Droughts cause danger to human health and socioeconomic development worldwide. The traditional station-based analysis of droughts has limitations. The most relevant is the insufficient spatial resolution of the observations, particularly over mountain topography. This study evaluates the performance of two satellite precipitation products—the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) and the Climate Prediction Center Morphing Method (CMORPH)—for monitoring meteorological droughts in mountainous environments, using the Armenian Highlands as a case study. We focused on a drought event in June 2021, which was the hottest and driest month in Armenia in nearly nine decades. The performance of gridded global precipitation products was evaluated against in-situ observations for June 2021. Statistical evaluation using the Pearson correlation coefficient, root mean square error, mean absolute error, mean bias, and standard deviation has been analyzed. Results indicate that both products have challenges in accurately estimating the Standardized Precipitation Index (SPI) under severe drought conditions. However, IMERG’s drought detection aligned more closely with in-situ observations than CMORPH’s, which tended to underestimate drought severity. In addition to precipitation-based indices, Landsat-8 and Sentinel-2 vegetation and moisture indices (NDVI, NDMI, NDWI) were evaluated, yielding complementary data regarding the impact of drought on the environment. We found a correlation between low SPI values and stressed vegetation (low NDVI/NDMI), validating the ecological impact of the meteorological drought. Outcomes discuss the merits and disadvantages of satellite precipitation records over mountainous regions and advise operational drought monitoring and early warning systems within data-limit-ed topographically complex areas worldwide.

CMORPH, IMERG, in-situ observations, Sentinel-2, Landsat-8, vegetation and drought indices