Articles | Volume 27, issue 22
https://doi.org/10.5194/hess-27-4187-2023
https://doi.org/10.5194/hess-27-4187-2023
Research article
 | 
21 Nov 2023
Research article |  | 21 Nov 2023

A statistical–dynamical approach for probabilistic prediction of sub-seasonal precipitation anomalies over 17 hydroclimatic regions in China

Yuan Li, Kangning Xü, Zhiyong Wu, Zhiwei Zhu, and Quan J. Wang

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Latest update: 15 Jun 2024
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Short summary
A spatial–temporal projection-based calibration, bridging, and merging (STP-CBaM) method is proposed. The calibration model is built by post-processing ECMWF raw forecasts, while the bridging models are built using atmospheric intraseasonal signals as predictors. The calibration model and bridging models are merged through a Bayesian modelling averaging (BMA) method. The results indicate that the newly developed method can generate skilful and reliable sub-seasonal precipitation forecasts.