biostudies-literatureSun XNational Natural Science Foundation of China (National Science Foundation of China)6658https://www.ebi.ac.uk/biostudies/studies/S-EPMC12276244biostudies-literatureUnknown16(1)Weather forecasting traditionally relies on numerical weather prediction (NWP) systems that integrate global observations, data assimilation (DA), and physics-based models. However, further advances are increasingly constrained by high computational costs, the underutilization of vast observational datasets, and challenges in obtaining finer resolution. Recent advances in machine learning present a promising alternative, but still depend on the initial conditions generated by NWP systems. Here, we introduce FuXi Weather, a machine learning-based global forecasting system that assimilates multi-satellite data and is capable of cycling DA and forecasting. FuXi Weather generates reliable 10-day forecasts at 0.25° resolution using fewer observations than conventional NWP systems. It demonstratNature communicationsA data-to-forecast machine learning system for global weather.PMC1227624442341205Li HWu LHuang YFeng JQi YHan WZhong XSun XXu XNeelin JDChen DfalseA data-to-forecast machine learning system for global weather.Weather forecasting traditionally relies on numerical weather prediction (NWP) systems that integrate global observations, data assimilation (DA), and physics-based models. However, further advances are increasingly constrained by high computational costs, the underutilization of vast observational datasets, and challenges in obtaining finer resolution. Recent advances in machine learning present a promising alternative, but still depend on the initial conditions generated by NWP systems. Here, we introduce FuXi Weather, a machine learning-based global forecasting system that assimilates multi-satellite data and is capable of cycling DA and forecasting. FuXi Weather generates reliable 10-day forecasts at 0.25° resolution using fewer observations than conventional NWP systems. It demonstrat2025-01-01T00:00:00Z2025 Jul2026-03-31T10:24:59.917Z2025-08-23T03:09:08.57ZS-EPMC122762444068387610.1038/s41467-025-62024-1