U-Net Kalman Filter (UNetKF): An Example of Machine Learning-assisted Ensemble Data Assimilation

arXiv:2403.12366v1 Announce Type: new
Abstract: Machine learning techniques have seen a tremendous rise in popularity in weather and climate sciences. Data assimilation (DA), which combines observations and numerical models, has great potential to incorporate machine learning and artificial intelligence (ML/AI) techniques. In this paper, we use U-Net, a type of convolutional neutral network (CNN), to predict the localized ensemble covariances for the Ensemble Kalman Filter (EnKF) algorithm. Using a 2-layer quasi-geostrophic model, U-Nets are trained using data from EnKF DA …

abstract artificial artificial intelligence arxiv climate cs.lg data ensemble example filter intelligence machine machine learning machine learning techniques numerical paper physics.ao-ph type weather