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<p>Accurate precipitation estimation in semi-arid, topographically complicated areas is critical for water resource management and climate risk monitoring. This work provides a detailed, multi-scale evaluation of four major satellite precipitation products (CHIRPS, PERSIANN-CDR, IMERG-F v07, and GSMaP) over Isfahan province, Iran, over a 9-year period (2015–2023). The performance of these products was benchmarked against a dense network of 98 rain gauges using a suite of continuous and categorical statistical metrics, following a two-stage quality control protocol to remove outliers and false alarms. The results revealed that the performance of all products improves with temporal aggregation. At the daily level, GSMaP performed marginally better, although all products were linked with considerable uncertainty. At the monthly and annual levels, the GPM-era products (IMERG and GSMaP) clearly beat the other two, establishing themselves as dependable tools for long-term hydro-climatological studies. Error analysis revealed that topography is the dominant regulating factor, creating a systematic elevation-dependent bias, largely characterized by underestimation from most products in high-elevation areas, though the PERSIANN-CDR product exhibited a contrasting overestimation tendency. Finally, the findings highlight the importance of implementing local, elevation-dependent calibration before deploying these products in hydrological modeling.</p>

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Spatiotemporal performance and error analysis of satellite precipitation products over a topographically complex semi-arid region in Iran

  • 期刊论文

  • 发表日期：

    2026年1月14日

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  • Moein Tosan,
  • Mohammad Reza Gharib,
  • Mahsa Mardani,
  • Amin Sabbagh

摘要

Accurate precipitation estimation in semi-arid, topographically complicated areas is critical for water resource management and climate risk monitoring. This work provides a detailed, multi-scale evaluation of four major satellite precipitation products (CHIRPS, PERSIANN-CDR, IMERG-F v07, and GSMaP) over Isfahan province, Iran, over a 9-year period (2015–2023). The performance of these products was benchmarked against a dense network of 98 rain gauges using a suite of continuous and categorical statistical metrics, following a two-stage quality control protocol to remove outliers and false alarms. The results revealed that the performance of all products improves with temporal aggregation. At the daily level, GSMaP performed marginally better, although all products were linked with considerable uncertainty. At the monthly and annual levels, the GPM-era products (IMERG and GSMaP) clearly beat the other two, establishing themselves as dependable tools for long-term hydro-climatological studies. Error analysis revealed that topography is the dominant regulating factor, creating a systematic elevation-dependent bias, largely characterized by underestimation from most products in high-elevation areas, though the PERSIANN-CDR product exhibited a contrasting overestimation tendency. Finally, the findings highlight the importance of implementing local, elevation-dependent calibration before deploying these products in hydrological modeling.