滇西北地区树轮晚材最大密度一阶差数据能更好地揭示温度年际变化

First-difference Data of Tree-ring Latewood Maximum Density Better Reveals Interannual Temperature Variation in Northwestern Yunnan Province

树轮晚材最大密度是反映当年生长季或者生长季末期温度较好的代用指标。基于采自滇西北地区的油麦吊云杉(Picea brachytyla var. complanata)树木样芯,利用DENDRO2003树轮密度分析系统获取了树轮晚材最大密度数据,选用步长为67年的样条函数拟合树轮晚材最大密度序列趋势,使用ARSTAN程序建立了1253—2017年的树轮晚材最大密度年表,并将树轮晚材最大密度年表与德钦站气候要素进行了相关分析。结果表明:树轮晚材最大密度年表与9~10月平均最高温的相关系数最高(r=0.495,p<0.01),一阶差序列相关更高(r=0.763,p<0.01),并且31年滑动相关分析结果显示,树轮晚材最大密度年表与9~10月平均最高温之间的滑动相关系数呈下降趋势,而一阶差序列的滑动相关系数较原始序列更高且呈上升趋势。该结果表明树轮晚材最大密度一阶差序列可以更好地揭示温度年际变化。该现象在滇西北地区是否具有普遍性,仍需进一步验证。

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.