Au cours du mois de mai 2024, le Front Inter Tropical (FIT) a continué sa remonté vers le Nord amorcée en février. A la dernière décade du mois de mai, sa position moyenne était de 13°N, soit une migration saisonnière moyenne d'environ 1,6° (environ 242 km) par rapport à sa position moyenne d'avril 2024. A la dernière décade du mois, il se situe sur un axe Sud Sénégal, Centre Mali, extrême Nord Burkina Faso, Sud Niger et Centre Tchad (Figure 1). Sa position était plus au Nord au centre du Sahel qu'à l'Ouest et à l'Est. Cette position est favorable au démarrage de la saison des pluies dans les zones centre et Est de la bande sahélienne.

AGRHYMET Regional Climate Center for West Africa and Sahel (AGRHYMET-CCR-AOS), as part of its statutory mandate works to improve seasonal and sub-seasonal forecasting capabilities by using the NextGen approach (Houngnibo et al., 2022; Ali et al.; 2022). The NextGen forecasting system helps forecasters evaluate the performance of different global climate models, which helps determine how best to correct and combine them. It also helps forecasters select the best climate models for any region of interest through process-based evaluation, and it automates the generation and verification of forecasts suitable for multiple time scales at the regional, national, or local levels (Hansen et al., 2022). Through the Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA) project, AGRHYMET Regional Climate Centre has been capacitating National Meteorological and Hydrological Services (NMHSs) in West Africa and the Sahel on NextGen seasonal forecasting systems. The capacity development efforts focus mainly on Python interface to the Climate Predictability Tool (CPT) or PyCPT, a tool developed by the International Research Institute for Climate and Society (IRI) to implement the NextGen approach to climate forecasting (Hansen et al., 2022). The continuous improvement of the PyCPT tool has recently enabled the integration of key characteristics of the rainy season such as the onset dates of the season, dry and wet sequences, and number of dry and wet days, in addition to total rainfall. While hydrological forecasts of water availability from watersheds in major river basins are essential to support operational planning and management, the latest version of PyCPT developed by IRI does not take into account the seasonal forecast of hydrological variables. A recent survey the NMHSs on the barriers to operationalization of the NextGen approach and use the PyCPT tool indicated that a key challenge limiting the operationalization and use the PyCPT tool was the lack of consideration of hydrologic parameters (Segnon et al., 2023).