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Dynamical downscaling generally performs poorly on the Tibetan Plateau (TP), due to the region’s complex topography and several aspects of model physics, especially convection and land surface processes. This study investigated the effects of the cumulus parameterization scheme (CPS) and land-surface hydrology scheme (LSHS) on TP climate simulation during the wet season using the RegCM4 regional climate model. To address these issues and seek an optimal simulation, we conducted four experiments at a 20 km resolution using various combinations of two CPSs (Grell and MIT-Emanuel), two LSHSs (the default TOPMODEL [TOP], and Variable Infiltration Capacity [VIC]). The simulations in terms of 2-m air temperature, precipitation (including large-scale precipitation [LSP] and convective precipitation [CP]), surface energy-water balance, as well as atmospheric moisture flux transport and vertical motion were compared with surface and satellite-based observations as well as the ERA5 reanalysis dataset for the period 2006–2016. The results revealed that the model using the Grell and TOP schemes better reproduced air temperature but with a warm bias, part of which could be significantly decreased by the MIT scheme. All schemes simulated a reasonable spatial distribution of precipitation, with the best performance in the experiment using the MIT and VIC schemes. Excessive precipitation was produced by the Grell scheme, mainly due to overestimated LSP, while the MIT scheme largely reduced the overestimation, and the simulated contribution of CP to total precipitation was in close agreement with the ERA5 data. The RegCM4 model satisfactorily captured diurnal cycles of precipitation amount and frequency, although there remained some differences in phase and magnitude, which were mainly caused by the CPSs. Relative to the Grell scheme, the MIT scheme yielded a weaker surface heating by reducing net radiation fluxes and the Bowen ratio. Consequently, anomalous moisture flux transport was substantially reduced over the southeastern TP, leading to a decrease in precipitation. The VIC scheme could also help decrease the wet bias by reducing surface heating. Further analysis indicated that the high CP in the MIT simulations could be attributed to destabilization in the low and mid-troposphere, while the VIC scheme tended to inhibit shallow convection, thereby decreasing CP. This study’s results also suggest that CPS interacts with LSHS to affect the simulated climate over the TP.

Despite the importance of the Yellow River to China, climate change for the middle reaches of the Yellow River Basin (YRB) has been investigated far less than for other regions. This work focuses on future changes in mean and extreme climate of the YRB for the near-term (2021–2040), mid-term (2041–2060), and far-term (2081–2100) future, and assesses these with respect to the reference period (1986–2005) using the latest REgional MOdel (REMO) simulations, driven by three global climate models (GCMs) and assuming historical and future [Representative Concentration Pathway (RCP) 2.6 and 8.5] forcing scenarios, over the CORDEX East Asia domain at 0.22° horizontal resolution. The results show that REMO reproduces the historical mean climate state and selected extreme climate indices reasonably well, although some cold and wet biases exist. Increases in mean temperature are strongest for the far-term in winter, with an average increase of 5.6 °C under RCP 8.5. As expected, the future temperatures of the warmest day (TXx) and coldest night (TNn) increase and the number of frost days (FD) declines considerably. Changes to mean temperature and FD depend on elevation, which could be explained by the snow-albedo feedback. A substantial increase in precipitation (34%) occurs in winter under RCP 8.5 for the far-term. Interannual variability in precipitation is projected to increase, indicating a future climate with more extreme events compared to that of today. Future daily precipitation intensity and maximum 5-day precipitation would increase and the number of consecutive dry days would decline under RCP 8.5. The results highlight that pronounced warming at high altitudes and more intense rainfall could cause increased future flood risk in the YRB, if a high GHG emission pathway is realized.

Global warming has already had a significant impact on social ecosystems. The Tibetan Plateau (TP), which is characterized by a cryosphere, is also recognized to have a profound influence on regional and global climate systems, as well as the ecological economy. Therefore, research on the cryosphere is of significant importance. This paper comprehensively reviews the current status and recent changes of the cryosphere (e.g., glacier, snow cover, and frozen ground) in the TP from the perspectives of observations and simulations. Because of enhanced climate warming in the TP, a large portion of glaciers have experienced significant retreat since the 1960s, with obvious regional differences. The retreat is the smallest in the TP interior, and gradually increases towards the edges. Glacier simulations are comparatively few and still under development. Snow cover is a highly sensitive element of the cryosphere and decreases with large interdecadal variations from the 1960s to the 2010s in general. Simulations of snow cover mostly focus on the mutual feedback between the snow cover anomaly, climate and atmospheric circulation. In situ observations and simulations both indicate that the mean annual temperature of frozen ground increases, causing permafrost thaw and degradation and decreasing the seasonal freeze depth of seasonally frozen ground. Under future climate warming, the cryospheric elements in the TP will continue to diminish on the whole. Studies of climate and the cryosphere are ongoing. To date, the lack of observations is the biggest challenge on the TP, resulting in a divergence of cryosphere dynamics and its simulation being a bottleneck. To overcome these issues, a strategy that combines sets of in situ and remote sensing measurements and improved numerical models is of great importance for achieving breakthroughs with respect to research on the TP cryosphere and its interaction with climate.

The Tibetan Plateau (TP) has a significant influence on local, regional, and even global weather and climate systems. Precipitation on the TP plays a critical role in the energy and water cycle and terrestrial ecosystem. This study reviewed recent research progress in precipitation changes in recent decades and explored their mechanisms involved based on observations (meteorological station data and satellite remote sensing data) and simulations [global climate models (GCMs) and downscaling modelling]. Our review suggested that the TP precipitation decreases progressively from southeast to northwest, mainly occurs in summer (June–August), accounting for ∼60–70% of annual total, and marginally occurs in winter (December–February), accounting for less than 10%. Diurnal variation of precipitation and convective activity are obvious on the TP. The TP has experienced an overall surface air wetting trend since the 1960s, but with apparent regional and seasonal differences. Projected precipitation on the TP from GCMs and statistical downscaling methods (SDMs) generally increases, while from dynamic downscaling methods (DDMs) slightly increases or even decreases as greenhouse gas emissions continue in the future. Influencing factors such as the TP' and Asian land heating, large-scale atmospheric circulations, climate warming, aerosols, and land surface conditions all exert prominent but complicated effects on precipitation changes on the TP. More efforts should be made to improve the reliabilities and accuracies of precipitation observational data sets, GCMs, and downscaling modelling. Finally, directions for future research are discussed based on the various means covering high-quality precipitation observations and more skilful simulations, which are synthetically used to investigate the TP precipitation and its driving mechanisms. It is expected that this review and its results will be beneficial for hydrological and precipitation studies over the TP.

The Tibetan Plateau (TP) is a vast elevated plateau in central Asia, and profoundly impacts regional weather and climate, and even global atmospheric circulation. Here, two frequently used ERA-Interim reanalyses with a spatial resolution of 1.5° × 1.5° (EIN15) and 0.75° × 0.75° (EIN75) are evaluated using a gridded observation dataset at 0.25° spatial resolution from the National Climate Center in China across the TP that covers the period 1979–2012. Climatological characteristics, mean monthly changes, and spatial–temporal trends are examined, with a focus on air temperature and precipitation. Topographic corrections for temperature in ERA-Interim are first conducted based on a vertical temperature lapse rate. The results show that EIN15 and EIN75 with topographic correction closely reproduce the spatial distribution and mean monthly change of temperature on the TP, notwithstanding some cold biases not seen in the observations. The two reanalysis datasets exhibit significant temperature increases over most of the TP, which is similar to the observations. However, the trends exhibit different spatial patterns for all seasons aside from summer, and have lower magnitudes than the observations. EIN15 and EIN75 also reproduce the broad spatial distribution of precipitation, but overestimate precipitation amounts, especially on the southern TP. They also capture some of the observed spatial patterns in the precipitation trend for the period 1979–2012, particularly in winter. Overall, the mean monthly change, mean annual, winter, and summer climatology, and their temporal trends of temperature reproduced by the ERA-Interim data are much better than those of precipitation. As a result of its higher resolution and more accurate topography, EIN75 generates a closer fit to the observed temperatures on the TP than EIN15, but there are no significant differences in precipitation between the two reanalysis datasets. Evaluation of these datasets would be very informative for further climate research and simulations on the TP.

Understanding the current regional climate is of great importance for better estimating future climate change and assessing its influence on water resources and ecosystems. The Yellow River provides important water resources for industrial and domestic activities. However, climate simulations over the Yellow River Basin (YRB) have rarely been attempted. In this study, downscaled mean climate over the upper and middle reaches of the YRB using the REgional MOdel (REMO) at 0.22° spatial resolution under the Coordinated Regional Downscaling Experiment (CORDEX), driven by ERA-Interim reanalysis, was evaluated by comparison against one gridded observational dataset (CN05.1) for the period 1982–2016. Two reanalysis datasets (ERA5 and ERA-Interim) were used to reveal possible causes for the differences between the simulations and observations. REMO reproduced the spatial patterns of mean temperature satisfactorily despite some evident deviations. REMO had a predominantly mixed bias (a cold bias for the upper reach and a warm bias for the rest) in all four seasons. Due to the effects of differential snow cover, temperature biases were elevation-dependent, especially in winter months. REMO broadly reproduced the spatial variability of precipitation with a wet bias, which could be largely attributed to anomalous moisture flux transport. In terms of interannual variability, the observational data showed significant warming across all four seasons, while REMO simulated weaker warming trends. Precipitation trends were positive in all seasons except in summer, but REMO failed to capture the trends in winter and spring. The observed elevation-dependent warming (EDW) was reproduced by REMO, except in spring. The EDW was likely to be explained by the snow-albedo feedback, owing to the apparent decrease in snow cover at high elevations.

To investigate the effects of land-surface schemes in 2 regional climate models (RegCM3 and RegCM4.3.4) on the Tibetan Plateau (TP) climate simulation, 3 groups of 10 yr (1992-2001) simulation experiments were performed based on 2 land-surface schemes (BATS and CLM3.5). The simulations (RegCM3_BATS, RegCM4_BATS, and RegCM4_CLM) were compared with observed data by setting the same domain and initial and lateral atmospheric boundary conditions and using 30 km spatial resolution. The results showed that, compared to observed data, regional average annual mean temperature was underestimated by 1.22, 2.11, and 1.32 degrees C, and regional average annual precipitation was overestimated by 43.2, 49.8, and 18.4% in RegCM3_BATS, RegCM4_BATS, and RegCM4_CLM respectively. There were significant differences in simulated energy and water budget components among the 3 models resulting from the influence of the 2 different land-surface parameterization schemes, which impacted the simulated precipitation and temperature results through interaction between the land surface and the atmosphere. Therefore, climate simulation over the TP is very sensitive to the use of different land-surface schemes in regional climate models. Overall, use of RegCM4_CLM instead of RegCM_BATS resulted in a warmer and drier land surface and a better simulation of annual average spatial patterns of temperature and precipitation.

Regional climate models are widely used because of their high resolution. They are especially useful for regions with complex topography and with sparse observations such as the Qinghai-Xizang (Tibetan) Plateau (QTP). We examined the effectiveness of a regional model for simulating climate along the route of the Qinghai-Xizang (Tibetan) Railway (QTR) for use as a practical tool to guide maintenance and long-term management of the railway. We present a 20 yr (1982-2001) climate simulation using a regional climate model (RegCM3) over the QTP with 45 km spatial resolution, and compare the simulated results with the CRU TS3.1 climate data set and with meteorological station data. We investigated the distribution and variation of temperature and precipitation over the QTP and along the QTR. The results show that RegCM3 is able to reproduce the broad characteristics and spatial distribution of temperature over the QTP, including significant regional differences and interannual variability, compared with the CRU dataset. The annual cycle of simulated temperature is close to the observed, although simulated temperatures are slightly higher than observed in winter. RegCM3 also reproduces the broad spatial distribution of summer precipitation (when most precipitation occurs on the QTP) and in more spatial detail than the limited observational data. More precipitation is simulated than observed in the southern QTP, and less in the northern QTP. Although RegCM3 does reproduce annual variations of precipitation at the QTR stations reasonably well, there are some flaws. The simulated inter annual variations of precipitation are not as good as those for temperature. Further improvements to the land-surface parameterization scheme for local conditions are required in future work on the QTP.

On the basis of meteorological station records during 1961-2010, we investigate the variations of temperature and precipitation in the Qaidam Basin. Results show that climate warming is significant in the region of Qaidam Basin over the past 50years, with an average warming rate of 0.53 degrees C10a(-1). The largest and smallest warming rate happened at Mangya station (0.89 degrees C10a(-1)) and Lenghu station (0.24 degrees C10a(-1)), respectively. Seasonal warming was greatest in winter at eight meteorological stations, ranging from 0.43 degrees C10a(-1) (Lenghu station) to 1.01 degrees C10a(-1) (Delingha station). Since 1961, the annual precipitation has increased with a rate of 7.38mm10a(-1). Seasonal precipitation mainly increased in summer (4.02mm10a(-1)). The maximum precipitation increase occurred at Delingha station (25.09mm10a(-1)) and the minimum at Lenghu station (0.10mm10a(-1)). The elevation dependency of warming trends is unremarkable because most of the stations are located at lower altitudes. It is suggested that sunshine duration is related to the tendencies of temperature increase at different stations. Pollution emissions from industrial processes (i.e. brown clouds) and urbanization are the main factors contributing to the warming climate. Furthermore, the predominant weakening of zonal wind speed over the Tibetan Plateau resulted from the global warming also contributes to the climate warming in the Qaidam Basin. Consequently, the warming rate in the Qaidam Basin is much higher than in other regions over the Tibetan Plateau. The Qaidam Basin is thus considered to be the most susceptible region with the most significant warming in the Tibetan Plateau.

Spatial patterns of annual and seasonal precipitation over the source region of the Yellow River and the corresponding long-term trends for the period 1960–2013 are investigated using the meteorological station data. The spatial precipitation variability analysis shows an increasing gradient of precipitation from northeast to southwest in the study area. Annual, spring, summer, and winter precipitation present increasing trend, but autumn precipitation shows a decreasing trend in the last 50 years. It is also noted that the distribution of the intra-annual precipitation is very uneven, precipitation in rainy season (May–October) accounts for about 90 % of the total annual rain. Meanwhile, this research analyzes the spatial precipitation characteristic of the rainy season in 2013 (mainly from June to September). Based on the observed precipitation data and the meteorological station data, the rainy season precipitation that varies according to different topographic conditions is analyzed, and the regression model between recorded precipitation and geographical factors is built up too. The spatial distribution graph of the rainy season precipitation is generated on GIS platform by regression model and graphical features. This distribution shows a general northeast–southwest gradient of increasing rainy season precipitation in the study area and has detailed spatial precipitation characteristic along with altitude.

The effects of different RegCM4 land-surface schemes on Tibetan Plateau (TP) precipitation simulations were investigated. Two groups of ten-year (1992–2001) simulation experiments (hereafter referred to as BATS and CLM) were performed based on two land-surface schemes (BATS and CLM3.5, resp.) and were compared with observed data using the same domain, initial, and lateral boundary conditions, cumulus convective scheme, and spatial resolution. The results showed that the CLM monthly precipitation more closely matched the observed data compared with BATS. BATS and CLM both overestimated summer precipitation in the northern TP but underestimated summer precipitation in the southern TP. However, CLM, because of its detailed land-surface process descriptions, reduced the overestimated precipitation areas and magnitudes of BATS. Compared to CN05, the regional average summer precipitation in BATS and CLM was overestimated by 34.7% and underestimated by 24.7%, respectively. Higher soil moisture, evapotranspiration, and heating effects in the BATS experiment triggered changes in atmospheric circulation patterns over the TP. Moreover, BATS simulated the lower atmosphere as warmer and more humid and the upper atmosphere (~150 hPa) as colder than the CLM simulations; these characteristics likely increased the instability for moist convection and produced more summer precipitation.

The Tibetan Plateau (TP), which is well known as “The Third Pole”, is of great importance to climate change in East Asia, and even the whole world. In this paper, we selected the monthly temperature (including the monthly mean and the maximum and minimum temperature) during 1971–2015 from 88 meteorological stations on the TP. The data were tested and corrected by using Penalized Maximal F Test (PMFT) based on RHtest. Afterwards, based on the Mann-Kendall test, we analyzed the seasonal and time-interval characteristics on each station in detail. The results show that the TP has experienced significant warming during 1971–2015. When comparing the selected elements, the warming rate of minimum temperature (Tmin) is the largest, the mean temperature (Tmean) comes second, and the maximum temperature (Tmax) is the smallest. The warming trends in four seasons are significant, and the highest warming rate occurs in winter. The warming trend on the TP has a prominent spatial difference, with a large warming rate on the eastern parts and a small one on the central regions. In different seasons, the warming trends on the TP have different characteristics in the time interval. Since 1998, the warming rate in spring increased markedly, spring has displaced winter as the season with the highest warming rate recently.

The Tibetan Plateau(TP) is known as ‘the water tower of Asian’, its precipitation variation play an important role in the eco-hydrological processes and water resources regimes. based on the monthly mean precipitation data of 65 meteorological stations over the Tibetan Plateau and the surrounding areas from 1961-2015,variations, trends and temporal-spatial distribution were analyzed, furthermore, the possible reasons were also discussed preliminarily. The main results are summarized as follows: the annual mean precipitation in the TP is 465.54mm during 1961-2015, among four seasons, the precipitation in summer accounts for 60.1% of the annual precipitation, the precipitation in summer half year (May.- Oct.) accounts for 91.0% while that in winter half year (Nov.- Apr.) only accounts for 9.0%; During 1961-2015, the annual precipitation variability is 0.45mm/a and the seasonal precipitation variability is 0.31mm/a, 0.13mm/a, -0.04mm/a and 0.04mm/a in spring, summer, autumn and winter respectively on the TP; The spatial distribution of precipitation can be summarized as decreasing from southeast to northwest in the TP, the trend of precipitation is decreasing with the increase of altitude, but the correlation is not significant. The rising of air temperature and land cover changes may cause the precipitation by changing the hydrologic cycle and energy budget, furthermore, different pattern of atmospheric circulation can also influence on precipitation variability in different regions.