A 210-year tree-ring δ¹⁸O record in North China and its relationship with large-scale circulations

Figures & data

Fig. 1. Geographical locations of the sampling site, three meteorological stations and one site for δ¹⁸O comparison (ERDS, Liu, Wang et al. 2019). The δ¹⁸O_P site in Xi’an from the Global Network of Isotopes in Precipitation project (GNIP) was denoted and the δ¹⁸O_P site in Baotou was at the same location of the Baotou meteorological station.

Fig. 2. The monthly variations of (a) precipitation, (b) temperature and (c) relative humidity and the annual variations of (d) precipitation, (e) temperature and (f) relative humidity at the Baotou, Damaoqi and Hohhot stations during 1954–2009 AD.

Fig. 3. The δ¹⁸O_TR series in Baotou. (a) The raw δ¹⁸O data of the eight cores. (b) The master δ¹⁸O_TR series produced by averaging the eight z-scored individual series. (c) Numbers of cores through the chronology interval. (d) Mean interseries correlation (Rbar), the running EPS calculated using 30-year windows and a lag time of 15 years.

Table 1. Statistical features of the eight individual series.

Cores	Time Span (AD)	Average (‰)	σ (‰)	Minimum (‰)	Maximum (‰)
WDW12 B	1800–1950	30.50	1.49	27.05	34.25
WDW15A	1800–1902	31.16	1.64	27.58	35.30
WDW10B	1800–1902	31.08	1.51	27.16	35.55
WDE 9A	1800–1900	31.35	1.34	28.34	33.84
WDE 13A	1917–2009	32.52	1.27	29.33	34.75
WDE 5B	1800–1990	31.55	1.39	27.07	35.06
WDW 7B	1929–2009	31.73	1.55	27.32	35.61
WDW 5B	1901–2009	31.45	1.63	27.17	34.52

Fig. 4. Comparisons of the δ¹⁸O_TR series and δ¹⁸O_P in (a) Baotou; (b) Xi’an.

Fig. 5. Correlations and comparisons between the δ¹⁸O_TR record and climate factors. (a) The correlations between the δ¹⁸O_TR series and the climate factors during 1954–2009 AD; (b) The comparison of the original data between the δ¹⁸O_TR series and RH_JJA. (c) The comparison of the first-order data between the δ¹⁸O_TR series and RH_JJA.

Fig. 6. Spatial correlations of the δ¹⁸O_TR record with (a) the vapour pressure (CRU TS4.03) from 1950 to 2009 AD; (b) precipitation (CRU TS4.03) from 1950 to 2009 AD; (c) scPDSI (UCAR) from 1950 to 2009 AD; (d) SST (ERSST dataset) from 1854 to 2009 AD. The black and grey rectangles denote the Niño 3.4 and Niño 4 regions, respectively, and the correlation coefficients with the δ¹⁸O_TR record are both indicated. The sampling site is illustrated with a red dot. All with p values < 0.1.

Fig. 7. Comparison of the δ¹⁸O_TR records from Baotou and ERDS. (a) The original series of the two records. The δ¹⁸O_TR record in ERDS (Liu, Wang et al. 2019) was normalised using the same method. The arrow line indicates the significant increasing trend of δ¹⁸O_TR in Baotou since 1934 (Liu, Liu et al. 2019; Liu, Wang et al. 2019). (b) The 11-year moving averaging series of the two records.

Fig. 8. The correlations of δ¹⁸O_TR with the ISM and ENSO. (a) Comparison of the original series between the δ¹⁸O_TR record in Baotou and all Indian precipitation (JJAS); (b) Comparison of the 21-year moving averaging series between the δ¹⁸O_TR record in Baotou and the all Indian precipitation (JJAS); (c) The 21-year moving correlations between δ¹⁸O_TR record in Baotou and the JJA Niño 3.4 index (ERSST), comparing with the 21-year moving correlation of the all Indian precipitation (JJAS). The all Indian precipitation (JJAS) was used to represent the ISM intensity.

Table 2. Correlations between δ¹⁸O_TR and different monsoon indexes (1948–2009 AD).

	ISM	EASM
Webster and Yang (1992)	−0.39**
Lau et al. (2000)	−0.38**	0.06
Li and Zeng (2002, 2003)	−0.31*	0.07
Zhang et al. (2003)		−0.25*

** and * represent significance at the 99% and 95% confidence levels, respectively.

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Data availability statement

Data that have contributed to the reported results are available from the corresponding author on request.