Pavel Berloff: hyper-parameterizations for ocean modeling

The seminar focused on the concept of hyperparameterization in ocean modeling, particularly using data to create emulators for complex processes. The main emphasis was on methods that enable the emulation of processes when direct modeling is challenging or computationally expensive. Various approaches were discussed, including the use of neural networks, differential equations, and innovative methods like multi-layer stochastic models. Hyperparameterization was presented as a way to enhance climate models by generating ensembles of solutions based on a single well-calibrated solution. The seminar addressed issues regarding the accuracy and reliability of such emulations and discussed the potential and limitations of the proposed methods.