The West African Monsoon, the principal driver of rainfall in the region, exhibits complex spatio-temporal variability. While significant progress has been made in synoptic and seasonal forecasting, the sub-seasonal (2-4 week) timescale remains a major challenge for numerical weather prediction models, particularly in Africa. This forecasting horizon is nevertheless critical for decision-making in key sectors such as agriculture, flood management, and public health.
Key Responsibilities:
- Evaluate the performance of sub-seasonal to seasonal (S2S) forecasting models developed by the consortium.
- Participate in the development and optimization of innovative ML methods for S2S forecasting and statistical downscaling, with a focus on West Africa.
- Act as a liaison between methodological developments and their operational applications within African meteorological services.
- Contribute to writing scientific publications and technical reports.
Candidate Profile
Essential Qualifications:
The candidate must:
- Hold a PhD in Atmospheric Sciences, Climate Physics, Meteorology, or a closely related field.
- Possess a strong understanding of atmospheric dynamics and the West African monsoon system, as well as numerical climate models, particularly atmospheric models.
- Have proven proficiency in programming languages for data analysis (Python is strongly preferred; R, MATLAB, or NCL are also acceptable).
