Abstract

Abstract In Mali the annual rainfall is highly variable, ranging from less than 200 mm–1 300 mm and its distribution is unevenly spread between north and south. Climate change threatens to increase air temperatures and evapotranspiration, increase the risk of intense rainstorms, and increase the risk of heat waves associated with drought. The objective of this study is to assess the change trends of daily temperature and precipitation extremes in Bamako and Segou in Mali during the period between 1961 and - 2014. Analyses of the changes in trends of daily temperature and precipitation extremes in two regions were studied by calculated extreme climate extreme indices series in RClimdex software. Trends in extreme indices were studied for 5 temperature and 4 precipitation series. Results showed a positive significant decrease of warming trends in cool days, cool nights, whereas warm extreme nights, day times and warm spells on the contrary showed positive significant increasing warming throughout the Segou region. In Bamako, temperature extreme showed an insignificant trend for negative extremes decreasing warming trends for cold nights and cold days while warm nights, warm days and warm spells showed insignificant positive trends over the period from 1961 to 2014. The results of precipitation extremes for Segou showed positive significant decrease in consecutive wet day and in extremely wet, whereas Maximum 5 day's precipitation showed positive insignificant increase and the total annual precipitation showed a positive insignificant decrease. In Bamako consecutive wet day, Maximum 5 day's precipitation and total annual precipitation showed positive insignificant decrease. Despite the small number of homogenous temperature and rainfall indices series, the study could present a proportion of significant extremes in Segou station averages trends. The study provided evidence that during the last 53 years; Segou was particularly affected by warm extremes based on night time indices rather than cold extremes based on day time indices.

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