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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]

During the past few decades, the climate over the entire TP changed obviously with general warming and the decreasing trends in wind speed and air humidity. As an important hydrological process of mass losses on the TP glaciers, especially during the cold period, sublimation may be influenced deeply by the climate changes. Therefore, it is imperative to identify the crucial factors controlling and limiting glacier sublimation and analyze its possible changes in the future. The sublimation on a flat‐topped glacier of TP was found to be more intense in spring (0.41 mm d−1) and autumn (0.34 mm d−1) and weak in winter (0.27 mm d−1) and summer (0.16 mm d−1). At yearly scale, sublimation was most sensitive to the surface temperature, followed by air temperature and humidity, and was relatively insensitive to wind speed. However, the main influencing factor was air humidity during summer, showing a strong inhibition on sublimation. The very low surface temperature was the most crucial variable limiting winter sublimation with the highest sensitivity coefficient than other variables. Current sublimation was also found to be more sensitive to the increasing temperature than the decreased air humidity and wind speed. If the climate trends continue, and the glacier climate has the relatively consistent change trend with that of entire TP, glacier sublimation will be more likely to increase, especially during winter. Plain Language Summary: The climate warming trend in the TP has been found to be more sensitive and accelerated since the end of last century. Our study found that, on the August‐one glacier, the very high air humidity and low surface temperature were the most crucial variables limiting summer and winter sublimation, respectively. The glacier sublimation was significantly more sensitive to the surface and air temperature than air humidity and wind speed at yearly scale. With a general warming and the decreasing trends in wind speed and air humidity over the entire TP, sublimation will be more likely to increase as the temperature rises on this glacier, especially during winter. Key Points: Very high air humidity and low surface temperature were the most crucial variables limiting summer and winter sublimation, respectivelyGlacier sublimation was significantly more sensitive to the surface and air temperature than air humidity and wind speed at yearly scaleUnder climate warming, sublimation will be more likely to increase as the temperature rises on this glacier, especially during winter [ABSTRACT FROM AUTHOR]

Solar radiation‐topography interaction plays an important role in surface energy balance over the Tibetan Plateau (TP). However, the impacts of such interaction over the TP on climate locally and in the Asian regions remain unclear. This study uses the Energy Exascale Earth System Model (E3SM) to evaluate the regional and teleconnected impacts of solar radiation‐topography interaction over the TP. Land‐atmosphere coupled experiments show that topography regulates the surface energy balance, snow processes, and surface climate over the TP across seasons. Accounting for solar radiation‐topography interaction improves E3SM simulation of surface climate. The winter cold bias in air temperature decreases from −4.57 to −3.79 K, and the wet bias in summer precipitation is mitigated in southern TP. The TP's solar radiation‐topography interaction further reduces the South and East Asian summer precipitation biases. Our results demonstrate the topographic roles in regional climate over the TP and highlight its teleconnected climate impacts. Plain Language Summary: The Tibetan Plateau (TP) is characterized by high elevation and complex topography. Interaction between solar radiation and the undulating topography has important impacts on the regional surface energy balance and hydrologic cycle. Here we use Earth System Model simulations to show the local and remote impacts of the TP's solar radiation‐topography interaction on the surface climate of the Asian regions. Such interaction overall increases the air temperature especially in winter over the TP and reduces the summer precipitation in southern TP. Teleconnectedly, the interaction further alters the precipitation patterns in South and East Asia, by altering the atmospheric circulation that influences moisture transport and clouds. Accounting for such interaction generally improves the model performance when benchmarked against observations. These findings underscore the important roles of the TP's solar radiation‐topography interaction in modulating the climate of the local and remote Asian regions. Key Points: Solar radiation‐topography interaction over the Tibetan Plateau (TP) increases annual average regional near‐surface air temperature by 0.26 KSolar radiation‐topography interaction over the TP also affects the precipitation patterns in South and East AsiaIncluding solar radiation‐topography interaction improves the simulation of surface climate over the TP and Asian regions [ABSTRACT FROM AUTHOR]

Variations in surface air temperature on the eastern Tibetan Plateau (TP‐SAT) during boreal summer, related to Barents‐Kara spring sea ice and summer Arctic Oscillation (AO), are investigated using observations and ERA‐5 reanalysis data during 1979–2018. Results show that the primary mode of summer eastern TP‐SAT (SAT_EOF1) is characterized by the consistent warming pattern with larger values over the northeastern TP, which is linked with the anticyclonic circulation located in the northeastern flank of the TP. This anticyclone enhances westward water vapor transport, warm temperature advection, and causes descending over the eastern TP, Descending further results in deceased middle level cloud cover and increased solar radiation, accordingly, favoring the eastern TP warming. Further statistical analysis reveals a robust connection between Barents‐Kara spring sea ice, summer AO and SAT_EOF1. Moreover, anticyclonic anomaly located in the northeastern region of the TP acts as an important driver of this consistent warming pattern over the eastern TP, which is modulated by two individual Rossby wave trains from the northwestern Russia and northwestern Atlantic. The spring sea ice in Barents‐Kara could cause decreased precipitation and reduced soil moisture in northwestern Russia during following summer, which further induces the Eurasian‐like teleconnection and affects the anticyclonic anomaly situated in the northeastern flank of the TP, thereby favoring eastern TP warming. In addition, from northwestern Atlantic to northeastern region of the TP, the Rossby wave train is mainly affected by summer AO, with positive AO causing anticyclonic anomaly over northeast of the TP, thus contributing to the TP warming. Plain Language Summary: Tibetan Plateau (TP) is a region that is easily affected by the global warming. Numerous studies have extensively documented a remarkable warming trend in the TP during boreal summer, particularly noticeable since the late 1990s. Despite these valuable observations, its mechanisms are not yet clear. In this study, we found that the anticyclonic anomaly over the northeast of TP is a crucial system affecting eastern TP warming in boreal summer. This anticyclonic anomaly leads to the strengthened westward water vapor transport and causes descending over the eastern TP. Descending, in turn, results in the reduction of middle level cloud cover and increased solar radiation. Further analysis indicated that this anomalous anticyclone is mainly modulated by two individual wave trains from the northwestern Russia and northwestern Atlantic, respectively. From northwestern Atlantic to northeastern flank of the TP, the wave train is mainly affected by the summer AO, and another is mainly driven by the spring Barents‐Kara sea ice. Those two factors account for about 36% of the summer eastern TP warming. Key Points: Anticyclonic anomaly located in the northeastern flank of the TP favors the eastern TP warmingSpring Barents‐Kara sea ice could affect this anticyclone through its influences on summer soil moisture over northwestern RussiaThis anticyclone is also modulated by the wave train from northwestern Atlantic, which is mainly affected by Arctic Oscillation [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]

The air temperature difference is an essential indicator to measure weather and climate change. The Tibetan Plateau (TP) is a sensitive area to global climate change. The study on its temperature difference variations is of great significance for further understanding the evolution of weather and climate systems, and scientific disaster prevention and mitigation. In this study, the spatio‐temporal evolution characteristics of the temperature difference on daily, monthly, seasonal and annual scales and their possible causes are analysed based on the daily observations at 59 meteorological stations over the TP from 1961 to 2020 and the circulation indexes such as the East Asian summer monsoon, South Asian summer monsoon, midlatitude westerly and TP summer monsoon. The results indicate that the diurnal temperature range (DTR) on the TP tends to decrease from 1961 to 2020. Compared with the situation in the late 20th century, the annual average of the DTR in the eastern TP turns from a nonsignificant increasing trend into a pronounced decreasing trend, while that in the western TP maintains a decreasing trend. This phenomenon is primarily influenced by the minimum and maximum temperature, precipitation and atmospheric circulations. The standardized temperature difference at different temporal scales shows decreasing trends and is distributed in north–south and east–west distribution patterns. The annual temperature range is mainly influenced by the remarkable increase of the minimum temperature, especially in the northern and southeastern TP. Besides, the increases of maximum temperature and precipitation also affect the annual temperature range. In terms of the seasonal temperature range, it is dramatically influenced by different meteorological factors, especially in the northern TP. The monthly temperature range (Mon‐TR) is dramatically influenced by the maximum and minimum temperature in the first and second half years, respectively. Moreover, the circulation systems, such as the midlatitude westerly, South Asian summer monsoon and TP summer monsoon, are the main influencing factors of the temperature difference variations on the TP. The midlatitude westerly have a large influence on Mon‐TR in June and September, and the significantly influenced stations reaches 54.2% and 35.6%. The impact stations of the TP summer monsoon on Mon‐TR is the largest in August, and the significantly influenced stations is 39%. In July, the influenced stations of the TP summer monsoon and South Asian summer monsoon on the Mon‐TR reaches 30.5%–33.9%. The influenced area of the Mon‐TR in June is largest affected by single summer monsoon or westerly index. Previous studies have shown that the warming mechanisms and their influencing factors have changed in the TP since the 21st century. The study results might provide the foundation for a scientific understanding of climate warming on the TP. [ABSTRACT FROM AUTHOR]

The systematic simulated cold biases in models for surface air temperature (SAT) over China have been under discussion for a long time, but the related attribution is still unclear. In this study, we investigate the main contributors and relevant physical processes of SAT biases over China based on 31 models participating in the sixth phase of the Coupled Model Intercomparison Project from a surface energy budget perspective. On annual and seasonal scales, less downward clear‐sky longwave radiation in the models, which is due to the underestimated tropospheric temperature and water vapor amount, is the main cause of cold biases over the Tibetan Plateau, Tarim Basin, Sichuan Basin, and most of eastern China. Meanwhile, the simulation biases in surface albedo and sensible heat flux induce cold biases depending on regions and seasons. In winter and spring, the overestimated surface albedo in association with more snow cover leads to prevalent cold biases over the western Tibetan Plateau and Northeast China. Excessive sensible heat release caused by the overestimated ground–air temperature difference facilitates SAT underestimation in the Sichuan Basin during summer and autumn. In addition, the cold biases in winter and spring are larger than those in summer and autumn, due to the stronger snow cover overestimation and tropospheric temperature underestimation. Plain Language Summary: The global climate model is a complex system used for describing the atmosphere, land surface, ocean, sea ice components, and their interactions. It has been widely applied to investigate climate change and its associated mechanisms. However, there are still deficiencies in current models for surface air temperature (SAT) simulations. The underlying cause for insufficient simulation is a hot topic of research. In past decades, many studies have shown prevalent SAT cold biases over China in most models, while the related mechanisms remain unknown. Based on the state‐of‐the‐art models, we investigate the causes of the cold biases over China from the perspective of a surface energy budget. The results indicate that the downward clear‐sky longwave radiation simulation error due to the bias of atmospheric states is the primary reason, and the cold biases induced by surface albedo and sensible heat flux vary among regions and seasons. Key Points: We investigate the reasons for the simulated surface air temperature cold biases in sixth phase of the Coupled Model Intercomparison Project models over ChinaLess downward clear‐sky longwave radiation due to underestimated tropospheric temperature and water vapor amount is the main causeCold biases induced by surface albedo and sensible heat flux vary among regions and seasons [ABSTRACT FROM AUTHOR]

Reliable precipitation simulation over the Tibetan Plateau (TP) remains a challenge, manifested by a prominent systematic wet bias in the warm season. Previous studies have generally neglected the potential linkage between surface radiation energy budget and precipitation bias. Prevalent scattered cumulus and thunderstorms over the TP in summer strongly influence surface radiation. A cloud fraction scheme considering subgrid temperature and humidity fluctuations is implemented in the WRF model and tested for a month‐long simulation. It is found that the scheme better reproduces the surface solar radiation compared to a default cloud fraction scheme in the WRF model. Using abundant surface observations, we find that overestimation of the downward surface shortwave radiation (DSSR) would lead to wet bias. DSSR overestimation contributes to higher surface temperature and larger evaporation and enhanced atmospheric instability, which favor more simulated convective precipitation. The study suggests that a better simulation of clouds and surface radiation would benefit precipitation simulation over the plateau. Plain Language Summary: Summer precipitation over the Tibetan Plateau (TP) is generally overestimated in general circulation models as well as regional weather forecasts and climate models. The prevailing "popcorn‐like" clouds over the TP in summer would strongly impact surface radiation. Considering the potential linkage between surface radiation energy budget and precipitation bias, a statistical cloud fraction and subgrid condensation scheme (GS‐PDF scheme) is implemented in the WRF model and tested for a month‐long simulation. The GS‐PDF scheme better captures clouds over the TP with more mid‐low cloud water (ice) than the default Xu‐Randall scheme. Increased mid‐low cloud water in the GS‐PDF scheme reduced simulated downward surface shortwave radiation, reduced simulated surface temperatures, atmospheric instabilities and convective precipitation, leading to alleviated wet bias over the TP. This study suggests that better simulations of cloud and surface radiation would be beneficial for simulations of hydrological cycles over the TP. Key Points: A new cloud macrophysics scheme considering subgrid temperature and humidity fluctuations is implemented in the WRF modelThe new macrophysics scheme reduced simulated downward surface shortwave radiation, surface temperatures and atmospheric instabilitiesA better simulation of clouds and surface radiation would benefit precipitation simulation over the Tibetan Plateau [ABSTRACT FROM AUTHOR]

This study investigated the performance of the Weather Research Forecasting (WRF) model at 4‐km horizontal grid spacing in simulating precipitation, 2 m air temperature (T2), snowfall, and lake‐effect snow (October 4–8, 2018) over the Tibetan Plateau (TP). Multiple simulations with different physical parameterization schemes (PPSs), including two planetary boundary layer schemes (Yonsei University and Mellor–Yamada–Janjic), no cumulus and multi‐scale Kain‐Fritsch, two land surface models (Noah and Noah‐MP), and two microphysics schemes (Thompson and Milbrandt), were conducted and compared. Compared with gauge observations, all PPSs simulate mean daily precipitation with mean relative errors (MREs) of 27.7%–53.6%. Besides, spatial correlation coefficients (SCCs) between simulated and observed mean daily precipitation range from 0.56 to 0.71. For simulations of T2, all PPSs perform similarly well, even though the mean cold biases are up to about 3°C. Meanwhile, all PPSs exhibit acceptable performance in simulating spatial distributions of snow depth, snow cover, and snowfall amount, with SCCs of 0.37–0.65 between simulations and observations. However, the WRF simulations significantly overestimate snow depth (∼0.4 cm mean error) and snowfall amount (MREs >372%). The Milbrandt scheme slightly outperforms the other PPSs in simulating snow‐related variable magnitudes. Due to their inaccurate temperature and airflow modeling over the lake surface and its surroundings, none of the WRF simulations well reproduce the characteristics that more snow occurs over the lake and downwind area. Overall, this study provides a useful reference for future convection‐permitting climate modeling of snow or other extreme events when using the WRF model in the TP and other alpine regions. Plain Language Summary: Snow falls frequently in cold seasons, especially in alpine regions. When there is a lake, a very interesting snowfall phenomenon named lake‐effect snow may happen, that is, more snow occurred over the lake and downwind areas. However, the lake‐effect snow caused by large lakes over the Tibetan Plateau (TP) may induce snow disaster events. Thus, conducting reliable simulations of lake‐effect snow events are essential for understanding the mechanism of these particular events over the TP. This study investigated the performance of the numerical model in simulating precipitation, 2 m air temperature (T2), snowfall, and lake‐effect snow (October 4–8, 2018) over the TP. The results show that the simulated precipitation and T2 perform reasonably well, although wet and cold biases are observed. However, the investigated numerical model fails to reproduce the characteristics of this event well, which may be due to the inaccurate temperature and airflow modeling over the lake surface and its surroundings. Continued improvement is needed for future modeling. Hence, this study provides some suggestions for future numerical modeling of lake‐effect snow or other snow events over the TP and other alpine regions. Key Points: All simulations of the Weather Research Forecasting model can reasonably capture the spatial distributions of precipitation, 2 m air temperature, and snow‐related variablesThe Milbrandt scheme slightly outperforms the other physical parameterization schemes (PPSs) in simulating the magnitudes of the snow‐related variablesNone of the PPSs reproduce the characteristics of lake‐effect snow well due to their inaccurate temperature and airflow modeling [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]

The recent rise in air temperatures detected at high altitudes of the Tibetan Plateau has accelerated glacier melt and retreat. Moreover, enhanced monsoonal precipitation has increased runoff and transport of allochthonous material to the lakes. Consequently, water levels are rising, modifying the spatial distribution and composition of local aquatic biota. To infer these environmental and biological changes in recent decades, a 30‐cm‐long sediment core, representing the past ~160 years, from Nam Co, an endorheic lake, was analyzed for subfossil chironomid assemblages and sediment geochemistry. In total, 25 chironomid morphotypes were identified. Nineteen were considered as non‐rare taxa (abundances ≥2%) and six as rare taxa (abundances <2%). Since 1956 ce, higher chironomid richness (S = 19) is evident compared to the previous 100 years. The simultaneous decrease in the abundance of profundal Micropsectra radialis‐type and increase of both Chironomus and Procladius, taxa adapted to more eurytopic and slightly warmer water bodies, indicate increasing water temperatures and intensified primary productivity. The dominance of littoral chironomid assemblages reflects increasing lake water levels, flooded shorelines and expansion of littoral areas driven by increased precipitation and glacial meltwater input both resulting from the increase in air temperatures. This scenario is confirmed by increases in total nitrogen and Zr/Rb ratios, indicating higher productivity and coarser grain size as a consequence of increased runoff via the Niya Qu. These hydrological changes have resulted in a positive water balance that can be linked to an increase in moisture supply from the Indian summer monsoon and glacier melt, reflecting increasing temperatures and precipitation since 1956 ce, ultimately driven by anthropogenic warming. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) contains the largest permafrost region in the mid–low latitudes and the largest area of glaciers outside of the polar regions. In recent decades, this region has experienced vegetation greening (e.g., increasing leaf area index) due to climate change. As the largest exorheic river on the TP, the Upper Brahmaputra Basin (UBB) is very sensitive to climate change, experiencing the humidifying and significant warming. In this study, we investigated the spatiotemporal variability of frozen ground and vegetation over the last four decades in the UBB and explored how these changes have impacted river runoff using a water‐ and energy‐budget distributed hydrological model (WEB‐DHM). We found that almost 50% of permafrost transformed into seasonally frozen or unfrozen ground from 1981 to 2019 with the great improvement of vegetation leaf area index (LAI). Based on the variable‐controlling approach (set the air temperature or vegetation unchanged), we revealed that frozen ground degradation caused an average of 9.3 billion m3 of water loss per year, accounting for 5.4% of total UBB river runoff, even if frozen ground degradation can increase water resources at the early stage. However, vegetation greening has caused a runoff decline by 10.9 billion m3 (6.4%) annually due to enhanced evapotranspiration. These findings highlight that it is critical to understand and mitigate the impacts of changing frozen ground and vegetation, when managing water resources availability and ecosystem conservation under rapid climate change. [ABSTRACT FROM AUTHOR]

The performance of land surface temperature (LST) simulations in land surface models is subject to uncertainties in atmospheric forcing datasets. However, the contributions of forcing variables in different datasets to the simulated LST over the Tibetan Plateau (TP) remain unclear. To investigate the sensitivity of LST simulation to atmospheric forcing, we conducted a series of experiments using the Community Land Model (CLM5.0) with different forcing datasets. Results showed that the simulated LST displayed large spatiotemporal variations, and the simulation driven by the China Meteorological Forcing Data set produced more reasonable estimates than the other simulations. Sensitivity analysis suggests that the 1% increase in air temperature causes the largest variation in LST (0.54%), while the same percentage change in precipitation leads to the smallest (only 0.002%) LST variation. However, the actual uncertainty in precipitation is much larger than that in air temperature, and thus uncertainty in precipitation contributes 24% of the LST variability in the cold season, compared to 18% for air temperature. Large precipitation uncertainty leads to strong uncertainties in snow processes (snowfall and snow cover fraction), and hence strong uncertainties in surface albedo and ground absorbed shortwave radiation, further exerting the absolute impact on LST in cold season. Moreover, the snowfall is also influenced by different schemes of snowfall/rainfall partitioning. This may result in uncertainties in snowfall and consequently LST for the southeastern TP. Our study highlights the importance of high‐quality precipitation data, a forcing variable usually ignored in previous studies of LST simulation on the TP. Plain Language Summary: This study quantifies the sensitivities of land surface temperature (LST) simulation to uncertainties in different forcing variables and estimates the actual influence of these uncertainties. Four prevalent atmospheric forcing datasets are utilized as the input to a physical‐based Community Land Model (CLM5.0) simulating LST over the Tibetan Plateau (TP). The results provide general images of LST simulations on the TP with different forcing data sets and the regionally tailored data set (CMFD) outperforms the other three global datasets. Sensitivity analysis suggests that the uncertainty in air temperature causes the largest variation in LST when forcing variables change by the same percentage. The sensitivity to uncertainty in precipitation is the lowest. However, large precipitation uncertainty in current forcing datasets exerts about 24% absolute impact on LST simulation in cold season. Large precipitation uncertainty leads to strong uncertainties in snowfall, snow cover fraction, and hence strong uncertainties in surface albedo and ground absorbed shortwave radiation, further exerting the absolute impact on LST. This study highlights that reliable forcing data, especially precipitation data, are of great significance to the accuracy of LST simulation on the TP. Key Points: Land surface temperature (LST) simulation driven by the China Meteorological Forcing Data set was more reasonable than the other simulationsSimulated LST is most sensitive to uncertainties in air temperatureLarge precipitation uncertainty in forcing datasets accounts for 24% of the LST variability in cold season [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) has warmed at a rate twice the global average and presents unique warming patterns in surface temperature changes. However, key characteristics of glacier surface heatwave duration and intensity over the TP during the present extreme warming period are still unknown. In this study, we show that surface temperatures in glacial regions of the TP (0.37 ± 0.10°C per decade) have increased faster than those in non‐glacial areas (0.29 ± 0.05°C per decade) between 2001 and 2020. Moreover, the duration (5.3 ± 3.2 days per decade) and cumulative intensity (24.9 ± 16.3 days °C per decade) of glacier surface heatwaves have increased significantly during autumn. Our results demonstrate an elevation dependence to these key warming characteristics, which we also suggest are associated with extreme glacier mass loss. Here, we highlight potential threats to the sustainability of glacier water resources and increasing risk of glacier related hazards at the "roof of the world." Plain Language Summary: The Tibetan Plateau, commonly referred to as "the roof of the world," has experienced substantial warming during the past 50 years, at a rate twice that of the global average. Previous studies in this climate sensitive environment have primarily focused on air temperature changes measured from a limited number of ground‐based observational stations, as well as from a number of satellite‐derived land surface temperature products. However, the spatiotemporal characteristics of glacier surface heatwaves—periods of extreme warm land surface temperatures—are yet to be explored. In this study, using satellite‐derived land surface temperature data, we investigated temperature changes across the Tibetan Plateau, and critically explored the occurrence of thermal extreme events of glacier surface temperatures from 2001 to 2020. We show that glacial regions have experienced faster surface warming than non‐glacial regions since 2001. Our results also suggest higher surface temperature trends and increases in heatwave intensity and duration during autumn, along with a clear elevation dependence, which is likely due to decreased albedo. Glaciers with extreme high mass loss were highly associated with increases in glacier heatwave duration and intensity. We highlight the implications of glacier heatwave threats to water resources and hazard risk. Key Points: Glacial areas experienced two times higher mean warming rates than non‐glacial areas in autumnThe duration and cumulative intensity of glacier surface heatwaves increased significantly during autumn, likely due to decreased albedoIncreases in glacier surface heatwave duration and cumulative intensity are associated with extreme high glacier mass loss [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]

In the context of global warming and the release of projection results from the Coupled Model Intercomparison Project Phase 6 (CMIP6), it is important to conduct research on climate change on the Tibetan Plateau (TP) which exhibits unique geographic characteristics and complex climatic conditions. Using 10 general circulation models (GCMs) from CMIP6 corrected for bias by the daily translation (DT) method, we investigated the projected changes in precipitation and air temperature for the mid‐term (2031–2050) and long‐term (2061–2080) of the 21st century on the TP after evaluating the reliability of the bias correction, for four scenarios based on different combinations of shared socioeconomic pathways and representative concentration pathways. The multimodel ensembles (MMEs) indicated that the projected annual precipitation shows an increasing trend for the mid‐term and long‐term periods, with the projected increase for the long‐term primarily concentrated in areas with less precipitation. Meanwhile, the future precipitation changes exhibit a significant elevation dependency. The rate of increase of precipitation firstly fluctuates and then gradually increases along with the elevation increasing from 1,500 to 5,800 m. The valley value of rate mainly appears in two elevation zones (2,200–2,600 m and 3,400–3,800 m). The projected temporal changes in annual air temperatures reveal obvious warming over the TP. The projected warming is overall more pronounced with increase in elevation; however, it reaches a peak at approximately 5,000–5,200 m and then slows down slightly, indicating that warming is not dependent on elevation in the higher elevation zones. The present results have important implications for investigating the impacts of climate change on the water cycle in alpine regions. [ABSTRACT FROM AUTHOR]

This study focuses on the trends and the causes of variation in actual evapotranspiration (AET) around the warming hiatus over China by a comprehensive analysis applying various temporal–spatial methods. It is observed that the annual AET showed a different trend around 2000 for China as a whole. By employing segmented regression analysis for detecting warming hiatus points, high temporal inconsistency can be found in eight climatic regions of China. The impacts of meteorological variables on AET were further identified by affecting the intensity and relative change of meteorological factors. AET was highly correlated (p <.01) with solar radiation in the southeast (R = 0.80) and air specific humidity in the northwest areas (R = 0.83). AET changes presented the highest sensitivity to specific humidity in Northwest before 2006 and in north central China after 2003, with sensitivity coefficients of 1.48 and 1.74, respectively. Three variables, including air specific humidity (with an average contribution rate of ~17% in the northwest), short‐wave radiation and air temperature, can be the main factors that lead to the changes in AET. The specific meteorological factors varied from region to region: the changes in AET can be ascribed to the increased wind and short‐wave radiation in north central China and east China, the decreased air temperature in Tibetan Plateau, the increased specific humidity in southeast China during warming hiatus, and so on. After the warming hiatus occurred, the dominant factor of AET trends changed from air specific humidity to short‐wave radiation and other factors. Generally, air specific humidity and air temperature have played leading roles in AET trends during the past 30 years. [ABSTRACT FROM AUTHOR]

An observation‐based parameterization of thermal roughness length (TRP) for bare ground has been implemented in the Weather Research and Forecasting model. This scheme introduces a temperature scale to account for the impact of atmospheric stability. The effect of the TRP scheme is evaluated by comparing simulations with the default and with the implemented one for the Tibetan Plateau (TP) region. We find that the newly implemented scheme generally shows remarkable improvement in simulating the nighttime near‐surface 2m air temperature (T2) and daytime surface skin temperature (TSK), with a reduction in cold biases. The newly implemented scheme directly leads to weakened sensible heat release to the atmosphere in the daytime, thereby increasing energy storage in the land. These changes enhance snow melting in spring and reduce snow accumulation in autumn. Due to reduced snow cover and decreased albedo in the two transitional seasons, more solar radiation is absorbed by the land surface, leading to higher TSK and T2. In summer, the snow albedo feedback plays a minor role when there is minimal snow cover. In winter, the solar radiation is weak, and the atmosphere is relatively stable. Consequently, the warming effect due to the newly implemented scheme is more remarkable in the transitional seasons than in summer and winter. This work demonstrates the importance of the TRP in simulating T2 and TSK in the coupled atmosphere‐land model, and reveals that the influence of this scheme on T2 and TSK over the TP region is mainly associated with snow‐albedo‐shortwave radiation processes. Key Points: The parameterization of thermal roughness length (TRP) is important for simulating the 2m air temperature (T2) and skin temperature (TSK)The influence of the TRP on T2 and TSK is more significant during transitional seasons than in summer and winterAt seasonal scale, the TRP influences T2 and TSK mainly through snow‐albedo‐shortwave radiation processes [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]

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]

Although some outcomes have been reported, our knowledge of the Tibetan Plateau (TP) climate and its prediction remains unclear due to land surface complexity and observational uncertainty. Here, long‐term observations and reanalysis data revealed a significant positive relationship between winter and the subsequent summer surface air temperatures (SATs) over the TP, in which we highlighted the role of the persistence of soil enthalpy (SE) process. The winter SE can memorize the winter SAT anomaly, and the signal decays with depth gradually, but the consistency with spring SE increases substantially. This persistence of the SE process facilitates the winter SAT signals to be preserved for months until summer, resulting in homogeneous SAT anomalies in summer. The atmospheric response to the SAT anomaly further demonstrates the significant effect of winter thermal conditions on the subsequent summer climate over the TP. Hence, this work brings a new perspective for understanding the TP climate. Plain Language Summary: As the powerful summertime heat source, TP has a significant impact on the climate both locally and in the surrounding areas. In this study, based on long‐term observation and reanalysis data sets, we found that the SAT anomaly during winter is positively related to the subsequent summer SAT variability over the TP. Importantly, we also demonstrate that the persistence of soil enthalpy can act as a bridge that links the winter and following summer SATs, and so retain the preceding winter SAT signal for months, and then release it during the following summer. Additionally, the atmospheric response to the TP SAT anomaly further indicates the winter heating effect on the subsequent summer climate. Consequently, this discovery provides a new perspective to understand the land‐atmosphere interaction in TP summer climate change. Key Points: This study observed a significant positive relationship between winter and the subsequent summer surface air temperature (SAT) over the Tibetan Plateau (TP)The persistence of soil enthalpy plays an important role as a bridge linking winter and the subsequent summer SATThe atmospheric response to SAT further validates the heating effect of winter on the subsequent summer climate over the TP [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is known as Asian Water Tower and its atmospheric water cycle has been a lasting challenge to climate modeling community. Here, we compare two sets of the Met Office Unified Model simulations—one is a convection‐parameterized version (large‐scale model; LSM) and the other is a convection‐permitting model (CPM) simulation. The added value of the CPM in terms of atmospheric water cycle process is analyzed, including external moisture transport, fraction of atmospheric water vapor converting to precipitation and the precipitation recycle ratio. Results show that the simulated TP precipitation and evaporation for the summer of 2009 is significantly improved in the CPM. First, the overestimation of atmospheric water cycle by LSM is improved in CPM due to a reasonable representation of the fraction of atmospheric water vapor converting to precipitation. The overestimation of precipitation recycle ratio also indicates the LSM generates excessive convection compared to the CPM and therefore has a larger wet bias over the TP. Second, a better simulation of local precipitation has feedback on the circulation. Compared with the LSM, the less moisture convergence in the CPM is dominated by the stronger outflow through the eastern edge of the TP rather than the weaker inflow, implying the upscale effects of the resolved moist convection on the moisture transport over the TP. Our results imply that the CPM is a useful tool in the reproduction of moisture transport and atmospheric water cycle process over the Asian Water Tower and other regions of the world with complex topography. Plain Language Summary: The atmospheric water cycle over the Tibetan Plateau (TP, also as known as the Asian Water Tower) has been a challenge to climate models with convection parameterization. Benefiting from the high enough resolution, convection‐permitting model (CPM) can explicitly resolve the deep convection and therefore reduce the bias related with the convection parameterization scheme. Here, we compare a CPM with its low resolution version that employs convection‐parameterization in simulating atmospheric water cycle process over the TP. We find the precipitation and evaporation over the TP is significantly improved in the CPM. There is more water vapor flowing out of the TP and less water vapor in the atmosphere converting into the precipitation in the CPM, resulting in a reduced wet bias. CPM is free from the constrains of the convection parameterization scheme and therefore depicts the atmospheric water cycle over the TP better. Key Points: The convection‐permitting model (CPM) better reproduces precipitation over the Tibetan Plateau than convection‐parameterized model (large‐scale model [LSM])The overestimation of atmospheric water cycle by LSM is improved in CPM simulationThe interaction between large‐scale circulation and convection further reduces moisture convergence and wet bias in the CPM [ABSTRACT FROM AUTHOR]

This study presents a comprehensive evaluation of the mean and extreme surface air temperature and precipitation in the Coupled Model Intercomparison Project Phase 6 (CMIP6) multimodel ensemble simulations over the Tibetan Plateau. Simulations from 29 climate models are compared against gridded observations for the period 1961–2012. Results show that models reasonably reproduce the overall spatial patterns of the 1961–2012 averages of seasonal mean temperature and precipitation. Nevertheless, models tend to underestimate mean temperature and overestimate precipitation accumulations. To be specific, the multimodel mean estimates of seasonal average temperatures over the plateau are 0.5°C–2.6°C colder than observed, while the corresponding estimates of seasonal precipitation accumulations are 218% (spring: March–May), 76% (summer: June–August), 129% (autumn: September–November), and 533% (winter: December–February) of those observed. As in observations, models also well capture increasing trend of mean temperature and precipitation in all seasons but underestimate the rates of increasing trends for both variables in all seasons. Models' ability to simulate temperature and precipitation extremes is also evaluated in terms of a set of chosen extreme indices defined by the Expert Team on Climate Change Detection and Indices. On average, models tend to underestimate the averages of annual maximum daily maximum temperature, annual minimum daily minimum temperature, frost days, warm nights, and consecutive dry days but overestimate the corresponding averages of annual maximum 5‐day precipitation accumulations and simply daily intensity. Generally, models are able to simulate the signs of the trends in extreme indices but underestimate their magnitudes and misrepresent spatial patterns. Key Points: CMIP6 models reasonably reproduce the spatial patterns and temporal variations of mean and extreme temperature and precipitationCMIP6 models continue to suffer from cold bias in temperature and wet bias in precipitation similar as its predecessor CMIP5Most models underestimate the observed trends in mean and extreme temperature and precipitation [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) are indispensable for climate change adaptive study over the Tibetan Plateau (TP), which is the potential trigger and amplifier in global climate fluctuations. With the release of Coupled Model Intercomparison Project Phase 6 (CMIP6), 24 GCMs from CMIP5 and CMIP6 were comparatively evaluated for precipitation and air temperature simulations based on the China Meteorological Forcing Dataset (CMFD). Rank score results showed that CMIP6 models generally performed better than CMIP5 for precipitation and surface air temperature over the TP. According to multimodel ensembles (MMEs) of the optimal GCMs for each climate variable, the overestimation of precipitation was both present in CMIP5 and CMIP6, but the results of CMIP6 MMEs were relatively lower in the mid‐west and northern edge of the TP. Furthermore, CMIP6 offered a better performance of precipitation in summer and autumn. For temperature, CMIP6 MMEs were able to reduce the relatively large cold bias that appeared in CMIP5 MMEs in northwest areas to about 1°C and had a smaller bias in spring and winter. Moreover, the investigation into the simulation effects of precipitation at different elevation zones demonstrated that the improved ability of CMIP6 MMEs to reduce bias was mainly concentrated in the elevation zones of 2,000–3,000 m and over 5,000 m, where the precipitation bias was more than 200%. Additionally, CMIP6 MMEs of temperature were able to reduce the bias to less than 2°C in each elevation zone, with the minimum bias of −0.22°C distributed in the region with altitudes from 3,000 to 4,000 m, while the biases of CMIP5 MMEs in the region of 4,000–5,000 m and over 5,000 m were smaller than those of CMIP6 MMEs. Findings obtained in this study could provide a scientific reference for related climate change research over the TP. GCMs of CMIP6 perform better than those of CMIP5 for precipitation and temperature over the TP. Multimodel ensembles (MMEs) of CMIP6 effectively reduce the overestimation of precipitation from CMIP5 MMEs by 40 mm at the annual scale. Improved ability of CMIP6 MMEs shows a significant elevation dependency, especially in elevation zones of 2,000–3,000 m and over 5,000 m for precipitation. [ABSTRACT FROM AUTHOR]

Surface air temperatures affect a diverse set of physical and biological systems in many parts of the world. For regional‐scale studies, gridded surface air temperature data sets are frequently used as input variables. Here we evaluate 10 commonly used gridded air temperature products with spatial resolutions ranging from 0.1° × 0.1° to 5.0° × 5.0°, relative to observations from in situ weather stations on the Tibetan Plateau. Gridded temperatures are consistently lower, with mean annual air temperature biases ranging from −4.68 °C to −1.72 °C, and root mean square error (RMSE) from 3.24 °C to 6.11 °C. The mean biases of mean seasonal air temperatures for spring, summer, autumn, and winter are −3.21 °C, −2.98 °C, −2.89 °C, and −2.98 °C, respectively, and RMSEs of 4.81 °C, 4.39 °C, 4.3 °C, and 4.7 °C. Of all 10 products, the China meteorological forcing data set compares best with observations. Annual and season temperatures all increase significantly during 1980–2018 on the Tibetan Plateau, with winter dominating the warming rate. Key Points: Out of 10 assessed gridded products, the China meteorological forcing data set compares best with temperature observationsTibetan Plateau temperatures increase significantly during 1980–2018, with winter dominating the warming rateThe limitations related to the irregular spatial distribution of in‐situ sites in this complex terrain, especially elevation biases result in uncertainties. [ABSTRACT FROM AUTHOR]

Snow and glacier are important components in the hydrological cycle of the Tibetan Plateau (TP). Air temperature, as the main driver in freezing and thawing processes, becomes vital for hydrological modelling and prediction in this region. Due to a sparse ground gauging network, spatial density of air temperature measurement is insufficient for hydro‐meteorological studies. Therefore, the aim of this study is to identify the best representative temperature data for hydrological applications from four widely used reanalysis products, including ERA‐Interim, ERA‐5, GLDAS‐2.1 and NCEP‐R2, with reference to in situ measurements and gridded snow depth from the year 2008–2017 over the entire TP. To reduce errors, Bayesian Joint Probability (BJP) approach based on K‐Nearest Neighbour (KNN) classification algorithm (KNN‐BJP) is proposed to post‐process gridded reanalyses. The results indicate that all the reanalysis datasets provide highly correlated but cold biased air temperature. The correlation ecoefficiency is greater than 0.85. The cold biases are near −3 ° C and mainly distributed in the southeastern TP. Bias in daily maximum temperature during Spring is greater than −8 ° C for most stations. ERA‐Interim is found to have the closest agreement with in situ measurements, closely followed by GLDAS‐2.1. KNN‐BJP is found to be effective within a distance smaller than 5°. After post‐processing, the prominent underestimation is efficiently corrected with Bias near 0. RMSE is markedly reduced to be smaller than 2.5 ° C. The post‐processed ERA‐5 and GLDAS‐2.1 are as accurate as ERA‐Interim, but able to provide more detailed information for extreme events due to their finer spatial resolution. Thus, ERA‐5 and GLDAS‐2.1 are more recommended to represent air temperature in the TP. Snow depth as complementary reference data is able to present spatial variance of air temperature. Our study can help alleviate the problem of sparse air temperature data over the TP. [ABSTRACT FROM AUTHOR]

Approximately 40% of the Tibetan Plateau (TP) is underlain by continuous permafrost, yet its impact on fluvial water and sediment dynamics remains poorly investigated. Here we show that water and sediment dynamics in the permafrost‐dominated Tuotuohe basin on the TP are driven by air temperature and permafrost thaw, based on 33‐year daily in situ observations (1985–2017). Air temperature regulates the seasonal patterns of discharge and suspended sediment concentration (SSC) by controlling the changes in active contributing drainage area (ACDA, the unfrozen erodible landscape that contributes hydrogeomorphic processes within a catchment) and governing multiple thermal processes such as glacier‐snow melt and permafrost thaw. Rainstorms determine the short‐lived fluvial extreme events by intensifying slope processes and channel erosion and likely also by enhancing thaw slumps. Furthermore, the SSCs at equal levels of discharges are lower in autumn (September–October) than in spring (May–June) and summer (July–August). This reduced sediment availability in autumn can possibly be attributed to the increased supra‐permafrost groundwater runoff and the reduced surface runoff and erosion. Due to rapid climate warming, the ACDA has increased significantly from 1985 to 2017, implying expanding erodible landscapes for hydrogeomorphic processes. As a result, the fluvial water and sediment fluxes have substantially increased. In a warmer and wetter future for the TP, the fluvial sediment fluxes of similar permafrost‐underlain basins will continue to increase with expanding erodible landscapes and intensifying thermal and pluvial‐driven geomorphic processes. Thus, permafrost thaw should be considered as an important driver of past and future water and sediment changes for the TP. Key Points: Climate warming expands the erodible landscape and increases fluvial water and sediment fluxes on the Tibetan PlateauAir temperature regulates seasonal discharge and sediment dynamics by controlling glacier‐snow melt and permafrost processesIncreasing rainstorms results in more frequent fluvial extreme events [ABSTRACT FROM AUTHOR]

Downward clear‐sky longwave radiation, which is related to atmospheric water vapour content, has been suggested as an important factor causing an interdecadal increase in boreal summer surface temperature over the Tibetan Plateau (TP). We reveal the relationship between the 2 m air temperature (t2m) and water vapour over the TP in boreal summer, as well as the mechanism modulating the change in atmospheric water vapour. In recent decades, spatiotemporal variations between water vapour and t2m in boreal summer over the TP have shown synchronicity at the decadal scale. Moreover, Rossby wave trains which originate over the Northwest Atlantic and trigger an anomalous anticyclone between the northeastern TP and Baikal Lake are suggested to play a crucial role in decadal warming over the TP. First, the anomalous anticyclone, with an equivalent barotropic structure, can directly heat near‐surface air across the northeastern TP. Second, it promotes net water vapour input into the northeastern TP, leading to an increase of the total water vapour content over the entire TP, ultimately contributing to warming. Finally, a linear baroclinic model experiment further indicates that the Rossby wave trains are mainly associated with interdecadal increases in sea surface temperature (SST) in the Labrador Sea, with the SST in Baffin Bay playing a secondary role. [ABSTRACT FROM AUTHOR]

Alpine wetlands play a sensitive function in global carbon cycle during the ongoing climate warming, yet the temporal patterns of carbon dynamics from in situ ground‐based long‐term observations remain unclear. Here, we analyzed the continuous net ecosystem CO2 exchange (NEE) measured with the eddy covariance technique over an alpine peatland on the northeastern Qinghai‐Tibetan Plateau from 2007 to 2016. The wetland acted as a net CO2 source with a positive NEE (120.4 ± 34.8 gC m−2 year−1, Mean ± SD), with the mean annual gross primary productivity (GPP) of 500.3 ± 59.4 gC m−2 year−1 and annual ecosystem respiration (RES) of 620.7 ± 74.2 gC m−2 year−1. At the seasonal scale, the classification and regression trees (CART) analysis showed that aggregated growing season degree days (GDDs) were the predominant determinant on variations in monthly NEE and monthly GPP. Variations in monthly RES were determined by soil temperature (Ts). Furthermore, nongrowing season Ts had a significant positive correlation with the following year annual GPP (p < 0.05). Nongrowing season RES only accounted for about 25% of annual RES but had significant correlation with annual RES and annual NEE (p < 0.05). The further partial correlation analysis showed that nongrowing season air temperature (Ta, p = 0.05), rather than precipitation (PPT, p = 0.25) was a predominant determinant on variations in annual NEE. Our results highlighted the importance in carbon dynamics of climate fluctuations and CO2 emission from the nongrowing season in alpine wetlands. We speculated that the vast peadlands would positively feedback to climate change on the Tibetan plateau where the nongrowing season warming was significant. Key Points: CO2 fluxes in alpine wetland during the nongrowing season were crucial for annual carbon balance of alpine wetlandThe hydrothermal conditions especially during the nongrowing season played crucial role in determining interannual CO2 fluxesGlobal warming will exacerbate carbon loss in the alpine wetlands of the Qinghai‐Tibetan Plateau [ABSTRACT FROM AUTHOR]

The Tibetan Plateau has experienced substantial warming during the last few decades. As a result, the cryosphere of the Tibetan Plateau, including the snow cover, has shown significant changes. We characterized the changes in snow over the Tibetan Plateau using several snow‐related indices, including snow depth and snow‐covered days based on the MERRA‐2 and JRA‐55 reanalysis data set and passive microwave (MW) satellite observations. The analyses were performed over different time periods—including the last 38, 30, 20, and 10 snow seasons—from 1980 to 2018. The results show that the significant trends in snow depth and snow‐covered days are dependent on both the season and region and vary with the data set and snow‐related index used. There was a clear decrease in the annual maximum consecutive snow‐covered days (CSCDMax), and this was characterized by a later begin time and an earlier end time for both MERRA‐2 and JRA‐55, but only a later begin time for MW during the time period 1980–2018. The changes in CSCDMax were generally dominated by changes in the begin time, which were mainly caused by the increase in the average 2‐m air temperature for November–December. The relatively weak trends in the end time were a result of the combined impact of warmer temperatures and more precipitation in March–April. The CSCDMax averaged over the Tibetan Plateau showed decreasing trends in all studied time periods for JRA‐55 and MW and in the last 38 and 10 snow seasons for MERRA‐2 during the time period 1980–2018. Key Points: The changes in snow show remarkable regional and seasonal differences and vary with data set and snow‐related index usedMost of the time series during 1980–2018 show a reduction in snow depth and snow‐covered days averaged over the Tibetan PlateauThe trends in the begin time of the annual maximum consecutive snow‐covered days are relatively stronger than in the end time [ABSTRACT FROM AUTHOR]

Glacier mass balance is a critical parameter in assessing glacial changes and meltwater runoff associated with climate change. This study used a modified distributed surface energy balance model at 3 hr temporal and 100‐ × 100‐m spatial resolutions to reconstruct a 1960–2009 mass balance time series of the alpine Dongkemadi Glacier in the central region of the Tibetan Plateau. The modified distributed surface energy balance model was able to reasonably simulate glacier mass balance estimations. The average annual mass balance of the reconstructed long‐term time series was −0.125 m w.e. (meter water equivalent), and the cumulative mass balance was −6.245 m w.e. throughout 1960–2009. Simulation results revealed that the glacier mass balance was more readily influenced by changes in air temperature (−362 mm w.e. [millimeter water equivalent]) than changes in precipitation (+138 mm w.e.). Therefore, a decreasing trend in the annual mass balance mainly derived from increasing air temperature throughout the simulated study period, although increasing precipitation inhibited the glacier ablation trend to some extent. Throughout 1960–2009, the glacial ablation zone expanded as shown by an increase in the equilibrium line altitude. This study offers comprehensive information on an important glacier monitored under harsh environmental conditions while aiding in our understanding of glacial response to climate change, using a method that can be applied to other glaciers to which mass balance observations are limited. Key Points: This study reconstructed the 1960–2009 glacier mass balance series for the alpine Dongkemadi Glacier in the Tibetan PlateauAir temperature had the greatest impact on glacier mass balance throughout 1960–2009, followed by precipitationBoth the glacier surface energy balance and the equilibrium line altitude responded to climate change throughout 1960–2009 [ABSTRACT FROM AUTHOR]

Satellite data, characterized by extensive regional coverage and relatively high spatial resolution, have a distinct advantage for examining elevation‐dependent warming (EDW) across rugged topography in mountain regions where there are sparse in situ observations. Based on recent (2001–2015) comprehensive satellite‐based data sets (2 m air temperature, land surface temperature, snow cover, and daytime and nighttime cloud), this study finds that annual mean 2 m  air temperature warming rates show rapid decrease above 4,500 m despite increasing from 2,000 to 4,500 m. This indicates a reversal in EDW at the highest elevations on the Tibetan Plateau, which is somehow different from the EDW derived from short‐term land surface temperature presented in earlier research. The decrease of warming rate above 4,500 m coincides with the elevation at which most of the current solid water resources reside. Thus, their decline may be less rapid than previously thought. Trends in nighttime cloud and snow cover are both correlated with patterns of EDW on the Tibetan Plateau, but the leading factor varies on an annual and seasonal basis. These results provide important evidence for understanding EDW and its controlling mechanisms in an extreme high‐elevation context. Key Points: The warming rate of satellite‐based 2 m air temperatures rapidly decreases above 4,500 m despite an increase from 2,000 to 4,500 m over the Tibetan PlateauThe decrease of warming rate above 4,500 m is conducive to less rapid decline of 83% of the current plateau solid water resourcesChanges in nighttime cloud cover and snow cover have a strong control on EDW patterns on the plateau [ABSTRACT FROM AUTHOR]

In this study, the spatiotemporal changes in net primary production (NPP) and drivers, including climate change, atmospheric CO2 concentration and land use change, over the Tibetan Plateau from 1979 to 2016 were investigated using the version 4.5 of the Community Land Model. Based on high-resolution atmospheric forcing data, six numerical experiments were designed to assess the relative contribution of different environmental factors on NPP. Our simulation results suggest that NPP over the Tibetan Plateau has increased significantly at a rate of 2.25 TgC/year² since 1979. At the plateau scale, changes in precipitation, CO2 concentration, and land use change contributed approximately 63.3%, 16.7%, and 9.5% to the interannual variation ofNPP, respectively. Temperature did not exert a significant effect on the trends ofNPP,which results from the increasing temperature enhancing the autotrophic respiration (AR) more than the gross primary production.We also divided the alpine grasslands into four types, including alpine meadow of permafrost, alpine steppe of permafrost, alpinemeadow of seasonal frost, and alpine steppe of seasonal frost. Wefound that the increasing rate of NPP in permafrost regions was significantly higher than that in seasonal frost regions. Compared with other factors, precipitation change played a dominant role in the NPP over the four different types of grasslands. Temperature-induced change on NPP and AR was larger in the alpine meadow regions compared to in the alpine steppe regions. In addition, NPP and AR showed a more remarkable response to temperature change over alpine meadow of permafrost than other regions. [ABSTRACT FROM AUTHOR]

This study implements a variable resolution version of Community Earth Systems Model (VR‐CESM; regionally refined at 1/8° resolution) to assess the improvement in simulating the seasonal climate across the Tibetan Plateau (TP) at higher horizontal resolutions compared to its uniform (UN) 1° counterpart (UN‐CESM). The Weather Research and Forecasting (WRF) model, run at 12‐km horizontal grid spacing, is compared to both CESM simulations. VR‐CESM and WRF are more comparable to satellite and surface‐based observations than UN‐CESM in simulating summertime (June to August) temperature across the TP and TP foothills, respectively. WRF and VR‐CESM also more accurately simulate precipitation than UN‐CESM across the region due to more accurate terrain treatment. The number of days in which effective (>2.5 mm/day) and heavy (>25 mm/day) precipitation events are generally better captured in VR‐CESM compared to UN‐CESM and WRF. Finally, snow cover fraction in VR‐CESM is better simulated for all months compared to UN‐CESM, with the largest improvements simulated from June to August, while WRF performs even better than VR‐CESM in simulating snow cover fraction. The improvements in simulated temperature, precipitation, and snow cover are due to WRF and VR‐CESM's ability to resolve more complex topographic features rather than time step differences between the UN‐CESM and VR‐CESM experiments. While it is fairly intuitive that improved topography accuracy should bring forth more accurate simulated meteorology, this evaluation suggests that VR‐CESM is competitive or may even be preferred over regional climate models (such as WRF) when examining internal and external climate variability, as it bypasses several drawbacks associated with regional climate models. Key Points: VR‐CESM more accurately captures Tibet's heterogeneous temperature, precipitation, and snow fields compared to tradition 1‐degreee CESMImprovements in simulated meteorology are brought about by better‐resolved mesoscale circulations, which regulate the surface energy budgetVR‐CESM better simulates moisture convergence and precipitation across Nepal, compared to 1‐degree CESM [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) has important influences on regional and global climate change. Here, we perform an in‐depth study of the relationship between cloud parameters and meteorological factors over the TP. The spatiotemporal variations in cloud cover and cloud optical thickness over the TP during the daytime from 2003 to 2015 are analysed using the Aqua‐MODIS level 2 atmospheric product data MYD06. Results show that the annual average cloud cover over the TP decreases from the southeast to the northwest. The cloud cover of the western TP is highest in spring and lowest in autumn, while the cloud cover of the eastern TP is higher in spring and summer. The cloud covers in most areas of the TP exceed 30% in spring and summer, and the cloud optical thickness in the southeastern TP exceeds 10 in summer, with substantial cloud cover and cloud optical thickness changes. Compared to other seasons, the cooling effect of the near surface cloud net radiative forcing is greater during daytime in summer, which is likely associated with thick cloud optical thickness or large cloud cover. The results of the analysis of relationships among cloud cover, water vapour and air temperature show that positive correlations exist between cloud cover and water vapour, and that significantly negative correlations exist between cloud cover and air temperature over the TP. Combined with the analysis of variation features in the cloud parameters and meteorological factors, we find that water vapour variations during the daytime over the TP lead to cloud cover changes, which affect the air temperature variations over the TP by the cooling effects of clouds, especially in summer. The cloud cover of the western Tibetan Plateau (TP) is highest in spring and lowest in autumn, while the cloud cover of the eastern TP is higher in spring and summer. Combined with the analysis of variation features in the cloud parameters and meteorological factors, we find that water vapour variations during the daytime over the TP lead to cloud cover changes, which affect the air temperature variations over the TP by the cooling effects of clouds, especially in summer. [ABSTRACT FROM AUTHOR]

Solar radiation changes (dimming/brightening) have recently received growing attention within the research community, although there is currently no generally accepted explanation. This article aims to provide a new perspective for identifying the reasons behind solar dimming/brightening by using long‐term measurements of direct and diffuse solar radiation, unlike previous studies which have focused on global solar radiation. We postulate that extinction processes can be more readily revealed by direct and diffuse radiation measurements with the help of a modelling tool that treats the two components separately. An example is presented for Golmud and Lhasa in the northern and southern Tibetan Plateau (TP) respectively, over the period 1957–2013. The following is found: (a) ground‐based observed cloud cover alone hardly explains the observed solar dimming at the two sites; (b) both the cloud‐free direct radiation transmittivity (τdir) and diffuse radiation proportion (pdif) declined; (c) variations in pdif are overwhelmingly dominated by variations in aerosols, while those in τdir are related to variations in both aerosol and water vapour; (d) on top of the suggested reduced aerosol concentrations, decreased snow cover can partly explain declined diffuse radiation via lowered surface albedo; (e) the decline in τdir can be partly attributed to the wetting atmosphere via strengthened absorption; and (f) the impact of volcanic eruptions was also identified from such radiative parameters, lasting into the following summer and especially strong in the southern TP. Location, surrounding topography, and upward‐looking hemispherical view shed (generated by Solar Analyst with dark grey as view‐blocked) of the two sites (Golmud and Lhasa). [ABSTRACT FROM AUTHOR]

Permafrost has significant impacts on climate change through its strong interaction with the climate system. In order to better understand the permafrost variation and the role it plays in climate change, model outputs from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used in the present study to diagnose the near‐surface permafrost on the Tibetan Plateau (TP), assess the abilities of the models to simulate present‐day (1986–2005) permafrost and project future permafrost change on the TP under four different representative concentration pathways (RCPs). The results indicate that estimations of present‐day permafrost using the surface frost index (SFI) and the Kudryavtsev method (KUD) show a spatial distribution similar to that of the frozen soil map on the TP. However, the permafrost area calculated via the KUD is larger than that calculated via the SFI. The SFI produces a present‐day permafrost area of 127.2 × 104 km2. The results also indicate that the permafrost on the TP will undergo regional degradation, mainly at the eastern, southern and northeastern edges, during the 21st century. Furthermore, most of the sustainable permafrost will probably exist only in the northwestern TP by 2099. The SFI also indicates that the permafrost area will shrink by 13.3 × 104 km2 (9.7%) and 14.6 × 104 km2 (10.5%) under the RCP4.5 and RCP8.5 scenarios, respectively, in the next 20 years and by 36.7 × 104 km2 (26.6%) and 45.7 × 104 km2 (32.7%), respectively, in the next 50 years. The results are helpful for us to better understand the permafrost response to climate change over the TP, further investigate the physical mechanism of the freeze–thaw process and improve the model parameterization scheme. Projections of the changes in permafrost area on the TP under RCP2.6, RCP4.5, RCP6.0 and RCP8.5 via (a) SFI and (b) KUD. Shaded areas show the SDs across the CMIP5 models, and the black lines show the equivalent present‐day area. [ABSTRACT FROM AUTHOR]

With the global warming slowdown in the twenty‐first century, a huge discrepancy in regional climate warming has been identified over the main region of the Tibetan Plateau (TP). Compared with the +0.04 °C/decade warming from 1961 to 1999, the warming greatly accelerated for the period 2000–2015 at a rate of +0.30 °C/decade. During the same period, warming in the cold season (November to March) was more pronounced than in the warm season (May to September) over the TP. The results also indicated that the middle‐level cloud (middle cloud) decreased (−0.359%/year), while the high‐level cloud (high cloud) increased (+0.241%/year) over almost all the TP during the cold season. Further analysis showed positive net cloud radiative forcing over the western TP from 2000–2015, that is, a heating effect of clouds, especially in the cold season. Combining the trends of the increase in high cloud and the decrease in middle cloud over most parts of the TP, the decreased albedo effect of middle cloud and the increased longwave greenhouse effect of high cloud may have partially contributed to the sustained warming, especially in the cold season from 2000 to 2015. Meanwhile, the results showed that the warming rate and cloud area fraction changes were significantly amplified with elevation. The analysis based on a model of Coupled Model Intercomparison Project Phase 5 shows that the decreased middle cloud plays more important role than the increased high cloud in modulating the enhanced warming over the TP, especially in the cold season. The percentage of SAT caused by longwave CRF (red bar) and shortwave CRF (blue bar) to total SAT derived from CNRM‐CM5 model of CMIP5 over the TP for cold season in the period of 2000–2005. [ABSTRACT FROM AUTHOR]

Circulation‐type classifications (CTCs) are useful tools for systematically describing atmospheric circulation and studying its variation and impact on surface climate. However, few circulation classification methods (CCMs) have been applied in the Tibetan Plateau (TP). In this study, six frequently used CCMs using 500 hPa geopotential height data were assessed with respect to their abilities in explaining observed daily mean temperature and precipitation variations in the central and eastern TP for the period 1980–2014. Two statistical measures, the explained variance and the Kolmogorov–Smirnov test, were used to quantify the performance of the CTCs in describing climate variable variations. SAN (simulated annealing and diversified randomization clustering) and KRZ (Kruizinga's eigenvector‐based scheme) were identified as optimum CCMs for synoptic typing over the study region. The daily mean temperatures are well conditioned on SAN‐CTC with 43.9–62.4% explained variance at annual scale and 11.1–25.2% at seasonal scale. For daily precipitation variations, the explained variance at the annual scale is less than 40%. The spatial characters of climate variation affected by large‐scale circulation are identified. Daily mean temperature variations in the Qaidam Basin and the Qilian Mountains (90°–103°E and 35°–40°N) all year round and in the region between the Tanggula Mountains and the Himalayan Mountains (88°–97°E and 30°–34°N) in wet season (May–September) are well resolved by the CTCs. Daily precipitation variations in the eastern TP in the dry season (October–April) and a region from the Brahmaputra River basin to the Tanggula Mountains (85°–92°E and 28°–32°N) and the southern Hengduan Mountains (98°–102°E and 27°–31°N) in the wet season show a close relationship with the identified CTCs by SAN. Schematic diagram of the circulation systems related to TP climate variations. The boundaries of the four spatial domains for circulation classification are drawn with different kinds of dashed lines (domain 1: 40°–135°E, 5°S–70°N, domain 2: 50°–125°E, 5°–60°N, domain 3: 60°–115°E, 15°–50°N, domain 4: 70°–105°E, 25°–40°N). [ABSTRACT FROM AUTHOR]

ABSTRACT: We review recent climate changes over the Tibetan Plateau (TP) and associated responses of cryospheric, biospheric, and hydrological variables. We focused on surface air temperature, precipitation, seasonal snow cover, mountain glaciers, permafrost, freshwater ice cover, lakes, streamflow, and biological system changes. TP is getting warmer and wetter, and air temperature has increased significantly, particularly since the 1980s. Most significant warming trends have occurred in the northern TP. Slight increases in precipitation have occurred over the entire TP with clear spatial variability. Intensification of surface air temperature is associated with variation in precipitation and decreases in snow cover depth, spatial extent, and persistence. Rising surface temperatures have caused recession of glaciers, permafrost thawing, and thickening of the active layers over the permafrost. Changing temperatures, precipitation, and other climate system components have also affected the TP biological system. In addition, elevation‐dependent changes in air temperature, wind speed, and summer precipitation have occurred in the TP and its surroundings in the past three decades. Before projecting multifaceted interactions and process responses to future climate change, further quantitative analysis and understanding of the change mechanisms is required. [ABSTRACT FROM AUTHOR]

ABSTRACT: Snow change over the Tibetan Plateau may exert a large influence on climate variability in the surrounding regions. However, the characteristics of snow changes at different time scales and the factors for these changes are still not clear. The present study documents linear trends in snow cover and snow water equivalent over the Tibetan Plateau and their relationship to surface air temperature changes during 1979–2006 based on satellite data. The long‐term snow variations display a remarkable regional difference and an obvious seasonal dependence. A significant decreasing trend is observed in the western part for snow cover and snow water equivalent in summer and fall and in the southern part for snow cover in all the four seasons. A significant increasing trend is identified in the central‐eastern part for snow cover in fall, winter, and spring and in the eastern and far western parts for snow water equivalent in winter and spring. The relationship between snow and surface air temperature changes features regional disparity. The temperature increase is accompanied by snow cover decrease in the southern and western parts, but by snow cover and snow water equivalent increase in the central‐eastern part. The reasons for the snow changes vary with the season. The increase in snowmelt following the temperature increase may be the reason for the snow cover decrease in the western and southern parts in summer. The snowfall change induced by vertical motion change appears to be a factor for the snow water equivalent increase in the far western part and the snow cover decrease in the southern part in winter. The increase in snowfall induced by the increase in atmospheric moisture following the temperature increase and the enhanced upward motion may contribute to the snow increase in the eastern part in winter. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate change affects mean and extreme temperature and precipitation, increasing the risk of related disasters. Assessing the performance of current models in simulating these aspects is therefore crucial to future projection and policymaking. Based on a large ensemble ( LE; 30 members) of the Community Earth System Model ( CESM- LE), this study seeks to answer the following two questions: (1) Are the simulated trends of mean and extreme temperature and precipitation over China consistent with observations? (2) What is the range of model uncertainty due to internal variability? The results show that CESM-LE can capture the trends of observed annul mean temperature and extremely low temperature days ( ELD) over 16-26% of China, but has difficulty in reproducing the observed trends in extremely high temperature days ( EHD). For precipitation, CESM-LE demonstrates similar capability in reproducing the observed trends in annual mean precipitation and extreme precipitation days ( EPD). For consecutive dry days ( CDD), the decreasing trends over part of northwestern China can be captured, but the increasing trends over northern China cannot be reproduced by CESM-LE. Regarding the uncertainty of the model resulting from natural internal variability, because all 30 ensemble members of CESM use the same model and external forcing, CESM-LE's spread (uncertainty) is mainly due to internal variability. Larger uncertainty in simulated trends is found over northern China and the Tibetan Plateau for annual mean temperature, over northeastern China and the Huang-Huai region for ELD, and over the Tibetan Plateau for EHD. The trends in annual mean precipitation show uniform uncertainty over nearly all of China, except for the northwest. Larger uncertainty trends appear over southern and northwestern China for EPD, and over the Tibetan Plateau and northern China for CDD. [ABSTRACT FROM AUTHOR]

ABSTRACT The Tibetan Plateau ( TP) affects its surroundings significantly through thermal and dynamic processes. Reductions in near-surface wind speed ( Ws) have been observed from ground measurements but how the trends of Ws vary with the elevation is less clear. Trends of Ws with respect to elevation were investigated using long-term daily records taken from 1970 to 2012 of Ws and maximum ( Tmax), minimum ( Tmin), and mean ( Tmean) air temperatures from 139 stations over and around the TP. The major findings are as follows. (1) Pronounced reductions in Ws can be observed in all seasons and annually across the TP. Spring demonstrates the most prominent weakening. The rate of reductions in Ws was amplified with elevation, and higher-elevation environments experienced greater changes in Ws than lower-elevation areas. Elevation-dependent reductions in Ws have intensified from 1970 to 2012. (2) Statistically significant negative correlations between Ws and corresponding near-surface temperatures were detected. We suggested that the elevation-dependent warming and thereby the increased surface roughness at higher-elevation environments may contribute to the elevation-dependent reductions in Ws over and around the TP. More detailed mechanisms causing this pattern are to be further explored. [ABSTRACT FROM AUTHOR]

ABSTRACT Quality of a downscaling depends primarily on the quality of the driving global climate model ( GCM). In this study, historical atmospheric conditions simulated by 14 GCMs in CMIP5 are evaluated for downscaling applications centred over the Tibetan Plateau ( TP) with ERA-Interim reanalysis as reference. Another reanalysis NCEP-DOE is also used to estimate the uncertainty associated with the reanalyses. Performances of six frequently used GCM variables, involving atmospheric circulation, air temperature and humidity, are evaluated in terms of biases, spatial correlation coefficient, mean absolute error as well as distinct seasonal features. To detect distributional biases, the two-sample Kolmogorov-Smirnov test ( KS test) is applied to both the original time series and their anomalies on the monthly scale. A spatial ranking scheme is finally applied to objectively quantify overall relative merits of the GCMs over this region. We found that differences between two reanalysis datasets are negligible over this region. Regarding the GCMs' performances, the biases of the simulated variables show remarkable differences among models. Sea level pressure and 500 hPa geopotential height are well simulated by all the GCMs, whereas specific humidity at 600 hPa has a significant dry bias and temperature at 500 hPa has a sizable cold bias. The spatial pattern of the upper-tropospheric circulation is relatively poorly simulated. The KS test suggests that the climatic mean and higher order moments play about an equal role in causing the errors. According to the ranking scores, CCSM4, CNRM-CM5, MPI-ESM-LR, NorESM1-M, MIROC4h, MPI_ESM_MR and CSIRO-MK are relatively superior to other GCMs for this region. [ABSTRACT FROM AUTHOR]

ABSTRACT The ecosystems of the Qinghai-Tibetan Plateau ( QTP) are highly sensitive to climate change, the effects of which can be expressed through alterations to some key thresholds, including bio-temperature. However, to date, few studies have investigated variations in bio-temperature on the QTP in the context of climate change. To address this, the present study selected the following key indicators of bio-temperature: mean temperature of the warmest month ( TWM); mean temperature of the coldest month ( TCM); accumulated temperature above 10 °C ( AT10), 5 °C ( AT5), and 0 °C ( AT0); and number of days with daily mean temperature above 10 °C ( DT10), 5 °C ( DT5), and 0 °C ( DT0). These indicators were selected owing to their roles in the growth and distribution of vegetation on the QTP. The trends exhibited by these indicators were examined on basis of the data obtained from 71 observation stations on the QTP from 1961 to 2013. The results demonstrate that both TWM and TCM at the regional scale exhibited significant rising trends over this period, although TCM increased at a considerably faster rate. Spatially, the greatest increases in TWM and TCM were observed in the Qaidam basin desert and Guoluo-Naqu alpine shrub meadow regions. Additionally, AT10, AT5, and AT0 exhibited increasing trends, with AT0 increasing most rapidly and exhibiting the most significant changes, followed by AT5 and then AT10. Similarly, DT0 exhibited a greater overall increase than DT10 and DT5. Spatially, AT and DT exhibited asymmetrical change, i.e. large increases in AT did not correspond to large increases in DT. In general, all the bio-temperature indicators considered indicate pronounced rising trends over this recent five decades. This was likely due to rising air temperatures across the QTP, which have affected the structures and functions of alpine ecosystems. [ABSTRACT FROM AUTHOR]

Pan evaporation ( Ep) is an important indicator of water and energy and the decline of Ep has been reported in many regions over the last decades. The climate and Ep are dependent on each other. In this study, the temporal trends of Ep and main Ep drivers, namely mean air temperature ( Ta), wind speed ( u), global solar radiation ( Rs), net long-wave radiation( R nl) and vapour pressure deficit ( D) from 1970 to 2012, were calculated on the basis of 26 meteorological stations on the Tibetan Plateau. The arithmetic average of Ep from 26 stations decreased with the rate of −11.91 mm a−2; the trends of Rs, R nl, Ta, u and D were −1.434 w m−2 decade−1, 0.2511 w m−2 decade−1, 0.3590°C decade−1, −0.2376 m s−1 decade−1 and 9.523 Pa decade−1, respectively. The diffuse irradiance is an essential parameter to model Ep and quantify the contribution of climatic factors to changing Ep. 60 724 observations of Rs and diffuse solar irradiance ( Rd) from seven of the 26 stations were used to develop the correlation between the diffuse fraction ( Rd/ Rs), and the clearness index ( Rs/ Ro). On the basis of the estimation of the diffuse component of Rs and climatic data, we modified the PenPan model to estimate Chinese micro-pan evaporation ( Ep) and assess the attribution of Ep dynamics using partial derivatives. The results showed that there was a good agreement between the observed and calculated daily Ep values. The observed decrease in Ep was mostly due to declining wind speed (−13.7 mm a−2) with some contributions from decreasing solar irradiance (−3.1 mm a−2); and the increase of temperature had a large positive effect (4.55 mm a−2) in total whilst the increase of R nl had insignificant effect (0.35 mm a−2) on Ep rates. The change of Ep is the net result of all the climatic variables. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The complementary relationship (CR) of evapotranspiration allows the estimation of the actual evapotranspiration rate ( ETa) of the land surface using only routine meteorological data, which is of great importance in the Tibetan Plateau (TP) due to its sparse observation network. With the highest in situ automatic climate observation system in a typical semiarid alpine steppe region of the TP, the wind function of Penman was replaced by one based on the Monin-Obukhov Similarity theory for calculating the potential evapotranspiration rate ( ETp); the Priestley-Taylor coefficient, α, was estimated using observations in wet days; and the slope of the saturation vapor pressure curve was evaluated at an estimate of the wet surface temperature, provided the latter was smaller than the actual air temperature. A symmetric CR was obtained between the observed daily actual and potential evapotranspiration. Local calibration of the parameter value (in this order) is key to obtaining a symmetric CR: α, wet environment air temperature ( Twea), and wind function. Also, present symmetric CR contradicts previous research that used default parameter values for claiming an asymmetric CR in arid and semiarid regions of the TP. The effectiveness of estimating the daily ETa via symmetric CR was greatly improved when local calibrations were implemented. At the same time, an asymmetric CR was found between the observed daily ETa and pan evaporation rates ( Epan), both for D20 aboveground and E601B sunken pans. The daily ETa could also be estimated by coupling the Epan of D20 aboveground and/or E601B sunken pan through CR. The former provided good descriptors for observed ETa, while the latter still tended to overestimate it to some extent. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) plays a significant role in the Earth's climate system. This letter examines the nighttime lake surface water temperature (LSWT) of 374 lakes (≥10 km2 each) over the TP for the past 15 years (2001–2015). An overall warming trend (0.037 °C/year) is found and it is consistent with the warming air temperature (0.036 °C/year) over the TP, with the vast majority of the lakes (70%, with 28% of which are significant) showing warming (0.076 °C/year) and the rest (30%, with 37% of which are significant) showing cooling (−0.053 °C/year). This astonishing contrast was controlled by different water sources recharging these lakes: (1) warming LSWT due to increased precipitation (central and northern TP) or permafrost degradation (northwestern TP) and (2) cooling LSWT due to increased glacier meltwater (southwestern TP), revealing LSWT a sensitive indicator to climate change that triggered different regional responses in precipitation, permafrost, and glacier changes over the TP. This study helps improve our understanding of high‐altitude lakes and their changing mechanisms under the warming climate. Plain Language Summary: The Tibetan Plateau (TP), a vast highland area in Asia, plays a significant role in the Earth's climate system. Here we examine the nighttime lake surface water temperature (LSWT) of 374 TP lakes (≥10 km2 each) over the past 15 years (2001–2015). An overall warmin trend (0.037 °C/year), consistent with the warming air temperature (0.036 °C/year) over the TP, is found, with the vast majority of the lakes (70%) showing fast warming (0.076 °C/year) and the rest (30%) showing fast cooling (−0.053 °C/year). This astonishing contrast was controlled by different water sources recharging these lakes: (1) warming LSWT due to increased precipitation (central and northern TP) or permafrost degradation (northwestern TP) and (2) cooling LSWT due to increased glacier meltwater (southwestern TP). Although there are clear regional differences in precipitation, permafrost degradation, and glacier melt, these changes were all due to the warming air temperature over the TP. This study reveals that LSWT is a sensitive indicator of the climate change that triggered different regional responses in precipitation, permafrost, and glacier changes over the TP. This study helps improve our understanding of high‐altitude lakes and their changing mechanisms under the warming climate. Key Points: Lake surface water temperature (LSWT) is warming rapidly with significant seasonal patterns over the Tibetan Plateau (TP)The LSWT warming rate is slightly higher than the global mean and is consistent with the warming air temperature in TPLSWT is a sensitive indicator of the warming climate that triggered different regional responses in precipitation, permafrost, and glacier changes over the TP [ABSTRACT FROM AUTHOR]