Earth Sciences

FuXi: a cascade machine learning forecasting system for 15-day global weather forecast

L. Chen, X. Zhong, et al.

Discover FuXi, a groundbreaking machine learning weather forecasting system that delivers 15-day global forecasts with impressive accuracy! Crafted by esteemed researchers Lei Chen, Xiaohui Zhong, Feng Zhang, Yuan Cheng, Yinghui Xu, Yuan Qi, and Hao Li, this innovative model not only competes with the ECMWF ensemble mean but also outshines the ECMWF HRES in forecast lead time. Get ready to explore the future of weather predictions!

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Index

Abstract

This paper introduces FuXi, a cascaded machine learning (ML) weather forecasting system capable of producing 15-day global forecasts at a 6-hour temporal and 0.25° spatial resolution. Trained on 39 years of ECMWF ERA5 reanalysis data, FuXi's performance is comparable to the ECMWF ensemble mean (EM) for 15-day forecasts, surpassing the ECMWF HRES in skillful forecast lead time. FuXi's ensemble, generated by perturbing initial conditions and model parameters, provides forecast uncertainty estimates.

Publisher

npj Climate and Atmospheric Science

Published On

Jul 26, 2023

Authors

Lei Chen, Xiaohui Zhong, Feng Zhang, Yuan Cheng, Yinghui Xu, Yuan Qi, Hao Li

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