Classic trend analysis methods’ paradoxical results and innovative trend analysis methodology with percentile ranges

Birpınar M. E., Kızılöz B., ŞİŞMAN E.

Theoretical and Applied Climatology, vol.153, no.1-2, pp.1-18, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 153 Issue: 1-2
  • Publication Date: 2023
  • Doi Number: 10.1007/s00704-023-04449-6
  • Journal Name: Theoretical and Applied Climatology
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, IBZ Online, PASCAL, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Artic & Antarctic Regions, BIOSIS, CAB Abstracts, Environment Index, Geobase, Index Islamicus, INSPEC, Pollution Abstracts, Veterinary Science Database
  • Page Numbers: pp.1-18
  • Yıldız Technical University Affiliated: Yes


In this study, spatial–temporal monotonic and non-monotonic trends in Assam, India, have been analyzed for annual precipitation data through the classical and innovative trend analysis (ITA) methodology. The results of the ITA method have been presented with percentile (quartile) intervals. Thus, within the scope of this study, piecewise trends (low; 25% < , medium; 25–75%, and high; 75% > categories) have been objectively analyzed and identified. The annual precipitation data that was measured in twenty stations in the Assam region from 1901 to 2002 is used for the analysis. According to the classical Modified Mann–Kendall (MMK) method results, only in one station of twenty stations, there is an increasing trend contrary to the decreasing trends in five stations; on the other hand, there is no trend in fourteen stations. As regards to the classical Sen’s slope (SS) method calculation, a method which is frequently used together with the MMK method to calculate trend slopes, there are paradoxical results between the MMK and SS method. For instance, at the Cachar station, while there is not any significant trend according to the MMK methodology, the result of the SS methodology points out the largest decreasing trend magnitude. Also, the MMK and SS results are incompatible for the Hailakandi, Karimganj, Dhemaji, Nagaon, Barpeta, Golaghat, Kokrajhar, and Lakhimpur stations. On the other hand, there is little incompatibility between the results of the ITA and SS methods. Also, comprehensive information regarding piecewise trends has been obtained through the ITA model graphs with a quartile range.