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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]

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]

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]

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]

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 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 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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]