The SST and δ18Ow records at Site U1429 were high-pass filtered to eliminate orbital-scale components to investigate the characteristics of abrupt variance (1–10 kyr periodicity) (Fig. 1C, Materials and Methods, Fig. S2, S3). We applied wavelet analysis to assess the coherence and phase relationships in the time–frequency space between SST and δ18Ow 19 (Fig. 1D). Considering the following reasons, we interpreted the observed millennial-scale variability as being dominated by changes in the freshwater influx from Yangtze River. The factors that potentially influence past δ18Ow values are ocean mixing, river runoff, and the δ18Ow endmember8,20. Shoreline migration and changes in geographic configuration due to sea-level change may alter the extent of mixing between δ18O-enriched seawater from the Kuroshio Current and δ18O-depleted river water on the orbital timescales8 but these factors are minimal on the millennial timescales. A high variability in the δ18Ow endmember in the western tropical Pacific (WTP) source region and freshwater δ18Ow itself may obscure changes in the freshwater influx from Yangtze River to the ECS. These δ18Ow endmembers have little influence on δ18Ow variability in the ECS21, although this has only been assessed for the Marine Isotope Stage (MIS) 321 owing to a lack of high-resolution data in the WTP. Nonetheless, the situation must be similar during interglacials and other glacials considering that δ18Ow endmember variability in the source regions is similar to or less than MIS 3, as indicated by the Chinese δ18Osp record for the freshwater δ18Ow endmember22. Therefore, freshwater influx from Yangtze River induced by basin-wide precipitation is considered the main factor influencing the millennial-scale δ18Ow signal at Site U1429.
The wavelet analysis revealed that the coherence between SST and δ18Ow has varied over the last 400 ka. SST and δ18Ow tended to be synchronous in the later stages of interglacials from the early through to middle glacial periods (from early MIS 3 through to late MIS 5, from middle MIS 6 through to late MIS 7, and from early MIS 8 through to late MIS 9), whereas SST and δ18Ow were mostly uncoupled during full interglacials and full glacials. In the youngest coherent interval (~40–110 ka), synchronous variations become recognisable from ~110 ka (late interglacial) and intermittently persist until ~40 ka (middle glacial). In contrast, during the full glacial interval after 40 ka, SST and δ18Ow in the ECS tended to be decoupled. Similar trends were found during MIS 6–7 and MIS 8–9. At intervals of high coherence, the phase indicates that drying (an increase in δ18Ow) was concomitant with cooling (180° phase lag) or slightly lagged by ~0.5 ka or less. This negative correlation between SST and δ18Ow (i.e. cooling and increasing salinity) is also evident in a direct comparison between the SST and δ18Ow time-series (Fig. 1C and S4–S7); near-simultaneous millennial-scale responses were observed during Heinrich events 5, 6, 7a, 8, 9, 10, and 11 during MIS 3 through to late MIS 5 (~40–110 ka), and abrupt climate events between the middle MIS 6 to late MIS 7 (~160–210 ka) and between early MIS 8 and late MIS 9 (~290–320 ka) (Fig. 1). A relatively broad interval of high coherence with high confidence was also found in early MIS 7 (~230–250 ka), where the phase relationship is ~180° opposite to the other intervals, suggesting a different forcing mechanism.
We infer that the ECS SST and δ18Ow signals reflect different climate forcings or internal feedbacks during intervals of low coherence but respond to similar mechanisms during times of high coherence. The apparent link between the degree of coupling and glacial state implies that aspects of orbital-scale forcing, such as insolation, atmospheric CO2 concentrations, and ice-sheet extent, might be involved. However, a comparison between Northern Hemisphere local insolation, wherein the precession cycle is the most prominent, and the ECS wavelet coherence does not show similarity (Fig. 1B, 1C). This implies that orbital configuration and the associated local insolation (31 °N) changes have little effect on the coherence pattern. For atmospheric CO2 and ice volume, the high coherence times correspond to ‘intermediate’ atmospheric CO2 levels and ice volume conditions, which we define as an ice volume equivalent to a −10 to −90 m reduction in the sea level, including both middle–late interglacial and early–middle glacial periods.
To consider the possible linkage between the intermediate glacial condition and the high coherence between δ18Ow and temperature in the ECS, we examined the changes in the spectral power of millennial-scale variance in the North Atlantic palaeoceanographic record as a measure of frequency and magnitude of abrupt hemispheric climate changes. A comparison between coherence in the ECS record and the wavelet spectrum of the relative abundance of Neogloboquadrina pachyderma sinistral at ODP Site 98323 (see Methods) revealed some similarities; periods of high coherence corresponded to a high spectral power in the North Atlantic record (Fig. 1D, 1E). The high spectral power in the North Atlantic wavelet reflects strong millennial-scale climate events, such as Heinrich events and DO oscillations24. Thus, we hypothesise that the magnitude and duration of Atlantic millennial-scale perturbations have a strong influence on the synchronicity of SST and δ18Ow in the ECS. Specifically, a strong period of Atlantic variability is required to produce coherent variations between these proxies in the ECS. Indeed, we identified counterparts in the North Atlantic for all the ECS cooling/drying events during the high-coherence intervals (dashed lines in Figs. S4–S7), indicating that both SST and δ18Ow are paced by events in the North Atlantic.
Modelled climate instability in response to abrupt changes in the Atlantic Meridional Overturning Circulation (AMOC) under different global climate states shows that the intermediate glacial state (the 15 ka condition in this case) is the most favourable for generating millennial-scale variability, whereby both Northern Hemisphere ice sheets and atmospheric CO2 concentration are crucial factors24. Based on the same model, the signal from abrupt events in the North Atlantic propagates on a hemispheric scale within a few hundred years24. Therefore, compared with other mean states, the intermediate glacial condition is more conducive to simultaneous cooling and drying in East Asia.
These findings indicate that abrupt climate change in East Asia is driven by two primary mechanisms: Atlantic perturbations and regional variability (feedbacks) primarily dependent on the magnitude of North Atlantic events, and the mean global climate state. To further examine whether the amplitude of East Asian climate variability is dependent on these forcings, we calculated the standard deviation for each glacial condition (Methods, Fig. S8), that is, full interglacial (>−10 m sea level), intermediate glacial (−10 to −90 m), and full glacial (<−90 m). We found the highest standard deviation under the intermediate glacial state for both SST and δ18Ow. Thus, the magnitudes of climate events in East Asia tend to increase when forced from outside the region. We hypothesise that strong climatic events in the North Atlantic, such as Heinrich events, quickly propagate worldwide, affecting East Asian climate variability during intermediate glacial states. Nevertheless, a relatively high climate variability in the ECS is also evident during full interglacials and glacial maxima, suggesting that regional (internal) sources of variability are also important. For example, during full interglacial and glacial states, regional dynamics tended to dominate the Atlantic climate forcing or respond differently at certain times, such as during early MIS 7 (~230–250 ka) when SST and δ18Ow were positively correlated, indicating warming and increasing salinity. This positive correlation can be explained by the changes in the extent of mixing between cold, diluted water formed near Yangtze River mouth and warm, saline water from the Kuroshio Current. A positive correlation between SST and δ18Ow is also observed during the Holocene, the early stage of the last deglaciation25, and at the maxima of MIS 5 (Fig. 1D), suggesting that ocean mixing has dominated during some full interglacial and glacial periods. In contrast, the periods with a negative correlation between SST and δ18Ow cannot be reasonably explained by ocean mixing. Rather, we interpret this relationship as reflecting the dominance of the atmospheric signal over ocean mixing.
The Heinrich events that occurred during full glacial stages (e.g., H-1 and H-2) are not correlated with the low SST and high δ18Ow signals in the ECS; however, MIS 6 is an exception, when SST and δ18Ow are negatively correlated with high coherence, especially around H-11. Thus, we infer that the mean temperature state during full glacial stages is critical for explaining millennial-scale variability in East Asia, as the full glacial period of MIS 6 was slightly (~1°C) warmer than other glacial stages based on the ECS Mg/Ca-SST record (Figs. S4–S7).
We directly compared our ECS data with the Greenland (NGRIP) record over the last 100 ky to elucidate the mechanism of signal propagation from the North Atlantic to East Asia. Specifically, we performed wavelet coherence analysis to clarify parameters in the ECS record that are more coherent with the Greenland isotope record (Fig. 2). The ECS δ18Opf and Greenland δ18O records show the largest coherent area. The ECS SST and Greenland δ18O records indicate a similar high degree of coherence, whereas the ECS δ18Ow and Greenland δ18O records show the least coherence (Fig. 2). The high level of coherence between the ECS SST and Greenland δ18O likely stems from the faster propagation of the temperature signal from the North Atlantic (via the Westerlies) relative to a more local and complex response to rainfall. In this regard, rainfall variability reflects inherent natural variability more so than temperature, which is dominated by external signals (from the North Atlantic) only during high-magnitude events, such as Heinrich events. This hypothesis and more in-depth investigation of the underlying mechanisms could be tested using a coupled climate model simulation that embeds water δ18O changes with different greenhouse gas, ice-volume, and sea-level boundary conditions.
Overall, our results provide an important perspective for interpreting δ18Osp records in the ECS. In particular, our records have the advantage of covering the interval from 260 to 310 ka, when millennial-scale variability is not well resolved in the δ18Osp record. Indeed, our δ18Opf record is well correlated with the δ18Osp record on a millennial scale except for 260–310 ka. The SST and δ18Ow records also show strong correlations with δ18Osp, although to a less extent (Fig. S9). Based on our wavelet coherence analysis of the three ECS records (δ18Opf, SST, and δ18Ow) vs. δ18Osp, coherence was reduced once the sea level and temperature effects were removed from the δ18Opf signal, although some high coherence areas remain in the intermediate glacial states between δ18Ow and δ18Osp (Fig. S10). This indicates that both SST and δ18Ow are essential components of the δ18Osp signal, and that the global condition, such as sea level, is the crucial factor affecting local rainfall variability in East Asia. Overall, our findings highlight the importance of the global background condition in determining the behaviour of the East Asian climate, offering a valuable baseline for predicting future climate change.