基于标准化后的高分辨率气候代用资料,应用高阶矩分析方法检测近2000年来气候极端异常演变特征;同时结合滤波方法进行具有物理背景的层次分离,进而研究了各时间层次气候极端异常变化信息及其贡献.结果表明:1)在100年以上的时间层次上,可能存在千年左右的气候变化振荡周期,而且20世纪是近2000年来气候极端异常现象最为活跃的时段,可能对应于气候极端异常现象活跃期.2)对于20—60年这一时间层次,公元300—1100年间气候极端异常现象比较明显,而公元1100—1980年间相对比较缓和;该层次对20世纪的气候异常没有显著贡献.世纪以上和20—60年时间层次均揭示出在近2000年的气候变化中,公元1100年前后可能是一个气候极端异常现象演变的关键转折时期.3)在年际尺度上(小于20年),北京石花洞石笋微层厚度时间序列中发生气候极端异常现象的年份与出现E1Ni o事件和La Ni a事件的年份有非常好的对应关系(仅讨论公元1960—1980年).4)高阶矩分析方法对于检测气候极端异常分布及演变规律有较好的应用前景.
Due to global warming, the general circulation, underlying surfaces characteristics, and geophysical and meteorological elements all show evident secular trends. This paper points out that when calculating the correlation of two variables containing their own obvious secular trends, the interannual correlation characteristics between the two variables may be distorted (overestimated or underestimated). Numerical experiments in this paper show that if two variables have opposite secular trends, the correlation coefficient between the two variables is reduced (the positive correlation is underestimated, or the negative correlation is overestimated); and if the two variables have the same sign of secular trends, the correlation coefficient between the two variables is increased (the positive correlation is overestimated, or the negative correlation is underestimated). Numerical experiments also suggest that the effect of secular trends on the interannual correlation of the two variables is interchangeable, that is to say, as long as the values of the two trends are not changed, the two variables interchange their positions, and the effect of the secular trends on the interannual correlation coefficient of the two variables remains the same. If the two variables have the same-(opposite-) sign trends, the effect of secular trends on the interannal correlation coefficient is more (less) distinctive. A meteorological example is given.
Extreme sensitivity to initial values is an intrinsic character of chaotic systems. The evolution of a chaotic system has a spatiotemporal structure containing quasi-periodic changes of different spatiotemporal scales. This paper uses an empirical mode decomposition (EMD) method to decompose and compare the evolution of the time-dependent evolutions of the x-component of the Lorenz system. The results indicate that the sensitivity of intrinsic mode function (IMF) component is dependent on initial values, which provides some scientific evidence for the possibility of long-range climatic prediction.