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<p>Precipitation is the primary source for replenishing water resources in the Gaza Strip. However, significant gaps and uncertainties in ground-based rainfall data pose a serious obstacle to water and climate studies. This study evaluates the suitability of three global gridded precipitation datasets of MSWEP, CHIRPS, and ERA5 as alternative data sources. Using daily observations from eight rain gauge stations over 1981–2017, the datasets were assessed at daily, monthly, and annual timescales. The findings reveal that all datasets demonstrate improved agreement at coarser temporal resolutions. At the daily scale, MSWEP and ERA5 showed the strongest performance, with Thiessen-polygon-aggregated Pearson correlation coefficients (r) of 0.59 and 0.61, respectively. Event-based analysis shows that ERA5 had the highest probability of detection (POD &gt; 0.79 for light rain), while MSWEP achieved the best critical success index (CSI ≈ 0.44 for 1&#xa0;mm threshold), indicating a superior balance between detection and false alarms. All datasets showed a tendency to overestimate event frequency (BIAS &gt; 1) at light precipitation. Conversely, CHIRPS exhibited the lowest accuracy (<i>r</i> = 0.34; CSI &lt; 0.30), likely due to limitations of the satellite-only approach in this complex coastal environment. For aggregated scales, MSWEP was the top performer, achieving very high correlations for monthly (<i>r</i> ≈ 0.90) and annual (<i>r</i> ≈ 0.86) precipitation. The findings provide robust guidance for hydrological modeling and water resource management, advocating for the use of MSWEP for long-term assessments and ERA5 for daily synoptic studies to support water security goals in data-scarce regions.</p>

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Performance evaluation of MSWEP, CHIRPS, and ERA5 global gridded precipitation products against ground observations in the Gaza Strip

  • 期刊论文

  • 发表日期：

    2026年2月6日

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  • Hassan Al-Najjar,
  • Mahmoud Abdel latif,
  • Hatem Taha AbuEltayef

摘要

Precipitation is the primary source for replenishing water resources in the Gaza Strip. However, significant gaps and uncertainties in ground-based rainfall data pose a serious obstacle to water and climate studies. This study evaluates the suitability of three global gridded precipitation datasets of MSWEP, CHIRPS, and ERA5 as alternative data sources. Using daily observations from eight rain gauge stations over 1981–2017, the datasets were assessed at daily, monthly, and annual timescales. The findings reveal that all datasets demonstrate improved agreement at coarser temporal resolutions. At the daily scale, MSWEP and ERA5 showed the strongest performance, with Thiessen-polygon-aggregated Pearson correlation coefficients (r) of 0.59 and 0.61, respectively. Event-based analysis shows that ERA5 had the highest probability of detection (POD > 0.79 for light rain), while MSWEP achieved the best critical success index (CSI ≈ 0.44 for 1 mm threshold), indicating a superior balance between detection and false alarms. All datasets showed a tendency to overestimate event frequency (BIAS > 1) at light precipitation. Conversely, CHIRPS exhibited the lowest accuracy (r = 0.34; CSI < 0.30), likely due to limitations of the satellite-only approach in this complex coastal environment. For aggregated scales, MSWEP was the top performer, achieving very high correlations for monthly (r ≈ 0.90) and annual (r ≈ 0.86) precipitation. The findings provide robust guidance for hydrological modeling and water resource management, advocating for the use of MSWEP for long-term assessments and ERA5 for daily synoptic studies to support water security goals in data-scarce regions.