Classical and innovative-Şen trend assessment under climate change perspective

Dabanlı İ., Şen Z.

International Journal of Global Warming, vol.15, no.1, pp.19-37, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 15 Issue: 1
  • Publication Date: 2018
  • Doi Number: 10.1504/ijgw.2018.091951
  • Journal Name: International Journal of Global Warming
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.19-37
  • Keywords: Akarcay, Category, Climate change, Innovative-Şen, Significance, Trend
  • Istanbul Medipol University Affiliated: Yes


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.