The uncertainty of break positions detected by homogenization algorithms in climate records
The uncertainty of break positions detected by homogenization algorithms in climate records
复制标题
气候记录中均质化算法检测到的断裂位置的不确定性
DOI：
10.1002/joc.4366
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Victor Venema
中科院分区：
文献类型：
--
作者：
Lindau;Victor Venema
长期的仪器气候记录由于站点的搬迁或仪器的改变而受到不均匀的影响，这可能会在时间序列中引入突然的跳跃。这些不均匀可能掩盖或强化真实的趋势。相对均化算法使用候选站与相邻站的差异时间序列来识别这样的中断(变化点)。现代多断点方法以段内内方差最小，段间外方差最大为特征，寻找最优分段方法，分析了这些方法的精度，并着重分析了分段位置的不确定性。由于差分时间序列中不可避免的随机噪声，分割方法可能会找到一个移位的突变位置，从而获得比真实突变更高的外部方差。考虑潜在交换的子段的不同长度；提供最大外部方差的子段将被选择为可能错误的最优。我们将证明，移位分割的方差可以描述为带有漂移的布朗运动，其中信噪比(SNR)定义了漂移大小。
Long instrumental climate records suffer from inhomogeneities due to, eg, relocations of the stations or changes in instrumentation, which may introduce sudden jumps into the time series. These inhomogeneities may mask or strengthen true trends. Relative homogenization algorithms use the difference time series of a candidate station with neighboring stations to identify such breaks (changepoints). Modern multiple breakpoint methods search for the optimum segmentation, which is characterized by minimum internal variance within the segments and maximum external variance between the segment means.We analyze the accuracy of these homogenization methods and concentrate on the uncertainty in the position of the break. Due to unavoidable random noise in the difference time series, the segmentation method may find a shifted break position, which attains a higher external variance than the true one. Different lengths of potentially exchanged subsegments are considered; that one providing the largest external variance will be chosen as possibly erroneous optimum. We will show that the variances of shifted segmentations can be described as Brownian motion with drift, where the signal-to-noise ratio (SNR) defines the drift size.