Early summer temperature changes in the southern Altai Mountains of Central Asia during the past 300 years

Zhang, Tongwen; Yuan, Yanbin; Hu, Yi-cheng; Wang, Wei; Shang, Huaming; Huang, Liping; Zhang, Ruibo; Chen, Feng; Yu, Shulong; Zhai, Fan; Qin, Li

doi:10.1016/j.quaint.2014.12.005

Cited by 13 publications

(8 citation statements)

References 37 publications

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“…The KAR chronology correlated positively with the mean monthly temperatures of June ( r = .66, p < .01), July ( r = .40, p < .01), and mean June–July ( r = .63, p < .01) of the current year, and of June ( r = .38, p < .01) and July ( r = .27, p < .01) of the previous year of the gridded CRU TS4.01 time series over the period 1963–2012 (Figure a). These results corroborate findings from previous studies in the Chinese southern Altai Mountains by Chen et al (), Zhang et al (), and Wang et al (), who showed positive correlations of tree ring widths with June–July air temperatures. They believe that the increased radial growth is caused both by higher photosynthetic rates and higher soil moisture levels due to increased snowmelt.…”

Section: Resultssupporting

confidence: 93%

“…Warming till the 1950s and cooling afterwards till the 1990s over the Altai Mountains was revealed in the mean June–July temperature‐related tree growth series from upper‐treeline sites in the Russian southeast Altai (Panyushkina et al , ) and in the mean July–August temperature reconstruction from tree ring oxygen and carbon isotopes of Siberian pine ( Pinus sibirica Du Tour) from the central Russian Altai (Loader et al , ). The temperature reconstruction from Siberian larch over the Chinese Altai Mountains from Chen et al () and in east Kazakhstan from Zhang et al () show similar patterns of change in mean June–July temperatures. This regional temperature variability contrasts with the area‐weighted average of the past estimated temperature of all continents from the PAGES 2k Consortium (), which locates the warmest period in the late 20th century between 1971 and 2000.…”

Section: Introductionmentioning

confidence: 79%

“…The Altai mountain range lies in the cross‐border region of Kazakhstan, China, Mongolia, and Russia. Its vegetation zones follow moisture and temperature gradients with a decrease in moisture and an increase in temperature from north to south and from west to east (Zhang et al , ). The Dzungarian semi‐desert basin is bounded by the Altai Mountains in the north and the Tian Shan mountains in the south.…”

Section: Introductionmentioning

confidence: 99%

“…Schwikowski et al () suggested that climate proxies based on tree rings, relict wood, lake sediments, and glaciers, which often can be found in such remote regions in still rather undisturbed states, should be used for exploring regional climate change and variability. Accordingly, tree rings from the Altai mountain range are widely used as climate proxies to reconstruct the past variability of temperature, precipitation, and drought in Mongolia, China, and Russia (Panyushkina et al , ; Davi et al , ; Loader et al , ; Chen et al , ; ; Zhang et al , ; Buentgen et al , ). Buentgen et al () reconstructed the so far longest summer temperature time series starting in the sixth century AD, using tree ring chronologies from the Russian Altai.…”

Section: Introductionmentioning

confidence: 99%

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Climate variations over the southern Altai Mountains and Dzungarian Basin region, central Asia, since 1580 CE

Oyunmunkh

Weijers

Loeffler

et al. 2019

Intl Journal of Climatology

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An improved knowledge of long-term climatic variations over the Altai-Dzungarian region will increase our understanding of the current climate and help to predict the effects of global warming on future water availability in this region. We sampled 77 Larix sibirica Ledeb. trees at upper and lower treelines in the southern Mongolian Altai mountains and reconstructed temperature and precipitation for longer periods than previous studies from this area. We reconstructed mean June-July air temperatures for the period 1402-2012 and June-December precipitation for the period 1569-2012 based on tree ring width chronologies. The temperature and precipitation reconstructions explain 39.7 and 41.3% of the respective station observation variance during the common periods. The precipitation reconstruction shows alternating wet and dry conditions during the Little Ice Age (1580-1874) followed by more stable conditions until a late 20th century wetting. The temperature reconstruction attributes the warmest period to the 20th century, which follows cooler periods related to volcanic and low solar activities during the Little Ice Age. Long-term climatic variation and change over the Altai-Dzungarian region is inferred from the analysis of the combined temperature and precipitation reconstructions for the common period 1580-2012. Accordingly, this region has become warmer since 1875 as the number of warm/moist and warm/dry years increased by 2 and 14%, respectively, while the number of cool/moist and cool/dry years both decreased by 8% compared to the Little Ice Age. Our findings also reveal a late 20th century cool and wet period, which has also been observed across other mountainous areas of China and Nepal. This period was most probably caused by volcanic-induced cooling and coincided positive phases of the Arctic Oscillation and North Atlantic Oscillation promoting an intensified subtropical westerly jet and a positive summer rainfall anomaly over the Altai-Dzungarian region.

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Section: Resultssupporting

confidence: 93%

Section: Introductionmentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Climate variations over the southern Altai Mountains and Dzungarian Basin region, central Asia, since 1580 CE

Oyunmunkh

Weijers

Loeffler

et al. 2019

Intl Journal of Climatology

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“…3.1 Dulamsuren et al 2014;Schluetz and Lehmkuhl 2007;Schwikowski et al 2009) and its impact on glaciers (Kamp et al 2013) and forests. Most tree ring-based past climate reconstruction studies in Western Mongolia (Davi et al 2015;Davi et al 2009) and north-western China (Chen et al 2012(Chen et al , 2014Zhang et al 2015) identified a significant climate and environmental change with rapid warming and precipitation increases caused by a general intensification of the global hydrological cycle. Bezuglova et al (2012) analysed the thermal regime of the Russian and northern part of the Mongolian Altai for the period between 1940 and 2008 using averaged monthly temperature observations.…”

Section: And Clemens Simmermentioning

confidence: 99%

Dynamical downscaling with COSMO and COSMO-CLM in the Sino-Mongolian Altai region

Kurzrock¹,

Buerkert

Oyunmunkh

et al. 2016

Meteorol Atmos Phys

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For the first time, regional atmospheric simulations with spatial resolution down to 6 km have been performed in the Sino-Mongolian Altai region using the COSMO weather forecast and regional climate model. Two 5-year periods (1979-1982 and 2008-2012) have been simulated for a first evaluation of the model in this special region. The added value of a dynamical downscaling with the COSMO regional climate model CCLM towards the driving ERA-Interim reanalysis is investigated by comparison with weather station observations. In the mountainous region, the CCLM simulation much better relates to the observed monthly mean 2 m temperature and maximum monthly precipitation sums in summer than ERAInterim. In addition, the intensity distribution of sub-daily precipitation amounts becomes more realistic with increasing altitude. CCLM does, however, overestimate convection in the mountains and accordingly simulates too much precipitation. Moreover, wintertime near-surface temperature inversions are underrated in the southern nearGobi area, which leads to too high 2 m temperatures in that region. To examine the ability of the COSMO model to reproduce the vertical thermodynamic structure of the troposphere, additional simulations with the weather forecast version of COSMO were performed for July 2013 and compared to radiosonde measurements of the WATER-COPE field experiment in this region. The results indicate that the COSMO model is quite capable of qualitatively simulating a range of features of the local tropospheric stratification. Mean differences between observed and simulated dew point and temperature profiles were in the range of only to 1-2°C in the lower troposphere.

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Reconstruction of hydrological changes based on tree-ring data of the Haba River, northwestern China

et al. 2018

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Reconstructing the hydrological change based on dendrohydrological data has important implications for understanding the dynamic distribution and evolution pattern of a given river. The widespread, long-living coniferous forests on the Altay Mountains provide a good example for carrying out the dendrohydrological studies. In this study, a regional composite tree-ring width chronology developed by Larix sibirica Ledeb. and Picea obovata Ledeb. was used to reconstruct a 301-year annual (from preceding July to succeeding June) streamflow for the Haba River, which originates in the southern Altay Mountains, Xinjiang, China. Results indicated that the reconstructed streamflow series and the observations were fitting well, and explained 47.5% of the variation in the observed streamflow of 1957-2008. Moreover, floods and droughts in 1949-2000 were precisely captured by the streamflow reconstruction. Based on the frequencies of the wettest/driest years and decades, we identified the 19 th century as the century with the largest occurrence of hydrological fluctuations for the last 300 years. After applying a 21-year moving average, we found five wet

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Early summer temperature changes in the southern Altai Mountains of Central Asia during the past 300 years

Cited by 13 publications

References 37 publications

Climate variations over the southern Altai Mountains and Dzungarian Basin region, central Asia, since 1580 CE

Climate variations over the southern Altai Mountains and Dzungarian Basin region, central Asia, since 1580 CE

Dynamical downscaling with COSMO and COSMO-CLM in the Sino-Mongolian Altai region

Reconstruction of hydrological changes based on tree-ring data of the Haba River, northwestern China

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