Coll John, Domonkos Peter, Guijarro José, Curley Mary, Rustemeier Elke, Aguilar Enric, Walsh Séamus, Sweeney John
Irish Climate Analysis and Research Units, Department of Geography Maynooth University Maynooth Ireland.
Centre for Climate Change (C3) Universitat Rovira i Virgili Tortosa Spain.
Int J Climatol. 2020 Nov 30;40(14):6169-6188. doi: 10.1002/joc.6575. Epub 2020 Apr 16.
Time series homogenization for 299 of the available precipitation records for the island of Ireland (IENet) was performed. Four modern relative homogenization methods, that is, HOMER, ACMANT, CLIMATOL and AHOPS were applied to this network of station series where contiguous intact monthly records range from 30 to 70 years within the base period 1941-2010. Break detection results are compared between homogenization methods, and coincidences with available documentary information (metadata) were analysed. The lowest (highest) number of breaks were detected with HOMER (ACMANT). Large differences of break frequency were found, namely ACMANT and AHOPS detected 8 times as many breaks than HOMER, while the break frequency with CLIMATOL was intermediate. Also, the ratio of series classified to be homogeneous varies widely between the methods. It is 85% with HOMER, 60% with CLIMATOL, 31% with AHOPS, while only 22% with ACMANT. In a further experiment, all the available time series for Ireland and Northern Ireland, (910 series) were used with ACMANT and CLIMATOL to explore the stability of break frequency for the same 299 series examined in the base experiment. While overall break frequency slightly increased (by 6-13%), the break positions notably changed for individual time series. The number of breaks changed for 59% (23%) of the series with ACMANT (CLIMATOL). For the breaks detected coincidentally by at least three methods including ACMANT and CLIMATOL in the base experiment, the second experiment confirmed the break positions in 86-87% of the breaks. The consequences of these results in relation to the reliability of statistical homogenization are discussed. Sometimes markedly different step functions provide comparable good approaches. However, the accuracy of homogenized time series cannot be related directly to the instability of break detection results.
对爱尔兰岛（IENet）299条可用降水记录进行了时间序列均一化处理。四种现代相对均一化方法，即HOMER、ACMANT、CLIMATOL和AHOPS，被应用于该站点序列网络，其中在1941 - 2010年基期内连续完整的月度记录时长为30至70年。比较了均一化方法之间的断点检测结果，并分析了与可用文献信息（元数据）的一致性。使用HOMER检测到的断点数量最少（最多）。发现断点频率存在较大差异，即ACMANT和AHOPS检测到的断点数量是HOMER的8倍，而CLIMATOL的断点频率处于中间水平。此外，被分类为均一的序列比例在不同方法之间差异很大。HOMER为85%，CLIMATOL为60%，AHOPS为31%，而ACMANT仅为22%。在进一步的实验中，使用ACMANT和CLIMATOL对爱尔兰和北爱尔兰的所有可用时间序列（910个序列）进行分析，以探究在基础实验中所研究的相同299个序列的断点频率稳定性。虽然总体断点频率略有增加（6% - 13%），但各个时间序列的断点位置显著变化。使用ACMANT（CLIMATOL）时，59%（23%）的序列断点数量发生了变化。对于在基础实验中至少由包括ACMANT和CLIMATOL在内的三种方法同时检测到的断点，第二次实验在86% - 87%的断点中确认了断点位置。讨论了这些结果对统计均一化可靠性的影响。有时明显不同的阶跃函数能提供相当好的方法。然而，均一化时间序列的准确性不能直接与断点检测结果的不稳定性相关联。
