Preprints
https://doi.org/10.5194/egusphere-2025-2704
https://doi.org/10.5194/egusphere-2025-2704
03 Jul 2025
 | 03 Jul 2025
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Stripe Patterns in Wind Forecasts Induced by Physics-Dynamics Coupling on a Staggered Grid in CMA-GFS 3.0

Jiong Chen, Yong Su, Zhe Li, Zhanshan Ma, and Xueshun Shen

Abstract. An unphysical stripe pattern is identified in low-level wind field in China Meteorological Administration Global Forecast System (CMA-GFS), characterized by meridional stripes in u-component and zonal stripes in v-component. This stripe noise is primarily confined to the planetary boundary layer over land. The absence of noise in both surface static fields and pure dynamic-core solutions proves that neither the dynamical core nor physical parameterizations alone can produce wind stripe patterns. These results suggest that staggered-grid mismatch in physics-dynamics coupling is likely the primary mechanism. Idealized two-dimensional experiments demonstrate that combining one-dimensional dynamic-core advection and physics-based vertical diffusion on a staggered grid generates 2Δx-wavelength spurious waves when surface friction is non-uniform. One-dimensional linear wave analysis further confirms that staggered-grid coupling between dynamic advection and inhomogeneous damping forcing induces dispersion errors in wave solutions. Sensitivity tests validate that eliminating grid mismatch in physics-dynamic coupling removes this stripe noise. These findings collectively indicate that while staggered grids benefit the dynamic core’s numerical stability and accuracy, their inherent grid mismatch with physics parameterizations requires specialized coupling strategies to avoid spurious noise. Potential solutions to remedy this issue are discussed.

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Jiong Chen, Yong Su, Zhe Li, Zhanshan Ma, and Xueshun Shen

Status: open (until 28 Aug 2025)

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Jiong Chen, Yong Su, Zhe Li, Zhanshan Ma, and Xueshun Shen
Jiong Chen, Yong Su, Zhe Li, Zhanshan Ma, and Xueshun Shen

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Short summary
Weather forecasts sometimes show high-frequency noise degrading predictions. Our study reveals stripe patterns arise from mismatches between dynamic and physical calculations in models. Simplified experiments demonstrate that adjusting their connection eliminates stripes. This advances numerical weather prediction understanding, aiding forecasters and the public. Our diagnostic methods provide a framework for solving this global meteorological modeling challenge.
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