Sci., Tech. and Dev., 31 (2): 152-164, 2012

*Author for correspondence E-mail: qbzhang@ibcas.ac.cn

Comparison of Temperature Sensitive Tree-Ring Chronologies

in Southern Tibetan Plateau and Northern Siberia

LI-XIN LV1, DMITRIY V. OVCHINNIKOV

2, ALEXANDER V. KIRDYANOV

2 AND

QI-BIN ZHANG1*

1State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of

Sciences, Beijing, 100093, China.

2V.N. Sukachev Institute of Forest SB RAS, 660036 Krasnoyarsk, Akademgorodok, Russia.

Abstract

Comparison of climate histories over different regions helps in understanding global climate change. Here we compiled temperature sensitive tree-ring chronologies over the southern Tibetan Plateau and Northern Siberia and compared temperature variations over these two regions for the past 350 years. Tree-ring width chronologies of the Eastern Himalayan fir (Abies spectabilis) and alpine junipers (Juniperus recurva and J. squamata) on the southern Tibetan Plateau were found to be sensitive to June-September temperature variations. Tree-ring maximum latewood density time series of Gmelin larch (Larix gmelinii Rupr.) and Siberian larch (L. sibirica) in Northern Siberia were correlated to temperature variations during June-August. Comparison of the two regional chronologies showed that both regions experienced two coldest summer episodes around 1810s-1820s and 1960s-1970s. Wavelet coherence analysis showed that a significant co-variability at around 4-year cycles existed in the periods 1740s-1760s, 1840s-1870s, 1890s-1910s and 1950s-1960s. These results suggested that summer temperature variations over the southern Tibetan Plateau and Northern Siberia had an unstable relationship which was probably a result of different climatic forcing. Yet, the two cold episodes around 1810s-1820s and 1960s-1970s might indicate common driving factors such as volcanic activities and solar forcing in these particular intervals.

Keywords: Summer temperature, Northern Siberia, Southern Tibetan Plateau, Tree rings, Cold episodes, Volcanic activities

Introduction Global warming shows uneven rates over

different regions (IPCC, 2007). Tibetan Plateau (TP), known as “the Third Pole of the Earth”, is located in the mid-latitude and has an average elevation about 4000m. Northern Siberia (SI) is located at high latitude with a typical continental climate. Comparisons of climate histories over these two regions could provide insights into teleconnections between different climatic systems (Ding & Krishnamurti, 1987; Feng & Hu, 2005) and help in understanding large spatial-scale patterns of climate change.

Tree rings have been widely used as climate proxies in studying history of past climate change (Stahle et al., 1988; Briffa et al., 1990; Villalba et al., 1998; Sheppard et al., 2004). Previous studies of tree rings on the TP showed that the growth of

juniper trees (Juniperus spp.) on the northern and central parts of TP mainly responded to spring and early summer moisture (Bräuning, 2001; Zhang et al., 2003; Sheppard et al., 2004; Liang et al., 2006; Zhang and Qiu, 2007; Wang et al., 2008; Shao et al., 2010). In the southern part of the TP, tree rings are more representative of temperatures (Cook et al., 2003; Liang et al., 2009; Yang et al., 2009; Yang et al., 2010; Yadav et al., 2011). Wang & Zhang (2011) found a significant 22-year cycle in the smith fir (Abies

georgei var. smithii) tree-rings in the southeastern TP and suggested a close linkage between solar activity and tree-ring growth. Wang et al. (2010), reconstructed the late summer (August-September) temperature based on tree-ring maximum density data for the past three centuries on the eastern TP and detected a 20-year climatic

COMPARISON OF TEMPERATURE SENSITIVE TREE-RING CHRONOLOGIES IN S.TIBETAN PLATEAU… 153

cycle during the period 1800-1860 and a ~50-year cycle at the beginning of the twentieth century.

In the Upper Kolyma region of northeastern Siberia, tree-ring width of Dahurian larch (Larix

gmelini) was found highly correlated with average daily maximum temperatures for summer months (Earle et al., 1994). Based on another larch species (Siberian larch, L. siberica), Briffa et al. (1995) reported a tree-ring-based reconstruction of mean summer temperature over the Northern Urals since 914 AD. Their reconstruction indicated that mean temperature of the twentieth century (1901-90) was highest in the last millennium. They also built a chronology network mainly based on tree-ring width and density data (Briffa et al., 1996). Correlation analyses indicated that the tree growth was significantly associated with summer seasons, slightly stronger and longer for the maximum latewood density (MXD) data than tree-ring width (TRW) data. Vaganov et al. (1999) found that the initiation of cambial activity was delayed relative to the pre-1960 period in the Siberian subarctic due to delayed snow melt in these permafrost environments. Naurzbaev et al. (2002) reconstructed a 2427-year summer temperature history in eastern Taimyr based on tree-ring chronology and earlier floating series. Multi-proxy based summer temperature reconstructions were also reported in the Siberia region (Kirdyanov et al., 2008; Loader et al., 2010; Sidorova et al., 2012).

Previous researches suggested that tree rings in the Northern Siberia and the Southern TP regions showed great sensitivity to temperature variations. Due to site-specific factors, a single tree-ring chronology may contain unwanted local variability. Tree-ring network could provide reliable dataset for accessing large-scale climate variations (Bräuning, 1994; Briffa et al., 1996). Here, we conduct a preliminary comparison between temperature sensitive tree-ring data from the Southern TP and Northern Siberia. Regional scale tree-ring chronologies were established for

both regions and were compared for the past centuries with the aim to investigate the possible linkages of the summer temperature variation over the Northern Siberia and Southern Tibetan Plateau. Materials and Methods

Study area and tree-ring database In the southern TP region, we used eight tree-

ring width (TRW) chronologies to build up the tree-ring network (Fig. 1). Two chronologies were obtained from our own study and six chronologies were collected from the International Tree-Ring Data Bank (ITRDB, http://www.ncdc.noaa.gov/paleo/treering.html). The climate of the southern TP is strongly affected by the Indian monsoon. According to the Climatic Research Unit data set (CRU TS 3.1, Mitchell & Jones, 2005), mean monthly temperature ranges from -9.6oC in January to 8.0oC in July for the study region (27.5°-28.5°N, 86°-89°E). Annual precipitation is 1133 mm with 80% during the monsoon season (June-September). The studied tree species include the Eastern Himalayan fir (Abies spectabilis) and alpine junipers (J. recurva

and J. squamata) growing in areas with elevations ranging from 2600 to 3600m (Table 1).

In the Northern Siberia, we used five tree-ring maximum density (MXD) chronologies to build up the tree-ring network. Two chronologies were obtained from our own study in the Central Siberian Plateau and three chronologies were collected from the ITRDB (Fig. 1). The study area has a typical sub-arctic continental climate. According to the CRU TS 3.1, mean monthly air temperature ranges from -34.4oC in January to 11.4oC in July for this region (69°-71°N, 89°-103°E). Annual precipitation is 369mm, with 40% falling in summer (June–August). The tree species under study are Gmelin larch (L. gmelinii

Rupr.) and Siberian larch (L. sibirica) with elevations ranging from 50 to 360m a.s.l. (Table 1).

154 L.V. LI-XIN ET AL.

Fig. 1. Map of the study area. The source of the map is the Version 4 of the SRTM 90m Digital Elevation Data (Jarvis

et al., 2008). Tree ring sites are denoted by triangles. Colours in the triangles indicate different tree genera: red

for Larix, black for Abies and blue for Juniperus

Table 1. Site information for the tree-ring network in the Siberia and Tibetan Plateau regions

Region Site code Species Latitude

(N°)

Longitude

(E°)

Altitude

(m)

Maximum series

length (yr)

SI

BKPI Larix gmelinii 71.333 93.833 60 422

KUPI Larix sibirica 67.966 88.880 160 417

IKPI Larix gmelinii 70.501 89.500 50 334

BVPI Larix gmelinii 70.500 92.833 360 314

KOPI Larix sibirica 70.510 104.250 130 607

TP

YDJS Juniperus squamata 27.550 88.840 3610 450

BHJS Juniperus recurva 27.667 86.405 3600 582

NLAS Abies spectabilis 27.950 85.980 2686 326

GHAS Abies spectabilus 27.635 87.940 3740 475

MUAS Abies spectabilus 27.703 87.211 3200 451

NKAS Abies spectabilus 27.772 87.148 3250 325

BHAS Abies spectabilus 27.672 86.415 3600 374

CHAS Abies spectabilus 27.696 86.271 3300 310

Chronology development

156 L.V. LI-XIN ET AL.

Raw tree-ring measurements were processed into site chronologies using the ARSTAN software (Cook, 1985). In order to remove age and size related growth trends, a flexible cubic smoothing spline with 50% frequency-response cut-off equal to 2/3 of the serial length was used while preserving variations that are likely related to climate, (Cook & Kairiukstis, 1990). For ring-width chronologies, the tree-ring indices were obtained by calculating division between the ring-width measurements and the fitted curves. For ring-density chronologies, the tree-ring indices were obtained by calculating differences between the MXD measurements and the fitted curves. Detrended series were then averaged into site standard chronologies by computing the bi-weight robust mean to reduce the influence of random factors as well as the outliers (Cook & Kairiukstis, 1990). Residual version of the TRW chronologies on the TP was used for comparative studies.

In the northern Siberia region, the five tree-ring chronologies well agree with each other both annually and in the decadal scale variations (Fig. 2 andTable 2). In the southern TP, the site chronologies share much similarity for the past centuries (Fig. 3). Except for that of NLAS and BHJS, all the other inter-site correlations pass the 0.05 significance level but with relatively lower values compared with those in Siberia regions (Table 3). Table 2. Spearman correlations among site chronologies

in the Siberian Region for the period 1791-1990

BKPI KUPI IKPI BVPI

KUPI 0.68

IKPI 0.89 0.76

BVPI 0.90 0.72 0.87

KOPI 0.74 0.55 0.67 0.72 Note: The bold values indicate significance at 0.05 level.

Table 3. Spearman correlations among site chronologies

in the Tibetan Plateau region for the period

1791-1990

BHJS MUAS CHAS NKAS GHAS BHAS YDJS

MUAS 0.29 CHAS 0.35 0.39 NKAS 0.49 0.46 0.55 GHAS 0.21 0.45 0.25 0.38 BHAS 0.34 0.47 0.42 0.54 0.40 YDJS 0.50 0.26 0.30 0.33 0.22 0.27 NLAS 0.13 0.39 0.35 0.19 0.30 0.47 0.19

Note: the bold values indicate significance at 0.05 level.

Fig. 2. Tree-ring maximum latewood density (MXD)

standard chronologies in the Siberian Region.

The red lines indicate 11-year low pass filter

Fig. 3. Tree-ring width residual chronologies in the

Tibetan Plateau Region. The red lines indicate

11-year low pass filter

COMPARISON OF TEMPERATURE SENSITIVE TREE-RING CHRONOLOGIES IN S.TIBETAN PLATEAU… 157

Due to the similarity between site chronologies within each region, two regional chronologies were then developed by averaging the site chronologies for the Siberia and TP regions, respectively. Growth-climate relationships

To identify tree growth and climate relationships, Pearson’s correlation coefficients were computed for the regional chronologies, monthly/seasonal mean temperatures and total precipitation. The instrumental climate records were sparse and short in the TP region. Longer but discontinuous instrumental climate records could go back to 1880s in nearby India and Kathmandu (Nepal). Based on these climate data, the CRU TS 3.1 database could provide monthly variations in climate and cover a period of 1901 to 2006 for this region (27.5°-28.5°N, 86°-89°E). However, the differences of the CRU climate variables in the Siberia region (69°-71°N, 89°-103°E) dropped abruptly before the 1930s due to the paucity in instrumental observations. To keep consistency in the two regions, monthly mean temperatures, monthly mean maximum temperature, monthly mean minimum temperature and monthly mean precipitation were extracted from the CRU TS 3.1 database for the period 1933-2002 AD for correlation analyses with tree-ring indices.

Wavelet transform and Wavelet coherency

analyses The Wavelet Transform is designed to study

the time-frequency variations of a time series (Farge, 1992). Thus, transient or intermittent components can be detected (Torrence & Compo, 1998). Here, we used the Morlet wavelet (Goupillaud et al., 1984) to decompose the series to explore relations among the two regional chronologies (Grinsted et al., 2004). Results

Statistics on the site chronologies Both MXD and TRW chronologies in Siberia

and TP regions have high values in inter-series correlations and variance explained by the first eigenvector. It indicates large portion of common signals between trees within each site in recording environmental changes (could possibly be climatic signals). Expressed population signals (EPS) are greater than 0.85 for all the site chronologies, indicating adequate sample replications (Table 4). The low absolute value of the first order autocorrelation coefficients is around zero for most site chronologies. It provides a solid statistical basis for the following analyses of the correlation between tree-rings and climate variables (Table 4).

Table 4. Dendrochronological statistics on the site chronologies in the Siberia and Tibetan Plateau regions

Region Site code MS Rbar AC1 VFE(%)* EPS

* SNR

*

Siberia

BKPI 0.149 0.687 0.121 70.5 0.979 46.06

KUPI 0.112 0.605 0.095 41.2 0.963 25.996

IKPI 0.148 0.651 0.096 66.7 0.982 54.131

BVPI 0.156 0.661 0.031 65 0.985 28.7

KOPI 0.132 0.551 0.077 58.8 0.986 37.7

Tibetan

Plateau

YDJS 0.163 0.502 0.05 36.2 0.859 6.117

BHJS 0.194 0.285 -0.066 26.5 0.884 7.592

NLAS 0.197 0.315 -0.035 29.3 0.881 7.37

GHAS 0.154 0.298 0.009 24.1 0.944 17.016

MUAS 0.224 0.229 0.006 20.4 0.887 7.826

NKAS 0.181 0.246 -0.012 24.2 0.861 6.209

BHAS 0.16 0.495 0.024 47.8 0.961 24.474

CHAS 0.189 0.305 -0.052 31.3 0.875 7.012

Note: MS= mean sensitivity; AC1= first order autocorrelation coefficient; VFE= variance in the first eigenvector;

EPS = expressed population signal; SNR = signal-noise- ratio. The two regional chronologies

158 L.V. LI-XIN ET AL.

The two regional chronologies shared the coldest periods during the 1810s-1820s and 1960s-1970s. Compared with that in TP, the cold

conditions in the Siberia lasted for a longer period, even in the 1850s (Fig. 4).

Fig. 4. Two regional chronologies over the northern Siberia region (a), and the southern Tibetan Plateau (b)

Growth-climate relationships Larch tree-ring maximum latewood density in

Siberia were significantly correlated with summer (June-August) temperature variations for the period 1933-2002 (r=0.73, p<0.0001). Correlation analyses indicate that tree-ring width chronologies of the Junipers and firs in the TP region were mainly correlated with summer temperatures (July-September) (r=0.44, p=0.0002). Precipitation was not or only weakly correlated to tree-ring indices in both Siberia and TP regions (Fig. 5).

Fig. 5. Correlations between the regional chronologies

and the monthly mean temperatures (Tem) and

monthly precipitations (Pre) for the common

period 1933-2002 AD over the Siberia (a) and the

Tibetan Plateau (b) regions.

158 L.V. LI-XIN ET AL.

Power spectra of the two regional chronologies The regional chronology in the northern

Siberia showed significant 17~21 year cycle across the whole time span with varying strength. A cycle of 3~8 years occurred before the 1920s. Besides, a longer cycle of 40~50 years existed for the period 1720s-1850s and then weakened and

disappeared at about the beginning of the 20th century (Fig. 6a).

The regional chronologies on the southern Tibetan Plateau also showed significant cycles at varying periodicity. The 2~5 year cycle is significant for some intervals in the 20th century and the 30~60 year cycle is significant between 1750s-1850s (Fig. 6b).

Fig. 6. Continuous power wavelet spectrum of the standardised chronologies in Siberia (a) and the Tibetan

Plateau (b) regions. Significant periodicities (p < 0.05) against red noise are outlined in black on the

wavelet spectra. Legend indicates power. The cone of influence, where edge effects might distort the

picture, is shown as a lighter shade

Wavelet coherency analyses of the two regional

chronologies Wavelet coherence analysis showed that a

significant co-variability at around 4-year cycle existed in the periods 1740s-1760s, 1840s-1870s, 1890s-1910s, and 1950s-1960s (Fig. 7). Besides, significant coherence was also observed between the two tree-ring series at long temporal scales in the period 1700s-1850s AD. Beginning at approximately 1850 AD, there was a sharp loss of

coherency between the two series at long temporal scales (40~60 years) while coherency at short time cycles was enhanced. Following the 1950s, the coherency of the two data-sets diminishes at most temporal scales and anti-phase variations were observed at a ~7-year cycle for the period 1950s (Fig. 7).

COMPARISON OF TEMPERATURE SENSITIVE TREE-RING CHRONOLOGIES IN S.TIBETAN PLATEAU… 159

Fig. 7. Squared wavelet coherence between the two chronologies in the Siberia and Tibetan Plateau. The relative

phase relationship is shown as arrows (in-phase pointing right, anti-phase pointing left) and legend indicates

squared coherence. Significant periodicities (p < 0.05) against red noise are outlined in black on the wavelet

squared coherency spectra. The cone of influence, where edge effects might distort the picture, is shown as a

lighter shade.

Discussion

The two common coldest episodes in the two

remote regions The two most conspicuous cold periods

occurred in the 1810s-1820s and 1960s -1970s in both Siberia and TP regions (Fig. 4). The first anomalous cold period on the Tibetan Plateau was observed by a number of climate reconstructions based on tree rings (Cook et al., 2003; Liang et al. 2008). This cold period was also recorded by the tree rings in the Siberia (MacDonald et al., 1998). Hughes et al. (1999) singled out the summers of years 1817 and 1818 as among the coldest 10 years in the 600-year early summer (June-July) temperature reconstruction. The cold period on the TP was widely believed to be a result of the Tambora eruption (8.25°S, 117.96°E; VEI =7) in Lesser Sunda Island in 1815 AD (Cook, 2003; Liang et

al., 2008). Aerosols from the Tambora eruption blocked out sunlight and reduced global temperatures by 2-3oC in 1816 AD (Trigo et al., 2009). In this study, the common cold period indicates common climate force from volcano effects. However, the two regions differed in the duration of cold events. The cold events endured ~10 year longer in the Siberia than did in TP (Fig. 4). It suggests that factors besides volcanic forcing might also play a role at the same time.

The anomalous cold episode in the 1960s-1970s was observed in previous studies in both Siberian (Briffa et al., 1995; Hughes et al. 1999) and TP (Kang et al., 2007; Yang et al., 2008) regions. This cold period coincided with an abrupt drop in the sea surface temperature in the northern hemisphere during 1968-1972 (Thompson et al., 2010). The concurrence of the ‘great salinity anomaly’ of the North Atlantic in the late 1960s-1970s (Dickson et al., 1988)

160 L.V. LI-XIN ET AL.

suggested possible connections, as discussed by Thompson et al. (2010).

The above two common cold episodes indicated that the climate of the Northern Siberia and Southern Tibetan Plateau were subject to cooling effects of the aerosols released from the volcanic activities and salinity anomalies in the Northern Atlantic. It also demonstrated that tree rings could have recorded the imprint of the effects of general circulation and/or global/hemispheric scale events (Linderholm et al., 2011). Interpretations of the tree-ring records from different climate zones could provide insights on the spatial characteristics of the effects from climatic circulations. Significant cycles of the two regional

chronologies Inter-annual scale periodicities were found in

the regional chronologies over both Siberia and TP regions (Fig. 6). Short cycle of 3-8 years in the regional chronology of the Northern Siberia may be related to the North Atlantic Oscillation (Mokhov et al., 2000). The significant cycles of 2-8 years in the power spectra of tree-ring chronology on the TP fall within the bandwidth of El Niño-Southern Oscillation events (Cane & Zebiak, 1985; Hanley et al., 2003; McPhaden et al., 2006). Footprints of ENSO events were also found on the TP as recorded by both instrumental observation (Shrestha et al., 2000) and proxies including tree rings (Xu et al., 2010) and ice cores (Yang et al., 2000). The underlying mechanism linking the climate on the TP is commonly deemed as its interaction with the Asian Monsoon systems (Gupta & Anderson, 2005; Chu et al., 2011; Khan, et al., 2011; Shaheen et al., 2012).

Significant decadal periodicities in the wavelet transformations of the tree-ring chronologies were observed in different time scales over these two study regions (Fig. 5a). The quasi-solar cycle of about 17~21 year across the last ~350 years in the Siberia region suggests possible solar effects (22-year, Hale cycle) on the summer temperatures (Cook et al., 1997). The Schwabe cycle (11-year cycle) in the solar activity was not detected in this study, which was consistent with other results in the northern Siberia (Kasatkina et al., 2007). Another cycle of about 40~50 years is similar to the North Atlantic Oscillation (Mokhov et al., 2000).

In contrast to the Siberian region, no significant Hale cycle was observed in the wavelet power spectra of the TP regional chronology. Whereas, significant cycle of 30-60 years was detected in the TP regional chronology (Fig. 6b), which was similar to the cycle of 20-50 years found in summer temperature reconstruction on the eastern TP based on tree-ring MXD (Wang et al., 2010). This cycle resembles the Pacific decadal oscillation (Mantua & Hare, 2002), as compared by Wang et al. (2010). Instable relationships between summer

temperature over the two remote regions Wavelet coherence analysis showed that a

significant co-variability at around 4-year cycle existed in some periods (Fig. 7), suggesting a possibility of common forcing from the ENSO events. The ENSO effects was, however, not stationary through time. It manifested itself after about the mid 19th century, which coincided with intensified ENSO amplitude in the background of accelerated global warming (Li et al., 2011).

A significant coherence in the cycle of about 40-60 years existed for the period 1700s-1850s, which might indicate common climatic forcing from ocean oscillation (Knight et al., 2005; Zhang et al., 2007). However, the interactive effects of different oceans make it complicated (Kim et al., 2009; Bothe et al., 2010) and the relative importance changed through time (Linderholm & Brauning, 2006; Yadav, 2011). Conclusions

We compiled two tree-ring networks over the Northern Siberia and Southern Tibetan Plateau. The correlation analyses indicated that tree-ring maximum late wood density chronology is correlated to the June-August mean temperatures in the Siberia, whilst tree-ring width chronology in TP was mainly correlated with July-August-September mean temperatures. Summer temperature on the southern TP showed significant cycles at 2~5 years and 30~60 years, whereas significant cycles at 3~8 years, 17~21 years and 40~50 years in the Northern Siberia were revealed. These cycles suggested that summer temperature variations over the southern TP and northern Siberia had an unstable relationship which was probably a result of different climatic forcing. Wavelet coherence

COMPARISON OF TEMPERATURE SENSITIVE TREE-RING CHRONOLOGIES IN S.TIBETAN PLATEAU… 161

analysis showed that a significant co-variability at around 40-60 year cycle disappeared after the 1850s, suggesting possible changes in the global/hemispheric scale climate driving forces in relation to the accelerated global warming. The two cold episodes around 1810s~1820s and 1960s~1970s indicate common driving factors such as volcanic activities and solar forcing in these particular intervals. Acknowledgement

This work was supported by NSFC-RFBR collaborative project number 31111120025 and NSFC project number 31170419.

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