Improve latent compression resolution

Background: The accuracy of deep learning weather models is fundamentally limited by the reconstruction error inherent in the autoencoder used to compress atmospheric fields into a latent space.

Question / Future Work: Future work should explore higher-resolution latent compressions, as the current spatial resolution (1.5°) constrains the model’s ability to capture fine-scale atmospheric features, such as the intensity of tropical cyclones.