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Article | Publishing Language: Chinese

Sensitivity study of the stochastic perturbed parameterization tendencies (SPPT) in the CMA convection-permitting ensemble prediction system

Yanan MA1,2Jing CHEN3,4,5( )Hongqi LI3,4,5Jingzhuo WANG3,4,5Wei FENG1
Chinese Academy of Meteorological Sciences,Beijing 100081,China
College of Earth and Planetary Sciences,University of Chinese Academy of Sciences,Beijing 100049,China
CMA Earth System Modeling and Prediction Centre,Beijing 100081,China
State Key Laboratory of Severe Weather Meteorological Science and Technology,CEMC,Beijing100081,China
Key Laboratory of Earth System Modeling and Prediction,China Meteorological Administration,Beijing 100081,China
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Abstract

Effective representation of model uncertainty is crucial for improving the forecast skill of convection-permitting ensemble prediction system. The Stochastic Perturbed Parameterization Tendencies (SPPT) scheme is one of the primary approaches used to represent model uncertainty, and its effect is controlled by three parameters: Perturbation magnitude, temporal correlation scale, and horizontal perturbation scale. There have been few studies on the optimization of these three parameters for the operational 3 km CMA-REPS (Regional Ensemble Prediction System of China Meteorological Administration) v4.0. Based on CMA-REPS, this study selects 13 heavy rainfall cases in North China in 2024 to conduct SPPT parameter sensitivity experiments. The forecast skill for upper-air and surface variables, precipitation, and perturbation energy growth are analyzed. First, using a smaller magnitude (with a standard deviation of 0.35) and dropping attenuation of the perturbations within the boundary layer most effectively enhances the forecast skill of the variables. Second, a 3 h temporal scale is conducive to improving the forecast skill within the initial 12 h, whereas a 6 h time scale performs better after 24 h of integration. A horizontal scale of 500 km yields the best overall performance. Compared with a 1000 km scale, it improves the spread and consistency for most variables. Further reducing the scale to 200 km can improve light and moderate rain forecasts within the initial 12 h but leads to a decline in forecast skill after 18 h. Third, spatiotemporal scales significantly influence the perturbation energy growth. The 3 h temporal scale promotes the perturbation energy growth across scales within the initial 12 h, while the 6 h scale is more favorable for perturbation growth after 18 h. The 500 km horizontal scale is most beneficial for the development of difference kinetic energy and difference latent energy. Although the 200 km horizontal scale can initially enhance low-level perturbation energy and promote smaller-scale perturbation growth during convectively active periods, it results in the minimal development of larger- and meso-scale components, as well as perturbation in the middle and late periods of integration. In conclusion, a 0.35 standard deviation with unattenuated boundary layer perturbations, a 6 h temporal scale, and a 500 km horizontal scale are recommended.

CLC number: P456

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Acta Meteorologica Sinica
Pages 711-730

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Cite this article:
MA Y, CHEN J, LI H, et al. Sensitivity study of the stochastic perturbed parameterization tendencies (SPPT) in the CMA convection-permitting ensemble prediction system. Acta Meteorologica Sinica, 2026, 84(4): 711-730. https://doi.org/10.11676/qxxb2026.20260014

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Received: 15 January 2026
Revised: 09 April 2026
Published: 25 August 2026
Copyright © 2026 Acta Meteorologica Sinica. All rights reserved.