Ice records provide a qualitative rather than a quantitative indication of the trend of climate change. Using the bulk aerodynamic method and degree day model, this study quantified ice mass loss attributable to sublimation/evaporation (S/E) and meltwater on the basis of integrated observations (1960-2006) of glacier-related and atmospheric variables in the northeastern Tibetan Plateau. During 1961-2005, the average annual mass loss in the ice core was 95.33 +/- 20.56 mm w.e. (minimum: 78.97 mm w.e. in 1967, maximum: 146.67 mm w.e. in 2001), while the average ratio of the revised annual ice accumulation was 21.2 +/- 7.7% (minimum: 11.0% in 1992, maximum 44.8% in 2000). A quantitative formula expressing the relationship between S/E and air temperature at the monthly scale was established, which could be extended to estimation of S/E changes of other glaciers in other regions. The elevation effect on alpine precipitation determined using revised ice accumulation and instrumental data was found remarkable. This work established a method for quantitative assessment of the temporal variation in ice core mass loss, and advanced the reconstruction of long-term precipitation at high elevations. Importantly, the formula established for reconstruction of S/E from temperature time series data could be used in other regions.

Lakes are commonly accepted as a sensitive indicator of regional climate change, including the Tibetan Plateau (TP). This study took the Ranwu Lake, located in the southeastern TP, as the research object to investigate the relationship between the lake and regional hydroclimatological regimes. The well-known Budyko framework was utilized to explore the relationship and its causes. The results showed air temperature, evapotranspiration and potential evapotranspiration in the Ranwu Lake Basin generally increased, while precipitation, soil moisture, and glacier area decreased. The Budyko space indicated that the basin experienced an obviously drying phase first, and then a slightly wetting phase. An overall increase in lake area appears inconsistent with the drying phase of the basin climate. The inconsistency is attributable to the significant expansion of proglacial lakes due to glacial melting, possibly driven by the Atlantic Multidecadal Oscillation. Our findings should be helpful for understanding the complicated relationships between lakes and climate, and beneficial to water resources management under changing climates, especially in glacier basins.

Snow cover variation significantly impacts alpine vegetation dynamics on the Tibetan Plateau (TP), yet this effect under climate change remains underexplored. This study uses a survival analysis model to assess the influence of snow on vegetation green-up dynamics, while controlling for key temperature and water availability factors. This analysis integrates multi-source data, including satellite-derived vegetation green-up dates (GUDs), snow depth, accumulated growing degree days (AGDD), downward shortwave radiation (SRAD), precipitation, and soil moisture. Our survival analysis model effectively simulated GUD on the TP, achieving an R of 0.62 (p < 0.01), a root mean square error (RMSE) of 11.20 days, and a bias of -1.41 days for 2020 GUD predictions. It outperformed both the model excluding snow depth and a linear regression model. By isolating snow's impact, we found it exerts a stronger influence on vegetation GUD than precipitation in snow-covered areas of the TP. Furthermore, snow depth effects varied seasonally: a 1-cm increase in preseason snow depth reduced green-up rates by 8.48% before 156(th) day but increased them by 4.74% afterward. This indicates that deeper preseason snow cover delays GUD before June, but advances it from June onward, rather than having a uniform effect. These findings highlight the critical role of snow and underscore the need to incorporate its distinct effects into vegetation phenology models in alpine regions.

Glaciers provide multiple ecosystem services (ES) to human society. Due to the continued global warming, the valuation of glacier ES is of urgent importance because this knowledge can support the protection of glaciers. However, a systematic valuation of glacier ES is still lacking, particularly from the perspective of ES contributors. In this study, we introduce the concept of emergy to establish a methodological framework for accounting glacier ES values, and take the Tibetan Plateau (TP) as a case study to comprehensively evaluate the spatiotemporal characteristics of glacier ES during the early 21st century. The results show that the total glacier ES values on the TP increased from 2.36E+24 sej/yr in the 2000s to 2.40E+24 sej/yr in the 2010s, with an overall growth rate of 1.6%. The values of the various services in the 2010s are ranked in descending order: climate regulation (1.59E+24 sej/yr, 66.1%), runoff regulation (4.40E+23 sej/yr, 18.4%), hydropower generation (1.88E+23 sej/ yr, 7.8%). Significantly higher glacier ES values were recorded in the marginal TP than in the endorheic area. With the exception of climate regulation and carbon sequestration, all other service values increased during the study period, partially cultural services, which have experienced rapid growth in tandem with social development. The results of this study will help establish the methodological basis for the assessment of regional and global glacier ES, as well as a scientific basis for the regional protection of glacier resources.

As a key component of the cryosphere, permafrost is sensitive to climate change, but mapping permafrost, especially in the Tibetan Plateau, has been challenging due to the heterogeneous mountainous landscape and limited representativeness of ground observations. Using 155 compiled ground observations and more than 20,000 rock glacier records, we developed a machine learning model to map the distribution of permafrost and produce an improved permafrost zonation index (PZI) map. The model was applied by incorporating several control variables, including terrain (elevation and relief), soil (bulk density, clay, coarse fragments, sand, and silt), and temperature (MAAT, FDD, and TDDT) to estimate the PZI at a 1-km resolution in the southern Tibetan Plateau. Excluding glaciers and lakes, the area of permafrost estimated by the new map is approximately 103.5 x 103 km2, accounting for 47.8% of the total area of the region. The result was assessed with various datasets and compared with existing permafrost maps and achieved higher accuracy compared with previous studies. The overall classification accuracy was 96.1% in high plain areas and 84.4% in mountain areas. The results demonstrated the substantial potential for improving mapping permafrost and understanding the periglacial environment with rock glacier inventories and machine learning, especially in complex terrain and climate.

Due to the impact of climate change, significant alterations in snowmelt have already occurred, which have been demonstrated to play a crucial role in photosynthetic carbon sequestration processes in vegetation. However, the effect of changes in snowmelt on light use efficiency (LUE) of grassland remain largely unknown in the permafrost region of Qinghai-Tibetan Plateau (QTP). By utilizing remote sensing data from 2000 to 2017, we conducted an analysis on the spatial and temporal patterns of LUE for various types of permafrost and grassland on the QTP. The LUE of the growing season was 1.1588 g CMJ(-1), displaying variations among different ecosystems: alpine steppe of seasonally frozen ground (ASS) > alpine meadow of seasonally frozen ground (AMS) > alpine meadow of permafrost (AMP) > alpine steppe of permafrost (ASP). Furthermore, our study demonstrated that decreasing snowmelt during the growing season had a negative impact on LUE through meteorological factors, elucidating its influence on LUE for approximately 40.65%, 34.06%, 41.05%, and 32.68% of ecosystems studied. Reduced snowmelt indirectly affects LUE by lowering air temperatures, vapor pressure deficit and solar radiation, while replenishing soil moisture. Additionally, changes in snowmelt can directly affect LUE by reducing the insulating properties of snow cover. Therefore, when estimating gross primary productivity (GPP) using remote sensing data based on LUE, it is essential to consider the impact of snowmelt. This will better represent vegetation phenology's response to climate change.

The Tibetan Plateau (TP) has experienced accelerated warming in recent decades, especially in winter. However, a comprehensive quantitative study of its long-term warming processes during daytime and nighttime is lacking. This study quantifies the different processes driving the acceleration of winter daytime and nighttime warming over the TP during 1961-2022 using surface energy budget analysis. The results show that the surface warming over the TP is mainly controlled by two processes: (a) a decrease in snow cover leading to a decrease in albedo and an increase in net downward shortwave radiation (snow-albedo feedback), and (b) a warming in tropospheric temperature (850 - 200 hPa) leading to an increase in downward longwave radiation (air warming-longwave radiation effect). The latter has a greater impact on the spatial distribution of warming than the former, and both factors jointly influence the elevation dependent warming pattern. Snow-albedo feedback is the primary factor in daytime warming over the monsoon region, contributing to about 59% of the simulated warming trend. In contrast, nighttime warming over the monsoon region and daytime/nighttime warming in the westerly region are primarily caused by the air warming-longwave radiation effect, contributing up to 67% of the simulated warming trend. The trend in the near-surface temperature mirrors that of the surface temperature, and the same process can explain changes in both. However, there are some differences: an increase in sensible heat flux is driven by a rise in the ground-atmosphere temperature difference. The increase in latent heat flux is associated with enhanced evaporation due to increased soil temperature and is also controlled by soil moisture. Both of these processes regulate the temperature difference between ground and near-surface atmosphere.

Elemental carbon (EC), also known as black carbon, plays an important role in climate change. Accurately assessing EC concentration in aerosols remains challenging due to the overestimations caused by carbonates and organic carbon (OC) during thermal-optical measurement in the Tibetan Plateau (TP). This study evaluates the extent of EC overestimated by carbonates and OC at four remote sites (Nyalamu, Lulang, Everest and Ngari) in southern and western of the TP using different treatments. The average overestimation of EC concentration due to acid treatment was consistent across all sites (25.5 f 2.4 %). After correction, the proportion of EC overestimated by carbonates were approximately 8.5 f 7.3 %, 12.3 f 6.9 %, 18.1 f 11.8 % and 22.7 f 13.3 %, respectively, revealing an increasing trend from humid to arid regions. Methanol-soluble OC (MSOC) concentrations were significantly correlated with the reduction of EC concentrations, indicating that the methanol extraction effectively mitigates EC overestimation. Seasonal variation of carbonaceous aerosol concentrations was significantly affected by sources from South Asia. Despite the variations in climate and aerosol sources, the average overestimations of measured EC concentration by carbonates and OC were similar at Nyalamu (49.4 f 14.0 %), Lulang (47.8 f 8.4 %), Everest (48.7 f 15.9 %) and Ngari (49.3 f 13.7 %) sites. Therefore, the actual EC concentrations were only about 51.2 f 13.1 % of the original values. This estimation will significantly enhance the contribution of brown carbon (BrC) to radiative forcing relative to EC, highlighting a critical area for future research. Investigating the actual concentrations of EC in the TP provides critical data to support model simulation and validate model accuracy, further enhancing our understanding of EC's impacts on climate warming and glacier melting.

Indian monsoon circulation is the primary driver of the long-range transboundary mercury (Hg) pollution from South Asia to the Himalayas and Tibet Plateau region, yet the northward extent of this transport remains unknown. In this study, a strong delta Hg-202 signature overlapping was found between Lake Gokyo and Indian anthropogenic sources, which is an indicative of the Hg source regions from South Asia. Most of the sediment samples were characterized with relatively large positive Delta Hg-199 values (mean = 0.07 parts per thousand-0.44 parts per thousand) and small positive Delta Hg-200 values (mean = 0.03 parts per thousand-0.08 parts per thousand). Notably, the Delta Hg-199 values in the lake sediments progressively increased from southwest to northeast. Moreover, the Delta Hg-199 values peaked at Lake Tanglha (mean = 0.44 parts per thousand +/- 0.04 parts per thousand) before decreased at Lake Qinghai that is under the influence of the westerlies. Our results suggest that transboundary atmospheric transport could transport Hg from South Asia northwards to at least the Tanglha Mountains in the northern Himalaya-Tibet.

Biomass burning play a key role in the global carbon cycle by altering the atmospheric composition, and affect regional and global climate. Despite its importance, a very few high-resolution records are available worldwide, especially for recent climate change. This study analyzes levoglucosan, a specific tracer of biomass burning emissions, in a 38-year ice core retrieved from the Shulehe Glacier No. 4, northeastern Tibetan Plateau. The levoglucosan concentration in the Shulehe Glacier No. 4 ice core ranged from 0.1 to 55 ng mL(-1), with an average concentration of 8 +/- 8 ng mL(-1). The concentrations showed a decreasing trend from 2002 to 2018. Meanwhile, regional wildfire activities in Central Asian also exhibited a declining trend during the same period, suggesting the potential correspondence between levoglucosan concentration of the Shulehe Glacier No. 4 ice core and the fire activity of Central Asia. Furthermore, a positive correlation also exists between the levoglucosan concentration of the Shulehe Glacier No. 4 ice core and the wildfire counts in Central Asia from 2002 to 2018. While backward air mass trajectory analysis and fire spots data showed a higher distribution of fire counts in South Asia compared to Central Asia, but the dominance of westerly circulation in the northern TP throughout the year. Therefore, the levoglucosan in the Shulehe Glacier No. 4 provides clear evidence of Central Asian wildfire influence on Tibetan Plateau glaciers through westerlies. This highlights a great importance of ice core data for wildfire history reconstruction in the Tibetan Plateau Glacier regions.