First-difference Data of Tree-ring Latewood Maximum Density Better Reveals Interannual Temperature Variation in Northwestern Yunnan Province
Received date: 2024-03-03
Revised date: 2024-04-16
Online published: 2024-05-14
Supported by
the National Natural Science Foundation of China(41977391)
Tree-ring latewood maximum density is a well-known proxy for temperature during and at the end of the growing season. Utilizing the DENDRO2003 tree ring density analysis system, density data were obtained from tree increment cores of Picea brachytyla var. complanata, collected from northwestern Yunnan Province. Each tree-ring latewood maximum density series was fitted with a 67-year cubic smoothing spline to remove non-climatic trends, and the latewood maximum density chronology was developed using the ARSTAN program spanning 1253-2017 AD for our study area. Correlation analyses were conducted between the latewood maximum density chronology and climatic elements recorded at Deqin meteorological station. The results indicated that the strongest correlation (r = 0.495, p <0.01) was found between the average September-October maximum temperature and the latewood maximum density chronology, and a stronger correlation (r = 0.763, p <0.01) was found for the first-difference data of the same variables. Furthermore, the results of a 31-year moving correlation analysis indicated that the correlation between maximum density chronology and average September-October maximum temperatures weakened during 1955-2017, whereas it exhibited a stronger correlation and further increased after the first difference during the same period. These results suggest that it would be better if the tree-ring latewood maximum density served as a proxy for inter-annual temperature variation. However, such a conclusion requires further validation for the northwestern Yunnan Province.
Yangfan LIN , Mingqi LI . First-difference Data of Tree-ring Latewood Maximum Density Better Reveals Interannual Temperature Variation in Northwestern Yunnan Province[J]. Advances in Earth Science, 2024 , 39(5) : 466 -475 . DOI: 10.11867/j.issn.1001-8166.2024.039
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