Researchers in charge :
● ACE SMIA
○ Prof. Ossénatou Mamadou, University of Abomey-Calavi, Benin.
● ACE MITIC, Senegal
○ Prof. Mamadou Bousso, Gaston Berger University, Senegal.
● Prof. Marc Aubinet, University of Liège, Belgium.
Title: Geometric and wavelet transform methods for driving information in atmospheric sciences
Type of project: Research project (4 years)
In the face of rapid climate change and dramatic global warming, it is essential to detect and quantify the underlying processes that control the changing amplitude of climate variables (radiation, water vapor, sensible heat, CO2, etc.). This will enable a precise understanding of these processes and a better prediction of their evolution, feedback cycles and influence on climate change in West Africa. Although advanced studies have been carried out worldwide, we cannot "blindly" transpose the models developed to West Africa without solid examination and analysis. For example, in temperate climates, soil temperature is the most important factor in the emission of CO2 into the atmosphere, whereas in some cultivated areas in the Sudanian climate (West Africa), soil moisture appears to be the most important factor. Consequently, there is an urgent need to develop appropriate methods for detecting, analyzing and monitoring climate variable factors with a view to prediction and action for a sustainable environment. To this end, GWAS will combine fundamental/applied mathematical methods/tools to make a relevant contribution to atmospheric sciences. In terms of fundamental mathematics, the project will use geometric analysis and wavelet transforms, while in terms of applied mathematical tools, machine learning and deep learning will be used, as well as topological analysis. With these tools, GWAS will track the course of key factors and models using eleven (11) years of in situ measurements (acquired as part of an international research program). By bringing together researchers from across West Africa to tackle challenging problems in their region, GWAS will create a multi-disciplinary network of researchers who will contribute to the region's development ideas.
● Digital science research topics: mathematics, wavelet transforms, statistics, data science, machine learning, deep learning.