The Tibetan Plateau (TP) covers the largest regions under low- and mid-latitude permafrost. The evolution of permafrost has significantly affected the hydrology, biogeochemistry, and infrastructure of Asia. However, model reconstructions of long-term permafrost evolution with high accuracy and reliability are insufficient. Here, spatial changes in mean annual ground temperature at the depth where the annual amplitude is zero (MAGT) on the TP since 1981 were modeled and validated based on temperature records from 155 boreholes, and future changes were predicted under scenarios from the Climate Model Intercomparison Project 6 (CMIP6). The results indicated that the MAGT on the TP was approximately 1.5 degrees C (2010 - 2018), and the corresponding permafrost extent on the TP is estimated to be approximately 1.03 x 106 km2, which is projected to decrease to 0.77 x 106, 0.50 x 106, 0.30 x 106, and 0.17 x 106 km2 under the scenarios of shared socioeconomic pathway (SSP)126, SSP245, SSP370, and SSP585, respectively, by 2100. As predicted in the SSP585 scenario, permafrost is predicted to largely disappear from many basins of major Asian rivers, such as the Yarlung Zangpo-Brahmaputra, NuSalween, and Lancang-Mekong Rivers, between 2041 and 2060, followed by the Yellow and Yangtze Rivers between 2061 and 2080. Moreover, the original stable permafrost in the West Kunlun Mountains will change to transitional and unstable conditions. Our study offers comprehensive datasets of year-to-year ground temperatures and permafrost extent maps for the TP, which can serve as a fundamental resource for further investigations on the hydrogeology, engineering geology, ecology, and geochemistry of the TP.

全球变暖对北半球多年冻土的影响日益显著，多年冻土退化是现代冰冻圈中与气候变化相关的最紧迫问题之一。本研究基于15种不同地球系统模式（ACCESS-CM2、ACCESS-ESM1-5、BCC-CSM2-MR、CanESM5、CESM2、CESM2-WACCM、EC-Earth3、FGOALS-f3-L、IPSL-CM6A-LR、MIROC6、MPI-ESM1-2-HR、MPI-ESM1-2-LR、MRI-ESM2-0、NorESM2-LM、NorESM2-MM）的CMIP6土壤温度数据，分析了未来不同排放情境（SSP126、SSP245、SSP370和SSP585）下北半球多年冻土面积和活动层厚度（ALT）的时空格局，重点解析了影响ALT变化的主要环境驱动因子。结果表明：各地球系统模式（ESM）对ALT的模拟能力差异显著。基于性能最优的4个ESM（MPI-ESM1-2-LR、ACCESS-ESM1-5、MPI-ESM1-2-HR和BCC-CSM2-MR）分析发现，2015—2100年间，高排放情境（SSP370、SSP585）下多年冻土面积减少速率显著加快，SSP585情境下冻土面积消退...

Surface albedo (SA) is crucial for understanding land surface processes and climate simulation. This study analyzed SA changes and its influencing factors in Central Asia from 2001 to 2020, with projections 2025 to 2100. Factors analyzed included snow cover fraction, fractional vegetation cover, soil moisture, average state climate indices (temperature and precipitation), and extreme climate indices (heatwave indices and extreme precipitation indices). Pearson correlation coefficient, geographical convergent cross mapping, and geographical detector were used to quantify the correlation, causal relationship strength, and impact degree between SA and the influencing factors. To address multicollinearity, ridge regression (RR), geographically weighted ridge regression (GWRR), and piecewise structural equation modeling (pSEM) were combined to construct RR-pSEM and GWRR-pSEM models. Results indicated that SA in Central Asia increased from 2001 to 2010 and decreased from 2011 to 2020, with a projected future decline. There is a strong correlation and significant causality between SA and each factor. Snow cover fraction was identified as the most critical factor influencing SA. Average temperature and precipitation had a greater impact on SA than extreme climate indices, with a 1 degrees C temperature increase corresponding to a 0.004 decrease in SA. This study enhances understanding of SA changes under climate change, and provides a methodological framework for analyzing complex systems with multicollinearity. The proposed models offer valuable tools for studying interrelated factors in Earth system science.

Snow is an important factor controlling vegetation functions in high latitudes/altitudes. However, due to the lack of reliable in -situ measurements, the effects of snow on vegetation phenology remains poorly understood. Here, we examine the effects of snow cover duration (SCD) on the start of growing season (SOS) for different vegetation types. SOS and SCD were extracted from in -situ carbon flux and albedo data, respectively, at 51 eddy covariance flux sites in the northern mid -high latitudes. The effects of SCD on SOS vary substantially among different vegetation types. For grassland, preseason SCD outperforms other factors controlling grassland SOS. However, for forests and cropland, the preseason air temperature is the dominant factor in controlling SOS. Preseason SCD mainly influences the SOS by regulating preseason air and soil temperature rather than soil moisture. The CMIP6 Earth system models (ESMs) fail to capture the effect of SCD on SOS. Thus, Random Forest (RF) models were established to predict future SOS changing trends considering the effect of SCD. For grassland and evergreen needleleaf forest, the projected SOS advance rate is slower when SCD is considered. These findings can help us better understand impacts of snow on vegetation phenology and carbon -climate feedbacks in the warming world.

In this paper, we used data from 42 soil temperature observation sites in permafrost regions throughout the Northern Hemisphere to analyze the characteristics and variability in soil temperature. The observation data were used to evaluate soil temperature simulations at different depths from 10 CMIP6 models in the permafrost region of the Northern Hemisphere. The results showed that the annual average soil temperature in the permafrost regions in the Northern Hemisphere gradually decreased with increasing latitude, and the soil temperature gradually decreased with depth. The average soil temperatures at different depths were mainly concentrated around 0 degrees C. The 10 CMIP6 models performed well in simulating soil temperature, but most models tended to underestimate temperatures compared to the measured values. Overall, the CESM2 model yielded the best simulation results, whereas the CNRM-CM6-1 model performed the worst. The change trends in annual average soil temperature across the 42 sites ranged from -0.17 degrees C/10a to 0.41 degrees C/10a from 1900 to 2014, the closer to the Arctic, the faster the soil warming rate. The rate of soil temperature change also varied at different depths between 1900-2014 and 1980-2014. The rate of soil temperature change from 1980 to 2014 was approximately three times greater than that from 1900 to 2014.

Permafrost degradation on the Tibetan Plateau (TP) is anticipated to result in the thaw of permafrost carbon. Existing studies have been conducted to assess the future thaw of frozen carbon on the TP, primarily focusing on the deepening of the active layer while neglecting the impact of permafrost area shrinkage. This oversight may lead to a significant underestimation of the potential thaw of frozen carbon. Our research underscores the pivotal role of permafrost area shrinkage in estimating the future thaw of frozen carbon. Our findings reveal that when the combined effects of permafrost area shrinkage and active layer deepening are considered, the thaw rates of frozen carbon in various radiative forcing scenarios are nearly four times those based on active layer deepening alone. Notably, our results demonstrate substantial thaw of frozen organic carbon in the TP permafrost area under all four future scenarios: In the low radiative forcing scenario SSP1-2.6, it is predicted that 55.4 % of the organic carbon in the permafrost area 0-10 m soils will be in a state of thaw by 2100, and more than 90 % in the high radiative forcing scenario SSP5-8.5. This substantial thaw is poised to diminish the TP's current carbon sink function significantly. Our study emphasizes that as global warming persists, frozen carbon in permafrost areas will play a more active role in global carbon cycle processes in the future. Furthermore, we stress the importance of considering permafrost area shrinkage in understanding the thaw of frozen carbon, providing valuable insights for carbon balance studies on the TP.

Many studies have focused on elevation-dependent warming (EDW) across high mountains, but few studies have examined both EDW and LDW (latitude-dependent warming) on Antarctic warming. This study analyzed the Antarctic amplification (AnA) with respect to EDW and LDW under SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 from Coupled Model Intercomparison Project Phase 6 (CMIP6) during the period 2015-2100. The results show that the AnA appears under all socioeconomic scenarios, and the greatest signal appears in austral autumn. In the future, Antarctic warming is not only elevation-dependent, but also latitude-dependent. Generally, positive EDW of mean temperature (T-mean), maximum temperature (T-max) and minimum temperature (T-min) appear in the range of 1.0-4.5 km, and the corresponding altitudinal amplification trends are 0.012/0.012/0.011 (SSP1-2.6)- 0.064/0.065/0.053 (SSP5-8.5) degrees C decade(-1)center dot km(-1). Antarctic EDW demonstrates seasonal differences, and is strong in summer and autumn and weak in winter under SSP3-7.0 and SSP5-8.5. For T(mea)n, T-max and T-min, the feature of LDW is varies in different latitude ranges, and also shows seasonal differences. The strongest LDW signal appears in autumn, and the warming rate increases with increasing latitude at 64-79 degrees S under SSP1-2.6. The similar phenomenon can be observed at 68-87 degrees S in the other cases. Moreover, the latitude component contributes more to the warming of T-mean and T-max relative to the corresponding altitude component, which may relates to the much larger range of latitude (similar to 2600 km) than altitude (similar to 4.5 km) over Antarctica, while the EDW contributes more warming than LDW in the changes in T-min in austral summer. Moreover, surface downwelling longwave radiation, water vapor and latent heat flux are the potential factors influencing Antarctic EDW, and the variation in surface downwelling longwave radiation can also be considered as an important influencing factor for Antarctic LDW. Our results provide preliminary insights into EDW and LDW in Antarctica.

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. 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. 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

In the context of global warming, the soil freeze depth (SFD) over the Tibetan Plateau (TP) has undergone significant changes, with a series of profound impacts on the hydrological cycle and ecosystem. The complex terrains and high elevations of the TP pose great challenges in data acquisition, presenting difficulties for studying SFD in this region. This study employs Stefan's solution and downscaled datasets from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate the future SFDs over the TP. The changing trends of the projected SFDs under different Shared Socio-economic Pathways (SSP) scenarios are investigated, and; the responses of SFDs to potential climatic factors, such as temperature and precipitation, are analyzed. The potential impacts of SFD changes on eco-hydrological processes are analyzed based on the relationships between SFDs, the distribution of frozen ground, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Results show that the projected SFDs of the TP are estimated to decrease at rates of 0.100 cm/yr under the SSP126, 0.330 cm/yr under the SSP245, 0.565 cm/yr under the SSP370, and 0.750 cm/yr under the SSP585. Additionally, the SFD decreased at a rate of 0.160 cm/yr during the historical period from 1950 to 2014, which was between the decreasing rates of the SSP126 and SSP245 scenarios. The projected SFDs are negatively correlated with air temperature and precipitation, more significant under the higher emissions scenario. The projected decrease in SFDs will significantly impact eco-hydrological processes. A rapid decrease in SFD may lead to a decline in soil moisture content and have adverse impacts on vegetation growth. This research provides valuable insights into the future changes in SFD on the TP and their impacts on eco-hydrological processes.

利用Climatic Research Unit （CRU）资料，系统评估了第六次国际耦合模式比较计划（Coupled Model Intercomparison Project Phase 6, CMIP6）17个全球气候模式及其集合平均对历史时期（1985—2014年）北半球及多年冻土区年降水量的模拟能力；分析了不同未来情景（SSP1-2.6、SSP2-4.5、SSP3-7.0、SSP5-8.5）下，北半球及多年冻土区未来年降水量的时空变化。结果表明：CMIP6模式对北半球及多年冻土区年降水的空间分布有较为合理的模拟能力，但相对于观测数据在北半球和多年冻土区分别有11%和42%的高估。未来北半球及多年冻土区的年降水量变化随着辐射强迫水平的升高而加快。在SSP5-8.5情景下增加速率最快，北半球和多年冻土区的年降水增加速率分别为13 mm·（10a）-1、20 mm·（10a）-1，相较于历史时期最后一年（2014年）年降水分别增加了134 mm、178 mm。北半球陆地平均年降水量始终高于多年冻土区，但多年冻土区增加速率要高于北半球。在S...