no code implementations • 12 May 2023 • Maximiliano A. Sacco, Manuel Pulido, Juan J. Ruiz, Pierre Tandeo
The performance of this approach is examined within a hybrid data assimilation method that combines a Kalman-like analysis update and the machine learning based estimation of a state-dependent forecast error covariance matrix.
no code implementations • 29 Nov 2021 • Maximiliano A. Sacco, Juan J. Ruiz, Manuel Pulido, Pierre Tandeo
Experiments using the Lorenz'96 model show that the ANNs are able to emulate some of the properties of ensemble forecasts like the filtering of the most unpredictable modes and a state-dependent quantification of the forecast uncertainty.