Abstract:In chaotic dynamical systems such as the weather, prediction errors grow faster in some situations than in others.Real-time knowledge about the error growth could enable strategies to adjust the modelling and forecasting infrastructure on-the-fly to increase accuracy and/or reduce computation time. For example one could change the spatiotemporal resolution of the numerical model, locally increase the data availability, etc. Local Lyapunov exponents are known indicators of the rate at which very small predictio… Show more
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