Articles | Volume 27, issue 22
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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Cited articles

Chen, Y. and Zhai, P.: Simultaneous modulations of precipitation and temperature extremes in Southern parts of China by the boreal summer intraseasonal oscillation, Clim. Dynam., 49, 3363–3381, 2017. 
Copernicus Climate Change Service: Fifth generation of ECMWF atmospheric reanalysis of the global climate, (last access: 10 December 2022), 2022. 
Cui, J., Yang, S., and Li, T.: How well do the S2S models predict intraseasonal wintertime surface air temperature over mid-high-latitude Eurasia?, Clim. Dynam., 57, 503–521, 2021.  
de Andrade, F. M., Coelho, C. A., and Cavalcanti, I. F.: Global precipitation hindcast quality assessment of the Subseasonal to Seasonal (S2S) prediction project models, Clim. Dynam., 52, 5451–5475, 2019. 
Duan, Q., Sorooshian, S., and Gupta, V. K.: Optimal use of the SCE-UA global optimization method for calibrating watershed models, J. Hydrol., 158, 265–284,, 1994. 
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.