Multi-scale decomposition of sea surface height snapshots using machine learning Article Swipe
Jingwen Lyu
,
Yue Wang
,
Christian Pedersen
,
Spencer Jones
,
Dhruv Balwada
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2409.17354
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2409.17354
Knowledge of ocean circulation is important for understanding and predicting weather and climate, and managing the blue economy. This circulation can be estimated through Sea Surface Height (SSH) observations, but requires decomposing the SSH into contributions from balanced and unbalanced motions (BMs and UBMs). This decomposition is particularly pertinent for the novel SWOT satellite, which measures SSH at an unprecedented spatial resolution. Specifically, the requirement, and the goal of this work, is to decompose instantaneous SSH into BMs and UBMs. While a few studies using deep learning (DL) approaches have shown promise in framing this decomposition as an image-to-image translation task, these models struggle to work well across a wide range of spatial scales and require extensive training data, which is scarce in this domain. These challenges are not unique to our task, and pervade many problems requiring multi-scale fidelity. We show that these challenges can be addressed by using zero-phase component analysis (ZCA) whitening and data augmentation; making this a viable option for SSH decomposition across scales.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2409.17354
- https://arxiv.org/pdf/2409.17354
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403795550
All OpenAlex metadata
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https://openalex.org/W4403795550Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2409.17354Digital Object Identifier
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Multi-scale decomposition of sea surface height snapshots using machine learningWork title
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-09-11Full publication date if available
- Authors
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Jingwen Lyu, Yue Wang, Christian Pedersen, Spencer Jones, Dhruv BalwadaList of authors in order
- Landing page
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https://arxiv.org/abs/2409.17354Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2409.17354Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2409.17354Direct OA link when available
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Scale (ratio), Decomposition, Surface (topology), Computer science, Artificial intelligence, Environmental science, Machine learning, Cartography, Geography, Mathematics, Geometry, Chemistry, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.unprecedented | 59 |
| abstract_inverted_index.image-to-image | 98 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile |