Abstract
AbstractClimate change impact on rainfall and temperature extreme indices in the Vea catchment was analyzed using observation and an ensemble mean of bias-corrected regional climate models datasets for Representative Concentration Pathway (RCP 4.5) scenario. Rainfall extreme indices such as annual total wet-day precipitation (PRCPTOT), extremely wet days (R99P), consecutive wet days (CWD), consecutive dry days (CDD), and temperature indices such as warmest day (TXx) and warmest night (TNx) from the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI) were computed for both the historical (1986–2016) and future (2020–2049) period using the RClimdex. The parametric ordinary least square (OLS) regression approach was used to detect trends in the time series of climate change and extreme indices. The results show an increase in mean annual temperature at the rate of 0.02 °C/year and a variability in rainfall at the catchment, under RCP 4.5 scenario. The warmest day and warmest night were projected to increase by 0.8 °C and 0.3 °C, respectively, in the future relative to the historical period. The intensity (e.g., R99p) and frequency (e.g., CDD) of extreme rainfall indices were projected to increase by 29 mm and 26 days, respectively, in the future. This is an indication of the vulnerability of the catchment to the risk of climate disasters (e.g., floods and drought). Adaptation strategies such as early warning systems, availability of climate information, and flood control measures are recommended to reduce the vulnerability of the people to the risk of the projected impact of climate extreme in the future.
Highlights
IntroductionGlobal surface temperature has increased by 0.71 °C with significant warming observed in many regions (Trenberth et al 2007)
95 Climate Change Impact on Climate Extremes and Adaptation Strategies in the. . . 1939 rainfall has resulted in higher frequency of flood and drought events, putting the socioeconomic activities at risk (Awotwi et al 2015)
Several climate extreme indices have been developed by the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI) for understanding climate extremes and are widely used in several regions (Mouhamed et al 2013; Soro et al 2016; M’Po et al 2017)
Summary
Global surface temperature has increased by 0.71 °C with significant warming observed in many regions (Trenberth et al 2007). Over 40% of the populace has encountered hunger situations, that resulted from failure of one-third of crop produced when compared to 2010 data, leading to humanitarian appeals (Sarr 2012; FAO 2013) These and other ensuing impacts have necessitated the analysis of changes in future climate extremes necessary in reducing potential social, economic, and ecological consequences (Amuzu et al 2018; Bohle et al 2018). This is based on the Representative Concentration Pathways (RCP 4.5) scenario, which would recommend adaptation strategies required at the community level to reduce the vulnerability of the people to the risk of climate change and extreme events in the future
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