The population of Senegal faces health challenges related to desert dust and heat waves (HWs). This study aims to (a) update the documentation of HWs in Senegal, expanding on the work of Sambou et al. (2019); (b) investigate the modulation of dust indicators during HWs; and (c) assess the distinct impacts of dust content on night-time and daytime HWs. We use [i] the daily maximum air temperature (Tx), minimum air temperature (Tn), and apparent temperature (Ta) from 12 stations in the Global Surface Summary of the Day (GSOD) database and [ii] the Dust Aerosol Optical Depth (Dust AOD), particulate matter (PM) concentrations, 925 hPa wind, and Mean Sea Level Pressure (MSLP) from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. HWs are defined for each station in spring as periods when Tx, Tn, or Ta exceeds the 95th percentile for at least three consecutive days. Three homogeneous zones from the Atlantic coast to inland Senegal are identified using hierarchical cluster analysis: Zone 1 (Saint-Louis, Dakar-Yoff, Ziguinchor, and Cap Skirring), Zone 2 (Podor, Linguère, Diourbel, and Kaolack), and Zone 3 (Matam, Tambacounda, Kédougou, and Kolda). Our results show that Zone 1 records the highest number of HWs for Tx, Tn, and Ta, while Zone 3 experiences more HWs in terms of Tn and Ta than Zone 2. The influence of dust is notably stronger for HWs linked to Tn and Ta than for those related to Tx. Analysis of the mechanisms shows that the presence of dust in Senegal and its surrounding regions is detected up to four days before the onset of HWs. These findings suggest that dust conditions associated with spring HWs in Senegal may be better distinguished and predicted.

Despite significant progress, precipitation forecasting in West Africa remains challenging due to the complexity of atmospheric processes and the region’s climatic variability. This study aims to identify optimal configurations of the WRF model to improve precipitation forecasting. To evaluate the sensitivity of the model’s physical parameterizations, 15 configurations were tested by combining various cumulus parameterization schemes (CPSs) and planetary boundary layer (PBL) schemes. The analysis examines two contrasting rainfall events in Senegal: one characterized by widespread intense precipitation and another featuring localized moderate rainfall. Simulated rainfall, temperature, and humidity were validated against rain gauges, satellite products (ENACTS, ARC2, CHIRPS, and IMERG), and ERA5 reanalysis data. The results show that the WRF configurations achieve correlation coefficients (r) ranging from 0.27 to 0.62 against ENACTS and from 0.15 to 0.41 against rain gauges. The sensitivity analysis reveals that PBL schemes primarily influence temperature and humidity, while CPSs significantly affect precipitation. For the heavy rainfall event, several configurations accurately captured the observed patterns, particularly those using Tiedtke or Grell–Devenyi CPSs coupled with the Mellor–Yamada–Janjic (MYJ) PBL. However, the model showed limited skill in simulating localized convection during the moderate rainfall event. These findings highlight the importance of selecting appropriate parameterizations to enhance WRF-based precipitation forecasting, especially for extreme weather events in West Africa.