Deep Learning for Koopman Operator Estimation in Idealized Atmospheric
Dynamics
Deep Learning for Koopman Operator Estimation in Idealized Atmospheric
Dynamics
Deep learning is revolutionizing weather forecasting, with new data-driven models achieving accuracy on par with operational physical models for medium-term predictions. However, these models often lack interpretability, making their underlying dynamics difficult to understand and explain. This paper proposes methodologies to estimate the Koopman operator, providing a linear representation of …