Grasslands have been increasingly impacted by human activities, gradually becoming one of the most threatened ecosystems globally. Advanced geographic information technology and remote sensing techniques allow for a fresh perspective on studying the response of the grassland degradation index ($GDI$) to climate change. This study utilized remote sensing image data of grasslands to calculate the vegetation coverage and derive the $GDI$ for five grassland regions of China from 2001 to 2019. The results indicate that the national degradation status of grasslands remained at a level of mild degradation. The increasing trend of the $GDI$ in some regions was effectively inhibited by regional climate change, especially in the Northeastern and Northern Plain–Mountain–Hill Grassland regions, where the $GDI$ showed a continuous decreasing trend. $GDI$ was strongly correlated with atmospheric pressure, precipitation, temperature, and wind speed. In the arid northern region, the increasing precipitation and decreasing temperatures predominantly contributed to the depressed $GDI$. In the Qinghai–Tibetan Plateau Grassland region, the instability of the $GDI$ is attributed to fluctuating atmospheric pressure, with a correlation coefficient ranging from 0.5 to 0.8. Our findings underscore the importance of meteorological factors to evaluate and forecast grassland ecosystem stability. This understanding is vital for developing informed conservation and management strategies to address current and future climate challenges.

Precipitation is a fundamental element in terrestrial water circulation and ecosystem hydrological balance. The occurrence of concentrated precipitation is closely linked to vegetation growth and soil fertility rather than accumulated or averaged precipitation. Despite its importance, the characteristics of continuous precipitation and its specific effects on vegetation cover remain uncertain. In this study, we formulated a new continuous precipitation index system, including $C{P}_d$ (continuous precipitation days); $AC{P}_t$ (annual continuous precipitation times); $C{P}_a$ (continuous precipitation amount); and $FCP$ (frequency in different ranges of $AC{P}_a$). We utilized daily precipitation data from 467 meteorological stations across China, which were divided into eight vegetation type regions. We observed that the spatial distribution of continuous precipitation differed to varying degrees from accumulated precipitation. The national average of $MAC{P}_a$ for a single event was 16.7 mm, ranging from 3.8 mm in the temperate desert region to 37.1 mm in the tropical monsoon forest and rainforest region. Similarly, the national average of $MC{P}_d$ ($MMC{P}_d$) for a single event was approximately 2.3 or 9 days. At the regional level, the tropical monsoon forest and rainforest region experienced the longest $MMC{P}_d$. Furthermore, the national average of $MAC{P}_t$ occurrences for 1 year was 57.7 times, varying from 29.8 times in the temperate desert region to 77.9 times in the tropical monsoon forest and rainforest region. Vegetation responses to precipitation regimes exhibit significant regional heterogeneity across China. Our analysis reveals that $MAC{P}_t$ and $M{P}_a$ show markedly positive correlations with vegetation growth. In subtropical monsoon climate zones, particularly the Yunnan–Guizhou Plateau and Qinling Mountains, $MAC{P}_t$ demonstrates strong positive correlations (r = 0.6–1.0) with NDVI, where sustained rainfall provides stable moisture availability for vegetation. While a positive correlation between vegetation (NDVI) and mean annual consecutive precipitation is observed in some arid northern regions, in ecosystems such as the Loess Plateau (TG/TM), vegetation growth shows greater dependence on $M{P}_a$, highlighting the crucial role of total precipitation amount in water-limited ecosystems. Notably, extreme precipitation events display dual effects on vegetation dynamics. Prolonged heavy rainfall ($MMC{P}_d$/$MMC{P}_a$) exhibits significant negative impacts on NDVI (r = −1.0 to −0.6) in topographically complex regions, including the Hengduan Mountains and Yangtze River Basin (SE), likely due to induced soil erosion and waterlogging stress. Our findings underscore the importance of incorporating continuous precipitation indices to evaluate and forecast the influence of precipitation on ecosystem stability. This understanding is vital for developing informed conservation and management strategies to address current and future climate challenges.