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In-phase and out-of-phase behavior of the East Asian summer and winter monsoons recorded in the South Yellow Sea sediment over the past 9.5 ka

Published online by Cambridge University Press:  01 September 2020

Liyan Wang
Affiliation:
Key Laboratory of Submarine Sciences and Prospecting Techniques, MOE, and College of Marine Geosciences, Ocean University of China, Qingdao 266100, China College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China
Guangxue Li*
Affiliation:
Key Laboratory of Submarine Sciences and Prospecting Techniques, MOE, and College of Marine Geosciences, Ocean University of China, Qingdao 266100, China
Linmiao Wang
Affiliation:
Key Laboratory of Marine Sedimentology and Environmental Geology, First Institute of Oceanography, SOA, Qingdao 266061, China
Wenchao Zhang
Affiliation:
Key Laboratory of Submarine Sciences and Prospecting Techniques, MOE, and College of Marine Geosciences, Ocean University of China, Qingdao 266100, China
Yang Zhang
Affiliation:
Key Laboratory of Submarine Sciences and Prospecting Techniques, MOE, and College of Marine Geosciences, Ocean University of China, Qingdao 266100, China
Yong Liu
Affiliation:
Key Laboratory of Submarine Sciences and Prospecting Techniques, MOE, and College of Marine Geosciences, Ocean University of China, Qingdao 266100, China
Xiangdong Wang
Affiliation:
Qingdao Blue Earth Big Data Technology Co., Ltd, Qingdao 266400, China
Haoyin Wang
Affiliation:
Key Laboratory of Ocean and Marginal Sea Geology, Chinese Academy of Sciences, Guangzhou 510301, China
*
*Corresponding author at: Key Laboratory of Submarine Sciences and Prospecting Techniques, MOE, and College of Marine Geosciences, Ocean University of China, Qingdao 266100, China. E-mail address: estuary@ouc.edu.cn (G. Li).
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Abstract

The variability of the East Asian monsoon (EAM) during the Holocene exhibits significant regional response, and its evolution needs further discussion. A well-dated, high-resolution sea-surface temperature record based on long-chain unsaturated alkenones, grain-size data, and clay mineral assemblages from the South Yellow Sea sediment is presented to investigate the sedimentary provenance and reconstruct the EAM over the past 9.5 ka. The results show that the sediments are most likely supplied by the Huanghe. The evolution of the East Asian summer monsoon (EASM) can be divided into three periods: strong and relatively stable conditions during 9.5–7.0 ka, weakened conditions during 7.0–1.5 ka, and strengthened conditions during 1.5–0 ka. The East Asian winter monsoon (EAWM) has experienced five periods: weakened conditions during 9.5–6.7 ka, weak and relatively stable conditions during 6.7–5.6 ka, strong and relatively stable conditions during 5.6–2.6 ka, strengthened conditions during 2.6–1.5 ka, and weak and stable conditions during 1.5–0 ka. Moreover, in-phase correlation was found between the EAWM and EASM at the orbital time scale in response to orbital-driven solar insolation, but out-of-phase correlation at a centennial time scale is predominantly associated with solar activity.

Information

Type
Research Article
Copyright
Copyright © University of Washington. Published by Cambridge University Press, 2020
Figure 0

Figure 1. Maps of the study area in the western North Pacific and regional surface current system. (a) The locations of the Yellow Sea, East China Sea, and South China Sea; the sphere of influence of the Asian monsoon; and the mean location of the westerly jet stream. The red box represents the area shown in b. (b) The ocean circulation of the region (modified from Nan et al., 2017). The red lines indicate the warm current systems and the blue lines indicate the cold coastal currents. Shaded areas represent the muddy areas, namely: 1, the Shandong mud wedge; 2, the central muddy deposit of the SYS; and 3, the southwest muddy deposit of Jeju Island. BS, Bohai Sea; NYS, North Yellow Sea; SYS, South Yellow Sea; ECS, East China Sea; SCS, South China Sea; KCC, Korean Coastal Current; YSCC, Yellow Sea Costal Current; YSWC, Yellow Sea Warm Current; TC, Tsushima Current; SPCC, Shandong Peninsula Coastal Current; CDW, Changjiang Diluted Water; KC, Kuroshio Current; TWC, Taiwan Warm Current; SEC, Shelf Edge Current. Orange crosses show the locations of the climate proxy records in the monsoon region. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Figure 1

Figure 2. Sedimentary characteristics of borehole core YS01. (a) Lithologic log for 0–11 m in depth. Ages were obtained by AMS 14C dating. SC, silty clay; CSi, clayey silt; S-Si-C, sand–silt–clay; S, sand. (b) Sedimentation rate (m/ka, blue line). (c) Age–depth model (red line). (d) Content of sand fractions (%). (e) Content of silt fractions (%). (f) Content of clay fractions (%). (g) Mean grain size (μm). h) Sorting. (i) Size–frequency plots and cumulative probability plots for sediments at 1.0 m, 3.0 m, 7.0 m, and 10.0 m. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Figure 2

Table 1. AMS radiocarbon dating results.

Figure 3

Figure 3. (color online) Variations in the environmental proxies recorded in core YS01. (a) Mz (μm) mean grain size, which indicates the concentration trend of grain-size distribution. (b, d) Sensitive fractions (%). (c, e) Mean grain size for sensitive fraction (μm). (f) ${\rm U}{{K^{\prime}} \over {37}}$-based sea-surface temperatures (SSTs) calibrated with the equation described in Müller et al. (1998).

Figure 4

Figure 4. (color online) Downcore variation of clay mineral assemblages (a–d), illite chemistry index (e), and illite/chlorite ratio (f).

Figure 5

Table 2. Comparison of clay mineral assemblage between core YS01 and potential provenances.

Figure 6

Figure 5. (color online) Ternary diagram (a) and discrimination plot (b) showing the variation in clay mineral assemblages of core YS01 from the South Yellow Sea. The clay mineral data of the potential sources are also plotted for comparison.

Figure 7

Figure 6. (color online) East Asian summer monsoon (EASM) variations on the orbital time scale during the Holocene. (a) Summer insolation at 35°N, W/m2(Laskar et al., 2004). (b) EASM wind index in TRACE21 (Wen et al., 2016); JJA, the simulated meridional wind speed in June-July-August. (c) Variations in the content of the coarser grain-size component (this study). (d) δ18O variability in stalagmites from the Dongge Cave (China; Wang et al., 2005). (e) Summer monsoon index derived from Qinghai Lake (An et al., 2012); SMI, Summer monsoon index. (f) Bulk Ti content from Cariaco basin sediments from Ocean Drilling Project (ODP) Site 1002 (Haug et al., 2001), which represents the Intertropical Convergence Zone (ITCZ) shift.

Figure 8

Figure 7. (color online) East Asian winter monsoon (EAWM) variations on the orbital time scale during the Holocene. (a) Winter insolation at 35°N and 65°N, W/m2(Laskar et al., 2004). (b) Lake Qinghai westerlies climate index (WI; flux of >25 μm fraction; An et al., 2012). (c) Gaussian smoothed (200 yr) GISP2 potassium (K+; ppb) ion proxy for the Siberian High (Mayewski et al., 2004). (d) EAWM wind index in TRACE21 (Wen et al., 2016); DJF, December-January-February. (e) The δ18O record from core SK-2 in the western North Pacific (Sagawa et al., 2014). (f) Sea-surface temperature (SST) gradient between the surface and thermocline waters in the South China Sea, core MD05-2904 (Steinke et al., 2011), and the west–east SST gradient between the southwestern and southeastern SST stacks (Huang et al., 2011). (g) ${\rm U}{{K^{\prime}} \over {37}}\;$-reconstructed SST in core YS01 (this study).

Figure 9

Figure 8. (color online) Centennial time scale variations in paleoclimatic indicators. (a) The westerlies index (WI; flux of >25 μm fraction) record (An et al., 2012). (b) The standardized record of GISP2 potassium (K+; ppb) ions, which can be used to reconstruct the Siberian High (SH; Mayewski et al., 2004). (c) The standardized record of drift ice for MC52-VM29-191 during the Holocene (Bond et al., 2001); HSG, Hematite-stained grains. (d) The standardized SK-2 δ18O record (Sagawa et al., 2014). (e) The standardized record of ${\rm U}{{K^{\prime}} \over {37}}$- reconstructed sea-surface temperature (SST) in the YS01 core (this study). (f) The standardized record of the total solar irradiance (TSI; Steinhilber et al., 2009). (g) The standardized YS01 coarser grain-size component content (this study). (h) The standardized Dongge Cave δ18O record (Wang et al., 2005). (i) The standardized record bulk Ti content from the Cariaco basin sediments from ODP Site 1002 (Haug et al., 2001), which represents the shift of the Intertropical Convergence Zone (ITCZ). (j) The frequency of El Niño per 100 yr (Conroy et al., 2008). Identical treatment of standardization, which includes the calculation of the 200 yr running mean anomaly from the 1000 yr running mean and its standardization using the standard deviation, is applied to the SST in the YS01 core, coarse-component content in the core, frequency of El Nino–Southern Oscillation (ENSO)/100 yr, flux of >25 μm fraction in sediment derived from Lake Qinghai, drift ice for the MC52-VM29-191 core, GISP2 potassium (K+; ppb) ions, bulk Ti content from the Cariaco basin sediments, and coarse component content in the core. Gray bars indicate significant cold periods in the YS01 record. EAWM, East Asian winter monsoon.

Figure 10

Figure 9. Spectral analysis results for paleoclimatic indicators. (a) Total solar irradiance (TSI; Steinhilber et al., 2009). (b) Ice-rafted debris (IRD; Bond et al., 2001). (c) Siberian High (SH; Mayewski et al., 2004). (d) Westerlies index (WI; flux of >25 μm fraction) record (An et al., 2012). (e) Sea-surface temperature (SST) in YS01 core (this study). (f) Sensitive coarse fraction (this study). (g) Bulk Ti content from the Cariaco basin sediments from ODP Site 1002 (Haug et al., 2001). (h) The Dongge Cave δ18O record (Wang et al., 2005). All data were interpolated at 10 yr intervals and analyzed using Redfit v. 3.8 software. The red and blue lines indicate the 99% and 95% confidence levels, respectively. ITCZ, Intertropical Convergence Zone. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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