Authors: İsmail Dabanlı; Zekâi Şen
Addresses: Department of Civil Engineering, School of Engineering and Natural Sciences, Istanbul Medipol University, Beykoz, 34810, Istanbul, Turkey ' Department of Civil Engineering, School of Engineering and Natural Sciences, Istanbul Medipol University, Beykoz, 34810, Istanbul, Turkey; Faculty of Arid Lands, Meteorology and Agriculture, Center of Excellence for Climate Change Research (CECCR), King Abdulaziz University, Jeddah, Saudi Arabia
Abstract: The main purpose of this paper is to provide a comparison between the innovative-Şen and classical trend methods. Additionally, significance levels at ±5% and ±10% levels are suggested for the first time on the innovative-Şen trend template, which works with the categorisation of given data into a set of classes such as 'low', 'medium' and 'high' values. However, the classical approaches consider holistic monotonic trend identification without categorisation. Classical trend analyses methods, Mann-Kendall trend test coupled with, Şen's slope and the classical regression line, are based on a set of restrictive assumptions, but the innovative-Şen approach does not have assumptions. Application of classical methods do not present significant trend component, however, the innovative-Şen trend method provides possible trend components in each cluster within the significance limits. Although the classical approaches do not indicate a significant trend, but innovative-Şen approach provides some categorically significant trends in detail and quantitative information.
Keywords: category; climate change; innovative-Şen; significance; trend; Akarcay.
International Journal of Global Warming, 2018 Vol.15 No.1, pp.19 - 37
Available online: 18 May 2018 *Full-text access for editors Access for subscribers Purchase this article Comment on this article