采用树轮图像分析方法研究历史时期气候变化的可行性

A PRELIMINARY STUDY ON CLIMATE CHANGE RESEARCH DURING HISTORICAL TIME USING IMAGE ANALYSIS OF TREE RING IN KANGDING AREA, SICHUAN PROVINCE

本文以川西云杉为例，探讨了采用树轮图像分析方法进行历史时期气候变化研究的可行性。对比分析发现，图像分析得到的年轮宽度序列与宽度仪的测量结果基本相同；而年轮宽度与年轮灰度序列之间不存在明显关系，其差异可能是不同环境因子作用的结果。图像分析得到的川西云杉年轮灰度年表在反映某些气候要素变化上优于年轮宽度年表，并以年轮最小灰度、年轮平均灰度和晚材平均灰度较为突出。川西云杉年轮灰度主要受初春月平均最高气温的影响，且两者为负相关关系。

In this paper. We concentrate on the study of the possibility of the usage of tree ring Image Analysis in the climate change research during historical time in Kangding area of Sichuan Province,with Picea balfouriana sampled from West Sichuan Province. Image analysis is a new method used in dendroclimatology with the reflected brightness (defined as Gray Value) as climate change indicators. There are ten different parameters, which include three ring width series and seven gray value series. got from image analysis. Twenty samples of eleven trees are selected by correlation analysis to be used in chronologies. The research period is 1950-1992. there is almost no difference between the ring width series derived from image analysis and from ring width measurement instrument. So the series from image analysis can be used in the comimg research. The relationship between the series of gray value parameters is not as close as that of the series of ring width parameters. Ten chronologies is built. Divide the seven Gray Value chronologies into two parts: on is the Maximum Gray Value, Early Wood Gray Value and Tree Ring Gray Value; the other is Minimum Gray Value, Ratio Between Maximum and Minimum Gray Value, difference Between maximum and Minimum Gray Value and later wood gray value. Relationship between the chronologies in part is closer than that of different parts. Four monthly averaged climate factors (precipitation,temperature, maximum temperature and minimum temperature) are used in the analysis to discover the relationship between the chronologies and climate change. It is shown that changes in ring width chronologies are closer to that of yearly precipitation, and the correlation coefficient is 0. 42.Changes in gray value chronologies are closer to that of monthly averaged temperature parameters.especially the relationship between the March-april maximum averaged temperature and the minimum gray value, gray value ratio, gray value difference, three ring gray value and later wood gray value. The correlation coefficients between is-0. 58. -0. 56. 0. 53, -0. 51 and -0. 58,respectively. So. we can see that more useful data are derived from image analysis. and more information on the climate change during the historical time will be derived from the analysis of these data.