π Tender Overview
Order At The Mesoscale: Connecting Supercomputing Of Compressible Convection To Classical And Quantum Machine Learning
Understanding The Origin And Role Of Mesoscale Convectionmesoscale Convection Is Often Found In The Form Of Ordered Patterns That Persist For Several Hours. These Systems Are Not Present At Larger And Smaller Scales, And Evolve In Unpredictable Ways. They Are Important Sources Of Uncertainty In The Prognosis Of Climate Change. In Climate Models Describing The Long-Term Evolution Of Earth~S Atmosphere, These Processes Are Greatly Simplified And Described As Additional Heat Fluxes. The Eu-Funded Mesocomp Project Will Conduct Parallel Simulations To Deepen Understanding Of Their Dynamics, Origin And Role In The Transport Of Heat And Momentum. These High-Fidelity Simulations Will Guide The Design Of Classical And Quantum Machine Learning Models To Predict The Evolution And Statistics Of Mesoscale Convection And Quantify The Transport Fluxes Beyond The Mesoscale.
Funded Under
European Research Council (Erc)
Total Cost
β¬ 2 500 000,00
Eu Contribution
β¬ 2 500 000,00
Coordinated By
Technische Universitaet Ilmenau
Germany