HClimRep-Ocean: A Global Ocean Emulator on an Unstructured Mesh
Machine-learning (ML) emulators for atmospheric processes have advanced rapidly in recent years, transforming weather forecasting. Although early ML ocean forecasting models now exist, they remain less developed than their atmospheric counterparts. Unlike the atmosphere, much of the ocean's kinetic energy resides in mesoscale eddies whose characteristic spatial scales are approximately an order of magnitude smaller than those of comparable atmospheric features. Moreover, complex coastlines, narrow straits, and ice-covered seas make boundary representation a central challenge that atmospheric models do not face. Consequently, numerical ocean simulations commonly use locally refined or even...
| Authors | Kacper Nowak, Aleksei Koldunov, Nikolay Koldunov et al. |
|---|---|
| Primary category | physics.ao-ph |
| Published | 23 September 2026 |
| Last updated at source | 28 September 2026 |
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