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Homogeneity assessment of phenological records from the Swiss Phenology Network

机译:瑞士候选网络的鉴别素记录的同质性评估

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Phenological data have become increasingly important as indicators of long-term climate change. Consequently, long-term homogeneity of the records is an important aspect. In this paper, we apply a breakpoint detection algorithm to the phenological series from the Swiss Phenology Network (SPN). A combination of three statistical tests is applied and different constraints are tested with respect to the choice of reference series. Breakpoint detection is only possible for a fraction of the series due to the shortness of some series and the lack of suitable reference series. Spring phases are more likely to be suitable than fall phases because of their higher spatial correlation. Out of nearly 3000 phenological series with at least 20 data points, only about 5% were found to be significantly inhomogeneous, although a visual validation indicates that many mid-sized breakpoints remained undetected. The detected breakpoints were compared with metadata and more than half of them could be attributed to a change of observer.
机译:作为长期气候变化的指标,职业数据变得越来越重要。因此,记录的长期同质性是一个重要方面。在本文中,我们将断点检测算法应用于瑞士珐琅网络(SPN)的毒性序列。应用三种统计测试的组合,并对参考系列的选择测试不同的约束。由于某些系列的短路和缺少合适的参考系列,因此仅可能对该系列的一部分进行分断点检测。由于其较高的空间相关性,弹簧相更可能与下降阶段合适。虽然视觉验证表明视觉验证表明许多中等大小断点未递断,但仅发现近3000个数据点的近3000个数据点。将检测到的断点与元数据进行比较,其中超过一半可能归因于观察者的变化。

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