Tan et al. (2025) Comparative Assessment of Eight Satellite Precipitation Products over the Complex Terrain of the Lower Yarlung Zangpo Basin: Performance Evaluation and Topographic Influence Analysis

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Identification

• Journal: Remote Sensing
• Year: 2025
• Date: 2025-12-24
• Authors: A. Serdar Tan, Ming Li, Heng Liu, Liangang Chen, Tao Wang, Wei Chun Wang, Yuanzhi Shi
• DOI: 10.3390/rs18010063

Research Groups

The provided text does not explicitly list the research groups, labs, or departments involved in the study.

Short Summary

This study systematically evaluates eight satellite-based precipitation retrieval algorithms against ground observations in the data-scarce Yarlung Zangpo watershed from 2014 to 2022, finding that IMERGEarlyRun and IMERGLateRun offer optimal real-time performance while IMERG_FinalRun exhibits severe deterioration due to gauge adjustment failures.

Objective

• To systematically assess the performance of eight satellite-based precipitation retrieval algorithms against ground truth observations from 18 meteorological stations in the downstream Yarlung Zangpo watershed.

Study Configuration

• Spatial Scale: Downstream Yarlung Zangpo watershed, utilizing data from 18 meteorological stations.
• Temporal Scale: 9 years (2014–2022), analyzed across annual, monthly, seasonal, and year-to-year scales.

Methodology and Data

• Models used: Eight satellite-based precipitation retrieval algorithms, including IMERGEarlyRun, IMERGLateRun, IMERGFinalRun, GSMaPMVK_G, and FY2. Reanalysis precipitation products were also considered for comparative context.
• Data sources: Ground truth observations from 18 meteorological stations, satellite-based precipitation retrieval algorithms, and reanalysis precipitation products. Statistical metrics included correlation analysis, root mean square error (RMSE), mean absolute error (MAE), and bias assessment.

Main Results

• Satellite retrieval algorithms generally demonstrated systematic underestimation, with observed precipitation averaging 2358 mm/yr, substantially exceeding remote sensing estimates across six of eight products.
• IMERGEarlyRun and IMERGLateRun achieved optimal performance with annual correlation coefficients of 0.41 and 0.37, respectively, and minimal relative biases of -3.0% and 1.4%.
• IMERG_FinalRun exhibited severe deterioration compared to Early/Late Run products, showing a correlation of 0.37 but a substantial relative bias of -73.8%, indicating critical limitations of its statistical correction procedures in data-sparse mountainous environments.
• Performance varied significantly across annual, monthly, and seasonal scales, with pronounced seasonal variations and elevation-dependent error patterns.
• Temporal analysis revealed substantial year-to-year performance variability across all products, strongly modulated by annual precipitation characteristics.
• Station-level assessment confirmed systematic gauge-adjustment failures for IMERGFinalRun (100% underestimation), while IMERGEarlyRun/LateRun showed more balanced patterns (53% underestimation, 47% overestimation).
• GSMaPMVKG showed superior spatial pattern representation, while IMERG_LateRun excelled in capturing temporal variations.

Contributions

• Provides a comprehensive and systematic evaluation of eight satellite-based precipitation retrieval algorithms in a data-scarce mountainous region (Yarlung Zangpo watershed), a critical frontier for operational hydrology.
• Identifies specific strengths and weaknesses of various satellite products, highlighting the superior real-time performance of IMERGEarlyRun and IMERGLateRun and the critical failure of IMERG_FinalRun's gauge adjustment in such environments.
• Offers practical recommendations for operational real-time applications (IMERGEarlyRun, IMERGLateRun), terrain-sensitive spatial analysis (GSMaPMVKG), and seasonal assessment (reanalysis products).
• Suggests multi-product integration strategies for comprehensive precipitation monitoring in complex terrain.
• Establishes that satellite products offer superior real-time availability but greater temporal variability compared to reanalysis products.

Funding

The provided text does not contain information regarding funding projects, programs, or reference codes.

Citation

@article{Tan2025Comparative,
  author = {Tan, A. Serdar and Li, Ming and Liu, Heng and Chen, Liangang and Wang, Tao and Wang, Wei Chun and Shi, Yuanzhi},
  title = {Comparative Assessment of Eight Satellite Precipitation Products over the Complex Terrain of the Lower Yarlung Zangpo Basin: Performance Evaluation and Topographic Influence Analysis},
  journal = {Remote Sensing},
  year = {2025},
  doi = {10.3390/rs18010063},
  url = {https://doi.org/10.3390/rs18010063}
}