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Seasonal Arctic sea ice forecasting with probabilistic deep learning
- Source :
- Nature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
- Publication Year :
- 2021
- Publisher :
- Nature Portfolio, 2021.
-
Abstract
- Accurate seasonal forecasts of sea ice are highly valuable, particularly in the context of sea ice loss due to global warming. A new machine learning tool for sea ice forecasting offers a substantial increase in accuracy over current physics-based dynamical model predictions.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 12
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.5d37269ed2734f7bac2303b89ff00149
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-021-25257-4