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Accurate medium-range global weather forecasting with 3D neural networks

Earth Sciences

Accurate medium-range global weather forecasting with 3D neural networks

K. Bi, L. Xie, et al.

Discover Pangu-Weather, an innovative AI-driven approach to global weather forecasting that surpasses the European Centre for Medium-Range Weather Forecasts. Developed by Kaifeng Bi, Lingxi Xie, Hengheng Zhang, Xin Chen, Xiaotao Gu, and Qi Tian from Huawei Cloud, this method excels in extreme weather prediction and offers significantly faster computation times.

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Playback language: English
Abstract
This paper introduces Pangu-Weather, an AI-based method for accurate medium-range global weather forecasting. Using three-dimensional deep networks with Earth-specific priors and a hierarchical temporal aggregation strategy, Pangu-Weather outperforms the European Centre for Medium-Range Weather Forecasts (ECMWF) operational integrated forecasting system in deterministic forecasts across all tested variables. It also excels in extreme weather and ensemble forecasting, demonstrating significantly faster computation times.
Publisher
Nature
Published On
Jul 20, 2023
Authors
Kaifeng Bi, Lingxi Xie, Hengheng Zhang, Xin Chen, Xiaotao Gu, Qi Tian
Tags
AI-based forecasting
medium-range weather
deep networks
extreme weather
computational efficiency
global forecasting
hierarchical aggregation

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