Estimating the Statistical Significance of Cross–Correlations between Hydroclimatic Processes in the Presence of Long–Range Dependence

IF 1.6 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Earth Interactions Pub Date : 2022-09-15 DOI:10.3390/earth3030059
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.
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在存在长期依赖的情况下,估算水文气候过程间相互相关的统计意义
水文气候过程如降水、温度、风速和露点通常被认为是相互独立的。在本研究中,主要水文循环过程之间的交叉相关性进行了检验,首先通过进行统计测试,然后添加了远程依赖的影响,这表明控制所有这些过程。随后,在蒙特卡罗模拟的基础上,引入了一种创新的随机测试,可以验证这些过程之间相互关联的重要性。检验的工作如下:从许多全球尺度时间序列中获得的观测数据,在根据长度和质量过滤数据后,然后通过估计年尺度上的交叉相关性,将传统的统计显著性验证方法(如t检验)用于应用和比较。所提出的方法有两个主要优点:它不需要可能破坏水文气候过程随机特性的预白化数据序列,并且与经典统计检验相比,在分析表现出长期依赖性的过程的交叉相关性时,统计显著性的上下限限制更严格。这一分析的结果强调需要获得过程之间的交叉相关性,这在长期依赖行为的情况下可能是重要的。
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来源期刊
Earth Interactions
Earth Interactions 地学-地球科学综合
CiteScore
2.70
自引率
5.00%
发文量
16
审稿时长
>12 weeks
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.
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