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The Tibetan Plateau (TP) vegetation plays an important role in the local ecosystem, which responds significantly to climate change and can affect local and large-scale weather and climate anomalies. However, little attention has been paid to its year-to-year variation. In this paper, using two NDVI datasets (GIMMS and MODIS) originated from satellite remote sensing, the variability characteristics of NDVI over the TP on the interannual time scale and associated local climatic factors were investigated. The results show that two primary patterns of NDVI governed TP during the main growing season (June–September, JJAS) for the period 1982–2020. The first one is a uniform pattern, with a consistent spatial variation over the entire TP, and the second is a dipole pattern, with an out-of-phase spatial variation of NDVI between the northern and southern TP. Interannual variations of the different climatic factors regulate the NDVI variability over the different regions of the TP. The interannual variability of the uniform NDVI pattern is mainly affected by the two local climatic factors, the preceding May–August precipitation and simultaneous JJAS sunshine duration. Specifically, NDVIs over the southern and eastern TP have a more significant response to the preceding precipitation and simultaneous sunshine duration, respectively. The variability of the dipole NDVI pattern is primarily modulated by the preceding May–August precipitation and simultaneous surface air temperature, ground surface temperature, and sunshine duration. However, NDVIs over the northern and southern TP have different degrees of response to the four climatic factors, with the most significant response being to preceding precipitation. The combined effect of these factors contributes to the formation of the interannual variability in the uniform and dipole patterns. This paper may shed light on deeply understanding the reasons for the inconsistency in variations of vegetation over the different regions of the TP under climate change. In addition to the effect of local climatic factors that this study focuses on, the influence of external climatic factors on the variability of the TP NDVI deserves further research in the future. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) plays a crucial role in the climate change of China as well as global climate change. It is therefore of great practical significance to study vegetation and its dynamic changes for regional ecological protection. The combination of a dry climate and notable temperature disparities can lead to intricate effects on the region's vegetation. However, there are few studies exploring the complex effects of diurnal temperature variations on vegetation growth that differ from the effects of mean temperature on the TP, especially under different frozen ground types. Based on the long-time series maximum temperature (Tmax), minimum temperature (Tmin), and Normalized Difference Vegetation Index (NDVI) of the TP, we conducted a comparative study of the warming effects on plant growth under different frozen types. The results exhibit that it warms up faster at night (0.223 °C de−1; p < 0.01) than during the day (0.06 °C de−1; p < 0.01), resulting in a significant decrease in the temperature difference between day and night (−0.078 °C de−1; p < 0.01) in the past few decades. The principal finding of this paper is that Tmin is the dominant temperature indicator for vegetation growth on the TP, which dominates 63.3% of the area for NDVI and 61.4% of the area for GPP, respectively. The results further identify a stronger correlation between air temperature and vegetation growth in seasonal frozen grounds (R = 0.68, p < 0.01) and permafrost regions (R = 0.7, p < 0.01) compared to unfrozen grounds (R = 0.58, p < 0.01). Moreover, the physiological mechanism underlying the asymmetric influence of Tmin and Tmax on vegetation growth is further elucidated in this study. Given that future climate changes are expected to exacerbate these changes, it is imperative to explore additional avenues in pursuit of potential mechanisms that can offer adaptive strategies for safeguarding the ecology of the TP. [ABSTRACT FROM AUTHOR]

Snow plays an important role in the water cycle and global climate change, and the accurate monitoring of changes in snow depth is an important task. However, monitoring snow properties is still challenging and unclear, particularly in the Tibetan Plateau, which has rough land and uneven terrain. The traditional monitoring methods have some limitations in monitoring snow depth changes, and the Global Navigation Satellite System-Reflectometry (GNSS-R) provides a new opportunity for snow monitoring. This paper employed data from the Cyclone Global Navigation Satellite System (CYGNSS) to discover the effect of snow properties. Firstly, the observations of CYGNSS were used to find the sensitive to snow properties, and the relationships between signal to noise ratio (SNR), leading edge slope (LES), surface reflectivity (SR), and snow depth were studied and analyzed, respectively. It is found that the correlation between the first two parameters and snow depth is poor, while SR can indicate the changes in snow depth, and is proposed as an indicator of SR change, namely, surface reflectivity–difference ratio factor (SR–DR factor). Furthermore, the long-time series data in the Tibetan Plateau (2018–2019) are used to analyze its effects on the time series of the SR–DR factor, while the influences of the soil freeze/thaw (F/T) process and soil moisture are excluded during the analysis. The results indicate that the SR–DR factor can be a good indicator and discriminator for snow depth. Our work shows that space-borne GNSS-R has the potential for the monitoring of snow properties. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau has experienced profound climate change with significant implication for spatial vegetation greenness. However, the spatiotemporal disparities of long-term vegetation trends in response to observed climate change remain unclear. Based on remote-sensing vegetation images indicated by the normalized difference vegetation index (NDVI) from two long-term combined datasets, GIMMS and MODIS, we identified two spatiotemporal evolution patterns (SEPs) in long-term vegetation anomalies across the Tibetan Plateau. This new perspective integrates spatial and temporal NDVI changes during the growing seasons over the past four decades. Notably, the dipole evolution pattern that rotates counterclockwise from May to September accounted for 62.8% of the spatial mean amplitude of vegetation trends, dominating the spatiotemporal disparities. This dominant pattern trend is attributed to simultaneous effects of spatial warming and rising CO2, which accounted for 75% and 15%, respectively, along with a lagged effect of dipole precipitation, accounting for 6%. Overall, wetting and warming promote greening evolution in the northern Tibetan Plateau, while slight drying and warming favor browning evolution in the southern Tibetan Plateau. These findings provide insights into the combined effects of climate change on spatiotemporal vegetation trends and inform future adaptive strategies in fragile regions. [ABSTRACT FROM AUTHOR]

Alpine grassland is one of the most fragile and sensitive ecosystems, and it serves as a crucial ecological security barrier on the Tibetan Plateau. Due to the combined influence of climate change and human activities, the degradation of the alpine grassland in Gannan Prefecture has been increasing recent years, causing increases in ecological risk (ER) and leading to the grassland ecosystem facing unprecedented challenges. In this context, it is particularly crucial to construct a potential grassland damage index (PGDI) and assessment framework that can be used to effectively characterize the damage and risk to the alpine grassland ecosystem. This study comprehensively uses multi-source data to construct a PGDI based on the grassland resilience index, landscape ER index, and grass–livestock balance index. Thereafter, we proposed a feasible framework for assessing the comprehensive ER of alpine grassland and analyzed the responsive relationship between the comprehensive ER and comprehensive ecosystem services (ESs) of the grassland. There are four findings. The first is that the comprehensive ER of the alpine grassland in Gannan Prefecture from 2000–2020 had a low distribution in the southeast and a high distribution trend in the northwest, with medium risk (29.27%) and lower risk (27.62%) dominating. The high-risk area accounted for 4.58% and was mainly in Lintan County, the border between Diebu and Zhuoni Counties, the eastern part of Xiahe County, and the southwest part of Hezuo. Second, the comprehensive ESs showed a pattern of low distribution in the northwest and high distribution in the southeast. The low and lower services accounted for only 9.30% of the studied area and were mainly distributed in the west of Maqu County and central Lintan County. Third, the Moran's index values for comprehensive ESs and ER for 2000, 2005, 2010, 2015, and 2020 were −0.246, −0.429, −0.348, −0.320, and −0.285, respectively, thereby indicating significant negative spatial autocorrelation for all aspects. Fourth, ER was caused by the combined action of multiple factors. There are significant differences in the driving factors that affect ER. Landscape index is the first dominant factor affecting ER, with q values greater than 0.25, followed by DEM and NDVI. In addition, the interaction between diversity index and NDVI had the greatest impact on ER. Overall, this study offers a new methodological framework for the quantification of comprehensive ER in alpine grasslands. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is a climate-sensitive and ecologically fragile area. Studying drought and its effects on vegetation over the TP is of great significance for ecological conservation. However, there were large uncertainties in previous studies on the drought characteristics and their impacts on alpine vegetation in this region. This study explored the drought changes and their impacts on alpine vegetation during the growing season over the TP in 1982–2018. The results showed that the TP has experienced a wetting trend in most regions of the TP. Correspondingly, the vegetation has become greener in most areas. The wetting and drying trend in the growing season changed around 1995. Before 1995, the TP experienced an overall drying trend with a spatial pattern of a drying trend in the northern regions and a wetting trend in the southern regions, while it showed an overall wetting trend after 1995, with a reversed spatial pattern to that before 1995. After 1995, wetting and drying trends affected the vegetation in 61% of the TP. However, before 1995, the NDVI presented an increasing trend in most areas of the TP under a drying trend. Therefore, a drying trend was not the primary factor affecting vegetation growth in this period. Instead, changes in the cryosphere induced by warming could be the main factor. In addition, the distribution of vegetation across the TP was primarily influenced by drought intensity, which had the greatest impact on sparse vegetation, followed by meadow and grassland. This study enhances our understanding of the impact of drought changes on alpine vegetation on the TP. [ABSTRACT FROM AUTHOR]

As a region susceptible to the impacts of climate change, evaluating the temporal and spatial variations in ecological environment quality (EEQ) and potential influencing factors is crucial for ensuring the ecological security of the Tibetan Plateau. This study utilized the Google Earth Engine (GEE) platform to construct a Remote Sensing-based Ecological Index (RSEI) and examined the temporal and spatial dynamics of the Tibetan Plateau's EEQ from 2000 to 2022. The findings revealed that the RSEI of the Tibetan Plateau predominantly exhibited a slight degradation trend from 2000 to 2022, with a multi-year average of 0.404. Utilizing SHAP (Shapley Additive Explanation) to interpret XGBoost (eXtreme Gradient Boosting), the study identified that natural factors as the primary influencers on the RSEI of the Tibetan Plateau, with temperature, soil moisture, and precipitation variables exhibiting higher SHAP values, indicating their substantial contributions. The interaction between temperature and precipitation showed a positive effect on RSEI, with the SHAP interaction value increasing with rising precipitation. The methodology and results of this study could provide insights for a comprehensive understanding and monitoring of the dynamic evolution of EEQ on the Tibetan Plateau amidst the context of climate change. [ABSTRACT FROM AUTHOR]

The study of the response of vegetation phenology in the Qinghai Tibet Plateau to various climatic variables is paramount to unveiling the reaction of alpine ecosystems to worldwide climate alterations. Nonetheless, the lagged and cumulative effects of various climatic variables on vegetation phenology in the Qinghai Tibet Plateau remain unclear. Therefore, based on MODIS NDVI data, we extracted vegetation phenological parameters from 2001 to 2020, including the start of the vegetation growing season (SOS) and the end of the vegetation growing season (EOS), and then analyzed the response mechanisms of vegetation phenology to pre-seasonal air temperature (T), precipitation (P), and daytime and nighttime land surface temperatures (DLST, NLST) in the Qinghai Tibet Plateau on the basis of an investigation of the lag and cumulative effects. The results showed that: (1) the multiyear mean values of the SOS mainly occurred from 120 to 160 days, accounting for 86.17% of the study area, while the multiyear mean values of the EOS were mainly concentrated between 260 and 280 days, accounting for 77.05% of the study area; (2) air temperature (T), precipitation (P), and daytime and nighttime land surface temperatures (DLST, NLST) had different degrees of lagging effects on the SOS and the EOS. Among them, the time lag effect of precipitation on vegetation phenology was more pronounced; (3) different climatic variables had distinct cumulative effects on vegetation phenology. In contrast to the insignificant cumulative effects of temperature and nighttime surface temperature on the SOS and the EOS, the cumulative effects of precipitation and daytime land surface temperature on the SOS were more pronounced than those on the EOS; (4) the SOS and air temperature, precipitation, and NLST were mainly negatively correlated, in which the proportion of the negative correlation between SOS and NLST was up to 68.80%, and SOS and DLST were mainly positively correlated with a positive correlation proportion of 73.27%, EOS and air temperature, precipitation, and NLST were positively correlated with a positive correlation proportion of EOS and precipitation of up to 71.52%, and EOS and DLST were mainly negatively correlated with a negative correlation ratio of 55.87%. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is distributed with large areas of permafrost, which have received increasing attention as the climate warms. Accurately modeling the extent of permafrost and permafrost changes is now an important challenge for climate change research and climate modeling in this region. Uncertainty in land use and land cover (LULC), which is important information characterizing surface conditions, directly affects the accuracy of the simulation of permafrost changes in land surface models. In order to investigate the effect of LULC uncertainty on permafrost simulation, we conducted simulation experiments on the TP using the Community Land Model, version 5 (CLM5) with five high-resolution LULC products in this study. Firstly, we evaluated the simulation results using shallow soil temperature data and deep borehole data at several sites. The results show that the model performs well in simulating shallow soil temperatures and deep soil temperature profiles. The effect of different land use products on the shallow soil temperature and deep soil temperature contours is not obvious due to the small differences in land use products at these sites. Although there is little difference in the simulating results of different land use products when compared to the permafrost distribution map, the differences are noticeable for the simulation of the active layer. Land cover had a greater impact on soil temperature simulations in regions with greater land use inconsistency, such as at the junction of bare soil and grassland in the northwestern part of the TP, as well as in the southeast region with complex topography. The main way in which this effect occurs is that land cover affects the net surface radiation, which in turn causes differences in soil temperature simulations. In addition, we discuss other factors affecting permafrost simulation results and point out that increasing the model plant function types as well as carefully selecting LULC products is one of the most important ways to improve the simulation performance of land-surface models in permafrost regions. [ABSTRACT FROM AUTHOR]

Soil moisture over the Tibetan Plateau (TP) can affect hydrological cycles on local and remote scales through land–atmosphere interactions. However, TP long-term surface soil moisture characteristics and their response to climate change are still unclear. In this study, we firstly evaluate two satellite-based products—SSM/I (the Special Sensor Microwave Imagers) and ECV COMBINED (the Essential Climate Variable combined)—and three reanalysis products—ERA5-Land (the fifth generation of the land component of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis), MERRA2 (the second version of Modern-Era Retrospective Analysis for Research and Applications), and GLDAS Noah (the Noah land surface model driven by Global Land Data Assimilation System)—against two in situ observation networks. SSM/I and GLDAS Noah outperform the other soil moisture products, followed by MERRA2 and ECV COMBINED, and ERA5-Land has a certain degree of uncertainty in evaluating TP surface soil moisture. Analysis of long-term soil moisture characteristics during 1988–2008 shows that annual and seasonal mean soil moisture have similar spatial distributions of soil moisture decreasing from southeast to northwest. Additionally, a significant increasing trend of soil moisture is found in most of the TP region. With a non-linear machine learning method, we quantify the contribution of each climatic variable to warm-season soil moisture. It indicates that precipitation dominates soil moisture changes rather than air temperature. Pixel-wise partial correlation coefficients further show that there are significant positive correlations between precipitation and soil moisture over most of the TP region. The results of this study will help to understand the role of TP soil moisture in land–atmosphere coupling and hydrological cycles under climate change. [ABSTRACT FROM AUTHOR]

Known as the "Asian Water Tower", the Tibetan Plateau (TP) is a rich water resource and serves an important ecological function. Climate change may cause changes to the water cycle, and these changes may affect the alpine vegetation growth. However, the variation characteristics of groundwater storage (GWS) and its driving factors and associated ecological effects in the TP are poorly understood. In this study, terrestrial water storage changes retrieved by GRACE (Gravity Recovery and Climate Experiment) were combined with GLDAS (Global Land Data Assimilation System) to estimate the GWS changes in the TP. The temporal and spatial variation characteristics of GWS were identified using linear regression and the modified Mann–Kendall (MMK) test, respectively. The analyses showed that the GWS of the TP decreased at an average rate of −0.89 mm/a from January 2003 to December 2021, but since January 2016, it gradually recovered at a rate of 1.47 mm/a. This shows that the GWS in the eastern and northern parts of the TP is decreasing, while the GWS in the western and southern parts is increasing. The influence of climate change on GWS in time and space was determined using the correlation analysis method. Decreased precipitation and permafrost degradation caused by increasing temperatures will lead to a decrease in GWS. On the other hand, rising temperatures may result in an increase in GWS in regions where glaciers are distributed. In this study, the ecological effects were represented by the relationship between GWS and vegetation change. A decline in GWS means that the vegetation will not receive enough water, leading to a decrease in the NDVI and the eventual degradation of grassland to sand, desert, or other kinds of unused land on the TP. On the other hand, an increase in GWS would promote vegetation restoration. The results of this study offer a new opportunity to reveal the groundwater changes in a cryosphere region and to assess the impact of changes in hydrological conditions on ecology. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is one of the most important areas for the study of the carbon budgets of terrestrial ecosystems. However, the estimation of the net ecosystem productivity (NEP) remains uncertain in this region due to its complex topographic properties and climatic conditions. Using CO2-eddy-covariance-flux data from 1982 to 2018 at 18 sites distributed around the TP grassland, we analyzed the spatial–temporal patterns of the grassland NEP and its driving factors from 1982 to 2018 using a random forest (RF) model. Our results showed that the RF model captured the size of the carbon sink (R2 = 0.65, p < 0.05) between the observed and simulated values for the validation samples. During the observation period, the grassland acted as a carbon sink of 26.2 Tg C yr−1 and increased significantly, by 0.4 g C m−2 yr−1. On a regional scale, the annual NEP gradually increased from the northwest to the southeast, and a similar pattern was also observed in the long-term trends. Furthermore, the moisture conditions, such as the specific humidity and precipitation, were proven to be the main driving factors of the carbon flux in the southeastern areas, while the temperature predominantly controlled the carbon flux in the northwest. Our results emphasize the net carbon sink of the TP and provide a reliable way to upscale NEP from sites. [ABSTRACT FROM AUTHOR]

As the Third Pole of the Earth and the Water Tower of Asia, the Tibetan Plateau (TP) nurtures large numbers of glacial lakes, which are sensitive to global climate change. These lakes modulate the freshwater ecosystem in the region but concurrently pose severe threats to the valley population by means of sudden glacial lake outbursts and consequent floods (GLOFs). The lack of high-resolution multi-temporal inventory of glacial lakes in TP hampers a better understanding and prediction of the future trend and risk of glacial lakes. Here, we created a multi-temporal inventory of glacial lakes in TP using a 30-year record of 42,833 satellite images (1990–2019), and we discussed their characteristics and spatio-temporal evolution over the years. Results showed that their number and area had increased by 3285 and 258.82 km2 in the last 3 decades, respectively. We noticed that different regions of the TP exhibited varying change rates in glacial lake size; most regions show a trend of expansion and increase in glacial lakes, while some regions show a trend of decreasing such as the western Pamir and the eastern Hindu Kush. The mapping uncertainty is about 17.5%, which is lower than other available datasets, thus making our inventory reliable for the spatio-temporal evolution analysis of glacial lakes in the TP. Our lake inventory data are publicly published, it can help to study climate change–glacier–glacial lake–GLOF interactions in the Third Pole and serve as input to various hydro-climatic studies. [ABSTRACT FROM AUTHOR]

Precipitation of future climate models is critical for the assessments of future drought but contains large systematic biases over the Tibetan Plateau. Although the common precipitation bias correction method, quantile mapping has achieved remarkable results in terms of temporal bias correction, it does not consider the spatial distribution of bias. Furthermore, the extent to which precipitation bias affects drought estimation remains unclear. In our study, we take the Qinghai–Tibet Plateau (QHTP) as the case study and quantify the impact of corrected precipitation bias for seven Coupled Model Intercomparison Project Phase 6 (CMIP6) models on drought assessment in historical and future scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). To improve the accuracy of drought prediction, potential evapotranspiration (PET) was also corrected. Firstly, the histogram matching-quantile mapping (HQ) algorithm considering spatial correction is established to correct precipitation and PET. Then, we quantified the effects of precipitation and potential evapotranspiration correction on the change of drought intensity, and finally analyzed the spatiotemporal trends of precipitation, PET, and SPEI over the QHTP in the future. The results show that the HQ method can effectively improve the simulation ability of the model, especially the simulation accuracy of the ensemble model. After correction, the average annual total precipitation (TP) declined by 64.262% in 99.952% of QHTP, the average PET increased in 11.902% of the area and decreased in 88.098% of the area, while the intensity of the drought in 81.331% of the area increased by 2.875% and the 18.669% area decreased by 1.139%. Therefore, the uncorrected simulation data overestimated the future increase trend in precipitation and underestimated the future decrease trend in SPEI. The trend of HQ-corrected TP increased by 3.730 mm/10a, 7.190 mm/10a, and 12.790 mm/10a, and the trend of SPEI (TP and PET corrected) decreased by 0.143/100a, 0.397/100a, and 0.675/100a, respectively. Therefore, quantifying the changing relationship between precipitation bias correction and drought assessments is useful for understanding regional climate change. [ABSTRACT FROM AUTHOR]

Soil freeze–thaw processes are remarkable features of the land surface across the Tibetan Plateau (TP). Soil moisture and temperature fluctuate during the freeze–thaw cycle, affecting the soil water and energy exchange between the land and atmosphere. This study investigates variations in the soil temperature, humidity, and freeze–thaw state and their responses to air temperature and precipitation on the TP from 1981 to 2016. Regional simulations of the TP using Community Land Model version 4.5 demonstrate that the climate of the TP has become warmer and wetter over the past 37 years, with increases in both regional average temperature and precipitation. Using empirical orthogonal function analysis and the Mann–Kendall trend test of air temperature, we show that 1980–1998 was relatively cold, and 1999–2016 was relatively warm. Soil temperature and moisture in most areas of the TP were affected by air temperature and precipitation, and both showed an upward trend during the past 37 years. Overall, from 1981 to 2016, the freezing date of the TP has become delayed, the thawing date has been hastened, and the duration of the freeze–thaw state has shortened. The surface soil freezes and thaws first, and these processes pervade deeper soil with the passage of time; freeze–thaw processes have an obvious hysteresis. Precipitation and air temperature had marked effects on the freeze–thaw processes. Higher air temperatures delay the freezing date, hasten the thawing date, and shorten the freeze–thaw period. Areas with the highest precipitation saw late soil freeze, early thaw, and the shortest freeze–thaw duration. Areas with less vegetation froze earlier and thawed later. The freeze–thaw duration increased in the northwest of the plateau and decreased on the rest of the plateau. This article informs research on frozen soil change in the context of global warming. [ABSTRACT FROM AUTHOR]

Glaciers are an important part of the cryosphere and important reservoirs of fresh water on Earth. Glaciers in the Gongga Mountains, located in the southeastern Tibetan Plateau, have been experiencing dramatic changes and substantially shrinking over the past two decades. We analyzed the glacier change over the Gongga Mountains using the Landsat data from 1994 to 2021 (interval of 4 or 5 years), with Gaofen-1 (GF-1) data to evaluate the uncertainty. The glacier shrinkage under different terrain conditions, including altitudes, slope, and slope direction, was further explored. Finally, we evaluated the response of glacier shrinkage to climate change using precipitation and temperature data for nearly 30 years. Results show that the glaciers in the Gongga Mountains are experiencing an accelerating ablation, with a glacier area of ~240 km2 in 1994 and ~212 km2 in 2021 (an average annual shrinkage rate of 1.04 km2/a). The shrinkage mainly occurs in areas with altitudes of 5000–5300 m and a slope of 30–40°. Moreover, the shrinkage is strongly related to the recent warming of the climate, with the warming rate being 0.19 °C/10a, while precipitation remains almost constant during 1978–2019. The results provide a scientific basis for water resources management, ecological environmental protection, and natural disaster protection in southeast Tibet for decision making. [ABSTRACT FROM AUTHOR]

Soil moisture (SM), as a crucial variable in the soil–vegetation–atmosphere continuum, plays an important role in the terrestrial water cycle. Analyzing SM's variation and driver factors is crucial to maintaining ecosystem diversity on the Tibetan Plateau (TP) and ensuring food security as well as water supply balance in developing countries. Gradual wetting of the soil has been detected and attributed to precipitation in this area. However, there is still a gap in understanding the potential mechanisms. It is unclear whether the greening, glacier melting, and different vegetation degradation caused by asymmetrical climate change and intensified human activities have significantly affected the balance of SM. Here, to test the hypothesis that heterogeneous SM caused by precipitation was subject to temperatures and anthropogenic constraints, GLDAS-2.1 (Global Land Data Assimilation System-2.1) SM products combined with the statistical downscaling and Geographic detectors were applied. The results revealed that: (1) Seasonal SM gradually increased (p < 0.05), while SM deficit frequently appeared with exposure to extreme climates, such as in the summer of 2010 and 2013, and changed into a pattern of precipitation transport to western dry lands in autumn. (2) There was a synergistic reaction between greening and local moisture in autumn. SM was dominated by low temperature (TMN) in winter, warming indirectly regulated SM by exacerbating the thawing of glaciers and permafrost. The spatial coupling between the faster rising rate of TMN and the frozen soil might further aggravate the imbalance of SM. (3) The land cover's mutual transformation principally affected SM in spring and autumn, and degradation accelerated the loss of SM replenished by precipitation. (4) Land cover responses were different; SM in grassland was less affected by external disturbance, while degraded woodland and shrub performed adaptive feedback under dry environments, SM increased by 0.05 and 0.04 m3/(m3 10a), respectively. Our research provides a scientific basis for improving hydrological models and developing vegetation restoration strategies for long-term adaptation to TP-changing environments. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? Principal component regressions revealed the climate sensitivity of Tibetan arid desert scrubs. Plant nutrient traits and soil nutrient availability regulate desert scrubs' climate sensitivity. What is the implication of the main finding? Scrubs' sensitivity to temperature is mainly regulated by the nitrogen contents of soils and leaves. Scrubs' sensitivity to precipitation is affected by the leaf carbon content of dominant species. Neither soil nor plant nutritional properties alone can well explain scrubs' sensitivity to droughts. Climate models predict the further intensification of global warming in the future. Drylands, as one of the most fragile ecosystems, are vulnerable to changes in temperature, precipitation, and drought extremes. However, it is still unclear how plant traits interact with soil properties to regulate drylands' responses to seasonal and interannual climate change. The vegetation sensitivity index (VSI) of desert scrubs in the Qaidam Basin (NE Tibetan Plateau) was assessed by summarizing the relative contributions of temperature (SGST), precipitation (SGSP), and drought (temperature vegetation dryness index, STVDI) to the dynamics of the normalized difference vegetation index (NDVI) during plant growing months yearly from 2000 to 2015. Nutrient contents, including carbon, nitrogen, phosphorus, and potassium in topsoils and leaves of plants, were measured for seven types of desert scrub communities at 22 sites in the summer of 2016. Multiple linear and structural equation models were used to reveal how leaf and soil nutrient regimes affect desert scrubs' sensitivity to climate variability. The results showed that total soil nitrogen (STN) and leaf carbon content (LC), respectively, explained 25.9% and 17.0% of the VSI variance across different scrub communities. Structural equation modeling (SEM) revealed that STN and total soil potassium (STK) mediated desert scrub's VSI indirectly via SGST (with standardized path strength of −0.35 and +0.32, respectively) while LC indirectly via SGST and SGSP (with standardized path strength of −0.31 and −0.19, respectively). Neither soil nor leave nutrient contents alone could explain the VSI variance across different sites, except for the indirect influences of STN and STK via STVDI (−0.18 and 0.16, respectively). Overall, this study disentangled the relative importance of plant nutrient traits and soil nutrient availability in mediating the climatic sensitivity of desert scrubs in the Tibetan Plateau. Integrating soil nutrient availability with plant functional traits together is recommended to better understand the mechanisms behind dryland dynamics under global climate change. [ABSTRACT FROM AUTHOR]

Changes in vegetation dynamics play a critical role in terrestrial ecosystems and environments. Remote sensing products and dynamic global vegetation models (DGVMs) are useful for studying vegetation dynamics. In this study, we revised the Community Land Surface Biogeochemical Dynamic Vegetation Model (referred to as the BGCDV_CTL experiment) and validated it for the Tibetan Plateau (TP) by comparing vegetation distribution and carbon flux simulations against observations. Then, seasonal–deciduous phenology parameterization was adopted according to the observed parameters (referred to as the BGCDV_NEW experiment). Compared to the observed parameters, monthly variations in gross primary productivity (GPP) showed that the BGCDV_NEW experiment had the best performance against the in situ observations on the TP. The climatology from the remote sensing and simulated GPPs showed similar patterns, with GPP increasing from northwest to southeast, although the BGCDV_NEW experiment overestimated GPP in the semi-arid and arid regions of the TP. The results show that temperature warming was the dominant factor resulting in the increase in GPP based on the remote sensing products, while precipitation enhancement was the reason for the GPP increase in the model simulation. [ABSTRACT FROM AUTHOR]

Lake levels in the Qinghai-Tibet Plateau (QTP) provide valuable records for climate change studies. We use two decades of measurements (January 1993-December 2014) from the TOPEX/Poseidon (T/P)-family satellite altimeters (T/P, Jason-1 and -2) to detect lake level variations at 23 lakes along their repeat ground tracks every 10 days. We employ an optimal processing technique to obtain quality measurements, including outlier detection, averaging and filtering. The lake level accuracies are improved by subwaveform retracking. Jason-1 delivers few measurements after waveform retracking and a cluster classification at most lakes. From January 1993 to December 2014, most lake levels in eastern Tibet rose, while those in western Tibet declined. In Qinghai, lake levels dropped before 2005 and then rose afterwards, coinciding with the measure in 2005 that protects the Qinghai ecosystem (e.g., grassland conservation). The overall pattern of lake level change in the QTP is largely affected by monsoons and lake locations. Most lake levels show clear annual and inter-annual oscillations. Certain lakes show alternating level highs and lows in the same seasons and varying amplitudes of annual oscillations due to lake level changes. We detect a sudden rise of lake level by 7 m caused by floods, varying lake level trends associated with the 1997-98 El Niño and other factors, and persistently rising and declining lake levels associated with the long-term precipitation trends in the QTP. The T/P-family satellites will continue to monitor lake levels here as long as the sea level monitoring program lasts, collecting a long-term climate record at highlands echoing sea level change. [ABSTRACT FROM AUTHOR]

The Yarlung Zangbo River basin is an important alley to transport moisture from the Indian Ocean to the inner Tibetan Plateau. With a wide range of elevations from 147 m to over 7000 m above sea level (a.s.l.), ecosystems respond differently to climate change at various elevations. However, the pattern of elevation-dependent vegetation change and how it responds to recent warming have been rarely reported. Here, we investigated the pattern of vegetation greening at different elevations in this river basin using SPOT normalized difference vegetation index (NDVI) data during 1999-2013, and examined its relationship with elevation-dependent changes in temperature and precipitation. The annual NDVI has increased by 8.83% from 1999 to 2013. In particular, the NDVI increased more apparently at lower elevations, but remained relatively stable or even decreased at high elevations. It seems that rising temperature has driven the basin-wide vegetation greening, but the greening rate is in contrast to the pattern of elevation-dependent warming (EDW) with more significant temperature increase at higher elevations. It appears that decreasing precipitation does not reverse the overall increasing trend in NDVI, but relatively limited precipitation (<500 mm) may constrain the NDVI increases, causing apparently stable or even decreased NDVI at higher elevations (>4000 m). [ABSTRACT FROM AUTHOR]

The coupling of rapid warming and wetland degradation on the Tibetan Plateau has motivated studies of climate influence on wetland change in the region. These studies typically examine large, topographically homogeneous regions, whereas conservation efforts sometimes require fine-grained information in rugged terrain. This study addresses topographically constrained wetlands on the Eastern Tibetan, where herders report significant wetland degradation. We used Landsat images to examine changes in wetland areas and Sentinel-1 SAR images to investigate water level and vegetation structure. We also analyzed trends in precipitation, growing season length, and reference evapotranspiration in weather station records. Snow cover and the vegetation growing season were quantified using MODIS observations. We analyzed estimates of actual evapotranspiration using the Atmosphere-Land Exchange Inverse model (ALEXI) and the Simplified Surface Energy Balance model (SSEBop). Satellite-informed analyses failed to confirm herders' accounts of reduced wetland function, as no coherent trends were found in wetland area, water content, or vegetation structure. An analysis of meteorological records did indicate a warming-induced increase in reference evapotranspiration, and both meteorological records and satellites suggest that the growing season had lengthened, potentially increasing water demand and driving wetland change. The discrepancies between the satellite data and local observations pointed to temporal, spatial, and epistemological gaps in combining scientific data with empirical evidence in understanding wetland change on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Climate change has significantly affected the ecosystem of the Tibetan Plateau. There, temperature rises and altered precipitation patterns have led to notable changes in its vegetation growth processes and vegetation cover features. Yet current research still pays relatively little attention to the regional climatic determinants and response patterns of such vegetation dynamics. In this study, spatial patterns in the response of the normalized difference vegetation index (NDVI) to climate change and its dynamic characteristics during the growing season were examined for the Tibetan Plateau, by using a pixel-scale-based geographically weighted regression (GWR) based on the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI data, as well as data for temperature and moisture indices collected at meteorological stations, for the period 1982–2015. The results show the following. Spatial nonstationary relationships, primarily positive, were found between the NDVI and climatic factors in the Tibetan Plateau. However, warming adversely affected vegetation growth and cover in some arid and semiarid regions of the northeast and west Tibetan Plateau. Additionally, precipitation played a dominant role in the NDVI of the Tibetan Plateau in the largest area (accounting for 39.7% of total area). This suggests that increased moisture conditions considerably facilitated vegetation growth and cover in these regions during the study period. Temperature mainly played a dominant role in the NDVI in some parts of the plateau sub-cold zone and some southeastern regions of the Tibetan Plateau. In particular, the minimum temperature was the dominant driver of NDVI over a larger area than any of the other temperature indices. Furthermore, spatial regressions between NDVI dynamics and climatic variability revealed that a faster warming rate in the arid and semiarid regions impeded vegetation growth through mechanisms such as drought intensification. Moisture variability was found to act as a key factor regulating the extent of vegetation cover on the south Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Permafrost is degrading on the Qinghai-Tibet Plateau (QTP) due to climate change. Permafrost degradation can result in ecosystem changes and damage to infrastructure. However, we lack baseline data related to permafrost thermal dynamics at a local scale. Here, we model climate change impacts on permafrost from 1986 to 2075 at a high resolution using a numerical model for the Beiluhe basin, which includes representative permafrost environments of the QTP. Ground surface temperatures are derived from air temperature using an n-factor vs Normalized Differential Vegetation Index (NDVI) relationship. Soil properties are defined by field measurements and ecosystem types. The climate projections are based on long-term observations. The modelled ground temperature (MAGT) and active-layer thickness (ALT) are close to in situ observations. The results show a discontinuous permafrost distribution (61.4%) in the Beiluhe basin at present. For the past 30 years, the permafrost area has decreased rapidly, by a total of 26%. The mean ALT has increased by 0.46 m. For the next 60 years, 8.5–35% of the permafrost area is likely to degrade under different trends of climate warming. The ALT will probably increase by 0.38–0.86 m. The results of this study are useful for developing a deeper understanding of ecosystem change, permafrost development, and infrastructure development on the QTP. [ABSTRACT FROM AUTHOR]

Alpine vegetation on the Tibetan Plateau (TP) is known to be sensitive to both climate change and anthropogenic disturbance. However, the magnitude and patterns of alpine vegetation dynamics and the driving mechanisms behind their variation on the TP remains under debate. In this study, we used updated MODIS Collection 6 Normalized Difference Vegetation Index (NDVI) from the Terra satellite combined with linear regression and the Break for Additive Season and Trend model to reanalyze the spatiotemporal patterns of vegetation change on the TP during 2000–2015. We then quantified the responses of vegetation variation to climatic and anthropogenic factors by coupling climatic and human footprint datasets. Results show that growing season NDVI (GNDVI) values increased significantly overall (0.0011 year−1, p < 0.01) during 2000–2015 and that 70.37% of vegetated area on the TP (23.47% significantly with p < 0.05) exhibited greening trends with the exception of the southwest TP. However, vegetation greenness experienced trend shifts from greening to browning in half of the ecosystem zones occurred around 2010, likely induced by spatially heterogeneous temporal trends of climate variables. The vegetation changes in the northeastern and southwestern TP were water limited, the mid-eastern TP exhibited strong temperature responses, and the south of TP was driven by a combination of temperature and solar radiation. Furthermore, we found that, to some extent, anthropogenic disturbances offset climate-driven vegetation greening and aggravated vegetation browning induced by water deficit. These findings suggest that the impact of anthropogenic activities on vegetation change might not overwhelm that of climate change at the region scale. [ABSTRACT FROM AUTHOR]