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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]

Global climate warming has profoundly affected terrestrial ecosystems. The Tibetan Plateau (TP) is an ecologically vulnerable region that emerged as an ideal place for investigating the mechanisms of vegetation response to climate change. In this study, we constructed an annual synthetic NDVI dataset with 500 m resolution based on MOD13A1 products from 2000 to 2021, which were extracted by the Google Earth Engine (GEE) and processed by the Kalman filter. Furthermore, considering topographic and climatic factors, a thorough analysis was conducted to ascertain the causes and effects of the NDVI's spatiotemporal variations on the TP. The main findings are: (1) The vegetation coverage on the TP has been growing slowly over the past 22 years at a rate of 0.0134/10a, with a notable heterogeneity due to its topography and climate conditions. (2) During the study period, the TP generally showed a "warming and humidification" trend. The influence of human activities on vegetation growth has exhibited a favorable trajectory, with a notable acceleration observed since 2011. (3) The primary factor influencing NDVI in the southeastern and western regions of the TP was the increasing temperature. Conversely, vegetation in the northeastern and central regions was mostly regulated by precipitation. (4) Combined with the principal component analysis, a PCA-CNN-LSTM (PCL) model demonstrated significant superiority in modeling NDVI sequences on the Tibetan Plateau. Understanding the results of this paper is important for the sustainable development and the formulation of ecological policies on the Tibetan Plateau. [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]

Most glaciers on the Tibetan Plateau have experienced continuous mass losses in response to global warming. However, the seasonal dynamics of glaciers on the southeastern Tibetan Plateau have rarely been reported in terms of glacier surface elevation and velocity. This paper presents a first attempt to explore the seasonal dynamics of the debris-covered Dagongba Glacier within the southeastern Tibetan Plateau. We use the multitemporal unoccupied aerial vehicle images collected over the lower ablation zone on 8 June and 17 October 2018, and 13 May 2019, and then perform an analysis concerning climatic fluctuations. The results reveal that the mean surface elevation decrease of the Dagongba Glacier during the warm season ($2.81\pm 0.44$ m) was remarkably higher than the cold season ($0.72\pm 0.45$ m). Particularly notable glacier surface elevation changes were found around supraglacial lakes and ice cliffs where ice ablation rates were $\sim$ 3 times higher than the average. In addition, a larger longitudinal decline of glacier surface velocity was observed in the warm season than that in the cold season. In terms of further comparative analysis, the Dagongba Glacier experienced a decrease in surface velocity between 1982–83 and 2018–19, with a decrease in the warm season possibly twice as large as that in the cold season. [ABSTRACT FROM AUTHOR]

Recent climate and environment over the Tibetan Plateau (TP) have undergone significant changes, dominated by variations in the Westerlies and the Indian summer monsoon. However, long‐term shifts in atmospheric circulation during the transitional seasons are still lacking. Here we investigate the modern distribution of Tsuga pollen over the central‐western TP and confirm it as an indicator of variable atmospheric circulation in spring. By combining our Tsuga record from Taro Co with existing records in the Tsuga pollen source area, we suggest that a potential particle transport pathway from the southern slope of the Himalayas to the interior of the plateau appeared in the spring of the late Holocene. Our results show that the springtime atmospheric circulation over the southwestern TP during the early and late Holocene is closely related to the substantial remnants of ice sheets at northern high latitudes and the frequency of El Niño events, respectively. Plain Language Summary: The spring climate over the Tibetan Plateau (TP) is undergoing significant changes that yield profound impacts on environmental changes such as variations in vegetation phenology and alpine treeline. Knowledge of long‐term variations in atmospheric circulation during spring can improve the understanding of current climatic and environmental change and the projection of future variability. In this paper, we use an exotic pollen grain, which can be transported long distances in the air, as an indicator to trace the variability of spring atmospheric circulation over the TP. The results indicate that the spring meridional atmospheric circulation from the southern slope of the TP to its interior has been enhanced in the last four thousand years, which is mainly influenced by the frequency of El Niño events. Key Points: Spring atmospheric circulation change over the southwestern Tibetan Plateau (TP) during Holocene is reconstructedMeridional atmospheric circulation in spring over the southwestern TP is strengthened in the late HoloceneHigh‐(low‐) latitude forcing mainly influence the variations in spring atmospheric circulation during the early (late) Holocene [ABSTRACT FROM AUTHOR]

The growth history of the Tibetan Plateau provides a valuable natural laboratory to understand tectonic processes of the India–Asia collision and their impact on and interactions with Asian and global climate change. However, both Tibetan Plateau growth and Asian paleoenvironments are generally poorly documented in pre-Pliocene times and reflect limited temporal coverage for different parts of the plateau. In this paper, the 238 m thick Cenozoic sediments in the Hongzhuang section of the Xunhua Basin were tested and analyzed via paleomagnetic and environmental magnetic methods. The formation age was determined, and the evolution history of the regional climate environment was analyzed. The magnetostratigraphy study shows that the sediments record a continuous sequence of geomagnetic polarity changes from C5ACn to C10r, which spans an interval of approximately 30~14.3 Ma from the early Oligocene to the middle Miocene. The magnetic susceptibility of the Hongzhuang section is basically similar to the deep-sea oxygen isotope fluctuation, indicating that the monsoon climate change indicated by the magnetic susceptibility is affected by global temperature. It is worth noting that at ~27 Ma and ~15 Ma, there is a negative correlation between magnetic susceptibility and deep-sea oxygen isotope, and magnetic susceptibility lags behind the increase in deep-sea oxygen isotope. Combined with the change in the sedimentary rate curve, we explain the asynchrony between the magnetic susceptibility and the deep-sea oxygen isotope around ~27 Ma and ~15 Ma. As the uplift of the plateau leads to the enhancement of the East Asian summer monsoon, the soil formation in the region is strengthened, resulting in an increase in magnetic susceptibility. At the same time, the rapid uplift of the plateau caused the erosion of the surrounding mountains to strengthen, and the input of near-source materials may promote the increase in magnetic susceptibility. [ABSTRACT FROM AUTHOR]

Areal changes in alpine lakes on the Tibetan Plateau (TP) are reliable indicators of climate change and anthropogenic disturbance. This study used long-term Landsat images and meteorological records to monitor the temporal evolution patterns of lakes within the Changtang National Nature Reserve between 1972 and 2021 and examine the climatic and anthropogenic impacts on lake area changes. The results revealed that the area of Lake LongmuCo and Lake Jiezechaqia significantly expanded by 12.81% and 12.88% from 1972 to 2021, respectively. After 1999, Lake LongmuCo and Lake Jiezechaqia entered into a period of rapid expansion. During 1972–2021, the annual mean temperature significantly increased at a rate of 0.05 °C/a, while the change in annual precipitation was not significant. The temperature change was a major contributor to the observed changes of Lake LongmuCo and Lake Jiezechaqia between 1972 and 2021, while human intervention also played a vital role during 2013–2021. The glaciers around these two lakes decreased by 21.81%, and the increase in water supply from warming-triggered glacier melting was a reason of expansion of Lake LongmuCo and Lake Jiezechaqia. The areas of the two artificial salt lakes affiliated with Lake LongmuCo and Lake Jiezechaqia were 0.24 km2 and 2.67 km2 in 2013 and rose to 0.51 km2 and 9.80 km2 in 2021, respectively. In particular, the continuous exploitations of salt lakes to extract lithium resources have retarded the rate of expansion of Lake LongmuCo and Lake Jiezechaqia. The dams constructed by industrial enterprises have blocked the expansion of Lake LongmuCo to the south. This paper sheds new light on the influences of recent human intervention and climatic variation on alpine lakes within the TP. Due to the importance of alpine lakes in the TP, we need more comprehensive and in-depth efforts to protect the lake ecosystems within the national nature reserves. [ABSTRACT FROM AUTHOR]

The unique characteristics of land–air coupling and troposphere–stratosphere interaction over the Tibetan Plateau (TP), the highest landform in the world, play a vital role in weather and climate on regional and global scales. Although a great deal of research has been carried out, large gaps remain in our understanding of TP land–air coupling and its climate effects, due to a lack of observations and the issue of model biases. To address these obstacles, a 10-yr national research program entitled "Changes in the Land–Air Coupled System over the Tibetan Plateau and its Impacts on Global Climate (LASTPIC)" was launched by the National Natural Science Foundation of China in January 2014. What LASTPIC does revolves around three aspects: TP land–air coupled processes; TP's influence on global climate; and reanalysis and model. This paper mainly focuses on the data collection, scientific understanding, and model development of LASTPIC in terms of TP land–atmosphere–ocean coupling and its global climate impacts since program's inception. [ABSTRACT FROM AUTHOR]

LST (Land Surface Temperature) is a significant parameter that represents the ground energy balance and plays a crucial role in understanding climate change. The LST of the Tibetan Plateau (TP) has a direct influence on the climate and environmental changes of the TP, and it also has a significant impact on global climate and atmospheric circulation. Although there are various factors that drive the spatial and temporal distribution of LST on the TP, the primary driving forces and its seasonal variations of LST are not yet well understood. The research focuses specifically on the TP region, selecting three types of LST data, using geodetector model, to analyze the driving factors affecting the spatial pattern of LST in different seasons. The results indicate that the three factors, Air Temperature (AT), Elevation (Ele), and Permafrost Thermal Stability (PTS), have a significant influence on LST throughout all seasons, whereas other variables demonstrate varying contributions to LST depending on the season. This study contributes to the understanding of the spatial variability of surface thermal conditions and the intricate relationships between their driving factors. It also emphasizes the potential changes in these relationships throughout the year. [ABSTRACT FROM AUTHOR]

Alpine glaciers are vulnerable to climate changes, and their recession due to warming has already induced a large number of geohazards closely related to the glacial motion, such as debris flow. Strong coupling of the geology, geomorphology, climate, and glacial action controls the type, size, development, and frequency of debris flow along the Parlung Zangbo River, Southeastern (SE) Tibetan Plateau. Field investigation in recent years indicates that the north bank is prone to much more frequenter debris flows than the south bank. The sharp contrast between the two river banks is due to the different formation conditions of debris flows, especially glaciers and geomorphology. The present paper examines the differences in the glacier and geomorphology conditions for glacier-related debris flows to occur, through a combination of field investigation, interviews with local residents, and geomorphological parameter, and glacier distribution analysis in the ArcGIS platform. The result indicates that, compared to the south bank of the Parlung River, the north bank has more favorable conditions in the glacier and geomorphology south, which is more conducive to the occurrence of debris flow. In conclusion, three kinds of mechanisms due to different formation conditions, especially glacier and geomorphology, are analyzed. The glacier-related debris flows on the south and north banks occur through different mechanisms due to different formation conditions. The debris flows on the north bank primarily occur in modes I and III, while the south bank is dominated by modes II and III debris flows. Based on the result, effective measures are proposed for mitigating damage to roads and railways within this area. [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]

Climate change is expected to affect plant communities worldwide. However, less is known about the consequences of global warming-induced decrease of soil moisture on alpine wetland ecosystem in the Qinghai-Tibetan Plateau. To determine response of natural alpine wetland community to decrease of soil moisture, we did a gradient analysis of soil moisture by sequence space-series variation. We used sequence space-series variation of soil moisture to reflect potential time-series variation of soil moisture in alpine wetland community, by examining the effects of spatial heterogeneity of soil moisture on wetland community, as well as by determining how shifts in above- and below-ground properties of alpine wetland community. We found that vegetation aboveground biomass, cover and height all significantly increased with increase of soil moisture, but species richness was decreased. Soil organic carbon, total nitrogen, available nitrogen, total phosphorus and available phosphorus all significantly increased with increase of soil moisture, but soil pH value, total potassium and available potassium were significantly decreased. Meanwhile, species richness showed significantly positive correlations to aboveground biomass, covers and height. Aboveground biomass, vegetation covers and height were all significant positively related to soil organic carbon, total N, P, and available N, P, but negatively related to total K. But, species richness were significant negatively related to soil organic carbon, total N, P, and available N, P, but positively related to total K. Our observation indicates that decreasing of soil moisture may potentially negatively impact on the above- and below-ground properties in alpine wetland community. [ABSTRACT FROM AUTHOR]

Over the past 50 years, temperatures on the Qinghai-Tibet Plateau (QTP) have risen roughly twice as fast as the global average, making it the most unpredictable region of environmental change due to global warming. In this paper, an Environmental Area Index model was developed using data from the Coupled Model Intercomparison Project to assess the ecological risk faced by QTP ecosystems under the influence of climate factors. The results show that ecological risk gradually decreases from northwest to the southeast, and there are different trends in ecological risk for each class in areas with different elevation gradients. As elevation increased, the proportion of potential risk areas gradually decreased, and the proportion of high- and higher-risk areas gradually increased. We predict that in the period 2021–2100, the overall ecological risk change trend on the QTP will not be obvious, but there will be a more obvious change on the vertical gradient. In general, under the existing global climate change scenario, the ecological risk faced by the QTP show a decreasing trend under the influence of climate factors, and the decrease in ecological risks is much higher at higher elevations than at lower elevations. [ABSTRACT FROM AUTHOR]

The westerly jet (WJ) is an important component of atmospheric circulation, which is characterized by prominent seasonal variations in intensity and position. However, the response of the WJ over Asia during the Last Glacial Maximum (LGM) is still not clear. Using general circulation model experiments, the seasonal behaviors of the WJ over central Asia and Japan are analyzed in this paper. The results show that, compared to the present day (PD), the WJ presents a complicated response during the LGM, both in intensity and position. Over central Asia, it becomes weaker in both summer and winter. But over Japan, it is enhanced in summer but becomes diminished in winter. In terms of position, the WJ over central Asia shifts southward in both summer and winter, whereas the WJ over Japan moves southward in summer but does not change obviously relative to PD in winter. Such WJ changes are well explained by meridional temperature gradients in high troposphere, which is closely linked to seasonal thermal anomalies over the Tibetan Plateau (TP). Despite cooler LGM conditions, the anomalous warming center over the TP becomes stronger in summer. Derived from the heat budget equation, the stronger heating center is mainly caused by the weaker adiabatic cooling generated from ascending motion over the area south of the TP. In winter, the cooling over the TP is also strengthened, mostly owing to the subsidence-induced weaker adiabatic heating. Due to the importance of the WJ, the potential role of TP thermal effects should be a focus when explaining the East Asian climate change during the LGM. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau is situated in one of Earth's extreme continental climate settings and is influenced by numerous climatic regimes such as the East Asian and Indian monsoons and westerlies. It is the largest region of the world where permafrost is present at mid-latitudes and its relative warmth and shallow thickness makes it more sensitive to climatic warming than the arctic region. Changes in permafrost temperature, extent and active layer thickness have been observed for decades. In this paper we review these changes in this dynamic permafrost region, especially noting the changes in permafrost distribution and area loss of about 99,000 km2 per decade, increases in active layer thickness of 4-8 cm/year, and increases in thawing days of about 10-16 days/decade. As soil temperature and soil water content have changed, river run-off has decreased over most of the year. Warmer temperatures may have transformed the Tibetan Plateau from a net carbon source in the 20th century to a net sink as the increase rate of net primary production is faster than that of soil respiration. [ABSTRACT FROM AUTHOR]

South Asian air pollutants exert substantial effect on the climate and environment change over the Tibetan Plateau (TP). This paper investigates the trans-boundary transport of PM 10 , PM 2.5 , and O 3 from South Asia to the TP via WRF-Chem sensitive analysis. It is found that PM 10 , PM 2.5 , and O 3 over South Asia are mainly sourced from anthropogenic sources. South Asian emissions contribute up to 54% of PM 10 (PM 2.5) in the TP in the pre-monsoon season. For O 3 , the highest contribution of 18.13% is in the monsoon season, while the lowest contribution of 8.67% is in the winter season. To evaluate the respective contributions of anthropogenic and biomass burning emissions in South Asia to PM 10 , PM 2.5 , and O 3 in the TP, anthropogenic and biomass burning emissions in South Asia are considered separately. The results show that the largest percentage contribution of PM 10 (PM 2.5) from South Asian anthropogenic emissions to PM 10 (PM 2.5) in the TP with value of 35.86% (37.77%) occurs in winter, while the lowest percentage contribution of 16.52% (16.77%) appears in the monsoon season. For O 3 , the largest contribution of 17.74% from South Asian anthropogenic emissions appears in the monsoon season, whereas the lowest contribution of 8.59% occurs in winter. Compared to the anthropogenic emissions, the biomass burning emissions in South Asia have a relative less contribution to PM 10 , PM 2.5 , and O 3 in the TP. The largest contribution of PM 10 (PM 2.5) from South Asian biomass burning emissions to PM 10 (PM 2.5) in the TP is 20.04% (18.37%) in the pre-monsoon season. Conversely, the lowest contribution of 0.58% (0.53) appears in the monsoon season. O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the TP in each season, implying that the biomass burning emissions in South Asia have little effect on O 3 in the TP. This study is of great significance to the ecological environment protection for the TP. • Contributions of South Asian emissions to PM 10 , PM 2.5 , and O 3 in the TP are quantified. • Anthropogenic emissions in South Asia have a larger contribution to PM 10 , PM 2.5 , and O 3 in the TP. • O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The collapse of glacial, permafrost, and ice-rich moraine slopes in high-altitude mountainous areas not only threatens downstream residents and infrastructure but also displaces ice mass to lower and warmer elevations, accelerating glacial ablation to some extent. Despite being considered rare, ice-rich slopes collapse more frequently than commonly thought due to climate change. For example, two adjacent mountain glaciers in the Aru Range of the Tibetan Plateau, characterized by large volumes (68 × 106 m3 and 83 × 106 m3, respectively) and low surface slope angles (12.3° and 12.9°, respectively), collapsed surprisingly in 2016. While the mechanisms behind these collapses have garnered broad attention, the ability to quantitatively assess the instability of ice-rich slopes remains limited due to the complex interplay of multi-physical processes. Taking the Aru glacier collapses as reference cases, this paper presents a conceptual model, implemented through coupled thermo-hydro-mechanical simulation, to evaluate the stability of high-altitude ice-rich slopes due to climate change, rainfall and ice ablation. Results indicate that the methodology captures the effects of temperature change, rainfall and meltwater on the instability events well, demonstrating promising potential in evaluating potential collapse zones of ice-rich slopes similar to the Aru glaciers. Furthermore, the role of climate change in the well-known Aru events is demonstrated using a state-of-the-art global climate reanalysis dataset. Findings reveal that the increase in liquid water infiltrating the Aru glaciers since 2010 was a critical factor leading to the instability events. • A conceptual model is proposed to analyse the stability and collapse zones of ice-rich slopes. • The modelling elucidates the causes of twin collapses of the Aru glaciers. • Results contribute to ice-rich slope instability prediction and associated disaster risk management. [ABSTRACT FROM AUTHOR]

Extreme heatwaves pose a significant threat to a wide range of environmental, ecological, and social systems. The rapid warming of the Arctic and the Tibetan Plateau (TP), which are the most prominent features in the Northern Hemisphere in the context of climate change, has significantly influenced mid-latitude extreme events in recent decades. This study utilizes observational data and numerical simulations to demonstrate that the variations in Arctic amplification (AA) and TP amplification (TA) play a crucial role in the interannual variability of summer heatwaves (HWs) in the Yangtze River Basin (YRB) (HWs_YRB) region. The HWs_YRB is associated with a zonally oriented barotropic high-pressure system anchored over the YRB region. The spatial distribution and intensity of the HWs_YRB are impacted by the synergistic effects of AA and TA, via a meridional atmospheric tripole pattern and double jets over East Asia. Furthermore, AA primarily impacts the geographical extent of the HWs_YRB, while TA plays a critical role in determining the intensity of the HWs_YRB. Our findings provide an innovative perspective on the linkage between the pronounced warming observed in the Arctic and TP and the occurrence of summer HWs_YRB, enhancing our comprehension of the climatic consequences of the rapid changes in these two geographical 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 climate of the Tibetan Plateau (TP) has experienced substantial changes in recent decades as a result of the location's susceptibility to global climate change. The changes observed across the TP are closely associated with regional land–atmosphere interactions. Current models and satellites struggle to accurately depict the interactions; therefore, critical field observations on land–atmosphere interactions outlined here provide necessary independent validation data and fine-scale process insights for constraining reanalysis products, remote sensing retrievals, and land surface model parameterizations. Scientific data sharing is crucial for the TP since in situ observations are rarely available under these harsh conditions. However, field observations are currently dispersed among individuals or groups and have not yet been integrated for comprehensive analysis. This has prevented a better understanding of the interactions, the unprecedented changes they generate, and the substantial ecological and environmental consequences they bring about. In this study, we collaborated with different agencies and organizations to present a comprehensive dataset for hourly measurements of surface energy balance components, soil hydrothermal properties, and near-surface micrometeorological conditions spanning up to 17 years (2005–2021). This dataset, derived from 12 field stations covering a variety of typical TP landscapes, provides the most extensive in situ observation data available for studying land–atmosphere interactions on the TP to date in terms of both spatial coverage and duration. Three categories of observations are provided in this dataset: meteorological gradient data (met), soil hydrothermal data (soil), and turbulent flux data (flux). To assure data quality, a set of rigorous data-processing and quality control procedures are implemented for all observation elements (e.g., wind speed and direction at different height) in this dataset. The operational workflow and procedures are individually tailored to the varied types of elements at each station, including automated error screening, manual inspection, diagnostic checking, adjustments, and quality flagging. The hourly raw data series; the quality-assured data; and supplementary information, including data integrity and the percentage of correct data on a monthly scale, are provided via the National Tibetan Plateau Data Center (10.11888/Atmos.tpdc.300977, Ma et al., 2023a). With the greatest number of stations covered, the fullest collection of meteorological elements, and the longest duration of observations and recordings to date, this dataset is the most extensive hourly land–atmosphere interaction observation dataset for the TP. It will serve as the benchmark for evaluating and refining land surface models, reanalysis products, and remote sensing retrievals, as well as for characterizing fine-scale land–atmosphere interaction processes of the TP and underlying influence mechanisms. [ABSTRACT FROM AUTHOR]

As a feature of global warming, climate change has been a severe issue in the 21st century. A more comprehensive reconstruction is necessary in the climate assessment process, considering the heterogeneity of climate change scenarios across various meteorological elements and seasons. To better comprehend the change in minimum temperature in winter in the Jinsha River Basin (China), we built a standard tree-ring chronology from Picea likiangensis var. balfouri and reconstructed the regional mean minimum temperature of the winter half-years from 1606 to 2016. This reconstruction provides a comprehensive overview of the changes in winter temperature over multiple centuries. During the last 411 years, the regional climate has undergone seven warm periods and six cold periods. The reconstructed temperature sensitively captures the climate warming that emerged at the end of the 20th century. Surprisingly, during 1650–1750, the lowest winter temperature within the research area was about 0.44 °C higher than that in the 20th century, which differs significantly from the concept of the "cooler" Little Ice Age during this period. This result is validated by the temperature results reconstructed from other tree-ring data from nearby areas, confirming the credibility of the reconstruction. The Ensemble Empirical Mode Decomposition method (EEMD) was adopted to decompose the reconstructed sequence into oscillations of different frequency domains. The decomposition results indicate that the temperature variations in this region exhibit significant periodic changes with quasi-3a, quasi-7a, 15.5-16.8a, 29.4-32.9a, and quasi-82a cycles. Factors like El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and solar activity, along with Atlantic Multidecadal Oscillation (AMO), may be important driving forces. To reconstruct this climate, this study integrates the results of three machine learning algorithms and traditional linear regression methods. This novel reconstruction method can provide valuable insights for related research endeavors. Furthermore, other global climate change scenarios can be explored through additional proxy reconstructions. [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]

The variations in snow cover on the Tibetan Plateau play a pivotal role in comprehending climate change patterns and governing hydrological processes within the region. This study leverages daily snow cover data and the NASA Digital Elevation Model (DEM) from 2003 to 2020 to analyze spatiotemporal snow cover days and assess their responsiveness to climatic shifts by integrating meteorological data. The results reveal significant spatial heterogeneity in snow cover across the Plateau, with a slight decreasing trend in annual average snow cover duration. Snow cover is predominantly observed during the spring and winter seasons, constituting approximately 32% of the total snow cover days annually. The onset and cessation of snow cover occur within a range of 120–220 days. Additionally, an increasing trend in snow cover duration below 5000 m altitude was observed, in addition to a decreasing trend above 5000 m altitude. Sub-basin analysis delineates the Tarim River Basin as exhibiting the lengthiest average annual snow cover duration of 83 days, while the Yellow River Basin records the shortest duration of 31 days. The decreasing trend in snow cover duration closely aligns with climate warming trends, characterized by a warming rate of 0.17 ± 0.54 °C per decade, coupled with a concurrent increase in precipitation at a rate of 3.09 ± 3.81 mm per year. Temperature exerts a more pronounced influence on annual snow cover duration variation compared to precipitation, as evidenced by a strong negative correlation (CC = −0.67). This study significantly augments the comprehension of hydrological cycle dynamics on the Tibetan Plateau, furnishing essential insights for informed decision-making in water resource management and ecological conservation efforts. [ABSTRACT FROM AUTHOR]

The Net Primary Productivity (NPP) of the Tibetan Plateau (TP) has undergone significant changes since the 1980s. The investigation of the spatiotemporal changes of NPP and its driving factors is of significant importance. Here, we analyze the spatial and temporal trends of Net Primary Production (NPP) and the effects of meteorological factors on the NPP change on the Tibetan Plateau (TP) using version 5.0 of the Community Land Model. The results showed that the average NPP was 256 (g C·m2·yr−1) over the past 40 years, with a continuously increasing trend of 2.38 (g C·m2·yr−1). Precipitation was the main factor affecting NPP changes, temperature had no significant effect on NPP changes, while radiation showed a negative trend. Changes in precipitation, temperature and radiation account for approximately 91%, 5.3%, and 3.8% of NPP variation, respectively. Based on grass coverage, we categorized alpine grasslands into three types: high, medium, and low coverage. Our findings indicate the NPP change of the high-coverage grasslands was mainly affected by precipitation, and then the temperature and radiation. Comparatively, the precipitation change is the driving factor of the increased NPP of low-coverage grasslands, but the temperature increase is the negative factor. Our studies have implications for assessing and predicting vegetation responses to future climate change. [ABSTRACT FROM AUTHOR]

The alpine grassland ecosystem accounts for 53% of the Qinghai-Tibet Plateau (QTP) area, which is an important ecological protection barrier, but fragile and highly vulnerable to climate change. Therefore, continuous monitoring of the aboveground biomass (AGB) of grassland is necessary. Although many studies have mapped the spatial distribution of AGB over the QTP, the results vary widely due to the limited ground samples and mismatches with satellite pixel scales. This paper proposed a new algorithm using unmanned aerial vehicles (UAVs) as a bridge to re-estimate the grassland AGB over 20 the QTP from 2000 to 2019. The innovations were as follows: 1) In the aspect of ground data collection, the spatial scale matching among the traditional ground quadrat sampling, UAV photos, and MODIS pixels was fully considered. From 2015 to 2019, 906 pairs of ground-UAV sample data at the quadrat scale and 2,602 sets of UAV data matching the MODIS pixel scale were collected. A total of more than 37,000 UAV photos were captured at the height of 20 meters. Therefore, the ground validation samples was sufficient and scale matched. 2) In terms of model construction, the traditional quadrat scale 25 (0.25m2) was successfully upscaled to the MODIS pixel scale (6,2500 m2) based on the random forest method and stepwise upscaling scheme. Compared with previous studies, the scale matching of independent and dependent variables was realized, effectively reducing the impact of scale mismatch. At the pixel scale, the AGB value estimated by UAV had a more linear correlation with the MODIS vegetation indices than the traditional sampling method. The multi-year independent crossvalidation results showed that the constructed pixel scale AGB estimation had good robustness, with an average R2 of 0.83 30 and RMSE of 34.13 g/m2. Our dataset provides an important input parameter for a comprehensive understanding of the QTP in the process of global climate change. [ABSTRACT FROM AUTHOR]

Highlights • We divided the households in the YNL river region into three types. • We identified the determinants affecting the livelihood choice of sample households. • We made some policy recommendations to help the local people get rid of poverty. Abstract Governmental policies that can develop advantageous endogenous livelihood transition are of great importance for anti-poverty. However, the existing research finds that in the Tibetan Plateau, there is a certain contradiction between the poverty alleviation policies and the local farmers' needs, and thus the effect of these policies will be weakened and the goal of poverty alleviation be missed. It is therefore imperative to identify and analyze the factors influencing the livelihood choice so that policy makers and development practitioners can design policies that will tackle the poverty afflicting the majority of the local people. This paper provides a new method for anti-poverty policymaking and conducts a case study to enrich the safety net/cargo net paradigms. In this paper, household data in the YNL river region are used and a two-step clustering method is developed to classify these households into three types: hanging in (type I), stepping up (type II) and stepping out (type III). Then a multinomial logit model is adopted to identify determinants of households' livelihood choice. The results indicate that drought poses a significant negative impact on farmers' choice of type II, while household size, educational level of labor and medical expenditure have a significant positive impact on the choice of type II; spring frost, proportion of skilled training, borrowed money and the ratio of agricultural equipment have a significant positive impact on their choice of type III. Some anti-poverty policy implications are put forward in the last on the basis of these determinants. [ABSTRACT FROM AUTHOR]

Global climate change has significantly affected vegetation variation in the third-polar region of the world - the Qinghai-Tibet Plateau. As one of the most important indicators of vegetation variation (growth, coverage and tempo-spatial change), the Normalized Difference Vegetation Index (NDVI) is widely employed to study the response of vegetation to climate change. However, a long-term series analysis cannot be achieved because a single data source is constrained by time sequence. Therefore, a new framework was presented in this paper to extend the product series of monthly NDVI, taking as an example the Yarlung Zangbo River Basin, one of the most important river basins in the Qinghai-Tibet Plateau. NDVI products were acquired from two public sources: Global Inventory Modeling and Mapping Studies (GIMMS) Advanced Very High Resolution Radiometer (AVHRR) and Moderate-Resolution Imaging spectroradiometer (MODIS). After having been extended using the new framework, the new time series of NDVI covers a 384 months period (1982-2013), 84 months longer than previous time series of NDVI product, greatly facilitating NDVI related scientific research. In the new framework, the Gauss Filtering Method was employed to filter out noise in the NDVI product. Next, the standard method was introduced to enhance the comparability of the two data sources, and a pixelbased regression method was used to construct NDVI-extending models with one pixel after another. The extended series of NDVI fit well with original AVHRR-NDVI. With the extended time-series, temporal trends and spatial heterogeneity of NDVI in the study area were studied. Principal influencing factors on NDVI were further determined. The monthly NDVI is highly correlated with air temperature and precipitation in terms of climatic change wherein the spatially averaged NDVI slightly increases in the summer and has increased in temperature and decreased in precipitation in the 32 years period. The spatial heterogeneity of NDVI is in accordance with the seasonal variation of the two climate-change factors. All of these findings can provide valuable scientific support for water-land resources exploration in the third-polar region of the world. [ABSTRACT FROM AUTHOR]

Climate change inevitably affects vegetation growth in the Tibetan Plateau (TP). Understanding the dynamics of vegetation phenology and the responses of vegetation phenology to climate change are crucial for evaluating the impacts of climate change on terrestrial ecosystems. Despite many relevant studies conducted in the past, there still remain research gaps concerning the dominant factors that induce changes in the start date of the vegetation growing season (SOS). In this study, the spatial and temporal variations of the SOS were investigated by using a long-term series of the Normalized Difference Vegetation Index (NDVI) spanning from 2001 to 2020, and the response of the SOS to climate change and the predominant climatic factors (air temperature, LST or precipitation) affecting the SOS were explored. The main findings were as follows: the annual mean SOS concentrated on 100 DOY–170 DOY (day of a year), with a delay from east to west. Although the SOS across the entire region exhibited an advancing trend at a rate of 0.261 days/year, there were notable differences in the advancement trends of SOS among different vegetation types. In contrast to the current advancing SOS, the trend of future SOS changes shows a delayed trend. For the impacts of climate change on the SOS, winter Tmax (maximum temperature) played the dominant role in the temporal shifting of spring phenology across the TP, and its effect on SOS was negative, meaning that an increase in winter Tmax led to an earlier SOS. Considering the different conditions required for the growth of various types of vegetation, the leading factor was different for the four vegetation types. This study contributes to the understanding of the mechanism of SOS variation in the TP. [ABSTRACT FROM AUTHOR]

A detailed understanding of snow cover and its possible feedback on climate change on the Tibetan Plateau (TP) is of great importance. However, spatiotemporal variability in snow phenology (SP) and its influencing factors on the TP remain unclear. Based on the daily gap-free snow cover product (HMRFS-TP) with 500 m resolution, this study investigated the spatiotemporal variability in snow cover days (SCDs), snow onset date (SOD), and snow end date (SED) on the TP from 2002 to 2022. A structural equation model was used to quantify the direct and indirect effects of meteorological factors, geographical location, topography, and vegetation greenness on SP. The results indicate that the spatial distribution of SP on the TP was extremely uneven and exhibited temporal heterogeneity. SP showed vertical zonality influenced by elevation (longer SCD, earlier SOD, and later SED at higher elevations). A total of 4.62 % of the TP area had a significant decrease in SCDs, at a rate of -1.74 d yr -1. The SOD of 2.34 % of the TP area showed a significant delayed trend, at a rate of 2.90 d yr -1 , while the SED of 1.52 % of the TP area had a significant advanced trend, at a rate of at -2.49 d yr -1. We also found a strong elevation dependence for the trend in SCDs (R=-0.73). Air temperature, precipitation, wind speed, and shortwave radiation can directly affect SP as well as indirectly affect it by influencing the growth of vegetation, whereas the direct effect was much greater than the indirect effect. Geographical location (latitude and longitude) and topographic conditions (elevation and slope) indirectly affected SP by modulating meteorological conditions and the growth of vegetation. Vegetation primarily influences SP by intercepting the snow and regulating the balance of the solar radiation budget. Regarding the total effect, air temperature was found to be the dominant factor. This study contributes to the understanding of snow variation in response to global warming over the past 2 decades by providing a basis for predicting future environmental and climate changes and their impacts on the TP. [ABSTRACT FROM AUTHOR]

In recent decades, glaciers in the southeastern Tibetan Plateau (SETP) have been rapidly melting and showing a large scale of glacier mass loss. Due to the lack of large-scale, high-resolution, and high-precision observations, knowledge on the spatial distribution of the glacier mass balance and the response to climate change is limited in this region. We propose a TanDEM-X bi-static InSAR (Interferometric Synthetic Aperture Radar) algorithm with a non-local mean filter method and difference strategy, to improve the precision of glacier surface elevation change detection. Moreover, we improved the glacier mass balance estimation algorithm with a correction method for multi-source system errors and an uncertainty evaluation method based on error propagation theory to reduce the uncertainty of estimations. We used 13 pairs of TanDEM-X bi-static InSAR images to obtain the glacier mass balance data for the entire SETP. The total area of glaciers monitored was 5821 km2 and the total number of glaciers monitored was 2321; the glacier surface elevation change rate was −0.505 ± 0.005 m/yr, and the glacier mass balance estimation was −454.5 ± 13.1 mm w.eq. during 2000–2014. Additionally, we analyzed the spatial distribution of the glacier mass balance within the SETP using the sub-watershed analysis method. The results showed that the mass loss rate had a decreasing trend from the southeast to the northwest. Furthermore, the temperature change and the glacier mass loss rate showed a positive correlation from the southeast to the northwest in this region. This study greatly advances our understanding of the regularities of glacier dynamics in this region, and can provide scientific support for major national goals such as the rational utilization of surrounding water resources and construction of important transportation projects. [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 Qinghai-Tibet Plateau is now experiencing ecological degradation risks as a result of climate change and human activities. The alpine grassland ecology in permafrost zones is fragile and susceptible to deterioration due to its high altitude, low temperature, and limited oxygen, which complicates the repair of damaged land. Biological soil crusts (BSCs) are crucial for land restoration in plateau regions because they can thrive in harsh conditions and have environmentally beneficial traits. Inoculated biological soil crust (IBSC) has shown success in low-altitude desert regions, but may not be easily duplicated to the plateau environment. Therefore, it is essential to do a comprehensive and multifaceted analysis of the basic theoretical comprehension and practical application of BSCs on the Tibetan Plateau. This review article aims to provide a brief summary of the ecological significance and the mechanisms related to the creation, growth, and progression of BSCs. It discusses the techniques used for cultivating BSCs in laboratories and using them in the field, focusing on the Qinghai-Tibet Plateau circumstance. We thoroughly discussed the potential and the required paths for further studies. This study may be used as a basis for selecting suitable microbial strains and accompanying supplemental actions for implementing IBSCs in the Qinghai-Tibet Plateau. [ABSTRACT FROM AUTHOR]

The major rivers on the Tibetan Plateau supply important freshwater resources to riparian regions but have been undergoing significant climate change in recent decades. Understanding the sensitivities of hydrological processes to climate change is important for water resource management, but large divergences exist in previous studies because of the uncertainties of hydrological models and climate projection data. Meanwhile, the spatial pattern of local hydrological sensitivities was poorly explored despite the strong heterogeneity on the Tibetan Plateau. This study adopted the climate perturbation method to analyze the hydrological sensitivities of a typical large mountainous basin (Yarlung Tsangpo River, YTR) to climate change. We utilized the tracer-aided hydrological model Tsinghua Representative Elementary Watershed-Tracer-aided version (THREW-T) to simulate the hydrological and cryospheric processes in the YTR basin. Multiple datasets and internal stations were used to validate the model to provide confidence in the baseline simulation and the sensitivity analysis. Results indicated that (1) the THREW-T model performed well in simulating the streamflow, snow cover area (SCA), glacier mass balance (GMB) and stream water isotope, ensuring good representation of the key cryospheric processes and a reasonable estimation of the runoff components. The model performed acceptably in simulating the streamflow at eight internal stations located in the mainstream and two major tributaries, indicating that the spatial pattern of hydrological processes was reflected by the model. (2) Increasing temperature led to decreasing annual runoff, smaller inter-annual variation, more even intra-annual distribution and an earlier maximum runoff. It also influenced the runoff regime by increasing the contributions of rainfall and glacier melt overland runoff but decreasing the subsurface runoff and snowmelt overland runoff. Increasing precipitation had the opposite effect to increasing temperature. (3) The local runoff change in response to increasing temperature varied significantly, with a changing rate of -18.6 % to 54.3 % for 5 ∘ of warming. The glacier area ratio (GAR) was the dominant factor in the spatial pattern of hydrological sensitivities to both perturbed temperature and precipitation. Some regions had a non-monotonic runoff change rate in response to climate perturbation, which represented the most dynamic regions within the basin, as they kept shifting between energy- and water-limited stages. The GAR and mean annual precipitation (MAP) of the non-monotonic regions had a linear relation and formed the boundary of regions with different runoff trends in the GAR–MAP plot. [ABSTRACT FROM AUTHOR]

Plant phenology is the most salient and sensitive indicator of terrestrial ecosystem response to climate change. Studying its change is significantly important in understanding and predicting impressively changes in terrestrial ecosystem. Based on NDVI from SPOT VGT, this paper analyzed the spatiotemporal changes in alpine grassland phenology in Qinghai-Tibetan Plateau from 1999 to 2009. The results are enumerated as follows: (1) The spatial distribution of the average alpine grassland phenology from 1999 to 2009 is closely related to water and heat conditions. Accompanying the deterioration in heat and water conditions from southeast to northwest, the start of growth season (SOG) was delayed gradually, the end of growth season (EOG) advanced slowly, and the length of growth season (LOG) shortened gradually. Elevation played an important role in the regional differentiation of phenology, but a dividing line of approximately 3500 m existed. Below this line, the phenology fluctuated irregularly with altitude change, whereas above the line, the phenology is closely related to altitude change. (2) From 1999 to 2009, SOG of the alpine grassland came earlier by six days per decade ( R=0.281, P=0.093), EOG was late by two days per decade ( R=0.031, P=0.605), and LOG lengthened by eight days per decade ( R=0.479, P=0.018). The early SOG, the late EOG, and the extended LOG mainly occurred at the center and east of the Plateau. SOG in most of the Plateau advanced significantly, especially in the eastern Plateau. (3) The inter-annual phenology changes of the alpine grassland in the Qinghai-Tibetan Plateau exhibited significant differentiation at different elevation and natural zones. The inter-annual changes at high altitude were more complicated than that at low altitude. The most significant phenology changes were found in the eastern Qinghai-Qilian montane steppe zone, and non-significant changes occurred in the Southern Tibet montane shrub-steppe zone. [ABSTRACT FROM AUTHOR]

The relationships amongst modern pollen assemblages, vegetation, climate and human activity are the basis for reconstructing palaeoenvironmental changes using pollen records. It is important to determine these relationships at regional scales due to the development of vegetation under different climatic conditions and human activities. In this paper, we report on an analysis of modern pollen assemblages of 31 surface lake samples from 31 lakes (one sample per lake) on the southwestern Tibetan Plateau where the knowledge of modern pollen and their relationships with vegetation, climate and human activities is insufficient. The region includes five vegetation zones: sub-alpine shrub steppe, alpine steppe, alpine meadow and steppe ecotone, mountain desert and alpine desert. The lakes span a wide range of mean annual precipitation (50-500 mm) and mean annual temperature (−8 to 6 °C). Modern pollen assemblages from our samples mainly consist of herb taxa ( Artemisia, Cyperaceae, Poaceae, Chenopodiaceae, etc.) and some tree taxa ( Pinus, Fagaceae, Alnus, etc.). The results indicate that modern pollen assemblages are able to reflect the main vegetation distribution. Redundancy analysis for the main pollen types and environmental variables shows that precipitation is the leading factor that influences the pollen distribution in the study area with the first axis capturing 13.7% of the variance in the pollen data set. The Artemisia/Chenopodiaceae ratio is valid for separating the desert component (<2) from the steppe and other vegetation zones (>2) but is unable to distinguish moisture variations. The Artemisia/Cyperaceae ratio is able to identify meadows (<1) and steppes (>1) and can be used as a moisture index on the southwestern Tibetan Plateau. Our results show that an appropriate range is needed for a modern pollen data set in order to perform pollen-based quantitative climate reconstructions in one region. It is essential to perform modern studies before using pollen ratios to reconstruct palaeovegetation and palaeoclimate at a regional scale. [ABSTRACT FROM AUTHOR]

Investigating the response of landslide activity to climate change is crucial for understanding the disastrous effects of climate change on high mountains. However, the lack of long-term, spatial-temporal consistent measurement of landslide activity prohibits the study of this relationship. In this work, we used two methods to derive the time series of a landslide's deformation and study its relationship with precipitation in the northeastern Tibetan Plateau. The small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) method with Sentinel-1A images is first applied to derive time series of the landslide's deformation from 2020 to 2021. A recently developed method to derive cumulative deformations of optical images was used with Landsat 5 and Sentinel-2 images to derive the long-term deformation time series from 1986 to 2023. Centimeter-scale deformations detected by using the InSAR method are mainly located in the upper and eastern parts of the landslide, whereas meter-scale deformations detected by using the optical method are in the middle of the landslide. Time-series results from both methods show that intra-annual initiations of the landslide's deformation occurred in rainy months (from July to October). Although there seems to be no direct relations between inter-annual deformations and precipitation, significant displacements since 2020 occurred after exceptionally wet years from 2018 (with a record-breaking precipitation year in 2020). With optical images, we found that the maximum cumulative deformation of the landslide has been >35 m since 1986 with major deformations (>20 m) found after 2020, which may indicate an imminent risk to the Lijie town near the toe of the landslide. With climate change, increased precipitation is expected in future, which may trigger more similar landslides in the vicinity of this region. This work demonstrates an executable framework to assess landslide hazard risk under climate change. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is the largest permafrost distribution zone at high‐altitude in the mid‐latitude region. Climate change has caused significant permafrost degradation on the TP, which has important impacts for the eco‐hydrological processes. In this study, the frost number is utilized to calculate the frost number (F) based on the air freezing/thawing index obtained from the downscaled Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets. A novel method is proposed to determine the frost number threshold (Ft) for diagnosing permafrost distribution. Then the simulated permafrost distribution maps are compared with the existing permafrost distribution map, employing the Kappa coefficient as the measure of classification accuracy to identify the optimal Ft. Finally, the permafrost distribution on the TP under different Shared Socio‐economic Pathways (SSP) scenarios are diagnosed with the optimal Ft. Simulation results demonstrate that across all scenarios, the rates of permafrost degradation during the mid‐future period (2040–2060) remain comparable to those observed in the baseline period (2000), ranging from 33% ± 3% to 53% ± 4%. Conversely, during the far‐future (2080–2099), the permafrost degradation rates display significant variation across different scenarios, ranging from 37% ± 4% to 96% ± 3%. The profound impacts of permafrost degradation on the TP are reflected in decreasing trends in soil moisture and runoff, as well as a slower increasing trend in Normalized Difference Vegetation Index (NDVI) compared to other regions, indicating negative impacts on vegetation growth. Plain Language Summary: The Tibetan Plateau, the highest plateau in the world and the largest high‐altitude permafrost region, is experiencing permafrost degradation due to climate change, significantly impacting eco‐hydrological processes in this region. In this study, we used the frost number model with air temperature to simulate the distribution of permafrost on the Tibetan Plateau under different scenarios. The results show that permafrost on the Tibetan Plateau is projected to degrade in the 21st century, especially under high‐emission scenarios. The degradation of permafrost will likely reduce soil moisture and runoff. Additionally, vegetation growth in areas with permafrost degradation is expected to be slow. These findings are of great significance for understanding permafrost changes on the Tibetan Plateau and their impacts on eco‐hydrological processes. Key Points: A new method using the frost number model with Kappa coefficient is proposed to diagnose permafrost distributionPermafrost on the Tibetan Plateau will experience the least degradation (33% ± 3%) under SSP126, and the most (96% ± 3%) under SSP585 in 2080–2099Permafrost degradation on the Tibetan Plateau is anticipated to reduce soil moisture and runoff, adversely affecting vegetation growth [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]

Three-River-Source (TRS) National Park stands as one of China's earliest established national parks, dedicated to significant ecological responsibilities that include conserving soil and water resources in the Tibetan Plateau region. Research on climate change's influence on the TRS region's grasslands is of great significance in our efforts to comprehend and conserve the grassland ecosystem. The most effective random forest (RF) model was chosen to invert the aboveground biomass (AGB) of grassland in the previous 6 years (2015-2020) and predict the grassland AGB in the following 20 years (2021-2040) by comparing linear regression and multivariate nonlinear regression models such as RF, support vector machine, decision tree, and artificial neural network. A Theil-Sen median trend analysis and a Mann-Kendal test were then used to examine the trends of grassland AGB. The results showed that (1) RF outperformed other models in estimating grassland AGB, with a test set decision coefficient of multiple determination (R²) of 0.722, a root mean square error of 42.596 g/m², and a mean absolute error of 35.619 g/m²; (2) over 6 years, the grassland AGB in TRS National Park had a spatial trend of a steady rise from the northwest to the southeast. The average annual grassland AGB was 247.333 g/m², with averages of 44.836 g/m² , 92.601 g/m² , and 120.217 g/m² in the Yangtze River, Yellow River, and Lancang River source parks respectively. The trend of the grassland AGB was primarily stabilized and slightly recovered, with a small portion of the slightly deteriorated areas; (3) climate change significantly affected grassland AGB, and when temperature and precipitation conditions were adequate, grassland AGB values increased with temperature and precipitation. In the scenarios of ssp119, ssp245, and ssp585, grassland AGB is projected to exhibit a dynamic upward trend over the next 20 years. Global warming is expected to boost grassland AGB. Comprehensive measures are essential to maintain grassland health and ensure a positive impact on global carbon and ecological balance. The study's findings hold great importance for the ecological security of the TRS region and contribute to our global understanding of sustainable grassland development. [ABSTRACT FROM AUTHOR]

Partitioning the contributions of climate, economic growth, and policy to a region's carbon flows is an important process for the Chinese government seeking to optimize their regional development policies to achieve carbon neutrality by 2060. A combination of the carbon emission analysis and human appropriation of net primary production (HANPP) framework was applied to a village in the Lhasa river valley, Tibet, to quantify the contributions of these different factors to carbon flows and neutrality. From 2010 to 2019, the average annual net sequestration of CO2 was 374.9 g CO2 m−2 a−1. Changes in climate conditions and the regional policy of Grassland Ecological Protection Subsidy and Reward increased carbon sequestrations by 409.5 and 25.7 g CO2 m−2 a−1, respectively. Socioeconomic development, policies for reducing poverty, and promotion of forage production led to the increase in CO2 emissions by 103.5, 88.8, and 4.3 g CO2 m−2 a−1, respectively. The cumulative CO2 emissions (including HANPP) caused by land use were 298.92 Tg CO2 (2479.63 g CO2 m−2; 1 Tg = 1012 g), while the cumulative CO2 emissions due to energy use were only 11.22 Tg CO2 (93.07 g CO2 m−2), equal to 3.75% of the CO2 emissions driven by land use. Livestock grazing and cropland cultivation were the two main land use factors affecting the carbon balance. We argue that unhooking economic growth from traditional nomadic animal husbandry and lifestyles through policy optimizations would highly contribute the carbon neutrality in Tibet. [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]

Previous studies have examined the projected climate types in China by 2100. This study identified the emergence time of climate shifts at a 1◦ scale over China from 1990 to 2100 and investigated the temporal evolution of Köppen-Geiger climate classifications computed from CMIP5 multi-model outputs. Climate shifts were detected in transition regions (7%-8% of China's land area) by 2010, including rapid replacement of mixed forest (Dwb) by deciduous forest (Dwa) over Northeast China, strong shrinkage of alpine climate type (ET) on the Tibetan Plateau, weak northward expansion of subtropical winterdry climate (Cwa) over Southeast China, and contraction of oceanic climate (Cwb) in Southwest China. Under all future RCP (Representative Concentration Pathway) scenarios, the reduction of Dwb in Northeast China and ET on the Tibetan Plateau was projected to accelerate substantially during 2010-30, and half of the total area occupied by ET in 1990 was projected to be redistributed by 2040. Under the most severe scenario (RCP8.5), sub-polar continental winter dry climate over Northeast China would disappear by 2040-50, ET on the Tibetan Plateau would disappear by 2070, and the climate types in 35.9% and 50.8% of China's land area would change by 2050 and 2100, respectively. The results presented in this paper indicate imperative impacts of anthropogenic climate change on China's ecoregions in future decades. [ABSTRACT FROM AUTHOR]

An ice core was extracted from the Zangser Kangri (ZK) ice field in the northern Tibetan Plateau (NTP), a location with limited instrumental and proxy records. In this paper, we present a continuous high–resolution dust concentration time series spanning the period AD 1951-2008 to investigate variations in atmospheric dust loading over the NTP. The results show that atmospheric dust loading exhibited significant decadal variations, with two periods of high dust loading (AD 1959–67 and AD 1979–89) and three periods of relatively low loading (AD 1951-58, AD 1968–78 and AD 1990–2008). The variability of atmospheric dust loading was related to wind speed at 500 hPa over the dust source regions. The winter Arctic Oscillation (AO) index showed a significant negative correlation with the annual dust concentration, implying a possible connection between the winter AO and the atmospheric dust loading over the NTP. [ABSTRACT FROM PUBLISHER]

In this paper, the thermal comfort and its changes in the Qinghai-Tibet Plateau over the last 50 years have been evaluated by using the physiological equivalent temperature (PET), and a more complete tourism climate picture is presented by the Climate-Tourism-Information Scheme (CTIS). The results show that PET classes in the Qinghai-Tibet Plateau cover six out of the nine-point thermal sensation scale - very cold, cold, cool, slightly cool, neutral and slightly warm - and cold stress is prevailing throughout the year. A small number of slightly cool/warm and neutral days occur in summer months. There occur no warm, hot and very hot days. The frequency of PET classes varies among regions, depending on their altitude/latitude conditions. Xining, Lhasa and Yushu are the top three cities in terms of thermal favorability. With global warming, annual cumulative number of thermally favorable days has been increasing, and that of cold stress has been reducing. The change is more obvious in lower elevation than that in higher elevation regions. The improving thermal comfort in the Qinghai-Tibet Plateau might be a glad tiding for local communities and tourists. Besides PET, CTIS can provide a number of additional bioclimatic information related to tourism and recreational activities. CTIS for Lhasa and Xining shows that sunshine is plentiful all the year round, and windy days occur frequently from late January to early May. This is a useful bioclimatic information for tourism authorities, travel agencies, resorts and tourists. [ABSTRACT FROM AUTHOR]

The high terrain of the Tibetan Plateau (TP) has a very important impact on the weather and climate of China, East Asia, South Asia, and even the Northern Hemisphere. However, in recent years, the reasons for the decrease in precipitation in the southeastern edge of the plateau have resulted in cutting-edge research regarding the impact of the TP and its surrounding areas on downstream weather and climate. In this study, the spatial and temporal distribution of surface heat flux and precipitation were analyzed from 1998 to 2022, and the possible mechanism of the decrease of precipitation in the eastern edge of the plateau is explored. The main conclusions are as follows: The annual average sensible heat flux in the TP and its east side is positive, with an average of 33.73 W/m². The annual average latent heat flux is positive, with an average of 42.71 W/m². Precipitation has a similar annual average and seasonal distribution, with modest amounts in the northwest and substantial amounts in the southeast. The average annual accumulated precipitation is 670.69 mm. The first mode of the Empirical Orthogonal Function (EOF) shows that sensible heat flux decreases first, then increases, and then finally decreases during 1998-2022. The modes show the opposite trend in middle part of the plateau. The latent heat flux initially decreases, then increases, and finally decreases in the western plateau and near Sichuan Basin. The mode, however, displays the opposite tendency throughout the rest of the region. The precipitation in the north and south sides of the plateau has decreased since 2013, which is consistent with the changing trend of sensible heat flux. In the rest of the region, the change trend is not obvious. The sensible heat of the main body of the plateau and its east side and Sichuan Basin is negatively correlated with precipitation, that is, when sensible heat flux of the main body of the plateau and its east side and Sichuan Basin is more (less), local precipitation is less (more). The latent heat of the main body of the plateau and its east side, Sichuan Basin is positively correlated with precipitation, indicating that when latent heat flux of the main body of the plateau and its east side, Sichuan Basin is more (less), local precipitation is more (less). [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]

The Three-Rivers Headwater Region (TRHR), located in the hinterland of the Tibetan Plateau, serves as the "Water Tower of China", providing vital water conservation (WC) services. Understanding the variations in WC is crucial for locally tailored efforts to adapt to climate change. This study improves the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) water yield model by integrating long-term time series of vegetation data, emphasizing the role of interannual vegetation variation. This study also analyzes the influences of various factors on WC variations. The results show a significant increase in WC from 1991 to 2020 (1.4 mm/yr, p < 0.05), with 78.17% of the TRHR showing improvement. Precipitation is the primary factor driving the interannual variations in WC. Moreover, distinct interactions play dominant roles in WC across different eco-geographical regions. In the north-central and western areas, the interaction between annual precipitation and potential evapotranspiration has the highest influence. Conversely, the interaction between annual precipitation and vegetation has the greatest impact in the eastern and central-southern areas. This study provides valuable insights into the complex interactions between the land and atmosphere of the TRHR, which are crucial for enhancing the stability of the ecosystem. [ABSTRACT FROM AUTHOR]

Wind erosion is recognized as one of the main environmental issues and seriously threatens ecosystem services in the Yarlung Zangbo River basin (YZRB), southern Tibetan Plateau. Exploring the spatiotemporal dynamics and drivers of wind erosion is crucial for improving regional ecosystem services and sustainable development. This study was conducted to examine the spatiotemporal patterns of soil wind erosion modulus (SWEM) in YZRB from 1990 to 2020 by using the revised wind erosion equation (RWEQ) and to identify the influence of climate change and anthropogenic activities on wind erosion dynamics. The results showed that temporally, the overall SWEM presented a significant downward trend (−0.912 t·hm−2·a−1) and a continuous downward trend in the key implementation areas of ecological engineering. Spatially, the severe area of wind erosion is mainly concentrated in the flat and broad river valley, where sand sources are widely distributed. Significant SWEM differences were found among various land use/cover (LULC) types. Exceeding 90% reduction rates in SWEM occurred in forests, grasslands, and cultivated land. Additionally, the influence analysis showed that climate change was the dominant factor driving the variations in wind erosion due to the reduction of wind speed. By contrast, the contribution of anthropogenic activities is relatively less, accounting for 43.50% of wind erosion change, which closely matches the transfer of LULC to grassland and forest land with the implementation area of ecological engineering projects. This study provides useful information on the driving mechanism of wind erosion, prevention service changes, and determining priority zones for desertification prevention in YZRB. We suggest that eco-restoration activities should be endorsed in the future, as well as the adaptive management that is required to control wind erosion and improve ecosystem services and human well-being for people in the YZRB region. [ABSTRACT FROM AUTHOR]

The unique geographical location of the Tibetan Plateau (TP) plays an important role in regulating global climate change, but the impacts of the chemical components and atmospheric processing on the size distribution and mixing state of individual particles are rarely explored in the south-eastern margin of the TP, which is a transport channel for pollutants from Southeast Asia to the TP during the pre-monsoon season. Thus a single-particle aerosol mass spectrometer (SPAMS) was deployed to investigate how the local emissions of chemical composition interact with the transporting particles and assess the mixing state of different particle types and secondary formation in this study. The TP particles were classified into six distinct types, mainly including the largest fraction of the potassium-rich (K-rich) type in the total particles (30.9 %), followed by the biomass burning (BB) type (18.7 %). Most particle types were mainly transported from the sampling site's surroundings and along the Sino-Myanmar border, but the air mass trajectories from north-eastern India and Myanmar show a greater impact on the number fraction of the BB (31.7 %) and dust (18.2 %) types, respectively. Then, the two episodes with high particle concentrations showed that the differences in the meteorological conditions in the same trajectory clusters could cause significant changes in chemical components, especially the dust and aged elemental carbon (aged EC) types, which changed by a total of 93.6 % and 72.0 %, respectively. Ammonium and dust particles distribute at a relatively larger size (∼600 nm), but the size peak of other types is present at ∼440 nm. Compared with the abundant sulfate (97 HSO 4-), the low nitrate (62 NO 3-) internally mixed in TP particles is mainly due to the fact that nitrate is more volatilized during the transport process. The formation mechanism of secondary speciation demonstrates that the formation capacity of atmospheric oxidation is presumably affected by the convective transmission and the regional transport in the TP. However, the relative humidity (RH) could significantly promote the formation of secondary species, especially 97 HSO 4- and 18 NH 4+. This study provides new insights into the particle composition and size, mixing state, and ageing mechanism in high time resolution over the TP region. [ABSTRACT FROM AUTHOR]

Climate change and anthropogenic activities have had a profound effect on the variation in grassland productivity in the Tibetan Plateau in recent decades. Quantifying the impacts of climatic and anthropogenic variables on grassland productivity is a necessary step in making the management policies of a sustainable grassland ecosystem. Net primary productivity (NPP) is an important part of the terrestrial carbon cycle and can be used to assess vegetation growth. Based on the Carnegie–Ames–Stanford Approach model and statistical analysis method, in this study we estimated the variations in grassland potential NPP (PNPP), actual NPP (ANPP) and human-induced NPP (HNPP) in the Northwest Sichuan Plateau (NWSP) of the Southeast Tibetan Plateau from 2001 to 2020. Also, we assessed the contribution of climatic change and anthropogenic activities to grassland ANPP. The results showed that the average values of grassland ANPP, PNPP and HNPP in the whole NWSP increased at the rates of 3.81, 9.14 and 7.18 g C m−2 a−1, respectively. Grassland ANPP increased in 91.7% of the total area. Climate-oriented impacts led grassland ANPP to increase in 82.6% of the area, and temperature increase was the dominant factor. Additionally, anthropogenic activity was the major reason for the grassland ANPP's decline (5.4% of the total area). Overall, our findings are beneficial for the formulation of practical countermeasures regarding climate change adaption and damaged grassland recovering in the plateau. [ABSTRACT FROM AUTHOR]