The multi-fractal behaviors of relative humidity over China are studied using the multi-fractal detrended fluctuation analysis (DFA) method. Three multi-fractal parameters (the spectrum width Δα, the asymmetry Δα ...The multi-fractal behaviors of relative humidity over China are studied using the multi-fractal detrended fluctuation analysis (DFA) method. Three multi-fractal parameters (the spectrum width Δα, the asymmetry Δα as , and the long-range correlation exponent α 0 ) of the singularity spectrum are introduced to quantify the multi-fractal behaviors. The results show that multi-fractality exists in daily humidity records over most stations in China and is mainly due to the broad distribution of the probability density of the sequence values. Strong multifractal behaviors over some stations in the Yunnan, Guangdong, and Inner Mongolia provinces are obvious. These behaviors are mainly caused by different longrange correlations between large and small fluctuations. The asymmetry of the singularity of relative humidity records is weak, except for a small number of stations in the far east and west of China, where the singularity spectrum is left-skewed. Finally, the long-range correlations in North China are stronger than those in South China, which indicates better predictability in North China. By studying the parameters of the multi-fractal spectrum, various data of long-range power law correlations of the relative humidity records are obtained, which may provide theoretical support for climate prediction.展开更多
基金supported by the National Natural Science Foundation of China (40975027)
文摘The multi-fractal behaviors of relative humidity over China are studied using the multi-fractal detrended fluctuation analysis (DFA) method. Three multi-fractal parameters (the spectrum width Δα, the asymmetry Δα as , and the long-range correlation exponent α 0 ) of the singularity spectrum are introduced to quantify the multi-fractal behaviors. The results show that multi-fractality exists in daily humidity records over most stations in China and is mainly due to the broad distribution of the probability density of the sequence values. Strong multifractal behaviors over some stations in the Yunnan, Guangdong, and Inner Mongolia provinces are obvious. These behaviors are mainly caused by different longrange correlations between large and small fluctuations. The asymmetry of the singularity of relative humidity records is weak, except for a small number of stations in the far east and west of China, where the singularity spectrum is left-skewed. Finally, the long-range correlations in North China are stronger than those in South China, which indicates better predictability in North China. By studying the parameters of the multi-fractal spectrum, various data of long-range power law correlations of the relative humidity records are obtained, which may provide theoretical support for climate prediction.
