Monthly Arctic Sea‐Ice Prediction With a Linear Inverse Model
Abstract We evaluate Linear Inverse Models (LIMs) trained on last millennium model data to predict Arctic sea‐ice concentration, thickness, and other atmospheric and oceanic variables on monthly timescales. We find that more than 500 years of training data and 100 years of validation data are needed...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-04-01
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| Series: | Geophysical Research Letters |
| Online Access: | https://doi.org/10.1029/2022GL101656 |
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