Projected changes in extreme precipitation and temperature events over Central Africa from COSMO‐CLM simulations under the global warming level of 1.5°C and above

Abstract

This study explores the response of the increased global warning levels (GWLs) on the spatio‐temporal characteristics of extreme precipitation and temperature events over Central Africa (CA). For this purpose, eight indices proposed by the Expert Team on Climate Change Detection and Indices have been computed based on an ensemble‐mean of simulations from the COnsortium for Small‐scale MOdelling in CLimate Mode (CCLM) regional climate model, under the Representative Concentration Pathways scenario RCP8.5. The ability of CCLM to represent the climatology of considered daily hydro‐climatic extreme indices related to both precipitation and temperature was also assessed. The results showed that despite the presence of some biases, the precipitation and temperature indices are satisfactorily represented by CCLM, with some notable improvements compared to the GCMs driving fields. The climate change signals under 1.5°C GWL threshold show mostly increases (decreases) in SDII, CDD, R95PTOT, T10, T90, WSDI, and DTR (RR1) over CA throughout the year, and these effects intensify towards a warmer world. Singularly, the strongest changes in these extreme events are generally recorded during the JJA season over the northern part of CA. The results also show on one hand a widespread decrease in mean precipitation (up to 2 mm · day−1 corresponding to ~50%) associated with the increase/decrease in CDD/RR1, and on the other hand an increase in mean temperatures (up to 4°C corresponding to ~18%) associated with the increase in both lowest and highest temperatures (T10, T90). This study suggests that the CA region will be prone to droughts and floods as well as heat waves in a warmer world and calls for climate action and adaptation strategies to mitigate the risks associated with the above changes on rain‐fed agriculture, water resource, and human health.

Runoff Simulation of the Upstream Watershed of the Feiling Hydrological Station in the Qinhe River Based on the SWAT Model

“…Recent years have seen significant strides in research on the effects of climate change and human activities on runoff, especially as global warming and frequent human activities intensify. Studies indicate that global warming has led to an increase in extreme precipitation events, profoundly impacting hydrological balance and water resource availability [14,15]. In China, rapid economic growth and urbanization have accentuated human impacts on basin runoff [16,17].…”