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The application of piecewise ITA method in Oxford, 1870–2019
Theoretical and Applied Climatology ( IF 3.4 ) Pub Date : 2021-07-09 , DOI: 10.1007/s00704-021-03703-z
Eyüp Şişman 1, 2 , Burak Kizilöz 3
Affiliation  

In this study, the trends, stabilities of temperature, and rainfall data have been analyzed in detail for hydrometeorology time series recorded since 1870 in Oxford city in England. The innovative trend analysis (ITA) method has been used to identify and analyze the piecewise trends and stabilities of the selected time series. To compare the results, the modified Mann–Kendall (MMK) and Sen’s slope (SS) methods have been applied to each series as a piecewise ITA application. To obtain reliable and objective conclusions, ± 5% and ± 10% trend percentage lines have been considered in the application of the ITA method. The piecewise ITA method provides more detailed information in this study, compared to the studies in the literature such as the MMK. Identification of trends that implies climate change is taken into consideration by the ITA approach for future design purposes. In this study, the available time series with a record length of 150 years has been divided into sub-series of 30 years considering the last 30-year period in which climate change began to be discussed due to its significant effects. As a result, when the trends of 150 years are examined for the different partial series, it is seen that the temperature increase in the 1990–2019 period is much higher than the past 120 years. The highest average rainfall occurred in the 1990–2019 and 1900–1929 periods, and their amounts are nearly similar.



中文翻译:

分段ITA方法在牛津的应用,1870-2019

在这项研究中,详细分析了自 1870 年以来在英格兰牛津市记录的水文气象时间序列的趋势、温度稳定性和降雨数据。创新的趋势分析 (ITA) 方法已被用于识别和分析所选时间序列的分段趋势和稳定性。为了比较结果,改进的 Mann-Kendall (MMK) 和 Sen 斜率 (SS) 方法已作为分段 ITA 应用程序应用于每个系列。为了获得可靠和客观的结论,在 ITA 方法的应用中考虑了 ± 5% 和 ± 10% 的趋势百分比线。与 MMK 等文献中的研究相比,分段 ITA 方法在本研究中提供了更详细的信息。ITA 方法将识别暗示气候变化的趋势用于未来设计目的。在这项研究中,考虑到气候变化因其显着影响而开始讨论的最后 30 年期间,将记录长度为 150 年的可用时间序列划分为 30 年的子序列。因此,当对不同的部分序列考察 150 年的趋势时,可以看到 1990-2019 年期间的温度升高远高于过去 120 年。最高的平均降雨量出现在 1990-2019 年和 1900-1929 年期间,它们的数量几乎相似。考虑到气候变化因其显着影响而开始被讨论的过去 30 年期间,已将记录长度为 150 年的可用时间序列分为 30 年的子序列。因此,当对不同的部分序列考察 150 年的趋势时,可以看到 1990-2019 年期间的温度升高远高于过去 120 年。最高的平均降雨量出现在 1990-2019 年和 1900-1929 年期间,它们的数量几乎相似。考虑到气候变化因其显着影响而开始被讨论的过去 30 年期间,已将记录长度为 150 年的可用时间序列分为 30 年的子序列。因此,当对不同的部分序列考察 150 年的趋势时,可以看到 1990-2019 年期间的温度升高远高于过去 120 年。最高的平均降雨量出现在 1990-2019 年和 1900-1929 年期间,它们的数量几乎相似。

更新日期:2021-07-09
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