Skillful Kilometer-Scale Regional Weather Forecasting via Global and Regional Coupling

• URL: http://arxiv.org/abs/2603.28173v1
• Date: Mon, 30 Mar 2026 08:40:36 GMT
• Title: Skillful Kilometer-Scale Regional Weather Forecasting via Global and Regional Coupling
• Abstract summary: This paper presents a global-regional coupling framework for kilometer-scale regional weather forecasting.<n>It couples a Transformer-based global model with a high-resolution regional network via a novel bidirectional coupling module, ScaleMixer.<n>The framework produces forecasts at $0.05circ$ ($sim 5 mathrmkm$ ) and 1-hour resolution over China, significantly outperforming operational NWP and AI baselines on both gridded reanalysis data and real-time weather station observations.
• Score: 13.378669933059015
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Data-driven weather models have advanced global medium-range forecasting, yet high-resolution regional prediction remains challenging due to unresolved multiscale interactions between large-scale dynamics and small-scale processes such as terrain-induced circulations and coastal effects. This paper presents a global-regional coupling framework for kilometer-scale regional weather forecasting that synergistically couples a pretrained Transformer-based global model with a high-resolution regional network via a novel bidirectional coupling module, ScaleMixer. ScaleMixer dynamically identifies meteorologically critical regions through adaptive key-position sampling and enables cross-scale feature interaction through dedicated attention mechanisms. The framework produces forecasts at $0.05^\circ$ ($\sim 5 \mathrm{km}$ ) and 1-hour resolution over China, significantly outperforming operational NWP and AI baselines on both gridded reanalysis data and real-time weather station observations. It exhibits exceptional skill in capturing fine-grained phenomena such as orographic wind patterns and Foehn warming, demonstrating effective global-scale coherence with high-resolution fidelity. The code is available at https://anonymous.4open.science/r/ScaleMixer-6B66.

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