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Snow cover is an important water source for vegetation growth in arid and semi-arid areas, and grassland phenology provides valuable information on the response of terrestrial ecosystems to climate change. The Mongolian Plateau features both abundant snow cover resources and typical grassland ecosystems. In recent years, with the intensification of global climate change, the snow cover on the Mongolian Plateau has changed correspondingly, with resulting effects on vegetation growth. In this study, using MOD10A1 snow cover data and MOD13A1 Normalized Difference Vegetation Index (NDVI) data combined with remote sensing (RS) and geographic information system (GIS) techniques, we analyzed the spatiotemporal changes in snow cover and grassland phenology on the Mongolian Plateau from 2001 to 2018. The correlation analysis and grey relation analysis were used to determine the influence of snow cover parameters (snow cover fraction (SCF), snow cover duration (SCD), snow cover onset date (SCOD), and snow cover end date (SCED)) on different types of grassland vegetation. The results showed wide snow cover areas, an early start time, a late end time, and a long duration of snow cover over the northern Mongolian Plateau. Additionally, a late start, an early end, and a short duration were observed for grassland phenology, but the southern area showed the opposite trend. The SCF decreased at an annual rate of 0.33%. The SCD was shortened at an annual rate of 0.57 d. The SCOD and SCED in more than half of the study area advanced at annual rates of 5.33 and 5.74 DOY (day of year), respectively. For grassland phenology, the start of the growing season (SOS) advanced at an annual rate of 0.03 DOY, the end of the growing season (EOS) was delayed at an annual rate of 0.14 DOY, and the length of the growing season (LOS) was prolonged at an annual rate of 0.17 d. The SCF, SCD, and SCED in the snow season were significantly positively correlated with the SOS and negatively correlated with the EOS and LOS. The SCOD was significantly negatively correlated with the SOS and positively correlated with the EOS and LOS. The SCD and SCF can directly affect the SOS of grassland vegetation, while the EOS and LOS were obviously influenced by the SCOD and SCED. This study provides a scientific basis for exploring the response trends of alpine vegetation to global climate change.

Snow is one of the important water sources for vegetation growth in the Mongolian Plateau, and temporal and spatial changes to it have a profound impact on terrestrial vegetation phenology. In recent years, due to global climate change, the snow associated with the different vegetation types of the Mongolian Plateau has changed substantially, and the mechanism of the resulting change in the vegetation growth date needs to be studied. To address this issue, we used the modified Carnegie Ames Stanford Approach (CASA) model was to estimate the start of growing season net primary productivity (SOSNPP) for different types of vegetation over the Mongolian Plateau from 2001 to 2019. An extensive study of the spatial changes in the SOSNPP and the responses reflected by the winter snow cover fraction (SCFWinter), spring snow melting date (SMDSpring), and SOSNPP to influencing factors is of great significance for ecosystem maintenance. We observed: (1) Different vegetation types exhibited similar changes; SCFWinter underwent a significant decrease of −0.2%, and SMDSpring followed a slow downward trend of −0.59 day of the year (DOY)/year for the whole study area. (2) In the Mongolia Plateau, SOSNPP showed a trend of significant decrease of −0.53 DOY/year. (3) The local hydrothermal condition coupling relationship effect on different vegetation types. Spring temperature (TEMSpring) has a direct effect on vegetation SOSNPP, with a path coefficient of −0.09 in the Mongolian Plateau. SCFWinter and SMDSpring were shown through a path analysis to employ different effects on vegetation SOSNPP. SMDSpring has a direct effect on vegetation SOSNPP, with a path coefficient of 0.53. (4) The SMDSpring and PRESpring factors have a significant impact on vegetation SOSNPP, and they account for 21.11% and 21.26% of the whole study area SOSNPP, respectively. This study is expected to promote the examination of the snow phonological parameters of different related vegetation types and theoretical research on SOSNPP.