关键词: 气候变化, 集合经验模态分解(EEMD), 本征模函数(IMF)

Abstract: Ensemble empirical mode decomposition (EEMD), a newly developed nonlinear data analysis method, is employed to derive climate change signals, such as annual cycle, low-frequency components and trends, etc. The data sets for the analysis are the well-homegenized, longer than 150 years, daily temperature series of five stations in Europe. The decomposed results indicate that there are three main time scales, e.g. interannual, interdecadal and century scales, for the low-frequency variations of all five stations. The intensities of the annual cycle were weak during the two warm periods: 1910?1940 and the last 30 years since 1970. And the weak trend was more obvious in the last 30 years. In addition, summers become more longer and winters shorter since the late of 1970s compared with that of warm period in 1910?1940.

Key words: climate change, ensemble empirical mode decomposition (EEMD), intrinsic mode function (IMF)