Abstract
A total of 290 tree-ring samples, collected from six sites in the West Qinling Mountains of China, were used to develop six new standard tree-ring chronologies. In addition, 73 proxy records were assembled in collaboration with Chinese and international scholars, from 27 publically available proxy records and 40 tree-ring chronologies that are not available in public datasets. These records were used to reconstruct annual mean temperature variability in the West Qinling Mountains over the past 500 years (AD 1500–1995), using a modified point-by-point regression (hybrid PPR) method. The results demonstrate that the hybrid PPR method successfully integrates the temperature signals from different types of proxies, and that the method preserves a high degree of low-frequency variability. The reconstruction shows greater temperature variability in the West Qinling Mountains than has been found in previous studies. Our temperature reconstruction for this region shows: 1) five distinct cold periods, at approximately AD 1520–1535, AD 1560–1575, AD 1610–1620, AD 1850–1875 and AD 1965–1985, and four warm periods, at approximately AD 1645–1660, AD 1705–1725, AD 1785–1795 and AD 1920–1945; 2) that in this region, the 20th century was not the warmest period of the past 500 years; and 3) that a dominant and persistent oscillation of ca. 64 years is significantly identified in the 1640–1790 period.
Highlights
Temperature-sensitive proxy data can be used as a primary basis for understanding temperature variations through time
Despite the advantages of tree-ring records as temperature proxies, tree-ring chronologies often include less low-frequency information than do other proxies because of the so-called segment-length curse problem [16], which refers to the difficulty of preserving cyclic signals that are longer than the duration of the age of individual trees
In this study, we employed a hybrid reconstruction method that considers the full spectrum of temperature variability, by separating the variability into high- and low-frequency bandwidths
Summary
Temperature-sensitive proxy data can be used as a primary basis for understanding temperature variations through time. The screening probability in original PPR frame is a method for selecting proxy records for use in the temperature reconstructions at a particular grid point, based on a threshold defined by a certain significance level for correlation [53]. Because of the high level of noise in the tree-ring chronologies, the same weighted model with the same coefficients was applied in this study as was used in the creation of the Monsoon Asia Drought Atlas [19] The screened proxy records were used to reconstruct temperature in separate high- and low-frequency bandwidths This frequency split makes it possible to assimilate proxy data series with different temporal resolutions.
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