arXiv (All)
open access
Learning native eddy-resolving ocean dynamics outperforms coarse emulation and downscaling
Eddy-resolving ocean simulations are essential for representing mesoscale dynamics that regulate ocean circulation, energy transport, and climate variability. However, they are costly to generate, store, and share. Artificial intelligence (AI) may help, but it remains unclear whether high-resolution
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Global Deep Ocean Observations of Horizontal Eddy–Mean Interactions of Temperature Variance#304462
- The GEOS/ECCO C1440-LLC2160 Coupled Atmosphere-Ocean Simulation Dataset#1081928
- Satellite-Based Identification of Mesoscale and Submesoscale Eddies and Fronts in the Gulf of Mexico#216026
- Inference of Unknown Dynamical Components Using Next Generation Reservoir Computing: From Chaotic Systems to Climate Data#1051157
- Inference of Unknown Dynamical Components Using Next Generation Reservoir Computing: From Chaotic Systems to Climate Data#1028695
Record · ID 1325541
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive