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

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

摘要

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