Derin et al. (2026) Environment-Conditioned Error Characterization of IMERG over Mountainous Terrain using Radar Networks

Identification

• Journal: Journal of Hydrometeorology
• Year: 2026
• Date: 2026-08-11
• Authors: Yagmur Derin, Pierre‐Emmanuel Kirstetter, Dominique Faure, Daniel C. Watters
• DOI: 10.1175/jhm-d-26-0017.1

Research Groups

• Department of Civil and Environmental Engineering, University of Iowa
• School of Meteorology, University of Oklahoma
• School of Civil Engineering and Environmental Science, University of Oklahoma
• NOAA/National Severe Storms Laboratory
• Advanced Radar Research Center, University of Oklahoma
• Météo-France Toulouse

Short Summary

This study evaluates the performance of IMERG V07B Final Run (IM-F) over six mountain ranges using high-resolution radar-gauge precipitation data and environmental reanalysis parameters. The results show that environmental conditions strongly control precipitation distributions and satellite retrieval biases.

Objective

• Investigate how environmental factors explain the distribution and extremes of radar-observed precipitation in each mountain range.
• Analyze how much of the variation in IM-F retrieval error across these mountain ranges is explained by environmental parameters.

Study Configuration

• Spatial Scale: Six mountain ranges (U.S. West Coast, Rockies, East Coast; French Alps, Central Massif, Pyrenees)
• Temporal Scale: Not specified

Methodology and Data

• Models used: IMERG V07B Final Run (IM-F)
• Data sources: High-resolution radar-gauge precipitation data, environmental reanalysis parameters

Main Results

• Environmental conditions strongly control precipitation distributions: convective windward regimes yield the highest median and 99th-percentile rain rates, whereas stable, stratiform conditions produce much lower rainfall totals.
• Conditional validation reveals that a substantial portion of IM-F error is attributable to these environmental factors: precipitation detection skill and bias vary systematically with cluster conditions.

Contributions

• This study provides novel insight into physical drivers of SPP errors by systematically dissecting IM-F error by environmental regimes across multiple global mountain ranges.
• The results expose how orographic lift, moisture convergence, and stability interact to shape both precipitation extremes and satellite retrieval biases.

Funding

• Not specified

Citation

@article{Derin2026EnvironmentConditioned,
  author = {Derin, Yagmur and Kirstetter, Pierre‐Emmanuel and Faure, Dominique and Watters, Daniel C.},
  title = {Environment-Conditioned Error Characterization of IMERG over Mountainous Terrain using Radar Networks},
  journal = {Journal of Hydrometeorology},
  year = {2026},
  doi = {10.1175/jhm-d-26-0017.1},
  url = {https://doi.org/10.1175/jhm-d-26-0017.1}
}