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<p>This study evaluated and compared the performance of 6 gridded satellite precipitation products (GSPP) including CHIRPS, CMORPH, IMERG, CPC, SM2RAIN and PERISIANN-CDR in Mazandaran Province (northern Iran) at spatial (regional and point-to-grid) and temporal (daily, monthly, seasonal and annual) scales from January 2007 to December 2023. The accuracy of GSPPs was evaluated by directly comparing them with precipitation time series from 15 ground-based synoptic stations using various statistical evaluation indices (RMSE, CC, BIAS, MAE, NSE and KGE) and categorical indices (FAR, POD, and CSI). Also, quantile regression was used to investigate the pattern of changes in different quantiles of the GSPPs versus observed precipitation. The results showed that in most GSPPs, the accuracy of monthly data was higher than annual and seasonal data. In the spatial analysis, the eastern and coastal areas of the province had higher performance than the mountainous areas, and GSPPs were underestimated in coastal and low-altitude areas, but overestimated in mountainous areas. In general, the highest accuracy is related to the CPC, IMERG, and CMORPH products, and the lowest accuracy in terms of continuous evaluation indices is related to the PERSIANN-CDR product (CC=-0.3, KGE=-2, RMSE = 6&#xa0;mm). However, the categorical indices have shown different results for GSPPs in different areas of the province. The CPC product had the best performance in investigating statistical evaluation criteria (CC = 0.89, RMSE = 2&#xa0;mm, BIAS=(−&#xa0;0.15)–0.4, KGE = 0.7 and NSE = 0–1) and categorical criteria (POD = 0.77, FAR = 0.3 and CSI = 0.7). The result is important and essential in hydrological modeling and water resources management that require high-resolution precipitation data.</p>

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Evaluation of the accuracy of six satellite precipitation products and their spatial-temporal variability patterns using ground station data (case study: Mazandaran province, Iran)

  • 期刊论文

  • 发表日期：

    2026年1月21日

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  • Sedigheh Bararkhanpour Ahmadi,
  • Reza Norooz-Valashedi,
  • Mehdi Nadi,
  • Khalil Ghorbani,
  • Karim Solaimani

摘要

This study evaluated and compared the performance of 6 gridded satellite precipitation products (GSPP) including CHIRPS, CMORPH, IMERG, CPC, SM2RAIN and PERISIANN-CDR in Mazandaran Province (northern Iran) at spatial (regional and point-to-grid) and temporal (daily, monthly, seasonal and annual) scales from January 2007 to December 2023. The accuracy of GSPPs was evaluated by directly comparing them with precipitation time series from 15 ground-based synoptic stations using various statistical evaluation indices (RMSE, CC, BIAS, MAE, NSE and KGE) and categorical indices (FAR, POD, and CSI). Also, quantile regression was used to investigate the pattern of changes in different quantiles of the GSPPs versus observed precipitation. The results showed that in most GSPPs, the accuracy of monthly data was higher than annual and seasonal data. In the spatial analysis, the eastern and coastal areas of the province had higher performance than the mountainous areas, and GSPPs were underestimated in coastal and low-altitude areas, but overestimated in mountainous areas. In general, the highest accuracy is related to the CPC, IMERG, and CMORPH products, and the lowest accuracy in terms of continuous evaluation indices is related to the PERSIANN-CDR product (CC=-0.3, KGE=-2, RMSE = 6 mm). However, the categorical indices have shown different results for GSPPs in different areas of the province. The CPC product had the best performance in investigating statistical evaluation criteria (CC = 0.89, RMSE = 2 mm, BIAS=(− 0.15)–0.4, KGE = 0.7 and NSE = 0–1) and categorical criteria (POD = 0.77, FAR = 0.3 and CSI = 0.7). The result is important and essential in hydrological modeling and water resources management that require high-resolution precipitation data.