In recent years, drought frequency has gradually increased, which has reduced vegetation growth and development. The response of grassland to meteorological drought is more sensitive than other vegetation types and can differ substantially among grassland types. In this study, the response of vegetation change to meteorological drought at different time scales was evaluated using data from the normalized difference vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI) to analyze the spatial and temporal variation trends and correlations of the NDVI and SPEI of three grassland types in Xinjiang from 1982 to 2015. Over this 34-year period, the NDVI of meadow, steppe, and desert grassland in Xinjiang increased, with growth rates of 0.002, 0.002, and 0.0003 per decade, respectively, although the increase was insignificant (p > 0.05). The most obvious vegetation improvement areas of the three grassland types were mainly distributed in the Tianshan Mountains. The SPEI-12 of meadow, steppe, and desert grassland in Xinjiang indicated an extremely significant drying trend (p < 0.01), with change rates of −0.31, −0.38, and −0.34 per decade, respectively. The overall pattern was the gradual drying from the northwest to southeast, and the degree of aridification was the largest in eastern Xinjiang. On the annual scale, the correlation between the NDVI and SPEI-12 of the three grassland types was significantly different between northern and southern Xinjiang. The degree to which the vegetation of the three grassland types responded to drought was higher in northern Xinjiang than in southern Xinjiang, and most responses were significant. On the monthly scale, the response of meadow to the SPEI-12 was the highest in autumn (September) (r = 0.53; p < 0.05), the response of steppe to the SPEI-3 was the highest in summer (August) (r = 0.49; p < 0.05), and the response of desert grassland to the SPEI-12 was the highest in summer (June) (r = 0.44; p < 0.05). The results can provide a scientific basis for natural grassland drought response, ecological environmental improvement, and disaster prevention and mitigation.

Aboveground biomass (AGB) is a key indicator of the physiological status and productivity of grasslands, and its accurate estimation is essential for understanding regional carbon cycles. In this study, we developed a suitable AGB model for grasslands in Xinjiang based on the random forest algorithm, using AGB observation data, remote sensing vegetation indices, and meteorological data. We estimated the grassland AGB from 2000 to 2022, analyzed its spatiotemporal changes, and explored its response to climatic factors. The results showed that (1) the model was reliable (R² = 0.55, RMSE = 64.33 g·m⁻²) and accurately estimated the AGB of grassland in Xinjiang; (2) the spatial distribution of grassland AGB in Xinjiang showed high levels in the northwest and low values in the southeast. AGB showed a growing trend in most areas, with a share of 61.19%. Among these areas, lowland meadows showed the fastest growth, with an average annual increment of 0.65 g·m⁻²·a⁻¹; and (3) Xinjiang’s climate exhibited characteristics of warm humidification, and grassland AGB showed a higher correlation with precipitation than temperature. Developing remote sensing models based on random forest algorithms proves an effective approach for estimating AGB, providing fundamental data for maintaining the balance between grass and livestock and for the sustainable use and conservation of grassland resources in Xinjiang, China.

Grassland biomass is a significant parameter for measuring grassland productivity and the ability to sequester carbon. Estimating desert grassland biomass using the best remote sensing inversion model is essential for understanding grassland carbon stocks in arid and semi-arid regions. The present study constructed an optimal inversion model of desert grassland biomass based on actual biomass measurement data and various remote-sensing product data. This model was used to analyze the spatiotemporal variation in desert grassland biomass and climate factor correlation in Xinjiang from 2000 to 2019. The results showed that (1) among the established inversion models of desert grasslands aboveground biomass (AGB), the exponential function model with the normalized differential vegetation index (NDVI) as the independent variable was the best. Furthermore, (2) the NDVI of desert grasslands in Xinjiang showed a highly significant increasing trend from 2000 to 2019 with a spatially concentrated distribution in the north and a more dispersed distribution in the south. In addition, (3) the average AGB value was 52.35 g·m⁻² in Xinjiang from 2000 to 2019 and showed a spatial distribution with low values in the southeast and high values in the northwest. Moreover, (4) the low fluctuation in the coefficient of desert grassland variation accounted for 65.26% of overall AGB fluctuation (<0.10) from 2000 to 2019. Desert grassland AGB in most areas (88.65%) showed a significant increase over the last 20 years. Lastly, (5) the correlation between desert grassland precipitation and AGB was stronger than that between temperature and AGB from 2000 to 2019. This study provides a scientific basis and technical support for grassland livestock management and carbon storage assessments in Xinjiang.

In this work, we examined spatial and temporal trends for light rain days based on daily precipitation measurements, obtained from 1960 to 2014, from 590 meteorological stations in China. For the analyzed time interval, light rain days over eastern China were determined to decrease by 0.23 days·year⁻¹. In western China, they increased by 0.3 days·year⁻¹. To detect underlying causes for changes in light rain days, lower-tropospheric relative humidity was set as a proxy for light rain days. We then calculated the respective impacts of lower-tropospheric temperature and specific humidity on changes in light rain days. A comparison of the contributions of temperature and specific humidity resulted in the identification of the main cause of changes. Our results indicated that increases in lower-tropospheric temperatures reduced light rain days over the entire country, while variations in specific humidity dominated regional differences for light rain day trends.

Grasslands, covering over 40% of terrestrial land surfaces, play a critical role in regional water cycling through their greening processes. However, the decoupling mechanisms between grassland greening and water availability (WA) changes across the Northern Hemisphere, along with their future trajectories, remain poorly understood. Here, we integrated multi-source satellite observations with CMIP6 model ensembles to systematically assess the spatiotemporal evolution and trend divergence of leaf area index (LAI) and WA across Northern Hemisphere grasslands from 2000 to 2100. Our results showed that grassland LAI exhibited sustained growth during 2000–2020, with 55.28% of regions showing significant increasing trends. However, 73.67% of grassland regions experienced declining WA during the historical period, revealing widespread decoupling between grassland greening and water deficit. Future scenario projections indicated a reversal to increasing WA trends, with 57.51% of regions showing significant increases under SSP5–8.5. Furthermore, 61.87% of grasslands exhibited greening-driven drying (GDD) characteristics during the historical period, while greening-driven wetting (GDW) regions were projected to expand to 72.44% in the future. Analysis along aridity gradients revealed that humid zones contributed most prominently to LAI and WA changes. Mechanistic decomposition demonstrated that grassland WA changes shifted from precipitation-dominated control (53.60%) in the historical period toward a regime jointly governed by precipitation dominance and coupled precipitation–evapotranspiration drivers in the future. Concurrently, the dominant factor controlling grassland greening transitioned from vapor-pressure deficit (VPD) to temperature (TEM) control. Additionally, driving factors exhibited pronounced differentiation patterns along aridity gradients during the historical phase: arid zones were dominated by soil moisture (SM) and semi-arid zones displayed dual control by SM and VPD, while humid zones were governed by coupled TEM-VPD regulation. This study reveals the divergent trends between grassland greening and WA and unravels their driving mechanisms, offering important scientific evidence for formulating regionally differentiated ecological water resource management strategies.