Trend Analysis for Extreme Rainfall at Sub-Daily and Daily Timescales in Côte d’Ivoire

Extreme rainfall events are meteorological hazards that cause great damage and many casualties in the world. This paper examines the trends in extreme rainfall from 10 sub-daily time series and 44 daily time series in Côte d’Ivoire. Rainfall data were converted into indices. In total, six (6) indices were used for daily extreme rainfall and one (1) index for sub-daily extreme rainfall (15 to 240 min). Two statistical tests for trend detection were used to evaluate the possible trend in these precipitation data. The first is a Mann-Kendall non-parametric trend test, used to evaluate the existence of monotonic trends. The second is a linear regression method, based on a parametric approach to trend detection. Results show that very few statistically significant decreasing trends can be detected at the sub-daily and daily timescales. Some decreasing trends in extreme rainfall events were localized in the south and southeast. These results could enhance the implementation of adaptation systems to flood risk