SM2RAIN-ASCAT, a bottom-up satellite-based precipitation product, has been increasingly used for drought monitoring due to its ability to estimate rainfall from soil moisture data. To determine its suitability for precipitation estimation and drought monitoring in Morocco, this study compares SM2RAIN-ASCAT dataset with observed data from 36 ground-based stations. This analysis examines the performance of the satellite product in a variety of climate zones across the country. The accuracy of the precipitation dataset was assessed using a suite of quantitative and qualitative metrics validated against observations. For the purpose of drought monitoring, the Standardized Precipitation Index (SPI) was calculated at 1, 3, 6, and 12 month timescales. To evaluate the performance of the product, the evaluation was also stratified by climate zone. The mean correlation coefficient (CC) with ground observations strengthened from 0.45 (daily) to 0.67 (monthly), with monthly and 10 days aggregations providing the most consistent performance. The dataset had a high probability of detecting rain events, with a monthly Probability of Detection (POD) exceeding 0.75 for 89% of stations. While the product showed a tendency to underestimate intense rainfall, the relative bias was low at nearly half of the stations, and the lowest RMSE value was found at monthly scale. With an underestimation of precipitation in Mediterranean regions and an overestimation in arid regions of Morocco, the product exhibits climatic bias; yet, its efficacy for drought monitoring has been proven. The calculated SPI values for short to medium-term durations (1, 3, 6 and 12 months) align well with ground observations across several climate zones in Morocco. While the 1 month SPI shows only weak to moderate agreement with gauge data, the correlation strengthens markedly for 3 and 6 month periods, with a CC of approximately 0.70 and 0.80, respectively. Notably, the results for long-term hydrological drought monitoring (SPI-12) are particularly promising, demonstrating excellent agreement with ground observations across nearly all stations. SM2RAIN-ASCAT is a reliable option for drought analysis in many arid regions like Morocco, it excels at detecting droughts in arid zones over humid ones, and similarly, it performs highly at identifying wet periods in hot arid climates than in wetter zones. Finding show that the integration of bottom-up (SM2RAIN) and top-down approaches can improve precipitation and drought monitoring performance, compensating for the limitations of each method. Overall SM2RAIN-ASCAT product is particularly recommended for agricultural drought monitoring and water management.