Land surface temperature (LST) is an important parameter that affects the water cycle, environmental changes, and energy balance at global and regional scales. Herein, a time series analysis was conducted to estimate the monthly, seasonal, and interannual variations in LST during 2001–2019 in the Tarim Basin, China. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) LST, air temperature, air pressure, relative humidity, wind speed, precipitation, elevation, and land-cover type data, we analyzed the spatio-temporal change characteristics of LST and the influencing factors. High LSTs occurred in the desert and plains and low LSTs occurred in surrounding mountain regions. The highest LST was recorded in July (25.1 °C) and the lowest was in January (−9.5 °C). On a seasonal scale, LST decreased in the order: summer > spring > autumn > winter. Annual LST showed an increasing trend of 0.2 °C/10 a in the desert and mountain areas, while the plains indicated a decreasing trend. In spring and autumn, western regions were dominated by a downward trend, whereas in winter a downward trend occurred in eastern regions. In summer, areas covered by vegetation were dominated by a downward trend, and desert and bare lands were dominated by an upward trend. Random forest (RF) model analysis showed that elevation was the most significant influencing factor (22.1%), followed by mean air temperature (20.1%). Correlation analysis showed that the main climatic factors air temperature, relative humidity, and elevation have a good correlation with the LST. Land-cover type also affected LST; during February–December the lowest LST was observed for permanent glacier snow and the highest was observed in the desert. El Nino and La Nina greatly influenced the LST variations. The North Atlantic Oscillation and Pacific Decadal Oscillation indices were consistent with the mean LST anomaly, indicating their considerable influence on LST variations.

Aerosol optical depth (AOD), which represents the optical attenuation, poses a major threat to the production activity, air quality, human health and regional sustainable development of arid and semi-arid areas. To some degree, AOD shows areal air pollution level and possesses obvious spatio-temporal characteristics. However, long-time sequences and detailed AOD information can not be provided due to currently limited monitoring technology. In this paper, a daily AOD product, MODIS-based Multi-angle Implementation of Atmospheric Correction (MAIAC), is deployed to analyze the spatio-temporal characteristics in Xinjiang Uygur Autonomous Region from 2000 to 2019. In addition, the importance of influencing factors for AOD is calculated through Random Forest (RF) Model and the propagation trajectories of pollutants are simulated through Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model. Spatio distribution of AOD presents a tendency that AOD value in northern Xinjiang is low while the value in southern Xinjiang is high. Regions with high AOD values are mainly concentrated in Tarim Basin. AOD in southern Xinjiang is the highest, followed by that in eastern Xinjiang and AOD value in northern Xinjiang is the lowest. Seasonal variation of AOD is significant: Spring (0.309) > summer (0.200) > autumn (0.161) > winter (0.158). Average AOD value in Xinjiang is 0.196. AOD appears wavy from 2000 to 2014 with its low inflection point (0.157) appearing in 2005, and then increases, reaching its peak in 2014 (0.223). The obvious downward tendency after 2014 shows that the use of coal to natural gas (NG) conversion project improves the conditions of local environment. According to RF Model, NG contributes most to AOD. HYSPLIT Model reveals that aerosol in southern Xinjiang is related to the short-distant carriage of dust aerosol from the Taklimakan Desert. Aerosol there can affect Inner Mongolia through long-distant transport. Blocked by the Tianshan Mountains, fine dust particles can not cross the Tianshan Mountains to become a factor contributing to AOD in northern Xinjiang.

Central Asia (CA) is one of the major sources of global dust aerosols. They pose a serious threat to regional climate change and environmental health and also make a significant contribution to the global dust load. However, there is still a gap in our understanding of dust transport in this region. Therefore, this study utilizes Cloud–Aerosol LiDAR with Orthogonal Polarization (CALIOP) data from 2007 to 2022 to depict the three-dimensional spatiotemporal distribution of dust aerosols over CA and to analyze their transport processes. In addition, the Tropospheric Monitoring Instrument (TROPOMI) was employed to assist in monitoring the movement of typical dust events, and the trajectory model was utilized to simulate the forward and backward trajectories of a dust incident. Additionally, a random forest (RF) model was employed to rank the contributions of various environmental factors. The findings demonstrate that high extinction values (0.6 km⁻¹) are mostly concentrated within the Tarim Basin of Xinjiang, China, maintaining high values up to 2 km in altitude, with a noticeable decrease as the altitude increases. The frequency of dust occurrences is especially pronounced in the spring and summer seasons, with dust frequencies in the Tarim Basin and the Karakum and Kyzylkum deserts exceeding 80%, indicating significant seasonal and regional differences. The high values of dust optical depth (DOD) in CA are primarily concentrated in the summer, concurrent with the presence of a stable aerosol layer of dust in the atmosphere with a thickness of 0.62 km. Furthermore, dust from CA can traverse the Tianshan mountains via the westerlies, transporting it eastward. Additionally, skin temperature can mitigate regional air pollution. Our results contribute to a deeper understanding of the dynamic processes of dust in CA and provide scientific support for the development of regional climate regulation strategies.

The precipitation on the northern slope of the Kunlun Mountains significantly impacts the green economy of the Tarim Basin’s southern edge. Observations have noted an expansion of the surface water area in this region, though the reasons for this are not yet fully understood. Due to limited instrumental data, this study leverages field measurements from the third Xinjiang comprehensive expedition and multiple gridded datasets. Through trend analysis and a geographical detector model, it examines the precipitation’s decadal, interannual, and seasonal variations across key areas (Hotan River Basin, Keriya River Basin, Qarqan River Basin, and Kumukuli Basin), identifying factors behind the spatial and temporal distribution of regional precipitation. The findings reveal the following: (1) An increase in annual precipitation across the region from 187.41 mm in the 1980s to 221.23 mm in the early 21st century, at a rate of 10.21 mm/decade, with the most significant rise in the eastern Kunlun-Kumukuli Basin. (2) Precipitation exhibits clear seasonal and spatial patterns, predominantly occurring in spring and summer, accounting for 90.27% of the annual total, with a general decrease from the mountains towards downstream areas. (3) Rising average annual temperatures contribute to an unstable atmospheric structure and increased water-holding capacity, facilitating precipitation. Significant influences on precipitation changes include the North Atlantic Oscillation and solar flux, explaining 43.98% and 31.21% of the variation, respectively.