Dynamic–statistic combined ensemble prediction and impact factors of China's summer precipitation

Wang, Xiaojuan; Yang, Zihan; Li, Shuai; Li, Qingquan; Feng, Guolin

doi:https://doi.org/10.5194/npg-32-117-2025

Articles | Volume 32, issue 2

https://doi.org/10.5194/npg-32-117-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Emerging predictability, prediction, and early-warning approaches...

https://doi.org/10.5194/npg-32-117-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 32, issue 2

Research article

|

15 May 2025

Research article |

| 15 May 2025

Dynamic–statistic combined ensemble prediction and impact factors of China's summer precipitation

Xiaojuan Wang, Zihan Yang, Shuai Li, Qingquan Li, and Guolin Feng

Data sets

BCC_CPSv3. CMDP Monitoring Beijing Climate Center http://cmdp.ncc-cma.net/Monitoring/cn_index_130.php

The combined rainfall analysis data CMAP https://www.cpc.ncep.noaa.gov/

The monthly precipitation data National Meteorological Information Center https://data.cma.cn/

Model code and software

Jupyter Notebook, Python 3.9.7 Anaconda, Inc. https://www.anaconda.com/

Short summary

Unequal-weighted ensemble prediction (UWE) using outputs of the dynamic–statistic prediction is presented, and its possible impact factors are also analysed. Results indicate that the UWE has shown promise in improving the prediction skill of summer precipitation in China on account of the fact that UWE can overcome the shortcomings of the structural inadequacy of individual dynamic–statistic predictions, reducing formulation uncertainties and resulting in more stable and accurate predictions.