Seasonality Effects on Nonlinear Properties of Hydrometeorological Records: A New Method of Data Analysis Academic Article uri icon

abstract

  • Climatic time series in general, and hydrological time series in particular, exhibit pronounced annual periodicity. This periodicity and its corresponding harmonics affect the nonlinear properties of the relevant time series (ie, the long-range volatility correlations and width of multifractal spectrum) and thus have to be filtered out before studying fractal and volatility properties. We compare several filtering techniques (one of them proposed here) and find that in order to eliminate the periodicity effect on the nonlinear properties of the time series (ie, the volatility and multifractal properties) it is necessary to filter out the seasonal standard deviation in addition to the filtering of the seasonal mean. The obtained results indicate weak volatility correlations (weak nonlinearity) in the river data, and this can be seen using different filterings approaches.[1] Livina~ V.~ N., Y.~ Ashkenazy, A.~ Bunde …

publication date

  • January 1, 2007