The variation of land surface temperature (LST) has a vital impact on the energy balance of the land surface process and the ecosystem stability. Based on MDO11C3, we used methods including regression analysis, GIS spatial analysis, correlation analysis, and center-of-gravity model, etc., to analyze the LST variation and its spatiotemporal diversity in China from 2001 to 2020. Finally, the Geodetector was used to identify the leading factors of LST variation in 38 eco-geographical zones of China, and explore the causes of its pattern. The results show that: (1) the average LST in China from 2001 to 2020 is 9.6 ℃, which is high in the plains, and low in the mountainous areas. Generally, LST has a striking negative correlation with altitude, with a correlation coefficient of -0.66. China's First Ladder has the most conspicuous negative correlation, with a correlation coefficient of -0.76 and the lapse rate of LST is 0.57 ℃/100 m. (2) The change rate of LST in China during the study period is 0.21 ℃/10 a, and the warming area accounts for 78%, showing the spatial characteristics of "multi-core warming and axial cooling" in general. (3) LST's variation has prominent seasonal characteristics in the whole country. The spatial distribution of average value in winter and summer is quite different and fluctuates obviously; the moving trajectory of the centroid in the warming/cooling area is close to a loop shape. The movement direction shows the corresponding seasonal reverse, and the movement range in the cooling zone is larger, indicating that the regional difference and seasonal variability of the cooling zone are more obvious. (4) China's LST variation is driven by natural conditions and human activities, of which natural factors contribute more, with sunshine hours and altitude being the key factors. The boundary trend between the two dominant type areas is highly consistent with the "Heihe-Tengchong Line". The eastern region is mostly dominated by human activity intensity and interacts with terrain factors, while the western region is dominated by natural factors, which enhance/weaken the change range of LST through mutual coupling with the climate, terrain, vegetation, and other factors. This study can provide scientific references for dealing with climate change, analyzing surface environmental models, and protecting the ecological environment.

Vegetation recovery under global change and its consequent evolution of eco-hydrological processes have modulated the water resources conservative capacity in the source region of the Yellow River (YRSR). Based on climatological data, remotely sensed vegetation index and geographical information, the integrated simulations of water and carbon cycles in the YRSR are presented, with the vegetation interface processes (VIP) distributed eco-hydrological dynamic model. Then the co-evolving mechanisms of hydrological and vegetation dynamics are investigated. Results show that warming and wetting climate in the YRSR has improved the vegetation growing condition and extended the growing period for more than 10 days in recent decades. Averaged NDVI from 2010 to 2020 increased by 4.5% relative to that from 2000 to 2009. Vegetation gross primary productivity (GPP) shows a significant uptrend with a rate of 4.57 gC m^-2 a^-1, 77% of which is contributed by climate change and elevated atmosphere CO₂ fertilization, and the rest 23% is by vegetation greening. Evapotranspiration (ET) is increasing at a rate of 2.54 mm a^-1 and vegetation water use efficiency (WUE, expressed as GPP/ET) is also improving at a relative rate of 5.1% a^-1. Generally, annual ET, GPP and WUE and their trends are decreasing along the elevation below 4200 m. At basin scale, there are significant positive correlations between the vegetation greenness and the runoff coefficient with precipitation in the current and previous years, demonstrating a legacy effect of precipitation for vegetation recovery on water conservation capacity. The increased ET might be a benefit to the water recycle between land surface and atmosphere, which will alleviate the reduced potential of water yield owing to ecological restoration and establish trades-off and synergies among precipitation, vegetation and water yield. Conclusively, exploring the mechanisms of hydrological responses to climate change and vegetation recovery and its feedback will provide scientific support to the assessment of ecological engineering programs in the source regions.

The composition of hydrogen and oxygen stable isotopes of atmospheric precipitation can indicate the climatic and environmental changes of precipitation process. It is of great significance to analyze and understand the changes of stable isotopes of atmospheric precipitation and examine the hydrological cycle process under current and past climatic conditions. Based on the determination of δ²H and δ¹⁸O in 152 precipitation samples collected from 8 stations in the eastern Loess Plateau in the summer of 2019 (April-October), the spatial and temporal distribution characteristics of δ²H and δ¹⁸O and their relationship with meteorological parameters and sub-cloud evaporation were systematically analyzed. The HYSPLIT model was used to analyze the source and migration path of water vapor. The results show that: (1) δ²H and δ¹⁸O of summer precipitation in the study area have obvious seasonal variation, which gradually enriched from May to July and gradually depleted from August to September; the precipitation δ²H and δ¹⁸O also showed significant spatial differences, with a gradual increase from southeast to northwest. (2) The results of regional atmospheric precipitation line show that the overall precipitation in this area is significantly affected by the sub-cloud evaporation, but the precipitation process in the basin area (Zhaocheng, Yangquan, and Changzhi) is significantly affected by the local circulation. (3) δ¹⁸O in the precipitation of this region did not show significant indigenous temperature effect and precipitation effect. The temperature effect only existed in the Jiexiu station of the Fenhe river basin valley, while the precipitation effect existed at the Jiexiu and Linfen stations. (4) The sub-cloud evaporation has a significant influence on the Yangquan station in the middle of the rocky areas of Taihang Mountains, the Datong station in the north and the Linfen station in the Fenhe river basin valley. The hydrogen and oxygen stable isotopes of the cloud bottom and surface precipitation are significantly different. (5) The results of water vapor source analysis show that the main sources of summer precipitation in the region are near the ground and the Bohai Sea in the southeast direction, and the water vapor content of the western path in the long distance is relatively small. The results of this study are of great significance to improve the understanding of regional water cycle and the rational allocation of water resources.

A clear understanding of the precipitation variation patterns at high altitudes of the Qinling Mountains is a prerequisite for an in-depth understanding of the characteristics of this mountain range as China's north-south transitional zone and its important role of water resources in the Middle Route of South-North Water Transfer Project. However, understanding the precipitation changes in the mountainous areas of the Qinling Mountains has been hindered by limited effective precipitation observation data in these mountainous areas. An analysis of precipitation data measured from June 1, 2018, to May 31, 2019, at an altitude of 3760 m at the Mount Taibai of the Qinling Mountains revealed that the annual precipitation at this altitude can reach 1300 mm, which is much more than the 600-800 mm annual precipitation recorded in the Hanjiang Basin and the Guanzhong Plain. On this basis, the persistence of annual and seasonal precipitation patterns in the Qinling Mountains was examined by kriging, inverse distance weighted interpolation, and ANUSPLIN methods, as well as GPM-corrected data (GPM-cal) and ERA5 reanalysis data. Accurate high-altitude precipitation values could not be obtained using kriging and IDW. However, GPM-cal, ANUSPLIN, and ERA5 data could more accurately portray the variation of annual precipitation with topography in the Qinling Mountains. An analysis of water vapor fluxes showed that the Mount Taibai has significant blocking, forcing, and intercepting effects on southward moist airflow below the 600 hPa height owing to its high terrains, making its southern slope a regional center of high precipitation values. Combining high mountain precipitation observations, ANUSPLIN, multi-source grid point information, and data correction methods is an effective way to understand precipitation formation and variation in the Qinling Mountains.

Research on the impact of human activities on global climate change is not only the frontier of the discipline, but also the hotspot and difficulty. At present, the research focuses on the climate phenomena of urban impervious surface (IS), such as heat island and rain island effects, while the research on other climate factors has not yet to be carried out. Based on the Global IS Data Set (GAIA) and the China Region High-resolution Surface Meteorological Element Data Set, though the Mann-Kendall (M-K) mutation test and Bayesian model, this paper studied the spatiotemporal variation of IS, the relationship between meteorological elements and IS, and abnormal climatic phenomena for the 34 lakeside urban agglomerations in the Central Yunnan Plateau controlled by the subtropical high from 1985 to 2018. The results showed that the IS area increased by 227.56% compared with that in 1985, with the highest growth rate (89.85 km²/a) in the past 10 years (2007-2018), mainly expanding in S, NE, SE and W directions. During the past 34 years, the climate of the Central Yunnan urban agglomeration experienced three rapid transformation stages: cold and humid (1985-1995), warm and humid (1996-2006), and warm and dry (2007-2018). Compared with the permeable surface, IS had some significant climatic phenomena, including heat island (air temperature increases by 0.63 ℃, long wave increases by 4.49 W m²), rain island (precipitation increased by 38.27 mm), wet island (specific humidity increases by 0.51 g/kg), wind speed low island (wind speed decreased by 0.025 m/s) and air pressure high island (air pressure increased by 602.64 Pa). The spatial distribution of IS has a significant relationship with meteorological elements in a specific interval, such as long wave of 313~329 W m², specific humidity of 8.9~9.9 g/kg, air pressure of 76235~79946 Pa, short wave of 186~194 W m², precipitation of 840~876 mm and 876~998 mm, wind speed of 2.08~2.38 m/s and air temperature of 13.85~15.85 ℃. In that interval, meteorological elements respond significantly with the increase of the proportion of IS distribution. The impact of IS on air pressure and humidity has the abnormal characteristics of air pressure-temperature and humidity, which may be caused by subtropical high, elevation and large lakes (lake-land breeze).

The lunar landform is the result of the geological and geomorphic processes on the lunar surface. It is very important to identify the type of the lunar landforms. Geomorphology is the scientific study of the origin and evolution of topographic landforms on the planetary surface. Elevation and relief amplitude are the most commonly used geomorphic indexes in the study of geomorphological classification. Previous studies have determined the elevation classification criterion of lunar surface. In this paper, we focus on the classification criterion of the topographic relief amplitude of the lunar surface. As for the estimation of the best window to calculate the relief amplitude of the lunar surface, we used the method of change-point in the mean based on LOLA (Lunar Orbiter Laser Altimeter) DEM data and DEM that combines the LOLA and SELENE TC (Terrain Camera) merged Digital Elevation Model (SLDEM2015). According to the statistical analysis of the basic lunar landforms, the classification criterion of lunar surface relief amplitude is determined. Taking the topographic relief amplitudes of 100 m, 200 m, 300 m, 700 m, 1500 m and 2500 m as the thresholds, the lunar surface is divided into seven geomorphic types, including slightly micro-relief plains (< 100 m), slightly micro-relief platforms [100 m, 200 m), micro-relief landforms [200 m, 300 m), small relief landforms [300 m, 700 m), medium relief landforms [700 m, 1500 m), large relief landforms [1500 m, 2500 m) and extremely large relief landforms (≥ 2500 m). The slightly micro-relief plains are mainly distributed in the maria, and the floor of craters and basins that are filled with basalts, while the slightly micro-relief platforms are mainly distributed in the transition regions between the maria and highlands. The micro-relief landforms are mainly located in the regions with higher topography than the mare, such as wrinkle ridges and sinuous rilles in the mare. The small relief landforms are mainly scattered in the central peak and floor-fractured of craters. The medium relief landforms are mainly distributed in the transition regions between the rater floor and carter wall, between the crater wall and crater rim, between the basin floor and basin wall, and between the basin wall and basin rim. Large and extremely larger relief landforms are mainly scattered in the crater wall and basin wall. The determination of classification criteria of lunar surface relief amplitude in this paper can provide important references for the construction of digital geomorphology classification schemes of the lunar surface.