A Novel Approach for the Detection of Inhomogeneities Affecting Climate Time Series
A Novel Approach for the Detection of Inhomogeneities Affecting Climate Time Series
复制标题
检测影响气候时间序列的不均匀性的新方法
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
J. Luterbacher
中科院分区：
文献类型：
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作者：
A. Toreti;F. G. Kuglitsch;E. Xoplaki;J. Luterbacher
摘要由非气候因子（非均匀性）引起的突变通常会影响气候变量的工具时间序列。为了在观测的基础上进行可靠的气候分析，有必要对这些变化进行适当的识别。本文提出了一种基于遗传算法和隐马尔可夫模型的方法（根据其组成和目的命名为“GAHMDI”方法），用于检测均值和方差变化引起的不均匀性。建立了模拟系列和案例研究（意大利米兰气象站的冬季降水），将GAHMDI与现有方法进行比较，并突出其特点。对于单个变化点的识别，GAHMDI执行类似于其他方法（例如，标准正态同质性检验）。然而，对于多重不均匀性和方差变化的识别，由于避免了过度检测，GAHMDI的结果优于三种广泛使用的方法。对于未来在家庭中的应用和研究…
AbstractSudden changes caused by nonclimatic factors (inhomogeneities) usually affect instrumental time series of climate variables. To perform robust climate analyses based on observations, a proper identification of such changes is necessary. Here, an approach (named the “GAHMDI” method, after its components and purpose) that is based on a genetic algorithm and hidden Markov models is proposed for detection of inhomogeneities caused by changes in the mean and variance. Simulated series and a case study (winter precipitation from a weather station located in Milan, Italy) are set up to compare GAHMDI with existing methodologies and to highlight its features. For the identification of a single changepoint, GAHMDI performs similarly to other methods (e.g., standard normal homogeneity test). However, for the identification of multiple inhomogeneities and changes in variance, GAHMDI returns better results than three widespread methods by avoiding overdetection. For future applications and research in the hom...