运气同化、异化与北京地区60年实际气候变化的吻合性研究

目的：验证运气同化、运气异化两组干支推演模式推演出的气候变化与北京地区60年实际气候变化的吻合情况。方法：首先,将60年分为运气同化26年和运气异化34年两组,统计出两组各年岁运、司天之气、在泉之气所主的气候特征与实际气候变化的符合年数,并进行χ2检验有无统计学显著性差异;然后,根据每年不同的整体符合率,分为4个等级进行评价,如整体符合率100%为完全符合,67%为基本符合,33%为部分符合,0%为完全不符合。分别计算出运气同化组、异化组的4个等级整体符合率的符合年数,采用非参数检验有无统计学显著性差异。结果：运气同化组的岁运、司天之气、在泉之气与实际气候变化的符合年数均比运气异化组高,但均无统计学显著性差异（P〉0.05）;而两组四个等级整体符合率的符合年数则具有统计学显著性差异（P〈0.05）,说明运气同化年与北京地区实际气候变化的吻合性较好。结论：运气同化年对预测北京地区的气候变化具有一定的参考意义。

Coincidence between Yun -qi of Assimilation and Alienation as Well as Actual Climate Changes in Beijing for 60 Years

Objective： To verify the coincidence between climatic changes deduced by two deduction modes, including Yun- qi assimilation and Yun- qi alienation, and actual climatic changes in Beijing area for 60 years. Methods： Firstly, the 60 years were divided into two groups of Yun - qi assimilation（26 years） and Yun - qi alienation （34 years） and the coincidence rate of each year was also caculated and the satistical difference was detected with x2 test. Secondly, the overall coincidence rate of every year in each group was divided into four grades ： overall coincidence rate of 100% Was full coincidence ;67% was basic coincidence ;33% was partial coincidence and 0% was full non -coincidence. Thirdly,the coincidence year number of the four grades in two modes, Yan- qi assimilation and Ynn - qi alienation, were calculated and the satistical difference was detected with non - parametric test. Results ： The coincidence year numbers in Yun - qi as- similation group were higher than that in Yun - qi alienation group, but there was no statistically significant difference （ P 〉 0.05 ）. In comparison, the difference in coincidence year numbers of the four grades had statistical significance （ P 〈 0.05） between Yun - qi assimilation group and Yun - qi alienation group. Conclusion ： The climatic changes deduced by Yun- qi assimilation mode are quite consistent with actual climatic changes in Beijing area, indicating that the Yun -qi assimilation year has the value of in - depth study in terms of weather forecast.