Stratospheric polar vortex predictability is multimodal, with short-term forecasts dominated by persistence of the leading state and extended forecasts arising from higher-order stratospheric structures plus tropospheric variability.
Charlton and Lorenzo M
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
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Explicit 3D vertical coupling emerges as a key inductive bias for ML emulation of SSW dynamics in idealised Isca runs, though prediction skill does not guarantee physical fidelity in wave driving.
citing papers explorer
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State-resolved multimodal contributions to stratospheric polar vortex predictability
Stratospheric polar vortex predictability is multimodal, with short-term forecasts dominated by persistence of the leading state and extended forecasts arising from higher-order stratospheric structures plus tropospheric variability.
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Investigating Inductive Biases for Machine Learning Emulation of Sudden Stratospheric Warmings in Idealised Isca Simulations
Explicit 3D vertical coupling emerges as a key inductive bias for ML emulation of SSW dynamics in idealised Isca runs, though prediction skill does not guarantee physical fidelity in wave driving.