pith:7DOZ3MH7
Multiscale Decomposition Reveals Predictable Interannual Variability and Climate Trends in Antarctic Sea Ice Loss
Regularized dynamic mode decomposition forecasts Antarctic sea ice anomalies up to two years ahead by isolating stationary modes.
arxiv:2604.26594 v2 · 2026-04-29 · physics.ao-ph
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Claims
The predictive DMD model (IceDMD) is regularised to prioritize the stationary spatiotemporal modes found by the decomposition. The predictive model can forecast SIC anomalies in 2023-2024 up to two years in advance, outperforming all existing approaches with the additional benefits of physical interpretability and extremely cheap computational cost.
That regularizing the DMD predictor to emphasize the stationary modes identified in the same decomposition produces genuine out-of-sample skill rather than fitting artifacts that fail on future data.
Hierarchical DMD on Antarctic sea ice data attributes 2014-2017 fluctuations to interannual modes, identifies a dominant climate trend after 2022, and delivers a low-cost IceDMD predictor that outperforms existing methods for 2023-2024 anomalies.
Receipt and verification
| First computed | 2026-05-28T01:04:41.048512Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/7DOZ3MH7SW5ICP6FIIHTU7P2S2 \
| jq -c '.canonical_record' \
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# expect: f8dd9db0ff95ba813fc5420f3a7dfa968708b5cdc10c73b5d3729bc6a2a6f18b
Canonical record JSON
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