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Arid Land Geography ›› 2021, Vol. 44 ›› Issue (1): 27-35.doi: 10.12118/j.issn.1000–6060.2021.01.03

• Climatology and Hydrology • Previous Articles     Next Articles

Reconstruction of early summer temperature during 1572—2014 from tree-rings in the Altay Prefecture

NIU Junqiang1,2,3(),YUAN Yujiang2(),ZHANG Tongwen2,CHEN Feng4,ZHANG Ruibo2,SHANG Huaming2,JIANG Shengxia2   

  1. 1. Editorial Department of Journal of Xinjiang Normal University, Urumqi 830017, Xinjiang, China
    2. Institute of Desert Meteorology, China Meteorological Administration, Key Laboratory of Tree-ring Physical and Chemical Research of China Meteorological Administration, Xinjiang Laboratory of Tree Ring Ecology, Urumqi 830002, Xinjiang, China
    3. College of Geography Science and Tourism, Xinjiang Normal University, Urumqi 830054, Xinjiang, China
    4. Institute of International Rivers and Eco-security, Yunnan University, Kunming 650504, Yunnan, China
  • Received:2020-06-22 Revised:2020-10-02 Online:2021-01-25 Published:2021-03-09
  • Contact: Yujiang YUAN E-mail:niujq01@163.com;yuanyuj5502@sina.com

Abstract:

Dendroclimatology is one of the important methods for examining the past global climate changes. Here, the study area is the upper stream of China’s climate and weather, located on the Altay Mountains’ southern slope in northwestern China. Reconstructing the climatic variation series in this region is very important in recognizing the climatic variations on the Altay Mountains’ southern slope in the past. In the summer of 2014, the three tree-ring samples sites (trees of 79 and tree cores of 261) were collected for Larix sibirica from the upper tree line of forests at the midwestern Altay Mountains. We developed three kinds of tree-ring width chronologies by the ARSTAN program. In this study, we chose the regional tree-ring standard chronology (DKH) and used 7 meteorological station data close to the sampling site. Single correlation census showed that the correlation between the regional tree-ring chronology from the 7 meteorological stations and the average current June temperature is significant with the best single correlation coefficient of 0.705 (P<0.00001). In this study, we used the regional tree-ring standard chronology to reconstruct this region’s average June temperature since 1572 AD. The explained variance of the function was 49.6% (F=50.27948, P<0.00001). Many verifications showed that the reconstructed temperature series was reliable. After 11 a of reconstructed temperature series was calculated, in the past 443 a, we found the following: (1) 10 warm periods in 1577—1585, 1605—1622, 1636—1644, 1654—1681, 1724—1752, 1805—1808, 1831—1844, 1875—1913, 1950—1980, and 1993—2009; and (2) nine cold periods were found in 1586—1604, 1623—1635, 1645—1653, 1682—1723, 1753—1804, 1809—1830, 1845—1874, 1929—1938, and 1981—1992. The warmest period occurred in 1605—1622, and the coldest period occurred in 1682—1723. The 1875—1913 period was the most extended warm period, whereas the 1753—1804 period was the most prolonged cold period. Power spectrum analysis showed that there exist some significant change periods of 2.37-2.39 a and 2.19 a (P<0.05) and 73.50 a, 14.00 a, 7.30 a, and 2.29 a (P<0.10) in temperature. The cycle of 2.19 a may be related to the quasi-biennial oscillation. The moving t-test technique showed the abrupt change of temperature occurred in the 1684 and 1719 periods from cold to warm in this region. According to the spatial correlation analysis results, the temperature reconstructed series represents the early summer temperature changes in the Altay Prefecture. Our reconstructed mean June temperature series change trend, cold, and warm periods were consistent with the former reconstructed temperature series of the Altay Mountains western and south slopes.

Key words: Altay Prefecture, Larix sibirica, regional standardization chronology, average temperature change