Zhang et al. (2025) Evaluation and Projection of Northwest China's Extreme Precipitation Using Statistically Downscaled CMIP6 Models

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: International Journal of Climatology
• Year: 2025
• Date: 2025-12-19
• Authors: Jingpeng Zhang, Zhangli Dang, Xixi Yang, Lingtong Du, Tianbao Zhao
• DOI: 10.1002/joc.70237

Research Groups

[Information not available in the provided abstract.]

Short Summary

This study quantitatively evaluates 23 statistically downscaled CMIP6 models for their ability to simulate historical extreme precipitation in Northwest China and projects future changes. Results indicate that while most models capture spatial patterns, they exhibit systematic dry biases, with the best-performing models projecting a mitigation of aridity and an increase in extreme precipitation frequency under future warming scenarios.

Objective

• To quantitatively evaluate 23 statistically downscaled CMIP6 models from the NASA NEX‐GDDP dataset in simulating historical (1961–2014) extreme precipitation over Northwest China and, based on their performance, project future changes in the mid‐ (2031–2060) and late‐21st century (2071–2100) under two Shared Socioeconomic Pathway (SSP) scenarios (SSP2‐4.5 and SSP5‐8.5).

Study Configuration

• Spatial Scale: Northwest China
• Temporal Scale: Historical (1961–2014), Mid-21st century (2031–2060), Late-21st century (2071–2100)

Methodology and Data

• Models used: 23 statistically downscaled CMIP6 models (including CESM2, CESM2‐WACCM, CMCC‐CM2‐SR5, EC‐Earth3‐Veg‐LR as superior performers).
• Data sources: NASA NEX‐GDDP dataset.

Main Results

• Most models reasonably capture spatial patterns of extreme precipitation indices with pattern correlations ranging from 0.4 to 0.9.
• Models exhibit systematic dry biases, characterized by positive biases for consecutive dry days (CDD) and negative biases for other extreme precipitation indices (PRCPTOT, R95pTOT, Rx5day, R10mm, CWD).
• Interannual variability is better simulated in western subregions compared to eastern subregions, particularly for total wet-day precipitation (PRCPTOT), very wet-day precipitation (R95pTOT), maximum 5-day precipitation (Rx5day), and heavy precipitation days (R10mm).
• Four specific models (CESM2, CESM2‐WACCM, CMCC‐CM2‐SR5, and EC‐Earth3‐Veg‐LR) demonstrate superior skill in both spatiotemporal simulations.
• Projections from these best-performing models indicate a mitigation of aridity and an increase in the frequency of extreme precipitation under both SSP2‐4.5 and SSP5‐8.5 scenarios.

Contributions

• Provides a comprehensive quantitative evaluation of 23 statistically downscaled CMIP6 models for simulating historical extreme precipitation over Northwest China using skill metrics.
• Identifies specific CMIP6 models (CESM2, CESM2‐WACCM, CMCC‐CM2‐SR5, EC‐Earth3‐Veg‐LR) with superior performance for the region, offering guidance for future regional climate impact studies.
• Projects future changes in extreme precipitation and aridity for Northwest China under mid- and late-21st century SSP scenarios, contributing to regional climate change adaptation strategies.

Funding

[Information not available in the provided abstract.]

Citation

@article{Zhang2025Evaluation,
  author = {Zhang, Jingpeng and Dang, Zhangli and Yang, Xixi and Du, Lingtong and Zhao, Tianbao},
  title = {Evaluation and Projection of Northwest China's Extreme Precipitation Using Statistically Downscaled <scp>CMIP6</scp> Models},
  journal = {International Journal of Climatology},
  year = {2025},
  doi = {10.1002/joc.70237},
  url = {https://doi.org/10.1002/joc.70237}
}