Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving ...

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving models while retaining their accuracy. The approach retains physics-based ...

Deep learning is increasingly being used to emulate cloud and convection processes in climate models, offering a faster alternative to computationally intensive cloud-resolving simulations. However, ...