article · Climate
An examination of long-term extreme precipitation indices in the northwestern highlands of Ethiopia evaluated climate data from 1981 to 2018 across three districts: Lay Gayint, Tach Gayint, and Simada. Using four by four kilometre gridded records from the National Meteorological Agency of Ethiopia, the research compared the Innovative Trend Analysis method against the traditional Mann-Kendall test. In Lay Gayint, Innovative Trend Analysis identified significant upward trends in ninety percent of analysed indices, whereas the Mann-Kendall test detected increases in thirty percent. In Tach Gayint, seventy percent of indices showed significantly increasing trends under the innovative approach. Conversely, sixty percent of extreme precipitation indices displayed significant downward trends in Simada. Overall, the comparative evaluation demonstrated that the Innovative Trend Analysis technique identifies a wider range of significant trends that the Mann-Kendall test misses.
Understanding regional variations in extreme rainfall helps communities and environmental planners identify areas facing heightened risks of flood or drought. Demonstrating that alternative statistical methods can detect trends that standard tests overlook provides climate researchers and planning bodies with better analytical approaches for assessing shifts in local weather extremes.
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This study analyzed long-term extreme precipitation indices using 4 × 4 km gridded data obtained from the National Meteorological Agency of Ethiopia between 1981 and 2018. The study examined trends in extreme precipitation over three districts (Lay Gayint, Tach Gayint, and Simada) in the northwestern highlands of Ethiopia. Innovative Trend Analysis (ITA) and Mann–Kendall (MK) trend tests were used to study extreme precipitation trends. Based on the ITA result, the calculated values of nine indices (90% of the analyzed indices) showed significant increasing trends (p < 0.01) in Lay Gayint. In Tach Gayint, 70% (seven indices) showed significantly increasing trends at p < 0.01. On the other hand, 60% of the extreme indices showed significant downward trends (p < 0.01) in Simada. The MK test revealed that 30% of the extreme indices had significantly increasing trends (p < 0.01) in Lay Gayint. In Tach Gayint, 30% of the extreme indices showed significant increasing trends at p < 0.05, while 10% of the extreme indices exhibited significant increasing trends at p < 0.01. In Simada, 20% of the extreme indices showed significant increasing trends at p < 0.05. Overall, the results showed that the ITA method can identify a variety of significant trends that the MK test misses.
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DOI: 10.3390/cli11080164
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