table S1) at section WN2 were incorporated into a Bayesian age-depth model (Blaauw and Christen, 2011) to produce the chronology, which was also adopted for the 15 OSL ages (ca. 31.7–1.8 ka) at section JY (Sun et al., 2012; Kang et al., 2018, 2020; Fig. 2; Fig. S2). The chronology at section GL, which covers the past ~700 k.y. (Fig. 2A), was achieved through correlation between loess grain size and speleothem δ18O records using 13 first-order and 22 second-order tie points (Sun et al., 2021), and its reliability over the past ~60 k.y. is well confirmed by the OSL-based chronology (Sun et al., 2012, 2021; Fig. S3). The robust chronology of each section is the critical basis for our reconstruction of past EAWM changes. Subsequently, we calculated the mean time resolutions for specific periods in each section (Table S2), which are a prerequisite for determining the temporal resolutions of the changes in the EAWM.

Grain-size measurements at section GB (below 2.6 m depth) were the same as those in our recent study (Kang et al., 2020). The mean grain size (MGS) of 2 cm intervals was finally used for the four studied sections (Fig. 2). As widely proposed in previous studies (An et al., 1991; Liu and Ding, 1998; Sun et al., 2012; Kang et al., 2020), we also argue that the MGS of the studied sections mainly reflects the EAWM intensity, with a larger grain size indicating a stronger EAWM. Then, the MGS time series of each section was linearly interpolated and subsequently smoothed using an adjacent-averaging approach in different time windows (10, 1, and 0.1 k.y.; Fig. S4). The resultant residual MGS records (interpolated minus smoothed MGS) are used to represent variations in EAWM amplitude.

Geological Changes

Loess MGS and residual MGS records of the four studied sections enable us to reconstruct changes in the EAWM intensity at orbital, multimillennial, multicentennial, and multidecadal scales during specific periods (Fig. 3). Moreover, we focus on comparisons of the EAWM intensity under relatively warm and cold periods.

Figure 3.

Multi-time-scale changes in the East Asian winter monsoon (EAWM) intensity represented by mean grain size (MGS) and residual (interpolated minus smoothed) MGS at sections GL (Gulang) (A), JY (Jingyuan) and GB (Gaobai) (B), and WN2 (Weinan) (C) on the Chinese Loess Plateau (see Fig. 1 for locations), with larger and smaller values indicating stronger and weaker EAWM, respectively. Light blue and pink bands indicate relatively cold and warm periods, respectively (MIS—marine isotope stage; LGM—Last Glacial Maximum; HTM—Holocene Thermal Maximum; MWP—Medieval Warm Period; LIA—Little Ice Age), and yellow band in B marks last deglaciation (LD). Limited by resolution (Table S2 [see footnote 1]), multidecadal-scale data covering Holocene at sections JY and GB were not used.

Figure 3.

Multi-time-scale changes in the East Asian winter monsoon (EAWM) intensity represented by mean grain size (MGS) and residual (interpolated minus smoothed) MGS at sections GL (Gulang) (A), JY (Jingyuan) and GB (Gaobai) (B), and WN2 (Weinan) (C) on the Chinese Loess Plateau (see Fig. 1 for locations), with larger and smaller values indicating stronger and weaker EAWM, respectively. Light blue and pink bands indicate relatively cold and warm periods, respectively (MIS—marine isotope stage; LGM—Last Glacial Maximum; HTM—Holocene Thermal Maximum; MWP—Medieval Warm Period; LIA—Little Ice Age), and yellow band in B marks last deglaciation (LD). Limited by resolution (Table S2 [see footnote 1]), multidecadal-scale data covering Holocene at sections JY and GB were not used.

At the orbital scale during the past ~700 k.y., the section GL MGS records show that the EAWM is greatly enhanced during even marine isotope stages (MISs) and/or glacial periods, in contrast to odd MISs and/or interglacial periods (Sun et al., 2021; Fig. 3A). With regard to the recent glacial-interglacial periods, the EAWM is much stronger during extreme glacial MIS 2 than during interglacial MIS 1, as revealed from the JY and GB sections (Sun et al., 2012; Kang et al., 2020; Fig. 3B). The MGS records for both the JY and GB sections also provide multimillennial-scale changes in the EAWM intensity over the past ~30 k.y. (Sun et al., 2012; Kang et al., 2020; Fig. 3B). The EAWM was extremely strengthened during the Last Glacial Maximum, followed by a gradual retraction during the last deglaciation, and was remarkably weakened during the Holocene Thermal Maximum (Fig. 3B). At the multicentennial scale, the MGS results at section WN2 indicate that the EAWM was clearly intensified during the Little Ice Age, in contrast to the previous Medieval Warm Period (Kang et al., 2018; Fig. 3C). Clearly, the global and/or Northern Hemisphere temperature is higher at different levels during odd MISs and/or interglacial periods, the Holocene Thermal Maximum, and the Medieval Warm Period than during even MISs and/or glacial periods, the Last Glacial Maximum, and the Little Ice Age, respectively (Snyder, 2016; Osman et al., 2021). Temperature and its related ice volume probably mainly contribute to the above geological-time-scale EAWM changes by altering the thermal contrast between the cold Asian continent and the adjacent warm oceans (Ding et al., 1995; An, 2000; Hao et al., 2012; Kang et al., 2020; Sun et al., 2021).

The residual MGS at section GL indicates that EAWM amplitudes at multimillennial and multicentennial scales are clearly low during odd MISs and/or interglacial periods, in contrast to those during even MISs and/or glacial periods over the past ~700 k.y. (Sun et al., 2021; Fig. 3A). During the past ~30 k.y., the amplitudes of the EAWM at the multicentennial scale are the largest during the Last Glacial Maximum, followed by a gradually decreasing trend during the last deglaciation, and they are the smallest during the Holocene Thermal Maximum, as shown by the JY and GB sections (Sun et al., 2012; Kang et al., 2020; Fig. 3B). At the multidecadal scale, the residual MGS at sections JY and GB shows that the amplitudes of the EAWM significantly increased during the Last Glacial Maximum, followed by a progressive decrease during the last deglaciation (Sun et al., 2012; Kang et al., 2020; Fig. 3B), and that at section WN2 represents slightly enhanced amplitudes of the EAWM during the Little Ice Age when compared with those during the Medieval Warm Period (Kang et al., 2018; Fig. 3C). Therefore, it is proposed that the amplitudes of the EAWM at a specific time scale are controlled by the corresponding climate context (Sun et al., 2021).

In addition to the above four loess sections, a great number of loess sections on the CLP also robustly support our findings (e.g., Hao et al., 2012; Stevens et al., 2018; Sun et al., 2021). In summary, loess grain-size records systematically demonstrate that the EAWM is weaker and has lower amplitudes during warm periods than during cold stages at various geological time scales.

Instrumental Changes

Robust instrumental data provide us with an opportunity to test whether the above EAWM changing pattern over larger geological time scales is still promising at finer time scales. At the multidecadal scale, the global and/or Northern Hemisphere surface temperature was relatively low between the late 1940s and the late 1970s and has shown a remarkable increasing trend since ca. 1980 (Morice et al., 2021; Fig. 4A). Correspondingly, a strong EAWM period occurred from the late 1940s to the mid-1980s, and subsequently, the EAWM has been weakening until now (Miao et al., 2020; Li et al., 2021; Wen et al., 2021; Fig. 4B). The above significant shift in the EAWM is closely associated with global warming and internal climate-system variability (Ding et al., 2014; Ma and Chen, 2021). Global warming can lead to a reduced land-sea thermal contrast during boreal winters and a subsequently weakened EAWM (Ding et al., 2014). Moreover, the observed EAWM index (EAWMI) shows that the interannual amplitudes of the EAWM seem to be broadly reduced after the mid-1980s (Miao et al., 2020; Li et al., 2021; Wen et al., 2021; Fig. 4B) when global warming significantly accelerated (Morice et al., 2021; Fig. 4A). However, limited by the time length, it is difficult to analyze larger-time-scale (e.g., decadal-scale) EAWM amplitudes based on instrumental data.

Figure 4.

Observed and projected East Asian winter monsoon (EAWM) index (EAWMI). (A) Global and Northern Hemisphere annual surface temperature anomalies relative to 1961–1990 CE (Morice et al., 2021). (B) Observed EAWMI in December-January-February during 1948–2017 (green, Miao et al., 2020; red, Wen et al., 2021) and in December during 1958–2017 (purple, Li et al., 2021), calculated from the Siberian High, the East Asian trough, and the East Asian jet stream. (C) Coupled Model Intercomparison Project (CMIP)–projected EAWMI during 2006–2099 under different Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathways (SSP) scenarios (Zhao et al., 2021), with dashed lines indicating corresponding long-term variation trends.

Figure 4.

Observed and projected East Asian winter monsoon (EAWM) index (EAWMI). (A) Global and Northern Hemisphere annual surface temperature anomalies relative to 1961–1990 CE (Morice et al., 2021). (B) Observed EAWMI in December-January-February during 1948–2017 (green, Miao et al., 2020; red, Wen et al., 2021) and in December during 1958–2017 (purple, Li et al., 2021), calculated from the Siberian High, the East Asian trough, and the East Asian jet stream. (C) Coupled Model Intercomparison Project (CMIP)–projected EAWMI during 2006–2099 under different Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathways (SSP) scenarios (Zhao et al., 2021), with dashed lines indicating corresponding long-term variation trends.

Future Changes

Both our geological reconstructions and the instrumental observations consistently suggest that a warmer global and/or Northern Hemisphere climate can lead to weaker and lower-amplitude EAWM at various time scales. If the above configuration pattern is still applicable in the warming future (e.g., the 21st century), it implies that the EAWM will undergo a long-term weakening trend and decreasing (e.g., interannual) amplitudes. Indeed, a weakened EAWM under different future warming scenarios was obtained from numerous projection studies (Ma and Chen, 2021; Xu and Fan, 2021; Zhao et al., 2021). For example, the projected EAWMIs based on CMIP Phases 5 and 6 (CMIP5 and CMIP6) all support a long-term weakening EAWM during the 21st century (Zhao et al., 2021; Fig. 4C). Moreover, the Siberian High, which is closely related to the EAWM, was also predicted to be persistently attenuated during the 21st century (Li and Gao, 2015; Fig. S5). However, due to the weak ability to simulate the EAWM's interannual variability, the reduced (interannual) amplitudes of the EAWM under future warming were not observed using CMIP5 and CMIP6 (Fig. 4C; Ma and Chen, 2021).

Geological and instrumental EAWM records indicate that the EAWM was weaker and had lower amplitudes during warm periods than during cold periods at various time scales. We propose that the EAWM will experience a long-term weakening trend and reduced (e.g., interannual) amplitudes under 21st-century warming scenarios. A weakened future EAWM possibly implies effects such as decreased wind speed, attenuated dust storms, and reduced low-temperature extremes during winters over East Asia, as already revealed by the observed data during the recent warming decades (Guo et al., 2011; CMA Climate Change Centre, 2021; Fig. S6), and is also not beneficial for cold-season removal of air pollutants particularly in northern China.

We appreciate the constructive comments and suggestions by Junsheng Nie and two anonymous reviewers. We thank Youbin Sun for helpful discussion, and Yan Yan, Shuyu Zhao, Tao Wang, and Tao Wen for providing original data in Figures 1, 4, and S5. This study was supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao) (grant 2022QNLM050202-1), the Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) (grant XDB40010100), the National Natural Science Foundation of China (grant 41772177), and the Youth Innovation Promotion Association of CAS (grant 2018447).

1Supplemental Material. Details of sampling, outcrops, OSL ages, chronology, interpolation, smoothing, and instrumental and projected data related to the EAWM. Please visit https://doi.org/10.1130/GEOL.S.20352852 to access the supplemental material, and contact editing@geosociety.org with any questions.
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