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A novel method for detecting abrupt dynamic change based on the changing Hurst exponent of spatial images

He, Wen-Ping, Liu, Qun-Qun, Gu, Bin, Zhao, Shan-Shan
Climate dynamics 2016 v.47 no.7-8 pp. 2561-2571
climate, dynamic models, methodology, temperature
The climate system is a classical spatiotemporal evolutionary dynamic system with spatiotemporal correlation characteristics. Based on this, two-dimensional detrended fluctuation analysis (TD-DFA) is used to estimate the Hurst exponent of two-dimensional images. Then, we monitored the change of the Hurst exponent of the images to identify an abrupt dynamic change. We tested the performance of this method with a coupled spatiotemporal dynamic model and found that it works well. The changes in the Hurst exponents of the spatial images are stable when there is no dynamic change in the system, but there will be a clear non-stationary change of the Hurst exponents; for example, the abrupt mean values change if the dynamics of the system change. Thus, the TD-DFA method is suitable for detecting an abrupt dynamic change from natural and artificial images. The spatial images of the NCEP reanalysis of the daily average temperature exhibited fractality. Based on this, we found three non-stationary changes in the Hurst exponents for the NCEP reanalysis of the daily average temperature or for the annual average temperature in the region (60°S–60°N). It can be concluded that the climate system may have incurred three dynamic changes since 1961 on decadal timescales, i.e., in approximately the mid-1970s, the mid-1980s, and between the late 1990s and the early 2000s.