Joint Seminar: When does the Lorenz 1963 Model exhibit the Signal-to-Noise Paradox?

Recent advances in seasonal prediction systems led to skillful seasonal dynamical ensemble predictions of the winter North Atlantic Oscillation (NAO). However, the predictive skill reported for these systems is accompanied by a potential inconsistency: The quality of the predictions measured over a set of retrospective forecasts and quantified by the correlation coefficient between prediction and observation exceeds expectations based exclusively on model properties. This puzzling phenomena is also known as the Signal-to-Noise Paradox (SNP).  We investigated the SNP in the Max Planck Institute Earth System Model (MPI-ESM) and in a conceptual model based on the Lorenz (1963) model (L63). For the latter, we set up a simple initialized ensemble prediction system, which enables us to separate the influence of uncertainties in the model initialization and uncertainties in the model formulation on the quality of the prediction. We show that, if we the uncertainty in the initialization systematically overestimates the observational uncertainty the SNP is also apparent in L63 even if there are no uncertainties in the model formulation itself.




15:15 h


Virtual Seminar


Bjoern Mayer, Institut für Meereskunde, Universität Hamburg


Shih-Wei Fang

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