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

• Published in: Theoretical and applied climatology Vol. 153; no. 1-2; pp. 1 - 18
• Main Authors: Birpinar, Mehmet Emin, Kizilöz, Burak, Sisman, Eyüp
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01.07.2023; Springer; Springer Nature B.V
• Subjects: Analysis; Annual precipitation; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Climate science; Climatology; Earth and Environmental Science; Earth Sciences; Graphs; Hydrologic data; Incompatibility; Methodology; Methods; Original Paper; Precipitation; Precipitation data; Slopes; Trend analysis; Trends; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-023-04449-6

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.