长期气象数据集参数和非参数时间序列分析方法的比较

T. Kocsis, I. Kovács-Székely, A. Anda
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引用次数: 24

摘要

本探索性研究采用移动平均法、确定性方法(随季节变化的线性趋势)和非参数Mann-Kendall趋势检验等不同的时间序列分析方法对1871年1月至2014年12月的逐月降水数据进行分析,比较不同分析方法的结果,发现气候变化的迹象。该数据集由潘诺尼亚大学提供,包含Keszthely气象站144年的月降水数据(1728个数据点)。这个数据集是特殊的,因为匈牙利很少有站点能够提供如此长时间和连续的测量,并提供详细的历史背景。研究结果可以为西巴拉顿地区过去气候变化的迹象提供见解。分析时间序列的参数方法(线性趋势和斜率的t检验)是最简单的方法,可以深入了解变量随时间的变化。这些方法对残差的正态分布有要求,这可能是其应用的一个限制。非参数方法是无分布的,研究人员可以更复杂地观察时间序列中的变量趋势。
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Comparison of parametric and non-parametric time-series analysis methods on a long-term meteorological data set
In the present explorative study, different time-series analysis methods, such as moving average, deterministic methods (linear trend with seasonality), and non-parametric Mann–Kendall trend test, were applied to monthly precipitation data from January 1871 to December 2014, with the aim of comparing the results of these methods and detecting the signs of climate change. The data set was provided by the University of Pannonia, and it contains monthly precipitation data of 144 years of measurements (1,728 data points) from the Keszthely Meteorological Station. This data set is special because few stations in Hungary can provide such long and continuous measurements with detailed historical background. The results of the research can provide insight into the signs of climate change in the past for the region of West Balaton. Parametric methods (linear trend and t-test for slope) for analyzing time series are the simplest ones to obtain insight into the changes in a variable over time. These methods have a requirement for normal distribution of the residuals that can be a limitation for their application. Non-parametric methods are distribution-free and investigators can get a more sophisticated view of the variable tendencies in time series.
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来源期刊
Central European Geology
Central European Geology Earth and Planetary Sciences-Geology
CiteScore
1.40
自引率
0.00%
发文量
8
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