Modern Computational Techniques for Environmental Data; Application to the Global Ozone Layer
Modern Computational Techniques for Environmental Data; Application to the Global Ozone Layer
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DOI：
10.1007/11428862_69
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发表时间：
2005-05
影响因子：
6
通讯作者：
C. Varotsos
中科院分区：
文献类型：
--
作者：
C. Varotsos
支配大气现象的物理定律大多是非线性的，因此，对大气量的时间序列应用常规傅立叶谱分析揭示了它们通常是非平稳的。这些非平稳性往往掩盖了现有的相关性，因此应采用能够消除数据中的非平稳性的新分析技术。沿着这些路线使用的最新分析方法是小波技术和去趋势波动分析。最近，人们对后一种技术给予了很大的关注，它已经在各种复杂系统中证明了它的有用性。作为一个范例，去趋势波动分析应用于柱臭氧数据。具体而言，地面（1964-2004年）和卫星（1979-2003年）仪器进行的纬向和全球平均气柱臭氧观测被用来检测气柱臭氧时间序列的长期相关性。结果表明，在4个月到11年的时间间隔内，臭氧柱的波动都表现出长期的幂律相关性。
The physics laws, which govern the atmospheric phenomena, are mostly non-linear and therefore the application of the conventional Fourier spectral analysis on the time series of the atmospheric quantities reveals that these are usually non-stationary. Quite often these non-stationarities conceals the existing correlations and therefore new analytical techniques capable to eliminate non-stationarities in the data should be employed. The most recent analytical methods used along these lines are the wavelet techniques and the detrended fluctuation analysis. Much attention has been paid recently to the latter technique, which has already proved its usefulness in a large variety of complex systems. As a paradigm, the detrended fluctuation analysis is applied to the column ozone data. Specifically the zonally and globally averaged column ozone observations conducted by ground-based (1964-2004) and satellite-borne (1979-2003) instrumentation are employed to detect long-range correlations in column ozone time series. The results show that column ozone fluctuations exhibit persistent long-range power-law correlations for all time lags between 4 months – 11 years.