Peak greenness timing (PGT), indicating the timings of seasonal peak canopy structure, plays a key role in the terrestrial ecosystem carbon cycle. We assumed that the peak dates of climatic factors would have a greater impact on PGT than preseason climates because the potential maximum gross primary productivity would only be achieved when PGT matches seasonal peak resource availability. To test this hypothesis, we selected the Mongolian grassland as the study area and extracted the PGT using the MODIS EVI dataset. We simultaneously identified the peak dates of temperature, precipitation and radiation from the ERA5-land dataset. Subsequently, we compared the performance of two multiple linear regression models with peak dates of climatic factors or preseason climates as independent variables to simulate PGT. Finally, we compared the standardised regression coefficients of independent variables for each pixel to identify the dominant factor of PGT in different regions. The results showed that the regression model based on peak dates of climatic factors could explain more interannual variance of PGT in 71.0% of the study area than the model based on preseason climates. Although the dominant factor controlling PGT varied across regions with different background climates, the peak date of precipitation (PDP) was identified as the dominant factor in nearly half of the study area, followed by temperature and radiation. The explanatory power of PDP on PGT was stronger in more arid regions. Our research provides new insights into the drivers of PGT in temperate grasslands and enhances our understanding of how plant phenology adapts to seasonal climate variations.