# Data-driven Global Ocean Modeling for Seasonal to Decadal Prediction

arXiv: https://arxiv.org/abs/2405.15412 · HTML: https://mlsanity.com/paper/2405.15412/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 74 references that are in the map.
- First posted on arXiv 24 May 2024.

## Builds on (most cited first, 9 of 9)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [Layer Normalization](https://mlsanity.com/paper/1607.06450/) (2016)
- [RoFormer: Enhanced Transformer with Rotary Position Embedding](https://mlsanity.com/paper/2104.09864/) (2021)
- [Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer](https://mlsanity.com/paper/1701.06538/) (2017)
- [GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks](https://mlsanity.com/paper/1711.02257/) (2017)
- [Neural General Circulation Models for Weather and Climate](https://mlsanity.com/paper/2311.07222/) (2023)
- [ResoNet: Robust and Explainable ENSO Forecasts with Hybrid Convolution and Transformer Networks](https://mlsanity.com/paper/2312.10429/) (2023)

## Built on by (most cited first, 14 of 14)

- [OmniEarth-Bench: Towards Holistic Evaluation of Earth's Six Spheres and Cross-Spheres Interactions with Multimodal Observational Earth Data](https://mlsanity.com/paper/2505.23522/) (2025)
- [NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal Simulation](https://mlsanity.com/paper/2505.21020/) (2025)
- [FuXi-2.0: Advancing machine learning weather forecasting model for practical applications](https://mlsanity.com/paper/2409.07188/) (2024)
- [FengWu-W2S: A deep learning model for seamless weather-to-subseasonal forecast of global atmosphere](https://mlsanity.com/paper/2411.10191/) (2024)
- [MedFormer: a data-driven model for forecasting the Mediterranean Sea](https://mlsanity.com/paper/2509.00015/) (2025)
- [FAConvLSTM: Factorized-Attention ConvLSTM for Efficient Feature Extraction in Multivariate Climate Data](https://mlsanity.com/paper/2601.10914/) (2026)
- [Eddy-Resolving Global Ocean Forecasting with Multi-Scale Graph Neural Networks](https://mlsanity.com/paper/2601.12775/) (2026)
- [Earth-o1: A Grid-free Observation-native Atmospheric World Model](https://mlsanity.com/paper/2605.06337/) (2026)
- [OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecasting](https://mlsanity.com/paper/2605.12639/) (2026)
- [Samudra 2: Scaling Ocean Emulators across Resolutions](https://mlsanity.com/paper/2606.02610/) (2026)
- [A-UTE: Advection Informed, Uncertainty Aware Temperature Emulator](https://mlsanity.com/paper/2410.21657/) (2024)
- [Data-driven global ocean model resolving ocean-atmosphere coupling dynamics](https://mlsanity.com/paper/2508.10908/) (2025)
- [Neptune: An AI model for Global Ocean Subseasonal Prediction](https://mlsanity.com/paper/2609.08606/) (2026)
- [OceanMoE: Structured Conditional Sparse Computation for Long-Horizon Multivariate Ocean Forecasting](https://mlsanity.com/paper/2609.19768/) (2026)

## Abstract (arXiv)

Accurate ocean dynamics modeling is crucial for enhancing understanding of ocean circulation, predicting climate variability, and tackling challenges posed by climate change. Despite improvements in traditional numerical models, predicting global ocean variability over multi-year scales remains challenging. Here, we propose ORCA-DL (Oceanic Reliable foreCAst via Deep Learning), the first data-driven 3D ocean model for seasonal to decadal prediction of global ocean circulation. ORCA-DL accurately simulates three-dimensional ocean dynamics and outperforms state-of-the-art dynamical models in capturing extreme events, including El Ni~no-Southern Oscillation and upper ocean heatwaves. This demonstrates the high potential of data-driven models for efficient and accurate global ocean forecasting. Moreover, ORCA-DL stably emulates ocean dynamics at decadal timescales, demonstrating its potential even for skillful decadal predictions and climate projections.