arXiv Open Access 2025

Advanced Long-term Earth System Forecasting

Hao Wu Yuan Gao Ruijian Gou Xian Wu Chuhan Wu +28 lainnya

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Abstrak

Reliable long-term forecasting of Earth system dynamics is fundamentally limited by instabilities in current artificial intelligence (AI) models during extended autoregressive simulations. These failures often originate from inherent spectral bias, leading to inadequate representation of critical high-frequency, small-scale processes and subsequent uncontrolled error amplification. Inspired by the nested grids in numerical models used to resolve small scales, we present TritonCast. At the core of its design is a dedicated latent dynamical core, which ensures the long-term stability of the macro-evolution at a coarse scale. An outer structure then fuses this stable trend with fine-grained local details. This design effectively mitigates the spectral bias caused by cross-scale interactions. In atmospheric science, it achieves state-of-the-art accuracy on the WeatherBench 2 benchmark while demonstrating exceptional long-term stability: executing year-long autoregressive global forecasts and completing multi-year climate simulations that span the entire available $2500$-day test period without drift. In oceanography, it extends skillful eddy forecast to $120$ days and exhibits unprecedented zero-shot cross-resolution generalization. Ablation studies reveal that this performance stems from the synergistic interplay of the architecture's core components. TritonCast thus offers a promising pathway towards a new generation of trustworthy, AI-driven simulations. This significant advance has the potential to accelerate discovery in climate and Earth system science, enabling more reliable long-term forecasting and deeper insights into complex geophysical dynamics.

Topik & Kata Kunci

cs.LG

Penulis (33)

Hao Wu

Yuan Gao

Ruijian Gou

Xian Wu

Chuhan Wu

Huahui Yi

Johannes Brandstetter

Fan Xu

Kun Wang

Penghao Zhao

Hao Jia

Qi Song

Xinliang Liu

Juncai He

Shuhao Cao

Huanshuo Dong

Yanfei Xiang

Fan Zhang

Haixin Wang

Xingjian Shi

Qiufeng Wang

Shuaipeng Li

Ruobing Xie

Feng Tao

Yuxu Lu

Yu Guo

Yuntian Chen

Yuxuan Liang

Qingsong Wen

Wanli Ouyang

Deliang Chen

Niklas Boers

Xiaomeng Huang

Format Sitasi

APA MLA BibTeX

Wu, H., Gao, Y., Gou, R., Wu, X., Wu, C., Yi, H. et al. (2025). Advanced Long-term Earth System Forecasting. https://arxiv.org/abs/2505.19432

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Informasi Jurnal

Tahun Terbit: 2025
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓