The precipitation recycling (PR) ratio is an important indicator that quantifies the land-atmosphere interaction strength in the Earth system’s water cycle. To better understand how the heterogeneous land surface in the Tibetan Plateau (TP) contributes to precipitation, we used the water-vapor tracer (WVT) method coupled with the Weather Research and Forecasting (WRF) regional climate model. The goals were to quantify the PR ratio, in terms of annual mean, seasonal variability and diurnal cycle, and to address the relationships of the PR ratio with lake treatments and precipitation amount. Simulations showed that the PR ratio increases from 0.1 in winter to 0.4 in summer when averaged over the TP with the maxima centered at the headwaters of three major rivers (Yangtze, Yellow and Mekong). For the central TP, the highest PR ratio rose to over 0.8 in August, indicating that most of the precipitation was recycled via local evapotranspiration in summer. The larger daily mean and standard deviation of the PR ratio in summer suggested a stronger effect of land-atmosphere interactions on precipitation in summer than in winter. Despite the relatively small spatial extent of inland lakes, the treatment of lakes in WRF significantly impacted the calculation of the PR ratio over the TP, and correcting lake temperature substantially improved both precipitation and PR ratio simulations. There was no clear relationship between PR ratio and precipitation amount; however, a significant positive correlation between PR and convective precipitation was revealed. This study is beneficial for the understanding of land-atmosphere interaction over high mountain regions.

Poyang Lake is the largest freshwater lake in China and is characterized by significant intra-annual variation, with higher water levels and area in the wet season compared to the dry season. However, the effects of the seasonal variation in Poyang Lake on the local weather are still not well-recognized. With the help of the weather research and forecasting (WRF) model, we designed one control experiment (CTL) using the default Poyang Lake level and area data and two sensitivity experiments, EXPT1 and EXPT2, the former representing the higher lake level and the greater area of Poyang Lake in the wet season and the latter representing the lower lake level and the smaller area of Poyang Lake in the dry season, to assess how these changes affect the local weather. The results of EXPT1 show that, as the lake’s level and area increase, the latent heat flux (LH), the sensible heat flux (SH), and the land surface temperature (LST) in the lake area decrease compared to those of the CTL. Meanwhile, the planetary boundary layer height (PBL), the convective available potential energy (CAPE), the wind speed, and the vapor flux over the lake decrease as well, indicating increased atmospheric stratification stability and resulting in a domain-averaged decline in precipitation of −22.3 mm. However, the low lake level and less area in EXPT2 show increasing SH, LST, PBL, and wind speed, and decreasing LH and CAPE compared to those of the CTL. The increasing SH and weakened atmospheric stratification stability in EXPT2 cause a significantly higher wind speed over the eastern part of the lake. As a result, more water vapor is transported to the east side of the lake by westerly upper winds, leading to a decreasing precipitation on the western side of the lake and a slightly increasing precipitation on the eastern side, resulting ultimately in a domain-averaged decline in precipitation of −23.8 mm in the simulation of the low level and less area of Poyang Lake. Although the LH and CAPE decline both in EXPT1 and EXPT2, the main cause is the higher water thermal capacity and lower lake-surface temperature with more lake water for EXPT1 and the lower evaporation with less lake water for EXPT2. Overall, a deeper and larger Poyang Lake will reduce the local temperature, inhibit water evaporation from the lake surface, and make the near-surface atmosphere more stable, resulting in restrained local precipitation. A shrinking lake level and area will raise the local temperature and the instability of the near-surface atmosphere but reduce water vapor and enlarge local wind and circulation, resulting in declining precipitation and a changing fall zone.

The Tibetan Plateau (TP) is distributed with large areas of permafrost, which have received increasing attention as the climate warms. Accurately modeling the extent of permafrost and permafrost changes is now an important challenge for climate change research and climate modeling in this region. Uncertainty in land use and land cover (LULC), which is important information characterizing surface conditions, directly affects the accuracy of the simulation of permafrost changes in land surface models. In order to investigate the effect of LULC uncertainty on permafrost simulation, we conducted simulation experiments on the TP using the Community Land Model, version 5 (CLM5) with five high-resolution LULC products in this study. Firstly, we evaluated the simulation results using shallow soil temperature data and deep borehole data at several sites. The results show that the model performs well in simulating shallow soil temperatures and deep soil temperature profiles. The effect of different land use products on the shallow soil temperature and deep soil temperature contours is not obvious due to the small differences in land use products at these sites. Although there is little difference in the simulating results of different land use products when compared to the permafrost distribution map, the differences are noticeable for the simulation of the active layer. Land cover had a greater impact on soil temperature simulations in regions with greater land use inconsistency, such as at the junction of bare soil and grassland in the northwestern part of the TP, as well as in the southeast region with complex topography. The main way in which this effect occurs is that land cover affects the net surface radiation, which in turn causes differences in soil temperature simulations. In addition, we discuss other factors affecting permafrost simulation results and point out that increasing the model plant function types as well as carefully selecting LULC products is one of the most important ways to improve the simulation performance of land-surface models in permafrost regions.

The Tibetan Plateau (TP) region contains maximal alpine grassland ecology at the mid-latitudes. This region is also recognized as an ecologically fragile and sensitive area under the effects of global warming. Regional climate modeling and ecosystem research depend on accurate land cover (LC) information. In order to obtain accurate LC information over the TP, the reliability and precision of five moderate/high-resolution LC products (MCD12Q1, C3S-LC, GlobeLand30, GLC_FCS30, and ESA2020 in 2020) were analyzed and evaluated in this study. The different LC products were compared with each other in terms of areal/spatial consistency and assessed with four reference sample datasets (Geo-Wiki, GLCVSS, GOFC-GOLD, and USGS) using the confusion matrix method for accuracy evaluation over the TP. Based on the paired comparison of these five LC datasets, all five LC products show that grass is the major land cover type on the TP, but the range of grass coverage identified by the different products varies noticeably, from 43.35% to 65.49%. The fully consistent spatial regions account for 43.72% of the entire region of the TP, while, in the transition area between grass and bare soil, there is still a large area of medium-to-low consistency. In addition, a comparison of LC datasets using integrated reference datasets shows that the overall accuracies of MCD12Q1, C3S-LC, GlobeLand30, GLC_FCS30, and ESA2020 are 54.29%, 49.32%, 53.03%, 53.73%, and 60.11%, respectively. The producer accuracy of the five products is highest for grass, while glaciers have the most reliable and accurate characteristics among all LC products for users. These findings provide valuable insights for the selection of rational and appropriate LC datasets for studying land-atmosphere interactions and promoting ecological preservation in the TP.

The Tibetan Plateau (TP) is a climate-sensitive and ecologically fragile area. Studying drought and its effects on vegetation over the TP is of great significance for ecological conservation. However, there were large uncertainties in previous studies on the drought characteristics and their impacts on alpine vegetation in this region. This study explored the drought changes and their impacts on alpine vegetation during the growing season over the TP in 1982–2018. The results showed that the TP has experienced a wetting trend in most regions of the TP. Correspondingly, the vegetation has become greener in most areas. The wetting and drying trend in the growing season changed around 1995. Before 1995, the TP experienced an overall drying trend with a spatial pattern of a drying trend in the northern regions and a wetting trend in the southern regions, while it showed an overall wetting trend after 1995, with a reversed spatial pattern to that before 1995. After 1995, wetting and drying trends affected the vegetation in 61% of the TP. However, before 1995, the NDVI presented an increasing trend in most areas of the TP under a drying trend. Therefore, a drying trend was not the primary factor affecting vegetation growth in this period. Instead, changes in the cryosphere induced by warming could be the main factor. In addition, the distribution of vegetation across the TP was primarily influenced by drought intensity, which had the greatest impact on sparse vegetation, followed by meadow and grassland. This study enhances our understanding of the impact of drought changes on alpine vegetation on the TP.