Modelling the complex and highly non-linear climate system remains a scientific challenge with an enormous societal impact. Advances in physical modelling and data assimilation techniques have greatly improved the quality of weather forecasts and climate projections. Techniques from artificial intelligence, such as deep learning, are increasingly used to enhance or emulate physics-based models, and to infer the ground truth from vast and heterogeneous sets of observational data.