The application of piecewise ITA method in Oxford, 1870–2019

Abstract

In this study, the trends and stabilities of temperature and precipitation hydro-meteorology time series recorded since 1870 in Oxford city of England were analyzed in detail. The Innovative Triangular Trend Analysis (ITTA) method has been inspired to identify and analyze the trends and stabilities of the selected time series. To compare the results obtained by the abovementioned method, the Classical Mann Kendall (MK) method has been applied to each series determined for ITTA design. Thanks to the innovative design of ITTA which is preferred by the Classic MK and Sen slope methods, the trends of time series could be analyzed in detail. In this study, the first draft structure has been improved with the help of ±5-±10 % percentage change levels which were added to the ITTA method, and thus more objective evaluations about the trend magnitudes in time series is possible. For the same draft, the monotonic trend slopes which were found by the classical MK were also calculated through the Sen slope method. The data trends could explain in more detail with the help of the draft used in this study, compared to the studies in the literature. Climate change, which has been the most important factor in trend formation in recent years, has been taken into consideration while determining the design series. The thirty-year period up to 2019, a year in which the climate change was felt much more, constitutes the most important reference years for the analysis beginning from 1990, a year in which the climate change effects started to emerge. When the data trends of one hundred fifty years are examined for the different sub-time series, it is seen that the temperature increase in during1990-2019 period is much higher than the past hundred and twenty years, according to the analysis results. The highest average precipitation occurred in the 1990-2019 and 1900-1929 periods, and their amounts and patterns are nearly similar.

Non-monotonic trend analysis using Mann-Kendall with self-quantiles

“…Non-monotonic trends (low and high values have different positive or negative trend directions in a time series) are lastly come into question with Şen ITA method (Şen-ITA). Some researchers (Alifujiang et al, 2021;Berhail et al, 2022;Dabanli et al, 2021;Şan et al, 2021;Saplıoğlu and Güçlü, 2022;Şişman and Kizilöz, 2021) claim that Şen-ITA method is superior to MK because of that MK method cannot detect non-monotonic trends on time series while Şen-ITA can. Research results support these claims using visual evaluations on a 1:1 graph.…”

Artvin ve Rize İstasyonlarına ait Aylık Toplam Yağış Verilerinin Trendinin Farklı Yöntemlerle Değerlendirilmesi

“…Daha sonra Şen [13] tarafından, ITA sonuçlarının belli bir anlamlılık düzeyinde trend varlığının nicel olarak belirlenmesi için Yenilikçi Trend Anlamlılık Testi (ITST) önerilmiştir. Birçok araştırmacı tarafından ITA ve ITST yöntemleri farklı çalışmalarda çeşitli parametrelerin trendlerinin belirlenmesinde tercih edilmiştir [14][15][16][17]. Bu trend belirleme yöntemlerinden farklı olarak Şen ve ark.…”