Development of operational seasonal and sub-seasonal forecast of precipitation - Benguerir
Secteur de l’entreprise : Enseignement / Formation
ENTREPRISE :
Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its fields The University is engaged in economic and human development and puts research and innovation at the forefront of African development. A mechanism that enables it to consolidate Morocco’s frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa. Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally.
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Culture de l'entreprise :
UM6P – Université Mohammed VI Polytechnique se caractérise par une culture fortement orientée innovation, où la créativité, l’expérimentation et l’audace intellectuelle constituent des piliers essentiels. L’université encourage l’initiative, l’ouverture d’esprit et l’autonomie, dans un environnement stimulant tourné vers la recherche, l’entrepreneuriat et l’impact. Cette dynamique innovante est enrichie par une dimension coopérative solide, valorisant la collaboration, le partage des savoirs et le développement humain. Une orientation vers la performance et l’excellence complète l’ensemble, tandis que les processus formels restent volontairement plus légers pour préserver l’agilité.
Poste :
Morocco, with its diverse geography, experiences highly variable precipitation patterns across different time scales. Managing water resources in this context presents substantial challenges. Reliable precipitation forecasts are indispensable for water stakeholders in Morocco, spanning various lead times. The country's precipitation exhibits a distinct seasonal pattern, with the majority occurring from November to April. Within this wet season, precipitation events are sporadic, often concentrated within a few days when storms approach Morocco. Predicting water availability for the upcoming season is therefore crucial, especially for stakeholders who allocate water resources at the start of the water year.
Previously, a straightforward algorithm was developed to predict seasonal precipitation in Morocco. This algorithm relies on Sea Surface Temperature (SST) data from various regions of the Atlantic and Pacific Oceans as predictors for Morocco's seasonal precipitation. The forecasting model employs multiple linear regression and offers probabilistic insights, explaining approximately 40% of inter-annual precipitation variability during winter and spring. The model's performance has been assessed over the past 5 years, consistently matching observed results in nearly 60% of cases.
The primary objective of this position is to develop an operational seasonal forecasting system based on existing literature. The candidate is also expected to conduct technology monitoring to support the sustainability of the forecasting system. Rigorous benchmarking tests will be conducted to continually enhance the forecasting system's accuracy. Additionally, the candidate will be responsible for supporting the ongoing research activities of the group by establishing various climate datasets and regularly updating them.
Profil recherché :
Requirements :
Profil : ingénieurs ou docteurs-ingénieurs en mécanique des fluides, hydraulique, hydrologie, data science ou climat.
Expérience : Une connaissance dans la gestion des plateformes de calculs HPC est souhaitée.
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