西秦岭地区工业革命前后250年温度和降水变化机理研究

西秦岭地区树轮气候学研究所用树轮宽度年表中存在温度和降水信号混合问题，阻碍了对该地区过去几百年历史气候变化的深入认识，而该问题也是国际树轮气候学研究的难点。本项目拟对西秦岭典型区域树轮宽度、氧同位素和蓝光强度三个指标进行测量，基于多指标年表对比分离宽度年表中温度和降水信号，提高单点气候重建序列的精度，重建该地区过去500年温度和降水空间格局。在此基础上，结合CMIP5多模式模拟结果，阐明工业革命前后250年，影响全球气候变化的主导因素转为人为因素的背景下，重建与模拟西秦岭地区温度和降水空间格局变化的异同，分析对应的模拟环流场和水汽输送特征，探讨该地区温度和降水变化的主要海气相互作用过程，尝试揭示工业革命前后西秦岭地区温度和降水空间格局变化的物理机理，为理解该地区当前气候变化和预估未来长期变化趋势提供科学参考。

Extreme climate change over the West Qinling Mountains has an important impact on the local economy and society. The mixing of temperature and precipitation signals in the tree-ring width chronology in the Western Qinling Mountains, hinders the deep understanding of the characteristics and mechanism of climate change in the region over the past several hundred years, and this question is also an issue of the international dendroclimatology research. Based on the measurements of tree width, oxygen isotope, and blue intensity, this project intends to develop a method to separate the temperature and precipitation signals from the tree ring width chronology to improve the accuracy of local temperature and precipitation reconstructions and update the integrated spatial patterns of temperature and precipitation variability over the past 500 years in the region. Combined this reconstruction with the Coupled Model Intercomparison Project Phase 5th (CMIP5) multi-model simulations, the similarities and differences between the reconstructed and simulated dominant modes of temperature and precipitation variability in the West Qinling Mountains during the 250 years before and after the industrial revolution are elucidated. Moreover, the corresponding simulated circulation fields and water vapor transportation, and the atmosphere-ocean interaction of the temperature and precipitation changes are analyzed to reveal the physical mechanism of the influences on the dominant modes of temperature and precipitation variability in the West Qinling Mountains under the background that the dominant factor affecting global climate change changed from natural factors to human factors before and after the industrial revolution, and provide a scientific reference for understanding the current climate change in the study area and forecasting the trend of future climate change.