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

Viewed

Total article views: 764 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
593 149 22 764 53 12 14
  • HTML: 593
  • PDF: 149
  • XML: 22
  • Total: 764
  • Supplement: 53
  • BibTeX: 12
  • EndNote: 14
Views and downloads (calculated since 25 Jul 2023)
Cumulative views and downloads (calculated since 25 Jul 2023)

Viewed (geographical distribution)

Total article views: 764 (including HTML, PDF, and XML) Thereof 737 with geography defined and 27 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 27 Feb 2024
Download
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.