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On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean–atmosphere systems
On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean–atmosphere systems
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On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean–atmosphere systems
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On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean–atmosphere systems
On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean–atmosphere systems

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On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean–atmosphere systems
On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean–atmosphere systems
Journal Article

On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean–atmosphere systems

2020
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Overview
The use of coupled Backward Lyapunov Vectors (BLV) for ensemble forecast is demonstrated in a coupled ocean–atmosphere system of reduced order, the Modular Arbitrary Order Ocean–Atmosphere Model (MAOOAM). It is found that overall the most suitable BLVs to initialize a (multiscale) coupled ocean–atmosphere forecasting system are the ones associated with near-neutral and slightly negative Lyapunov exponents. This unexpected result is related to the fact that these BLVs display larger projections on the ocean variables than the others, leading to an appropriate spread for the ocean, and at the same time a rapid transfer of these errors toward the most unstable BLVs affecting predominantly the atmosphere is experienced. The latter dynamics is a natural property of any generic perturbation in nonlinear chaotic dynamical systems, allowing for a reliable spread with the atmosphere too. Furthermore, this specific choice becomes even more crucial when the goal is the forecasting of low-frequency variability at annual and decadal time scales. The implications of these results for operational ensemble forecasts in coupled ocean–atmosphere systems are briefly discussed.