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<p>Rainfall is a critical element of the climate across the west African nation of Nigeria. The spatial inhomogeneity of tropical rainfall makes high-resolution monitoring essential, but this is difficult to achieve with a sparse network of in-situ gauges. Supplementing gauge data with satellite-derived rainfall products is appealing but requires validation to determine usefulness. In this study, two widely available satellite-derived rainfall datasets are aligned with daily rainfall data from 20 stations across Nigeria for a comparative statistical analysis for the period 1982–2011. Both the United States Climate Prediction Center’s (CPC) Merged Analysis of Precipitation (CMAP) and the National Aeronautics and Space Administration’s Prediction of Worldwide Energy Resources (POWER) data replicate the spatial variability in mean rainfall across Nigeria as portrayed by the gauge network. However, each dataset considerably overestimates rainfall frequency, while rainfall amount exhibits weak interannual co-variability with gauge data and temporal trends that are in the opposite direction of gauge data. A coarser temporal resolution, such as that of the pentad-level CMAP data, produces better alignment with gauge data. The results indicate that the POWER and CMAP rainfall data are inadequate for hydroclimate monitoring across Nigeria.</p>

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Comparative assessment of POWER and CMAP satellite-derived rainfall products for hydroclimate monitoring in Nigeria

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月19日

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  • Andrew W. Ellis,
  • Bright Samson

摘要

Rainfall is a critical element of the climate across the west African nation of Nigeria. The spatial inhomogeneity of tropical rainfall makes high-resolution monitoring essential, but this is difficult to achieve with a sparse network of in-situ gauges. Supplementing gauge data with satellite-derived rainfall products is appealing but requires validation to determine usefulness. In this study, two widely available satellite-derived rainfall datasets are aligned with daily rainfall data from 20 stations across Nigeria for a comparative statistical analysis for the period 1982–2011. Both the United States Climate Prediction Center’s (CPC) Merged Analysis of Precipitation (CMAP) and the National Aeronautics and Space Administration’s Prediction of Worldwide Energy Resources (POWER) data replicate the spatial variability in mean rainfall across Nigeria as portrayed by the gauge network. However, each dataset considerably overestimates rainfall frequency, while rainfall amount exhibits weak interannual co-variability with gauge data and temporal trends that are in the opposite direction of gauge data. A coarser temporal resolution, such as that of the pentad-level CMAP data, produces better alignment with gauge data. The results indicate that the POWER and CMAP rainfall data are inadequate for hydroclimate monitoring across Nigeria.