Abstract:
Understanding the variability of rainfall is important for sustaining rain-dependent agriculture
and driving the local economy of Nigeria. Paucity and inadequate rain gauge network across
Nigeria has made satellite-based rainfall products (SRPs), which o er a complete spatial and
consistent temporal coverage, a better alternative. However, the accuracy of these products
must be ascertained before use in water resource developments and planning. In this study,
the performances of Climate Hazards Group Infrared Precipitation with Station data (CHIRPS),
Precipitation estimation from Remotely Sensed Information using Artificial Neural Networks–Climate
Data Record (PERSIANN-CDR), and Tropical Applications of Meteorology using SATellite data
and ground-based observations (TAMSAT), were evaluated to investigate their ability to reproduce
long term (1983–2013) observed rainfall characteristics derived from twenty-four (24) gauges in
Nigeria. Results show that all products performed well in terms of capturing the observed annual
cycle and spatial trends in all selected stations. Statistical evaluation of the SRPs performance show
that CHIRPS agree more with observations in all climatic zones by reproducing the local rainfall
characteristics. The performance of PERSIANN and TAMSAT, however, varies with season and
across the climatic zones. Findings from this study highlight the benefits of using SRPs to augment
or fill gaps in the distribution of local rainfall data, which is critical for water resources planning,
agricultural development, and policy making.
