Yu et al. (2026) Evaluation of model performance in simulating extreme precipitation indices over eastern China: A comparison of CORDEX and NEX-GDDP models

Identification

• Journal: Atmospheric Research
• Year: 2026
• Date: 2026-01-10
• Authors: Honglin Yu, Shuping Li, Siyi Wang, Wenping He
• DOI: 10.1016/j.atmosres.2026.108760

Research Groups

• School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
• College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou, China

Short Summary

This study evaluates the performance of two types of downscaled climate models, CORDEX (dynamical downscaling) and NEX-GDDP (statistical downscaling), in simulating mean and extreme precipitation indices over eastern China. It finds that CORDEX models generally outperform NEX models in capturing extreme precipitation events, while NEX models show higher skill for total precipitation.

Objective

• To evaluate and compare the performance of regional climate models (RCMs) from CORDEX (dynamical downscaling) and NEX-GDDP models (statistical downscaling) in simulating mean and extreme precipitation indices over eastern China.

Study Configuration

• Spatial Scale: Eastern China, with specific improvements noted south of 30°N.
• Temporal Scale: Evaluation of model performance in simulating annual precipitation cycles and various precipitation indices, implying a focus on climatological patterns and historical/current climate simulation capabilities.

Methodology and Data

• Models used:
  • Regional Climate Models (RCMs) from the Coordinated Regional Downscaling Experiment Phase II for East Asia (CORDEX), using dynamical downscaling, driven by CMIP5 Global Climate Model (GCM) outputs.
  • NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP, NEX), applying statistical downscaling, driven by CMIP6 GCM outputs.
• Data sources: Model outputs from CMIP5 and CMIP6 GCMs served as drivers for the downscaling methods. Evaluation was performed against unspecified reference data for precipitation indices.

Main Results

• The CORDEX ensemble mean marginally improves the representation of all precipitation indices (PRCPTOT, R95p, R99p, Rx5day, CWD, and SDII) south of 30°N compared to CMIP5.
• NEX models achieve the highest skill in reproducing PRCPTOT (total precipitation) over eastern China.
• CORDEX models outperform NEX models in simulating extreme precipitation events, with NEX models systematically underestimating extremes.
• Dynamical downscaling (CORDEX) is generally more effective than statistical downscaling (NEX) for capturing extreme precipitation.
• Both CORDEX and NEX models successfully capture the timing and peak of the annual precipitation cycle over eastern China, despite notable inter-model discrepancies.

Contributions

• Provides a comprehensive comparison of two distinct downscaling approaches (dynamical vs. statistical) for simulating mean and extreme precipitation over eastern China.
• Offers valuable insights into the relative strengths and weaknesses of CORDEX and NEX-GDDP models for different precipitation characteristics.
• Serves as a reference for selecting appropriate climate models for future projections of mean and extreme precipitation in eastern China, aiding in regional climate risk management and adaptation policies.

Funding

• Not specified in the provided text.

Citation

@article{Yu2026Evaluation,
  author = {Yu, Honglin and Li, Shuping and Wang, Siyi and He, Wenping},
  title = {Evaluation of model performance in simulating extreme precipitation indices over eastern China: A comparison of CORDEX and NEX-GDDP models},
  journal = {Atmospheric Research},
  year = {2026},
  doi = {10.1016/j.atmosres.2026.108760},
  url = {https://doi.org/10.1016/j.atmosres.2026.108760}
}