Yang et al. (2026) Cross-Scale Performance Evaluation of GPM IMERG V07 Precipitation Products in a Typical Mountainous Monsoon Region

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Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-08-24
• Authors: Shao-E Yang, Yanli Chen, Guoxue Xie, Qiting Huang
• DOI: 10.3390/rs18172867

Research Groups

Not specified in the provided text.

Short Summary

This study evaluates the performance of GPM IMERG V07 and V06 precipitation products in Guangxi, China, finding that while V07 improves daily detection, it introduces systematic positive biases that amplify at monthly scales.

Objective

• To evaluate the daily and monthly performance of IMERG V07 and V06 and analyze the mechanisms of cross-scale error propagation and the influence of topography and climate on retrieval accuracy in a mountainous monsoon region.

Study Configuration

• Spatial Scale: Guangxi, China (mountainous monsoon region).
• Temporal Scale: 2014 to 2020 (Daily and Monthly resolutions).

Methodology and Data

• Models used: GPM IMERG V07 and V06 (Early, Late, and Final Runs).
• Data sources: 91 rain gauges (ground truth) and satellite-based precipitation products.

Main Results

• Bias Shift: V07 (specifically the Late Run) improves daily precipitation detection but increases the proportion of systematic positive bias to 67.2–68.9%, compared to 62.3–64.8% in V06.
• Temporal Aggregation: Systematic overestimation is severely amplified when aggregating daily data to a monthly scale, with the Final Run exhibiting the most significant loss in accuracy.
• Topographic-Climatic Coupling: Retrieval accuracy is lowest (highest overestimation) in areas characterized by complex terrain (elevation 100–500 m) and relatively dry conditions (mean annual precipitation < 1300 mm).
• Algorithm Performance: The Climatological Calibration Algorithm (CCA) improves estimations during the dry season but introduces substantial positive biases during the wet season.

Contributions

• Identifies a critical trade-off in IMERG V07 where improved short-term precipitation dynamics are offset by structural systematic biases that compromise long-term cumulative reliability.
• Provides a multi-dimensional stratification of error propagation based on elevation, intensity, and seasonality in complex mountainous monsoon terrains.

Funding

Not specified in the provided text.

Citation

@article{Yang2026CrossScale,
  author = {Yang, Shao-E and Chen, Yanli and Xie, Guoxue and Huang, Qiting},
  title = {Cross-Scale Performance Evaluation of GPM IMERG V07 Precipitation Products in a Typical Mountainous Monsoon Region},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18172867},
  url = {https://doi.org/10.3390/rs18172867}
}