Guo, L., J. Wu, Q. Q. Li, and X. L. Jia, 2025: Advantages of the multimodel ensemble approach for subseasonal precipitation prediction in China and the driving factor of the MJO. Adv. Atmos. Sci., 42(3), 551−563, https://doi.org/10.1007/s00376-024-4107-9.
Citation: Guo, L., J. Wu, Q. Q. Li, and X. L. Jia, 2025: Advantages of the multimodel ensemble approach for subseasonal precipitation prediction in China and the driving factor of the MJO. Adv. Atmos. Sci., 42(3), 551−563, https://doi.org/10.1007/s00376-024-4107-9.

Advantages of the Multimodel Ensemble Approach for Subseasonal Precipitation Prediction in China and the Driving Factor of the MJO

  • Based on the hindcasts from five subseasonal-to-seasonal (S2S) models participating in the S2S Prediction Project, this study evaluates the performance of the multimodel ensemble (MME) approach in predicting the subseasonal precipitation anomalies during summer in China and reveals the contributions of possible driving factors. The results suggest that while single-model ensembles (SMEs) exhibit constrained predictive skills within a limited forecast lead time of three pentads, the MME illustrates an enhanced predictive skill at a lead time of up to four pentads, and even six pentads, in southern China. Based on both deterministic and probabilistic verification metrics, the MME consistently outperforms SMEs, with a more evident advantage observed in probabilistic forecasting. The superior performance of the MME is primarily attributable to the increase in ensemble size, and the enhanced model diversity is also a contributing factor. The reliability of probabilistic skill is largely improved due to the increase in ensemble members, while the resolution term does not exhibit consistent improvement. Furthermore, the Madden–Julian Oscillation (MJO) is revealed as the primary driving factor for the successful prediction of summer precipitation in China using the MME. The improvement by the MME is not solely attributable to the enhancement in the inherent predictive capacity of the MJO itself, but derives from its capability in capturing the more realistic relationship between the MJO and subseasonal precipitation anomalies in China. This study establishes a scientific foundation for acknowledging the advantageous predictive capability of the MME approach in subseasonal predictions of summer precipitation in China, and sheds light on further improving S2S predictions.
  • loading

Catalog

    Turn off MathJax
    Article Contents

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return