王 (2026) Dataset for: Diagnosing Physical-Parameterization Uncertainty in WRF-Simulated Extreme Precipitation over the Hanjiang River Basin

Identification

• Journal: Mendeley Data
• Year: 2026
• Date: 2026-09-29
• Authors: 成栋 王
• DOI: 10.17632/2nccmn87wb.2

Research Groups

• Shaanxi Normal University

Short Summary

This study aims to diagnose physical-parameterization uncertainty in WRF-simulated extreme precipitation over the Hanjiang River Basin by analyzing 15 different microphysics-cumulus parameterization combinations.

Objective

• Investigate the impact of physical parameterizations on simulated extreme precipitation events in the Hanjiang River Basin.

Study Configuration

• Spatial Scale: Regional scale, focusing on the Hanjiang River Basin.
• Temporal Scale: Short-term to medium-term (hours to days) during extreme rainfall events.

Methodology and Data

• Models used: WRF (Weather Research and Forecasting model)
• Data sources: Satellite data, observation data, reanalysis datasets

Main Results

• The study found significant differences in simulated precipitation amounts and patterns among the 15 different parameterization combinations.
• Threshold-robustness results showed that certain parameterizations performed better than others for specific extreme rainfall events.

Contributions

• This study provides original insights into the impact of physical parameterizations on WRF-simulated extreme precipitation, contributing to a better understanding of uncertainty in regional climate modeling.

Funding

• This research was funded by [project/program name] with reference code [reference code].

Citation

@article{王2026Dataset,
  author = {王, 成栋},
  title = {Dataset for: Diagnosing Physical-Parameterization Uncertainty in WRF-Simulated Extreme Precipitation over the Hanjiang River Basin},
  journal = {Mendeley Data},
  year = {2026},
  doi = {10.17632/2nccmn87wb.2},
  url = {https://doi.org/10.17632/2nccmn87wb.2}
}