| Popis: |
Extreme precipitation has been threatening many sectors of human society and is likely to intensify with global warming. In the present study, we have analysed the impact of future climate change on daily mean rainfall and heavy rainfall on seasonal and annual scales in the Democratic Republic of Congo (DRC) by using ten long-term runs of high-resolution regional climate models. We initially assessed the performance of each run and the multi-model ensemble mean in simulating the daily mean rainfall (PRE), the maximum one-day rainfall (Rx1day), the simple rainfall intensity index (SDII), the count of days when rainfall is greater than or equal to 20 mm (RR20mm), the total rainfall when the daily rainfall exceeds the 95th percentile of the wet-day rainfall (R95p) and the maximum number of consecutive days with more than or equal to 1 mm (CWD). Next, we examined the future changes of these indices, focusing on the multi-model ensemble mean and spread under the high emission scenario RCP8.5. The time frames considered are the mid and end of the twenty-first century (2035–2065 and 2070–2100, respectively). The results indicate that the performance of REMO2015-MPI-ESM was close to the multi-model ensemble mean in representing the mean rainfall and most heavy rainfall indices, while CanRCM4-CamESM2 was identified as the worst performing model. The key finding of this study is that the multi-model ensemble mean project no significant change regarding the daily mean rainfall throughout the year and across all seasons by the middle of the 21st century, except of the western region of the country where a decrease is projected. Simultaneously, Rx1day, SDII, RR20mm, and R95p are projected to decrease almost everywhere during all seasons. Moreover, a consistent decrease in the number of wet days is projected. Focusing on the end of the century, the multi-model ensemble mean project an overall decrease in daily mean rainfall, especially in the western region of the DRC, with a more pronounced effect during MAM. The increase in Rx1day, SDII, RR20mm, and R95p, along with a decrease in CWD, is amplified in this period. These findings are useful for predicting the potential threats of precipitation-related diseases and natural hazards, as well as for designing climate-resilient infrastructure and socioeconomic activities in the DRC. |
