TLDR: It is very evident that large scale DL methods have had great success in predicting weather. However, very little attention has been paid to predicting climate and even less has been explored for extremes. Nevertheless, there is a wealth of information present within these models as they input large amounts of Multivariate, spatiotemporal data. We will look at using these pretrained models as dynamical models which can be included as relevant covariates to our extremes models. We can use standard nonlinear SSM to apply them, e.g., EKF, UKF, or ADF. We can also include methods like ensemble Kalman filters or particle filters. Lastly, we can explore retraining these models to predict the appropriate scales necessary for climate projections and extremes.