A5106245878- Climate variability and models
- Precipitation Measurement and Analysis
- demographic modeling and climate adaptation
- Hydrology and Drought Analysis
University of Abou Bekr Belkaïd
2024
In light of the lack ground-based observations, this study utilizes reanalysis data from CHIRPS database and CMIP6 models under SSP5-8.5 scenario to predict future rainfall in Beni–Irumu region eastern DR Congo. The use offers a viable method for understanding historical climate trends regions with limited ground data. Using spatial resolution 0.05°, selected general circulation (GCMs) were downscaled Analysis over 32 years reveals disparities, high-altitude like Mount Stanley experiencing...
Abstract Understanding changes in rainfall patterns is vital for effective water resource management and agricultural planning climate-sensitive regions. In Northeastern South Kivu, Democratic Republic of the Congo, limited knowledge dynamics poses challenges local climate assessments. This study analyzed using Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset from 1981 to 2023 fill this gap. The findings revealed significant spatial temporal across regions Kabare,...