Search

The main concern of this study is using a new type of innovative trend analysis (ITA) method with a particular graphical illustration. It compares the results with the classic MK trend test at a 95% confidence level. Among the 15 annual and seasonal data series (3 weather stations annually, spring, summer, autumn, and winter) studied, the MK trend test found significant increasing trends of 3 data series (20%). However, using the new ITA method, 6 data series (40%) ‘high’ and ‘low’ simultaneously showed a significant increasing trend. The new ITA method can also detect all significant trends identified by the MK trend test. As for the new ITA method, the ‘high’ values of the 12 data series (80%) exhibited significant increasing patterns, and the 9 data series (60%) displayed significant increasing patterns for ‘low’ values. According to the ‘low’ and ‘high’ values, a gain one data series (6.7%) manifested significant decreasing trends. These results detailed annual and seasonal precipitation data series patterns by evaluating ‘low’ and ‘high’ values. The findings also demonstrated that the new method runs counter to the previous ITA. HIGHLIGHTS Use MK trend test and innovative trend analysis method.; Compare long-term annual and seasonal precipitation variability.; Determine the data series change point on the new graph through the Pettit test for sub-categories.; To enhance the visual effect of the ITA methodology through the new type of innovative trend analysis method.; Classify the annual and seasonal time series in detail.;