Zheng et al. (2025) The characteristics of heavy rainfall during the rainy season over North China and prediction skill of NCEP S2S

Identification

• Journal: Atmospheric Research
• Year: 2025
• Date: 2025-11-16
• Authors: Ting Zheng, Zhihai Zheng, Peiyi Fan, Xintong Hou, Guolin Feng
• DOI: 10.1016/j.atmosres.2025.108626

Research Groups

• College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
• China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Centre, Beijing 100081, China
• College of Physical Science and Technology, Yangzhou University, Yangzhou 225002, China
• Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China

Short Summary

This study characterizes two distinct types of heavy rainfall during the North China rainy season and evaluates the prediction skill of the NCEP S2S model for these events, attributing forecast discrepancies to the model's ability to predict key atmospheric circulation patterns.

Objective

• To understand the distribution characteristics and underlying atmospheric circulation mechanisms of heavy rainfall during the North China rainy season.
• To evaluate the prediction skill of the National Centers for Environmental Prediction (NCEP) Sub-seasonal to Seasonal (S2S) model for these heavy rainfall events and identify reasons for forecast skill variations.

Study Configuration

• Spatial Scale: North China region, with specific focus on Beijing-Tianjin-Hebei and southern North China.
• Temporal Scale: Rainy season (primarily July and August), with an analysis of 2024 precipitation anomalies and context from the past 45 years.

Methodology and Data

• Models used: NCEP Sub-seasonal to Seasonal (S2S) model.
• Data sources: Observational/reanalysis data for precipitation characteristics and anomalies, and atmospheric circulation patterns (e.g., Western Pacific Subtropical High, South Asian High, Pacific-Japan pattern).

Main Results

• Heavy rainfall in North China can be categorized into two types:
  1. Type 1 (Beijing-Tianjin-Hebei): Primarily caused by the descending branch of the Pacific-Japan (PJ) pattern coinciding with and strengthening a northward-jumping Western Pacific Subtropical High (WPSH).
  2. Type 2 (Southern North China): Primarily caused by the eastward extension of the eastern boundary of the South Asian High (SAH), which enhances moisture transport and strengthens the WPSH.
• The NCEP S2S model exhibits low forecast skill for Type 1 heavy rainfall, mainly due to its failure to predict the northward shift of the WPSH, resulting in a southern bias in the forecasted anomaly center.
• The NCEP S2S model shows modestly higher forecasting skill for Type 2 heavy rainfall, attributed to its ability to predict the eastward extension of the SAH.
• The 2024 precipitation anomaly in North China was a hybrid of both types, linked to an unusually intense and northward-displaced WPSH coupled with an exceptionally eastward-extended SAH.
• For 2024, the model successfully predicted precipitation anomalies in southeastern North China but had limited skill in forecasting anomalies across the Beijing-Tianjin-Hebei region.

Contributions

• Provides a novel classification and detailed dynamic analysis of two distinct heavy rainfall types in North China.
• Offers a comprehensive evaluation of the NCEP S2S model's prediction skill for these specific heavy rainfall types, linking skill variations to the model's ability to forecast crucial atmospheric circulation patterns.
• Identifies specific atmospheric mechanisms (e.g., WPSH northward shift, SAH eastward extension) that are critical for heavy rainfall prediction in North China and highlights areas for model improvement.

Funding

• Not specified in the provided text.

Citation

@article{Zheng2025characteristics,
  author = {Zheng, Ting and Zheng, Zhihai and Fan, Peiyi and Hou, Xintong and Feng, Guolin},
  title = {The characteristics of heavy rainfall during the rainy season over North China and prediction skill of NCEP S2S},
  journal = {Atmospheric Research},
  year = {2025},
  doi = {10.1016/j.atmosres.2025.108626},
  url = {https://doi.org/10.1016/j.atmosres.2025.108626}
}