Spherical multigrid neural operator for improving autoregressive global weather forecasting

Abstract Data-driven approaches for global weather forecasting have shown great potential. However, conventional architectures of these models struggle with spherical distortions, leading to unstable autoregressive forecasts. Although methods such as spherical Fourier neural operator (SFNO) based on...

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Autori principali:	Yifan Hu, Fukang Yin, Weimin Zhang, Kaijun Ren, Junqiang Song, Kefeng Deng, Di Zhang
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Nature Portfolio 2025-04-01
Serie:	Scientific Reports
Soggetti:	Spherical convolution Autoregressive forecasts Multigrid neural operator Spherical shallow water equations Global weather forecasting
Accesso online:	https://doi.org/10.1038/s41598-025-96208-y
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