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About this paper
Marc Bocquet, Tobias S. Finn, Sibo Cheng
The IEnKF-G learns a conditional distribution of possible next states and uses observations to jointly adjust the starting state and generative model’s random seed. It was tested in twin experiments with two idealized chaotic systems. In partially observed stochastic Lorenz 1963, filtering and one-step smoothing RMSEs were about 2.5 and 2.3, versus 3.2 and 3.4 for IEnKF-Q; operational forecasting was not tested.
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