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

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

The study of climate element distribution models under complex terrain conditions is a popular topic in the field of GIS application in climatology, especially in plateau areas with a complex topography and scarce meteorological station information. In this paper, the spatial and temporal heterogeneity of temperature and precipitation at the northeastern edge of the Tibetan Plateau was analyzed by taking the northeastern edge of the plateau as the study area and constructing a topographic spatial statistical model using 47 meteorological stations and digital elevation models from 1981 to 2010. The following conclusions were drawn from the study: (1) The ME of the temperature distribution model for each month is below 0.9 °C; the maximum ME of the precipitation distribution model for each month is −5.808 mm in July, and the precipitation distribution model has similar error characteristics with the temperature distribution model, which can reflect the horizontal zone distribution pattern of meteorological data and can clearly show the changes of temperature and precipitation as the altitude increases. (2) The spatial distribution pattern of temperature is as follows: the temperature in the study area gradually increases from the southwest to the northeast, with Zhouqu County in Linxia Prefecture and Gannan Prefecture as the main high-temperature areas; the spatial distribution of precipitation is as follows: the precipitation in the southwest of the study area is significantly higher than that in the north, and the precipitation in Linxia Prefecture is significantly lower than that in Gannan Prefecture. (3) The temporal distribution pattern of the temperature distribution model is as follows: the overall temperature in the study area is at its lowest level in January, and the maximum temperature is only 2.6 °C, until July, when the maximum temperature rises to 24.2 °C and then gradually starts to decline; the spatial distribution of precipitation is as follows: the precipitation in the study area gradually rises from January, and the maximum precipitation rises to July and then starts to decline, and in December the precipitation falls to the lowest level. The temporal distribution characteristics of the precipitation distribution model are similar to those of the air temperature model, with obvious hydrothermal synchronization characteristics. [ABSTRACT FROM AUTHOR]

Soil moisture and soil temperature (SMST) are important state variables for quantifying the exchange of heat and water between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements are scarce on the Tibetan Plateau (TP), with even fewer are available for multiple soil depths. Tibet-Obs is such a long-term, regional-scale SMST observatory in the TP that has been established 10 years ago and includes three SMST monitoring networks, i.e. Maqu, Naqu, and Ngari (including Ali and Shiquanhe), located in the cold humid area covered by grassland, the cold semiarid area dominated by tundra, and the cold arid area dominated by desert, respectively. This paper presents a long-term (∼ 10 years) SMST profile dataset collected from the Tibet-Obs, which includes the original in situ measurements at a 15 min interval collected between 2008 and 2019 from all the three networks and the spatially upscaled data (SM ups and ST ups) for the Maqu and Shiquanhe networks. The quality of the upscaled data is proved to be good, with errors that are generally better than the measured accuracy of adopted SMST sensors. Long-term analysis of the upscaled SMST profile data shows that the amplitudes of SMST variations decrease with increasing soil depth, and the deeper soil layers present a later onset of freezing and an earlier start of thawing and, thus, a shorter freeze–thaw duration in both the Maqu and Shiquanhe networks. In addition, there are notable differences between the relationships of SM ups and ST ups under freezing conditions for the Maqu and Shiquanhe networks. No significant trend can be found for the SM ups profile in the warm season (from May to October) for both networks that is consistent with the tendency of precipitation. A similar finding is also found for the ST ups profile and air temperature in the Shiquanhe network during the warm season. For the cold season (from November to April), a drying trend is noted for the SM ups above 20 cm in the Maqu network, while no significant trend is found for those in the Shiquanhe network. Comparisons between the long-term upscaled data and five reanalysis datasets, including the ECMWF reanalysis v5 (ERA5), Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), Global Land Data Assimilation System version 2 Catchment Land Surface Model (GLDAS-2.1 CLSM), GLDAS-2.1 Noah, and GLDAS-2.1 variable infiltration capacity (GLDAS-2.1 VIC), indicate that none of the current model-based products can reproduce the seasonal variations and interannual trend changes in the measured SMST profile dynamics in both networks. All the products underestimate the ST ups at every depth, leading to an earlier onset of freezing and a later onset of thawing, which essentially demonstrates that the current models are not able to adequately simulate winter conditions on the TP. In short, the presented dataset would be valuable for evaluation and improvement in long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/20141567.v1 (Zhang et al., 2022). [ABSTRACT FROM AUTHOR]

The northeastern Tibetan Plateau is located in a climatic junction, which is considered an ideal region to explore the interactions between the summer monsoons and the westerly circulation patterns. However, to date, the needed long-term precipitation-based isotopic dataset is too limited to predict the interactions and patterns. This paper presents an evaluation of hydrometeorological processes and climate dynamics in the northeastern Tibetan Plateau based on a 7-yr precipitation isotope dataset covering the summer monsoon periods from 2012 to 2018. Results illustrated remarkable seasonal isotopic variability, characterized by lower δ18O and δ2H values in June with an average of −10‰ and −66.7‰, respectively. Higher δ18O and δ2H values in July averaged −6.7‰ and −39.5‰, respectively. This clear isotopic variability is largely related to seasonal changes of moisture sources and hydrometeorological processes. These precipitation isotopic values were primarily determined by the amount of precipitation, relative humidity, and convective activity, but showed no correlation with air temperature. Backward trajectory model results showed that Xinjiang, northern China, the Arctic, central Asia, and the South China Sea (SCS) were the primary sources of precipitation for the study site with varying seasonal contributions. The maritime moisture source of the SCS primarily resulted in the lowest precipitation δ18O values during the prevailing summer monsoon, which is mainly as a result of the strong convective activity and rainout processes along the air trajectory. The higher average deuterium excess (d-excess) value of precipitation in September indicated continental sources from central Asia (e.g., 75.4%) as land vapor recycling increases d-excess concentration in the atmosphere. These findings provide further insights into the main factors of precipitation isotopic variability related to atmospheric processes along the trajectory and the relevant factors in the monsoon regions. Significance Statement: Recently, scientists and policy makers have become aware that Tibetan hydroclimate variability provides evidence of changes in regional and global circulation patterns that may result in the intensification of climate-driven extremes. However, these studies largely depend on crucial paleoclimate records of past precipitation isotopes in monsoon regions, which contain great uncertainties because of the complex relationship between climatic variability and precipitation isotopes. This study first presented a 7-yr isotopic dataset to understand the hydrological processes and climate dynamics controlling the isotopic variability in the northeastern Tibetan Plateau. The findings reveal important factors on the isotopic variability associated with atmospheric processes and their key climatic variables, which can enhance our interpretation of the paleoclimate records in monsoon regions. [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]

The surface air temperature (SAT) trend on the Tibetan Plateau (TP) was 3.45°C 100 years−1 from 1961 to 2014. The multi‐model ensemble (MME) of 33 coupled models participated in the Coupled Model Intercomparison Project phase six (CMIP6) was about 1°C 100 years−1 lower than the observation. Although MME generally shows better skill in reproducing the distribution of SAT trend over TP than most of the CMIP6 models, its performance is greatly degraded by a small group of models, about 12% on average, with large biases. In this paper, the constrained multi‐model ensemble (CMME) based on a certain observation‐based threshold is used to constrain future projections of the SAT trend over TP. Compared with the MME results, the improvements in CMME are mainly over the eastern plateau in historical simulation and are relative to the reduction of the model biases to carbon dioxide (CO2) forcing. Under the high‐emission SSP5‐8.5 scenario, SAT increases significantly over the entire TP. The constraint of CMME on the MME is mainly over the eastern plateau with a difference of 0.5°C 100 years−1, about 6% of the MME results. Under the intermediate‐emission scenario SSP2‐4.5, the effect of CMME is relatively smaller, but the corresponding spatial distribution is similar to that under the SSP5‐8.5 scenario. The CMIP6 models tend to underestimate the warming trend projections over the water source regions in the northeastern plateau and should be noticed. Key Points: The Coupled Model Intercomparison Project phase six model ensemble in surface air temperature trend reproduction on the Tibetan Plateau are greatly degraded by a small group of models with large biasesThe impact of constrained ensemble (CMME) is mainly over the eastern plateau in relative to the reduction of model biases to CO2 forcingThe CMME results indicate the underestimated warming projections in multi‐model ensemble over the northeastern plateau [ABSTRACT FROM AUTHOR]

Precipitation is the key component determining the water budget and climate change of the Tibetan Plateau (TP) under a warming climate. This high-latitude region is regarded as "the Third Pole" of the Earth and the "Asian Water Tower" and influences the eco-economy of downstream regions. However, the intensity and diurnal cycle of precipitation are inadequately depicted by current reanalysis products and regional climate models (RCMs). Spectral nudging is an effective dynamical downscaling method used to improve precipitation simulations of RCMs by preventing simulated fields from drifting away from large-scale reference fields, but the most effective manner of applying spectral nudging over the TP is unclear. In this paper, the effects of spectral nudging parameters (e.g., nudging variables, strengths, and levels) on summer precipitation simulations and associated meteorological variables were evaluated over the TP. The results show that using a conventional continuous integration method with a single initialization is likely to result in the over-forecasting of precipitation events and the over-forecasting of horizontal wind speeds over the TP. In particular, model simulations show clear improvements in their representations of downscaled precipitation intensity and its diurnal variations, atmospheric temperature, and water vapor when spectral nudging is applied towards the horizontal wind and geopotential height rather than towards the potential temperature and water vapor mixing ratio. This altering of the spectral nudging method not only reduces the wet bias of water vapor in the lower troposphere of the ERA-Interim reanalysis (when it is used as the driving field) but also alleviates the cold bias of atmospheric temperatures in the upper troposphere, while maintaining the accuracy of horizontal wind features for the regional model field. The conclusions of this study imply how driving field errors affect model simulations, and these results may improve the reliability of RCM results used to study the long-term regional climate change. [ABSTRACT FROM AUTHOR]

Soil moisture and soil temperature (SMST) are important state variables for quantifying exchange of heat and water between land and atmosphere. Yet, long-term regional-scale in-situ SMST measurements are scarce on the Tibetan Plateau (TP), even fewer are available for multiple soil depths. "Tibet-Obs" is such a long-term regional-scale SMST observatory in the TP established 10 years ago that includes three SMST monitoring networks, i.e., Maqu, Naqu, and Ngari (including Ali and Shiquanhe), located in the cold humid area covered by short grasses, the cold semiarid area dominated by tundra, and the cold arid area dominated by desert, respectively. This paper presents a long-term (~10 years) SMST profile dataset collected from the Tibet-Obs, which includes the original in-situ measurements at a 15-min interval collected between 2008 and 2019 from all the three networks and the spatially upscaled data (SMups and STups) for the Maqu and Shiquanhe networks. The quality of the upscaled data is proved to be good with errors that are generally better than the measured accuracy of adopted SMST sensors. Long term analysis of the upscaled SMST profile data shows that the amplitudes of SMST variations decrease with increasing soil depth, and the deeper soil layers present later onset of freezing and earlier start of thawing and thus shorter freeze-thaw duration in both Maqu and Shiquanhe networks. In addition, there are notably differences noted between the relationships of SMups and STups under freezing conditions for the Maqu and Shiquanhe networks. No significant trend can be found for the SMups profile in the warm season (from May to October) for both networks that is consistent with the tendency of precipitation. Similar finding is also found for the STups profile and air temperature in the Shiquanhe network during the warm season. For the cold season (from November to April), a drying trend is noted for the SMups above 20 cm in the Maqu network, while no significant trend is found for those in the Shiquanhe network. Comparisons between the long-term upscaled data and five reanalysis datasets indicate that none of current model-based products can reproduce the seasonal variations and inter-annual trend changes of measured SMST profile dynamics in both networks. All the products underestimate the STups at every depth, leading to earlier onset of freezing and later onset of thawing, which essentially demonstrates the current model are not able to adequately simulate winter conditions on the TP. In short, the presented dataset would be valuable for evaluation and improvement of long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/20141567.v1. [ABSTRACT FROM AUTHOR]

• Sand wedge deposits were identified in the Early Miocene Wuqia Group. • Sand wedges occurred in braided fluvial environment under arid and cold climate. • The northern Tibetan Plateau surpassed 1000 m elevation in the Early Miocene. The uplift of the Tibet Plateau and its climatic effects have long been a hot topic in academic research. However, there is still significant controversy regarding the uplift history and related climate changes along the northern margin of the plateau. In this paper, we present sand wedge deposits from the base of the Wuqia Group (∼20 Ma) on the southwestern Tarim Basin, representing the oldest reported sand wedges in the Tibetan Plateau. A comprehensive study was conducted on lithostratigraphy, sedimentary environment, and macroscopic–microscopic features of the sand wedge deposits. The results indicate that the lithostratigraphic succession preserving the sand wedge deposits consists mainly of lenticular conglomerates and cross-bedded gravelly sandstone interbedded with medium–thin-bedded mudstone, consistent with the braided fluvial environment. The sand wedge deposits commonly exhibit a V-shape geometry and are filled with gravelly sandstone, with the gravels arranged parallel to the walls of the wedge. The clasts of the wedge-filled sandstone are well-rounded and show a unimodal grain size distribution. The quartz surfaces commonly display dish-shaped and crescent-shaped impact features, indicating an eolian origin and an arid climate. Based on the relationship between the formation temperature of modern sand wedges, the atmospheric temperature gradient, and altitude, the reconstructed paleo-elevation of the sand wedge deposits at the base of the Wuqia Group in the southwestern Tarim Basin is approximately ∼ 1000 m. These results indicate that the northern margin of the Tibet Plateau had already reached an elevation of ∼ 1000 m during the Early Miocene, forming a seasonal arid and cold climate. [ABSTRACT FROM AUTHOR]

Surface runoff is a major component of the hydrological cycle, and it is essential for supporting the ecosystem services provided by grassland and forest ecosystems. It is of practical importance to understand the mechanisms and the dynamic processes of runoff in a river's basin, and in this study, we focused on the restored montane Pailugou Basin in the Qilian Mountains, Gansu Province, China, since its water status is extremely important for the large arid area and local economies therein. Our purpose was to determine the annual variation in the surface runoff in the Pailugou Basin because it is important to understand the influence of climate fluctuations on surface water resources and the economy of the basin. In addition, little is known about the annual variations in precipitation and runoff in this region of the world. Daily atmospheric precipitation, air temperature and runoff data from 2000 to 2019 were analyzed by the calculation of the uneven annual distribution of surface runoff, the calculation of the complete adjustment coefficient, and the vector accumulation expressed by the concentration degree. We also used the cumulative anomaly approach to determine the interannual variation trend of runoff, while the change trend was quantified by the sliding average method. Finally, we used the Mann–Kendall mutation test method and regression analysis to establish the time-series trend for precipitation and runoff and to determine the period of abrupt runoff changes. The results indicated concentrated and positive distributions of surface runoff on an annual basis, with a small degree of dispersion, and an explicit concentration of extreme flows. The relative variation ranges exhibited a decreasing trend, and the distribution of the surface runoff gradually was uniform over the year. The runoff was highest from July to September (85% of the annual total). We also determined that annual surface runoff in the basin fluctuated over the 20-year period but showed an overall increasing trend, increasing by 3.94 × 105 m3, with an average increase rate of 0.42 × 105 m3 every ten years. From 2005 to 2014, the annual runoff and the proportion of runoff in the flood season (July to September) to the annual runoff fluctuated greatly. The correlation between the runoff and precipitation was significant (r = 0.839, p < 0.05), whereas the correlation between air temperature and surface runoff was low (r = 0.421, p < 0.05). [ABSTRACT FROM AUTHOR]

The intermittency of gravity wave potential energy (GWPE) in the upper troposphere and stratosphere was investigated using the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) temperature data over three typical mountains (Tibetan Plateau, Rocky Mountains, and Andes). These typical mountains have high sea level elevations but different land–sea contrast. The probability density function (PDF) of GWPE has the independent variable of GWPE and dependent variable of occurrence probability of GWPE over a region. Our analysis showed that the PDFs of GWPE over these three mountains roughly followed lognormal distributions in all heights and months. But, the key parameters (mean value and standard deviation) of lognormal distribution varied with heights and months. Above each mountain, the two key parameters exhibited similar temporal and spatial distributions. They had the largest values around the tropopause region, smaller values in the lower stratosphere (~20–30 km), and larger values in the upper stratosphere (~35–45 km). The intermittency of GWs is represented as the ratio of the GWPE at 50th percentile to the GWPE at 90th percentile. The weakest intermittency was at ~20–30 km (above the zonal mean winds of zero) over the Tibetan Plateau and Rocky Mountains in all months and over the Andes from November to March, respectively. Generally, the weakest intermittency (~0.4) occurred in the region where the key parameters were the smallest around summer. The key parameters of lognormal distribution were dominated by annual variation over the Andes throughout the height range, 8–50 km. However, the semiannual variations are also significant in the lower stratosphere over the Tibetan Plateau and Rocky Mountains. The seasonal variations in the intermittency were not as obvious as those of the key parameters. The lognormal distributions and the intermittencies derived here provide an observational constraint on the tunable parameters in GW parameterization schemes. [ABSTRACT FROM AUTHOR]

This paper examines the local and non-local climatic effects of wetter arid areas of Northwestern China (ANWC) in summer using a fully coupled climate model. In response to soil moisture increase, the local air temperature significantly decreases, and precipitation increases in summer. The wetter ANWC results in a warmer and rainless climate over the Central part of North China Plain (CNCP). While the influence of increasing soil moisture on the Tibetan Plateau (TP) precipitation is negligible due to the high altitude. A cooler climate over ANWC leads to an abnormal descending motion occurring. Meanwhile, an anomalous high pressure and an abnormal anticyclonic circulation occurs in 500 hPa over the west of ANWC. Correspondingly, a huge anomalous cyclone circulation occurs over the northeastern part of China and Mongolia, which can hinder the northward movement of the East Asian summer Monsoon (EASM) and reduce the water vapor transport into Central China Plain. As a result, the weakened EASM thus leads to rainless over CNCP. As soil moisture increases over ANWC is stronger, the magnitudes of the influence on the atmospheric field become larger. This study highlights the wetter ANWC effect on local climate and provides more information about the mechanism of wetter ANWC remote effect on non-local climate. • This paper examines the local and non-local climatic effects of wetter arid areas of Northwestern China (ANWC) in summer using a fully coupled climate model. • It finds that the wetter ANWC can result in a warmer and rainless climate over the Central part of North China Plain (CNCP) through a complex atmospheric circulation response. • A cooler climate leads to an abnormal descending motion occurring over ANWC. • A huge anomalous cyclone circulation over the northeastern part of China and Mongolia can block the East Asian summer Monsoon northward and decrease the water vapor transport into Central China Plain. • This study highlights the wetter ANWC effect on local climate and provides more information about the mechanism of wetter ANWC remote effect on non-local climate. [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]

This study applies three widely used land models (SSiB, CLM, and Noah-MP) coupled in a regional climate model to quantitatively assess their skill in preserving the imposed ± 5 °C anomalies on the initial land surface and subsurface temperature (LST/SUBT) and generating the 2-m air temperature (T2m) anomalies over Tibetan Plateau (TP) during May–August. The memory of the LST/SUBT initial anomalies (surface/soil memory) is defined as the first time when time series of the differences in daily LST/SUBT cross the zero line during the simulation, with the unit of days. The memory of the T2m anomalies (T2m memory) is defined in the same way. The ensemble results indicate that the simulated soil memory generally increases with soil depth, which is consistent with the results based on the observations with statistic methods. And the soil memory is found to change rapidly with depth above ~ 0.6–0.7 m and vary slowly below it. The land models have fairly long soil memories, with the regional mean 1.0-m soil memory generally longer than 60 days. However, they have short T2m memory, with the regional means generally below 20 days. This may bring a big challenge to use the LST/SUBT approach on the sub-seasonal to seasonal (S2S) prediction. Comparison between the three land models shows that CLM and Noah-MP have longer soil memory at the deeper layers (> ~ 0.05 m) while SSiB has longer T2m/surface memories and near-surface (≤ ~ 0.05 m) soil memory. As a result, it is difficult to say which land model is optimal for the application of the LST/SUBT approach on the S2S prediction. The T2m/surface/soil memories are various over TP, distinct among the land models, and different between the + 5 °C and − 5 °C experiment, which can be explained by both changes in the surface heat fluxes and variances in the hydrological processes over the plateau. [ABSTRACT FROM AUTHOR]

Precipitation is the key component determining the water budget and climate change of the Tibetan Plateau (TP) under a warming climate. This high-latitude region is regarded as the Third Pole of the Earth and the Asian Water Tower and influences the eco-economy of downstream regions. However, the intensity and diurnal cycle of precipitation are inadequately depicted by current reanalysis products and regional climate models (RCMs). Spectral nudging is an effective dynamical downscaling method used to improve precipitation simulations of RCMs by preventing simulated fields from drifting away from large-scale reference fields, but the most effective manner of applying spectral nudging over the TP is unclear. In this paper, the effects of spectral nudging parameters (e.g., nudging variables, strengths and levels) on summer precipitation simulations and associated meteorological variables were evaluated over the TP. The results show that using a conventional continuous integration method with a single initialization is likely to result in the overforecasting of precipitation events and the overforecasting of horizontal wind speeds over the TP. In particular, model simulations show clear improvements in their representations of downscaled precipitation intensity and its diurnal variations, atmospheric temperature and water vapor when spectral nudging is applied towards the horizontal wind and geopotential height rather than towards the potential temperature and water vapor mixing ratio. This altering to the spectral nudging method not only reduces the wet bias of water vapor in the lower troposphere of the ERA-Interim reanalysis (when it is used as the reference fields) but also alleviates the cold bias of atmospheric temperatures in the upper troposphere, while maintaining the accuracy of horizontal wind features for the simulated fields. The conclusions of this study imply how reference fields errors impact model simulations, and these results may improve the reliability of RCM results used to study the long-term regional climate change. [ABSTRACT FROM AUTHOR]

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

The Tibetan Plateau (TP) is 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 relationship between Arctic Oscillation (AO) and surface air temperature (SAT) over the Tibetan Plateau (TP) has been long debated, particularly in boreal summer. Based on the statistical analysis, this study reveals a significant interdecadal shift in the relationship between summer AO and the first mode of the summer SAT (SAT_EOF1) over the eastern TP in recent decades. Specifically, during 1979–1998, the correlation between summer AO and SAT_EOF1 was weak and insignificant, but during 1999–2018, it was strong and significant. Changes in the AO-related regional atmospheric circulations are responsible for this enhanced AO-SAT_EOF1 connection. During the latter period, the anomalous anticyclone related to AO has extended further westward from eastern China to the eastern TP, leading to the increased water vapor transport and prevalent descending over the eastern TP. As a result, there has been a decrease in cloud cover over the eastern TP, allowing more solar radiation to reach the ground surface and thus contributing to the enhanced AO-SAT_EOF1 linkage. Further analysis indicates that the phase transition of the Pacific decadal oscillation (PDO) is a crucial factor in regulating the AO-SAT_EOF1 linkage. Since the late 1990s, the PDO has transitioned from a positive to a negative phase, playing a role in the westward extension of the AO-related anomalous anticyclone over the eastern side of the TP through the Pacific-East Asian (PEA) teleconnection. Finally, the model simulation results provide conclusive evidence that the phase transition of the PDO contributes to the unstable AO-SAT_EOF1 connection. [ABSTRACT FROM AUTHOR]

The temperature rise during the growing season on the Tibetan Plateau (TP) is crucial for the local vegetation phenology and atmospheric circulation. In this study, we investigated the possible effects of soil moisture (SM) anomalies associated with the freeze–thaw process on the surface air temperature (SAT) rise during the growing season using observations and reanalysis data from 1979 to 2014. Results demonstrate that winter SM anomalies associated with the freeze–thaw process can persist until July, significantly modulating SAT rise intensity from May to July on the TP. Positive winter SM anomalies can lead to decreased in SAT in May but increased in SAT in July, thus strengthening the SAT rise from May to July. Further analysis of physical mechanisms suggest the positive winter SM anomaly leads to the increase of surface latent heat flux but the decrease of surface sensible heat flux in May, thus cooling the SAT. As July approaches, significantly increased atmospheric water vapor caused by the positive winter SM anomaly leads to the enhancement of surface downward longwave radiation, which exceeds the cooling effect of decreased sensible heat, resulting in a warmer SAT. Previous studies mainly revealed the "drier SM—higher SAT" feedback. Here we highlight that the thermal variations caused by SM anomalies related with the freeze–thaw process are complicated in the TP, with completely opposite climatic effects during different months. [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]

Precipitation is a crucial influencing factor in the global hydrological cycle and terrestrial ecosystems. Previous studies have mostly focused on the historical precipitation variations over the Tibetan Plateau (TP). However, little attention has been given to the differences between convective and stratiform precipitation under future climate change scenarios. In order to acquire the high‐resolution precipitation information over the TP, the dynamical downscaling simulation was conducted utilizing a regional climate model (Weather Research and Forecasting [WRF] model) forced with a global climate model (Community Climate System Model [CCSM]). In this study, we focus on projections of future changes in convective and stratiform precipitation over the TP. The downscaling results during a 26‐year period 1980–2005 are compared for dry season, wet season and annual mean precipitation against the gridded observation dataset. Then, the changes in the wet season convective and stratiform precipitation with warming between CCSM and WRF‐CCSM were compared in the future period 2070–2099 under two scenarios (RCP4.5 and RCP8.5). Compared with the coarse‐resolution forcing, the historical precipitation of dry season, wet season and annual mean over the TP were found to better reproduce in WRF‐CCSM simulation. WRF‐CCSM projects an opposite spatial pattern of total precipitation change between the northern and southern TP in the future under different scenarios, which were attributed to the decreased stratiform precipitation in the southern TP and the increased convective precipitation in the northern TP, contrasting with the uniform increase of total precipitation in its forcing. The surface air temperature projected in WRF‐CCSM is larger increase than in the CCSM forcing. Compared to the CCSM forcing, WRF‐CCSM projects more pronounced increase in convective precipitation in response to rapid warming, and increasingly dominates changes of total precipitation with temperature exceeds the Clausius–Clapeyron rate over the northern TP. [ABSTRACT FROM AUTHOR]

We have used bias-corrected data from CMIP6 models to drive a regional climate model and project climate on the Tibetan Plateau (TP) in the 21st century. Changes in two background fields, namely, 2-meter air temperature and total precipitation, were analyzed. The results show that the WRF simulations capture the terrain effect that cannot be represented in low-resolution models. The simulation of temperature is better in summer than in winter, while the simulated precipitation is the opposite. By the end of the 21st century, the entire TP region experiences significant warming, with an average warming of 3°C and 7°C in the SSP245 and SSP585 scenarios, respectively. The western region shows a greater warming amplitude, with a maximum of more than 10°C in the SSP585 scenario. Most regions of the TP had significant increases in precipitation by the end of the 21st century, with precipitation increasing by 90 mm and 200 mm in the two scenarios, respectively. However, in the low-altitude areas of southeastern TP, total winter precipitation is significantly reduced in the SSP585 scenario. The strengthening of the East Asian summer monsoon and westerly disturbances collectively leads to a significant increase in precipitation within the TP region. By the end of the 21st century, the average annual precipitation in the TP is projected to reach approximately 600 millimeters. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is an important component of the global climate system, while the characteristics of its climate are poorly represented in most regional climate models at coarse resolutions. In this study, a 20-year (2000–2019) dynamical downscaling simulation at the gray-zone resolution (9 km) using the WRF model driven by the ERA5 reanalysis is conducted over the TP. Based on comparisons against in-situ observations and the Integrated Multi-satellite Retrievals for GPM (IMERG) version 6 satellite precipitation product, the assessment of basic climate variables, such as near-surface air temperature (T2m) and precipitation, is performed to evaluate the model's performance and understand its added value better. Results show that both WRF and ERA5 can successfully reproduce the spatial patterns of annual mean and seasonal mean surface air temperature. However, significant cold and wet biases are found especially over the southeastern TP in ERA5, which are greatly improved in WRF with reduced RMSEs. Not only the climatological characteristics, but also the inter-annual variability and seasonal variation of T2m and precipitation are well captured by WRF which reduces the cold and wet biases especially in winter and summer compared to ERA5, respectively. Besides, at daily scale, the overestimation of precipitation in WRF and ERA5 is mainly caused by the overestimated precipitation frequency when precipitation intensity changed slightly. Furthermore, WRF outperforms ERA5 in capturing the diurnal variation of precipitation with more realistic peak time in all sub-regions over the TP. Further investigation into the mechanism of model bias reveals that less simulated snow cover fraction plays a crucial role in increasing the surface net energy by affecting surface albedo over the southeastern TP in WRF, leading to higher T2m. In addition, less water vapor transport from the southern boundary of TP leads to reduced wet bias in WRF, indicating that the added value in dynamical downscaling at gray-zone resolution is obtained by representing water vapor transport more realistically. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) exerts strong powerful thermal forcing, which plays a vital role in influencing weather–climate variations in Asia and even the Northern Hemisphere. However, the causes of thermal variation over the TP have not been fully revealed. Here, the role of winter soil moisture (SM) in subsequent summer thermal anomalies on the TP was investigated through multisource datasets for the period 1979–2014. Results indicate a significant positive relationship (r = 0.52) between winter SM and subsequent summer-mean surface air temperature (SAT). Further investigations show that more (less) winter SM results in abundant (deficient) atmospheric water vapor in subsequent summer owing to its persistence. Furthermore, Earth’s surface energy budget equation confirms that strengthened (weakened) surface downward longwave radiation caused by increased (decreased) water vapor is the dominant factor leading to SAT variations, even more significant for nocturnal SAT. The winter SM–atmospheric temperature positive relationship can extend from the surface to 200 hPa over the TP. In addition, the enhanced (weakened) atmospheric latent heat release associated with increased (decreased) water vapor content may be another important factor contributing to changes in atmospheric temperatures over the TP. Therefore, our results contribute to a better understanding of the effect of land–surface processes on thermal anomalies over the TP. Significance Statement Understanding the causes of thermal anomalies over the Tibetan Plateau (TP) is crucial for weather and climate variations, but the role of winter soil moisture (SM) in subsequent summer thermal effects is largely unknown. This study investigated the relationship between winter SM and thermal anomalies in subsequent summers on the TP. Results show that the above (below)-normal winter SM will cause warm (cold) atmospheric temperatures in the subsequent summer. The above (below)-normal winter SM anomalies bring increased (decreased) atmospheric water vapor in summer owing to its persistence, resulting in strengthened (weakened) downward longwave radiation and atmospheric latent heat release to heat (cool) the atmosphere. [ABSTRACT FROM AUTHOR]

The influence of mid–high-latitude intraseasonal variability (ISV) on the occurrence frequency of the Northeast China cold vortex (NCCV) in early summer was examined through statistical analysis and thermal–dynamic diagnostics. A multivariable empirical orthogonal function (MVEOF) was employed to extract the thermal–pressure coupled ISV mode. Our results show that the geopotential height and air temperature over the NCCV active region exhibit a statistically significant intraseasonal periodicity of 20–60 days. The dominant ISV mode features a westward-propagated zonal dipole pattern, which is generated over the Lake Baikal region and triggered by intraseasonal wave energy accumulation. By dividing the ISV cycle into eight phases, it is found that more NCCVs with a large scope occur in phases 5–8 than those in phases 1–4. The positive (negative) geopotential height and air temperature tendencies in phases 1–4 (5–8) act to suppress (facilitate) the NCCV activity. The thermodynamic tendency budget and scale decomposition reveal that when an anomalous intraseasonal cyclonic circulation propagates westward from Lake Baikal to the Ural Mountains, the anomalous southwesterly transports mean negative vorticity from the north side of the Tibetan Plateau to Northeast Asia and transports mean warm air temperature from low latitudes to high latitudes, leading to the positive geopotential height and air temperature tendencies and thereby restraining the NCCV activity. The opposite is also true for the facilitation of the NCCV modulated by the negative geopotential height and air temperature tendencies. Significance Statement: The purpose of this study is to better understand the factors controlling the Northeast China cold vortex (NCCV) activity in early summer. It is important because influences of the subtropical monsoonal circulation are usually confined to southern China in this season and the anomalous atmospheric circulation from the mid–high latitudes plays a more important role in the generation of the NCCV. Our results provide a guide on how intraseasonal variability at mid–high latitudes controls the occurrence frequency of the NCCV and highlight the process of thermal and dynamical modulation in the NCCV. [ABSTRACT FROM AUTHOR]

The southern Tibetan Plateau (TP) is snow covered during cold season but exhibits faster snow melting in early summer. Using in situ observations and improved satellite-derived data, the present study indicates that the snow depth (SD) over the southern TP exhibits distinction characteristics between late spring (i.e., P1: April 16th–May 15th) and early summer (i.e., P2: May 16th–June 14th). In terms of climate states, the snow melting rate over the southern TP in P2 is faster than that in P1. The acceleration of snow melting during P2 is mainly found over high elevation areas caused by the increase of local air temperature. Diagnoses of the thermodynamic equation further demonstrate that the warming over the southern TP during the two periods is mainly attributed to the meridional temperature advection and diabatic heating in situ. On the interannual time scale, the SD over the southern TP is closely related to diabatic heating over South Asia. During P1, the diabatic cooling from the southern Bay of Bengal eastward to the western South China Sea suppresses convection over the Bay of Bengal and southern TP and has resulted in an upper-level anomalous cyclone and cold temperature anomalies from the surface to 200 hPa over the southern TP, favoring the above-normal SD over the southern TP. On the other hand, SD over the southern TP in P2 is closely related to diabatic cooling over the northern Indochina Peninsula and diabatic heating over the southern China. But we could not prove that these diabatic heating anomalies can affect the SD over the southern TP by modulating local surface air temperature. This may be limited by the quality of the data and the simulation capability of the simple model. [ABSTRACT FROM AUTHOR]

Subseasonal forecasts have recently attracted widespread interest yet remain a challenging issue. A statistical Kalman filter pattern projection method (KFPPM), which absorbs the projection conception of the raw covariance pattern projection (COVPPM) and the adaptive adjustments of the Kalman filter, is proposed to calibrate the single-model forecasts of the daily maximum and minimum temperatures (Tmax and Tmin) for lead times of 8-42 days over East Asia in 2018 derived from the UKMO control (CTL) forecast. The Kalman filter-based gridly calibration (KFGC) is carried out in parallel as a benchmark, which could improve the forecast skills to a certain extent. The COVPPM effectively calibrates the temperature forecasts at the early stage and displays better performances than the CTL and KFGC. However, with the growing lead times, it shows speedily decreasing skills and can no longer produce positive adjustments over the areas outside the plateaus. By contrast, the KFPPM consistently outperforms the other calibrations and reduces the forecast errors by almost 1.0° and 0.5°C for Tmax and Tmin, respectively, both retaining superiorities to the random climatology benchmark till the lead time of 24 days. The optimization of KFPPM maintains throughout the whole range of the subseasonal time scale, showing the most conspicuous improvements distributed over the Tibetan Plateau and its surroundings. Though the postprocessing procedures are more skillful in calibrating Tmax forecasts than Tmin forecasts, the Tmax forecasts are still characterized by lower skills than the latter. Case experiments further demonstrate the abovementioned features and imply the potential capability of KFPPM in improving forecast skills and disaster preventions for extreme temperature events. [ABSTRACT FROM AUTHOR]

Previous studies suggest that boreal summer intraseasonal variations along the subtropical westerly jet (SJ), featuring quasi-biweekly periodicity, frequently modulate downstream subseasonal variations over East Asia (EA). Based on subseasonal hindcasts from six dynamical models, this study discovered that the leading two–three-week prediction skills for surface air temperature (SAT) are significantly higher in summer with stronger intraseasonal oscillation along the SJ, which are best demonstrated over the eastern Tibetan Plateau, Southwest Basin, and North China. The reasons are that the enhanced quasi-biweekly wave and its energy dispersion along the SJ cause more regular quasi-biweekly periodic variations of downstream SAT, which potentially increase regional predictability. This study suggests that the strengthened intraseasonal periodic signals along the SJ would enhance the subseasonal predictability in downstream regions, which could provide a window of opportunity for achieving better subseasonal prediction for EA SAT. [ABSTRACT FROM AUTHOR]

Both South Asia and East Asia are the most polluted regions of the world. Unlike East Asia, the aerosol optical depth (AOD) over South Asia keeps increasing for all recent years, which calls for more attention. This study investigates the impacts of anthropogenic emissions over South Asia on the downstream regional climate during spring with the Community Earth System Model 2 (CESM2). The model results suggest that South Asian pollutants have significant impacts on East Asian spring climate, and the impacts could be even larger than locally emitted aerosols. Two possible dynamical pathways (i.e., the northern and the southern pathways) bridging South Asian aerosol forcing and East Asian climate are proposed, and both ways are associated with the black carbon (BC)-induced climate feedbacks surrounding the Tibetan Plateau (TP). The northern pathway is mainly due to the TP warming induced by the BC snow darkening effect (SDE), which significantly reduces the surface air temperature (SAT) over northern East Asia. BC-induced TP warming increases the meridional thermal gradient and accelerates the midlatitude jet stream, which favors the cold-air advection over northern East Asia. The southern pathway is associated with the BC "elevated heat pump" hypothesis, which mainly affects the precipitation in southern East Asia. BC from South Asia accumulates near the south slope of TP, inducing an abnormal ascending motion near the Bay of Bengal. A compensating anomalous sinking motion is then forced in South China, which suppresses the precipitation there. A primary observational analysis is also performed to verify both dynamical pathways. [ABSTRACT FROM AUTHOR]

The vegetation–temperature relationship is crucial in understanding land–atmosphere interactions on the Tibetan Plateau. Although many studies have investigated the connections between vegetation and climate variables in this region using remote sensing technology, there remain notable gaps in our understanding of vegetation–temperature interactions over different timescales. Here, we combined site-level air temperature observations, information from the global inventory modeling and mapping studies (GIMMS) dataset, and moderate-resolution imaging spectroradiometer (MODIS) products to analyze the spatial and temporal patterns of air temperature, vegetation, and land surface temperature (LST) on the Tibetan Plateau at annual and seasonal scales. We achieved these spatiotemporal patterns by using Sen's slope, sequential Mann–Kendall tests, and partial correlation analysis. The timescale differences of vegetation-induced LST were subsequently discussed. Our results demonstrate that a breakpoint of air temperature change occurred on the Tibetan Plateau during 1994–1998, dividing the study period (1982–2013) into two phases. A more significant greening response of NDVI occurred in the spring and autumn with earlier breakpoints and a more sensitive NDVI response occurred in recent warming phase. Both MODIS and GIMMS data showed a common increase in the normalized difference vegetation index (NDVI) on the Tibetan Plateau for all timescales, while the former had a larger greening area since 2000. The most prominent trends in NDVI and LST were identified in spring and autumn, respectively, and the largest areas of significant variation in NDVI and LST mostly occurred in winter and autumn, respectively. The partial correlation analysis revealed a significant negative impact of NDVI on LST during the annual scale and autumn, and it had a significant positive impact during spring. Our findings improve the general understanding of vegetation–climate relationships at annual and seasonal scales. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau is a sensitive area of global climate change, where few conventional observations exist. Satellite AMSU-A microwave temperature sounding observations of brightness temperature (TB) are located in the absorption band of oxygen, which is well mixed in the atmosphere, and have microwave frequencies varying from 50.3 to 57.6 GHz. Therefore, AMSU-A TB observations at different sounding channels reflect atmospheric temperatures at different altitudes. In this study, AMSU-A TB observations during 1998-2020 from five polar-orbiting environmental meteorological satellites (POESs) are employed to investigate the interdecadal warming/cooling trends over the Tibetan Plateau. A limb correction is first applied to all AMSU-A channels before using TB observations at all fields of view for examining geographic distributions and differences of global warming/cooling trends. It is found that interdecadal trends of uppertropospheric warming and stratospheric cooling are stronger over the Qinghai Tibetan Plateau than its eastern plain areas. An interdecadal variation of the annual cycle over the Tibetan Plateau is an important factor for the enhanced tropospheric warming trend. We also applied a different approach of significance testing that is based on counting signs of local trends (sign test) and confirmed that the detected significant local trends were not a result of chance. In addition, high-frequency noise in TB observations with periods smaller than annual and semiannual oscillations do not affect the climate trends of TB very much, but significantly reduced the uncertainty of the TB trends over the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

This paper discusses the transport of water vapour in the tropopause region over the Tibetan Plateau, where high water vapour mixing ratio is observed during the Northern Hemisphere (NH) summer-monsoon period. The Weather Research and Forecasting (WRF) model has been used to study the two contrasting cases i.e. when water vapour is high and low at 100 hPa (close to tropopause). The composite distribution of water vapour shows two key results (a) the water vapour appears be transported to the Tibetan plateau region from the extra-tropics under the influence of stronger northwesterly winds and (b) the vertical water vapour flux is relatively higher over the Tibetan Plateau region during the period when water vapour amount at this level is higher. This suggests that in addition to the horizontal transport from the extra-tropics, the local convection occurring over the Tibetan Plateau also contributes to the increase in the water vapour over this region. The differences in the circulation during high and low water vapour cases suggest that a cyclonic circulation difference over the central Indian region limit the transport of water vapour from the Bay of Bengal to the Tibetan Plateau region. [ABSTRACT FROM AUTHOR]

Most state-of-the-art climate models substantially underestimate the near-surface air temperature (SAT) over the Tibetan Plateau (TP), especially for the cold season. While previous studies have attributed this cold bias to local factors such as the elevation difference, coarse resolution, and excessive snow cover, this investigation addresses the potential contributions of the systematic bias of tropical sea surface temperature (SST) to the TP cold bias. Experiments with the NCAR Community Atmosphere Model demonstrate that tropical SST bias results in an apparent cold bias over the TP, especially in boreal winter, and explains about 40% of the deviation in multi-model mean SAT over the TP relative to station observations. Forced by the tropical SST bias, heat flux exhibits an anomalous divergence over the plateau, causing a cooling center in the mid- and lower-troposphere over the TP. This atmospheric cooling in turn leads to a reduction of the downward longwave radiative fluxes reaching the surface, less energy supply, and thus a cold bias over the TP. [ABSTRACT FROM AUTHOR]

Tibetan Plateau (TP) precipitation is affected by anomalous circulation systems in both the tropics and mid-latitudes, due to the TP's unique geographical location. By using observational, reanalysis, and CMIP6 model datasets, this study reveals the individual and joint effects of the Indian Ocean Dipole (IOD) and Silk Road pattern (SRP) on the interannual variability of TP precipitation in September. In the positive IOD phase, the zonal gradient of the sea-surface temperature anomalies (SSTAs) drives a Gill-type response with an anticyclonic anomaly over the Indian subcontinent and Bay of Bengal. To the north, anomalous westerlies induce a shallow trough, and the associated anomalous southwesterlies transport moisture to the southeastern TP, resulting in surplus precipitation there. Meanwhile, the westerly jet disturbances over the North Atlantic excite an SRP-like pattern, resulting in a baroclinic structure in northern India with the upper (lower) tropospheric anomalous anticyclone (cyclone) over west-central Asia (northern India). The anomalous southwesterlies to the east of the low-level cyclone transport abundant moisture to the southeastern TP, which results in increased precipitation there. The joint effects of IOD and SRP can explain nearly 52% of the TP precipitation anomaly, exceeding the contribution of IOD (19%) and SRP (27%) alone. Our results highlight the necessity of considering the joint effects of drivers in the tropics and mid-latitudes, providing a basis for more accurate simulations and predictions of TP precipitation. [ABSTRACT FROM AUTHOR]

The ability of climate models to represent extratropical storm tracks is vital to provide useful projections. In previous work, the representation of the extratropical storm tracks in the Northern Hemisphere was found to have improved from phase 5 to phase 6 of the Coupled Model Intercomparison Project (CMIP). Here we investigate the remaining and persistent biases in models from phase 6 of CMIP, by contrasting the atmosphere-only simulations (AMIP6) with the historical coupled simulations (CMIP6). The comparison of AMIP6 and CMIP6 simulations reveals that biases in sea surface temperatures (SSTs) in the coupled simulations across the North Pacific Ocean in winter modify the atmospheric temperature gradient, which is associated with an equatorward bias of the storm track. In the North Atlantic Ocean, cyclones do not propagate poleward enough in coupled simulations, which is partly driven by cold SSTs to the south of Greenland, decreasing the latent heat fluxes. In summer, excessive heating across central Asia and the Tibetan Plateau reduces the local baroclinicity, causing fewer cyclones to form and propagate from eastern China into the North Pacific in both the coupled and atmosphere-only simulations. Several of the biases described in the coupled models are reduced considerably in the atmosphere-only models when the SSTs are prescribed. For example, the equatorward bias of the North Pacific storm track is reduced significantly. However, other biases are apparent in both CMIP6 and AMIP6 (e.g., persistent reduction in track density and cyclogenesis over eastern Asia in summer), which are associated with other processes (e.g., land surface temperatures). [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) plays a dominant role in the surface energy budget (SEB) and hydrological cycling. Thermal infrared (TIR) remote sensing is the primary method of estimating LST globally. However, cloud cover leaves numerous data gaps in satellite LST products, which seriously restricts their applications. Efforts have been made to produce gap-free LST products from polar-orbiting satellites (e.g., Terra and Aqua); however, satellite data from limited overpasses are not suitable for characterizing the diurnal temperature cycle (DTC), which is directly related to heat waves, plant water stress, and soil moisture. Considering the high temporal variability in LST and the importance of the DTC, we refined the SEB-based cloudy-sky LST recovery method by improving its feasibility and efficiency and produced a global hourly, 5 km, all-sky land surface temperature (GHA-LST) dataset from 2011 to 2021. The GHA-LST product was generated using TIR LST products from geostationary and polar-orbiting satellite data from the Copernicus Global Land Service (CGLS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). Based on ground measurements at the 201 global sites from the Surface Radiation Budget (SURFRAD), Baseline Surface Radiation Network (BSRN), Fluxnet, AmeriFlux, Heihe River basin (HRB), and Tibetan Plateau (TP) networks, the overall root-mean-square error (RMSE) of the hourly GHA-LST product was 3.31 K, with a bias of -0.57 K and R2 of 0.95. Thus, this product was more accurate than the clear-sky CGLS and MODIS MYD21C1 LST samples. The RMSE value of the daily mean LST was 1.76 K. Validation results at individual sites indicate that the GHA-LST dataset has relatively larger RMSEs for high-elevation regions, which can be attributed to high surface heterogeneity and input data uncertainty. Temporal and spatial analyses suggested that GHA-LST has satisfactory spatiotemporal continuity and reasonable variation and matches the reference data well at hourly and daily scales. Furthermore, the regional comparison of GHA-LST with other gap-free hourly datasets (ERA5 and Global Land Data Assimilation System, GLDAS) demonstrated that GHA-LST can provide more spatial texture information. The monthly anomaly analysis suggests that GHA-LST couples well with global surface air temperature datasets and other LST datasets at daily mean and minimum temperature scales, whereas the maximum temperature and diurnal temperature range of LST and air temperature (AT) have different anomalous magnitudes. The GHA-LST dataset is the first global gap-free LST dataset at an hourly, 5 km scale with high accuracy, and it can be used to estimate global evapotranspiration, monitor extreme weather, and advance meteorological forecasting models. GHA-LST is freely available at 10.5281/zenodo.7487284 (Jia et al., 2022b) and http://glass.umd.edu/allsky%5fLST/GHA-LST (last access: 10 February 2023; Jia et al., 2022c). [ABSTRACT FROM AUTHOR]

Considered as a sensitive indicator of climate change, lake ice phenology can have significant influences on regional climate by affecting lake-atmosphere energy and water exchange. However, in situ measurements of ice phenology events are quite limited over high-elevation lakes on the Tibetan Plateau, where satellite monitoring can make up such deficiency. In this study, by a combination of AMSR-E (2002–2011) and AMSR-2 (2012–2021) passive microwave data, MODIS optimal products and in situ measurements of temperature profiles in four lakes, the ice phenology events of 40 high-elevation large lakes were derived and their inter-annual trends and influencing factors were analyzed. The freeze-up start date (FUS) mainly occurs in November-December with an average date of 9 December and the break-up end date (BUE) is concentrated in April-May with a multi-year average of 5 May. Under climate warming, 24 of the 34 (70.6%) lakes show delayed FUS at an average trend of 0.35 days/year, and 7 (20.6%) lakes show advanced BUE (rate of change CR = −0.17 days/year). The average ice coverage duration (ID) was 147 days, and 13 (38.2%) lakes shortened ID at an average rate of −0.33 days/year. By synthesizing other ice phenology products, we obtained the assembled products of lake ice phenology, and found that air temperature dominates during the freeze-thaw process, with a higher dependence of BUE than that of FUS on air temperature. [ABSTRACT FROM AUTHOR]

Surface air temperature (SAT) is a key indicator of global warming and plays an important role in glacier melting. On the Tibetan Plateau (TP), there exists a large number of glaciers. However, station SAT observations on these glaciers are extremely scarce, and moreover the available ones are characterized by short time series, which substantively hinder our deep understanding of glacier dynamics due to climate changes on the TP. In this study, an ensemble learning model is constructed and trained to estimate glacial SATs with a spatial resolution of 1 km × 1 km from 2002 to 2020 using monthly MODIS land surface temperature products and many auxiliary variables, such as vegetation index, satellite overpass time, and near-surface air pressure. The satellite-estimated glacial SATs are validated against SAT observations at glacier validation stations. Then, long-term (1961–2020) glacial SATs on the TP are reconstructed by temporally extending the satellite SAT estimates through a Bayesian linear regression. The long-term glacial SAT estimates are validated with root mean squared error, mean bias error, and determination coefficient being 1.61 ∘ C, 0.21 ∘ C, and 0.93, respectively. The comparisons are conducted with other satellite SAT estimates and ERA5-Land reanalysis data over the validation glaciers, showing that the accuracy of our satellite glacial SATs and their temporal extensions are both higher. The preliminary analysis illustrates that the glaciers on the TP as a whole have been undergoing fast warming, but the warming exhibits a great spatial heterogeneity. Our dataset can contribute to the monitoring of glaciers' warming, analysis of their evolution, etc. on the TP. The dataset is freely available from the National Tibetan Plateau Data Center at 10.11888/Atmos.tpdc.272550 (Qin, 2022). [ABSTRACT FROM AUTHOR]

In situ measurements are the most important basis of obtaining precise meteorological datasets. However, it is difficult to accurately extrapolate the plausible meteorological field in certain regions based on in situ measurements alone, especially in areas with complex topography like the Tibetan Plateau (TP). Gridded products, remote sensing, and data assimilation technique overcome this problem but they have their own weaknesses, such as low resolution, huge computation, and time‐consuming. Here we applied the state‐of‐the‐art generative adversarial networks (GAN) in image inpainting to construct the surface temperature over the TP combined with high‐resolution China Meteorological Forcing Dataset (CMFD) air temperature product and in situ observations. In this study, the surface air temperature at 2 m dataset with grids of 0.1° over the TP from 1979 to 2020 based on GAN‐based model have been generated, which can capture the spatial patterns and trends of surface air temperature over the TP. Moreover, the GAN‐based daily temperature has higher correlation coefficients (0.99) and lower root‐mean‐square errors (1.06°C) than CMFD (0.98, 1.43°C) and reanalysis products when compared with in situ observations. Finally, the temperature fields over the TP from 2019 to 2020 is constructed, whereas CMFD is only available from 1979 to 2018. The results reflect the advantages of GAN on big‐data computation and fully utilizing effective information over the TP, and GAN‐based temperature dataset can be used to detect climate change over the region. This study demonstrated the potential and applicability of artificial intelligence for developing and extending practicable high‐resolution meteorological dataset over regions with sparse stations and rugged topography. [ABSTRACT FROM AUTHOR]

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

Understanding the spatial–temporal changes in glacier mass balance and associated drivers on the Tibetan Plateau (TP) is important for predicting future water supplies and glacier-related hazards. However, the comparative study of changes in glacier mass balance in different regions of the same glacierized massif on the TP remains scarce. Combining the reconstructed detailed mass balance time-series from 1970 to 2015 for Ningchan No.1 Glacier in the eastern Qilian Mountains and Qiyi Glacier in the western Qilian Mountains using the energy and mass balance model in this work with the published mass balance data from different glaciers, we find that interannual changes in glacier mass balance are broadly similar in different regions of the Qilian Mountains. These interannual changes are primarily driven by variations in ablation-season (June–September) air temperature (Ta), which impact albedo and melt by changing snowfall and incoming longwave radiation (Lin). We link such interannual mass balance variability to the combination of changes in atmospheric circulation over Europe and changes in sea surface temperature (SST) in the Northwest Pacific during the ablation season which can cause the changes in Ta across the Qilian Mountains. In addition, we find a trend of increasingly negative glacier mass balance across the Qilian Mountains from 1970–1994 compared to 1995–2015. This interdecadal trend is driven by higher ablation-season Ta through increasing Lin and through increasing precipitation falling as rain. Lastly, higher glacier mass loss in the east than in the west Qilian Mountains from 1970–1994 and 1995–2015 was mainly caused by lower glacier area-altitude distribution, as well as a reduction in ablation-season precipitation in the eastern Qilian Mountains. [ABSTRACT FROM AUTHOR]

Previous studies have revealed that the Madden–Julian oscillation (MJO) can exert a profound impact on the surface air temperature (SAT) anomalies over East Asia during winter (December–February). In this study, it is found that such MJO-related winter SAT anomalies can be modulated by the interannual variability of the Tibetan Plateau snow cover (TPSC). During the excessive TPSC (ETPSC) winters, the MJO-related East Asian SAT anomalies in phase 3 are significantly colder than normal. However, during the reduced TPSC (RTPSC) winters, such SAT anomalies are close to normal. A linear baroclinic model is used to examine the possible physical mechanisms. During the ETPSC winters, the more energetic MJO can excite stronger poleward Rossby waves and intensify the upper level cyclonic anomalies over East Asia and lead to the significantly colder SAT anomalies. While during the RTPSC winters, the suppressed MJO convection excites weaker poleward Rossby waves and cannot make colder SAT anomalies over East Asia. The numerical evidences also show that the variation of the mean state could affect the teleconnections but it does not benefit a stronger Rossby wave train over East Asia in ETPSC winters. These results confirm that the TPSC can exert a profound modulation effect on the MJO teleconnection and further impact on the winter SAT anomalies over East Asia. [ABSTRACT FROM AUTHOR]

Estimates of the permafrost-climate feedback vary in magnitude and sign, partly because permafrost carbon stability in warmer-than-present conditions is not well constrained. Here we use a Plio-Pleistocene lacustrine reconstruction of mean annual air temperature (MAAT) from the Tibetan Plateau, the largest alpine permafrost region on the Earth, to constrain past and future changes in permafrost carbon storage. Clumped isotope-temperatures (Δ47-T) indicate warmer MAAT (~1.2 °C) prior to 2.7 Ma, and support a permafrost-free environment on the northern Tibetan Plateau in a warmer-than-present climate. Δ47-T indicate ~8.1 °C cooling from 2.7 Ma, coincident with Northern Hemisphere glacial intensification. Combined with climate models and global permafrost distribution, these results indicate, under conditions similar to mid-Pliocene Warm period (3.3–3.0 Ma), ~60% of alpine permafrost containing ~85 petagrams of carbon may be vulnerable to thawing compared to ~20% of circumarctic permafrost. This estimate highlights ~25% of permafrost carbon and the permafrost-climate feedback could originate in alpine areas. The stability of permafrost carbon is poorly understood. Here the authors use Plio-Pleistocene clumped isotope reconstructions from the Tibetan Plateau and climate simulation to determine that ~85 petagrams of alpine carbon is vulnerable to thawing. [ABSTRACT FROM AUTHOR]

The last millennium (LM, 1000–1850 AD) is crucial for studying historical climate change on decadal to multidecadal timescales. The summer surface air temperature (SAT) evolutions on regional scales (e.g. over China) are more uncertain than the globe/Northern Hemisphere, especially in response to external forcing factors and internal climate variability. Here, we provide one‐signal (full‐forcing) fingerprints of summer SAT in China derived from three large ensemble model archives with a multi‐proxy reconstruction during the LM, Little Ice Age (LIA, 1451–1850 AD), and Medieval Climate Anomaly (MCA, 1000–1250 AD), respectively. Our results show that (a) SATs in the northeast, southeast, northwest, and Tibetan Plateau (TP) regions of China show evident decreasing trends during the LM. External forcing response from all model archives agrees with the regional SAT reconstruction but underestimates variability in northwest China at the multidecadal timescale. (b) During the LIA, the summer regional SAT exhibits a cold condition in the reconstruction and simulations, especially in the northeast and northwest regions of China. External forcing responses in most model archives are the dominant factor on multidecadal SAT evolutions in the southeast, northeast, and TP regions of China and decadal SAT evolutions in northwest China. (c) During the MCA, detection and attribution of SAT shows that internal climate variability dominates in southeast, northeast, and TP regions of China, but external forcing dominates in northwest China at decadal to multidecadal timescales. These results contribute to a better understanding of the causes and mechanisms of regional climate change. [ABSTRACT FROM AUTHOR]

Under global warming, the permafrost-underlain headwater catchments of the Tibetan Plateau have undergone extensive permafrost degradation and changes in precipitation characteristics, which may substantially alter the riverine suspended sediment and riverine solute fluxes. However, these fluxes and their influencing factors in such catchments are poorly understood. We studied the suspended sediment and solute fluxes in a permafrost-underlain headwater catchment on the northeastern Tibetan Plateau, based on comprehensive measurements of various water types in spring and summer in 2017. The daily flux of suspended sediment in spring was close to that in summer, but heavy rainfall events following a relatively long dry period made the largest contribution to the suspended sediment fluxes in summer. The riverine solute flux (in tons) was 12.6% and 27.8% of the suspended sediment flux (in tons) in spring and summer, indicating the dominating role of physical weathering in total material exportation. The snowmelt mobilized more suspended sediment fluxes and fewer solutes fluxes than summer rain, which may be due to the meltwater erosion and freeze–thaw processes in spring and the thicker thawed soil layer and better vegetation coverage in summer, and the longer contact time between the soil pore water and the soil and rock minerals after the thawing of frozen soil. The input of snowmelt driven by higher air temperatures in spring and the direct input of rainfall in summer would both act to dilute the stream water; however, the supra-permafrost water, with high solute contents, recharged the adjacent streamflow as frozen soil seeps and thus moderated the decrease in the riverine solute content during heavy snowmelt or rainfall events. With the permafrost degradation under future global warming, the solute fluxes in permafrost-underlain headwater catchments may increase, but the suspended sediment flux in spring may decrease due to the expansion of discontinuous permafrost areas and active layer thickness. [ABSTRACT FROM AUTHOR]

The lake surface water temperature (LSWT) on Tibetan Plateau (TP) is sensitive to climate change. Based on a 1‐D lake model, we have investigated the interdecadal variation and long‐term trend of LSWT in Lake Nam Co (LNC) on TP during 1980–2018 and quantified the relative contributions of atmospheric factors to the LSWT trend. Results show LNC was warmed with a rate of 0.29°C decade−1, which is smaller than the warming of ambient air (0.45°C decade−1). The weakened wind speed, rising air temperature, increased downward longwave radiation, and decreased shortwave radiation contributed about 35%, 30%, 20%, and −15% of the estimated long‐term LSWT trend during 1980–2018, respectively. The contribution rate of 32.5% was from the interactions among all forcing variables. The primary warming was completed before 1997 (0.30°C decade−1) and was followed by a hiatus that the LSWT jumped to a warm level with a slightly negative trend (−0.08°C decade−1) after 1997. During this hiatus, the wind speed recovered from decrease and the deceleratingly increased downward longwave radiation slowed down the LNC warming. Particularly, the specific humidity shifted from increasing to decreasing trend played a key role in the hiatus of LNC warming after 1997, despite its slight contribution (−2.5%) to the LSWT trend during 1980–2018. The results showed the particularity of warming for a TP lake compared to the other ice‐covered lakes worldwide and provided a quantitative perspective for understanding the relative contributions of atmospheric factors to the long‐term trend of LSWT. Key Points: As an ice‐covered lake, Lake Nam Co (LNC) warmed with a smaller rate than the local surface air temperature during 1980–2018The interdecadal shift of surface specific humidity played a key role in the hiatus of LNC warming after 1997The individual and cross contributions of different atmospheric factors to the long‐term trend of surface water temperature are quantified [ABSTRACT FROM AUTHOR]

Ecosystem carbon balance might be affected by the variability of seasonal distribution of precipitation under global climate change. Using the eddy covariance (EC) technique, long-term observations of ecosystem net CO2 exchange (NEE) were acquired over Lijiang alpine meadow in the southeastern Tibetan Plateau from January 2014 to August 2019. During the wet season (from June to October), Lijiang meadow functioned as a carbon sink (− 37.6 ± 22.5 g C m−2 month−1), while in dry season, the meadow varied between a weak carbon source and sink with an average monthly NEE of − 3.9 ± 11.9 g C m−2 month−1. Monthly CO2 fluxes were mainly controlled by air temperature and soil water content. A large annual variation of CO2 uptake was observed. The annual NEE was − 140.3 g C m−2 year−1 in 2014 while − 247.0 g C m−2 year−1 in 2016. Correspondingly, the precipitation in wet season accounted 90% of annual precipitation in 2014 and 74% of that in 2016 despite the annual precipitation was larger than 1200 mm in both years. More precipitation in dry season can lead to longer period of net CO2 uptake, while more precipitation concentrated in wet season depressed the meadow's light response through the decrease of the magnitude of light-saturated net CO2 exchange (NEEsat) at the onset and the end of growing season. [ABSTRACT FROM AUTHOR]