The NASA Prediction of Worldwide Energy Resources (POWER) system delivers globally consistent, satellite-based climate and solar data that support applications in renewable energy, agriculture, and hydrology. Its open access and robust processing chain have made it a widely used source of long-term environmental information for both scientists and decision-makers. This study evaluates NASA POWER precipitation estimates against observations from 23 meteorological stations across Tunisia for the period 1981-2023. The network covers sites located in humid, semi-arid, and Saharan climate regimes. The analysis included regression performed by station and by month. Descriptive statistics were also used to describe the main features of rainfall variability. This framework allowed the assessment of both average performance and the ability of the product to reproduce interannual and spatial variability. Results show that NASA POWER reproduces the large-scale spatial pattern of mean annual rainfall well, but systematically underestimates orographic extremes and markedly dampens variability, especially in summer. The relationship between NASA POWER and observed precipitation is strongest in autumn and spring (R2 > 0.75), when rainfall is primarily driven by large-scale synoptic systems. In contrast, performance degrades sharply in August (R2 < 0.30 at central and southern stations), reflecting the product's limited capacity to capture localized convective events. The coefficient of variation is consistently underestimated throughout the country, indicating a structural mismatch between the product's coarse spatial resolution (about 50 km) and the fine-scale characteristics of Mediterranean rainfall. These shortcomings substantially constrain the direct use of NASA POWER for hydrological and agricultural applications in water-stressed regions without local bias correction.