Aristotelis Koskinas, Eleni Zaharopoulou, George Pouliasis, Ilias Deligiannis, P. Dimitriadis, T. Iliopoulou, N. Mamassis, Demetris Koutsoyiannis
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引用次数: 2
Abstract
Hydroclimatic processes such as precipitation, temperature, wind speed and dew point are usually considered to be independent of each other. In this study, the cross−correlations between key hydrological−cycle processes are examined, initially by conducting statistical tests, then adding the impact of long−range dependence, which is shown to govern all these processes. Subsequently, an innovative stochastic test that can validate the significance of the cross−correlation among these processes is introduced based on Monte−Carlo simulations. The test works as follows: observations obtained from numerous global−scale timeseries were used for application to, and a comparison of, the traditional methods of validation of statistical significance, such as the t−test, after filtering the data based on length and quality, and then by estimating the cross−correlations on an annual−scale. The proposed method has two main benefits: it negates the need of the pre−whitening data series which could disrupt the stochastic properties of hydroclimatic processes, and indicates tighter limits for upper and lower boundaries of statistical significance when analyzing cross−correlations of processes that exhibit long−range dependence, compared to classical statistical tests. The results of this analysis highlight the need to acquire cross−correlations between processes, which may be significant in the case of long−range dependence behavior.
期刊介绍:
Publishes research on the interactions among the atmosphere, hydrosphere, biosphere, cryosphere, and lithosphere, including, but not limited to, research on human impacts, such as land cover change, irrigation, dams/reservoirs, urbanization, pollution, and landslides. Earth Interactions is a joint publication of the American Meteorological Society, American Geophysical Union, and American Association of Geographers.