Spatiotemporal coherent displacements for ensemble-based neural data assimilation
Abstract While deep learning (DL) methods have expanded the approach to solving state estimation problems in data assimilation (DA), a robust approach requires extending them for uncertainty quantification. In this work, we propose a method to represent location-based uncertainty through random, spatiotemporally cohere...