Soil temperature is an important physical variable that characterises geothermal conditions and influences geophysical, biological and chemical processes in the earth sciences. Soil temperature is not only affected by climatic and geographical factors; it is also modulated by local factors such as snow cover and vegetation. This paper investigates the relationship between snow cover and vegetation and soil temperature with the help of two classical remote sensing indicators, the Snow Cover Days (SCD) based Advanced Very High Resolution Radiometer and the Normalized Difference Vegetation Index (NDVI)-based Global Inventory Modelling and Mapping Studies, to analyse the influence of local factors on soil temperature in the Three River Source Region (TRSR). Combing multi-layer geothermal observations from 23 stations in the TRSR with meteorological dataset, soil properties datasets, snow cover and vegetation indices, a non-linear model, the Random Forest model, is used to establish a multi-layer soil temperature dataset to analyse the influence of surface cover factors in each depth. The results showed that the annual SCD had a decreasing trend during 1982–2015 and was negatively correlated with the annual mean soil temperature; the annual NDVI had no significant trend, but it was positively correlated with the annual mean soil temperature. Regionally, there was a significant decrease in SCD in the mountainous areas bordering the source areas of the three rivers, and there was a trend of increasing NDVI in the northwest and decreasing vegetation in the southwest in the TRSR. The stronger the correlation with soil temperature in areas with a larger SCD, the more the snow has a cooling effect on the shallower soil temperatures due to the high albedo of the accumulated snow and the repeated melting and heat absorption of the snow in the area. The snow has an insulating effect on the 40 cm soil layer by impeding the cooling effect of the atmosphere in winter. In sparsely vegetated areas, vegetation lowers ground albedo and warms the soil, but in July and August, in areas with more vegetation, NDVI is negatively correlated with soil temperature, with heavy vegetation intercepting summer radiant energy and having a cooling effect on the soil.

Depth-to-bedrock (DTB) determines soil thickness in land surface models and controls the active depth of hydrological and biogeochemical processes, particularly important in permafrost regions where soil thickness affects both hydrologic and heat transfer. In this study, we evaluate the sensitivity of permafrost hydrothermal regime to DTB parameterization in Community Land Model version 5.0 (CLM5.0) by comparing two datasets: DTB_P (default DTB in CLM5.0, developed by Pelletier) and DTB_SG (Shangguan-derived DTB) over three sites (BLH, TGL, and XDT) and the Qinghai-Tibet Plateau (QTP). Through four experiments with increasing soil thickness, we find significant sensitivity of permafrost simulations to DTB, shallow DTB_P results in excess water being redistributed and overestimated active layer thickness (ALT) at three sites (9.1 m and 10.5 m at BLH and TGL, exceeding 42 m at XDT), while deeper DTB_SG improves simulations by enhancing soil column's water storage capacity and extending the depth of soil-parameterized heat transfer, where both thermal conductivity and heat capacity vary with soil properties rather than using constant bedrock values. At the regional scale, implementation of DTB_SG significantly reduces mean ALT from 8.83 m to 3.11 m across the QTP and from 9.04 m to 2.55 m in the Three Rivers Source Region, producing more realistic spatial patterns and temporal variations. We conclude that while soil liquid water simulations stabilize beyond 4.0 m, greater soil thickness continues to benefit thermal processes, establishing a minimum DTB threshold of 4.0 m for reliable permafrost simulations in the QTP.

Ozone (O₃) pollution in coastal urban regions is strongly influenced by sea–land breeze (SLB) circulation. However, linking its long-term surface effects with vertically resolved observations remains an important research need in the western Pearl River Delta (PRD). This study combines meteorological and surface O₃ observations from 2014–2023 with lidar measurements and ERA5 reanalysis for a case study on 25–26 July 2023. We examine three complementary aspects: SLB frequency and temporal characteristics, surface O₃ concentrations and peak timing, and vertical O₃ redistribution. SLB days accounted for 13.1–19.4% of days annually, with mean sea-breeze and land-breeze durations of 8.79 and 6.63 h, respectively. Surface O₃ concentrations were generally higher on SLB days in all seasons, with larger increases at inland sites, particularly in spring and autumn. Changes in peak timing varied by season and site. The case study suggests a vertical recirculation pathway in which nocturnal return flow transports O₃-rich air inland aloft, followed by downward redistribution during daytime boundary-layer development. By integrating a decade of surface observations with vertically resolved evidence from an individual event, this study connects regional statistical patterns with a physical interpretation of coupled horizontal recirculation and vertical redistribution. These findings highlight the importance of considering breeze timing, elevated O₃ layers, and boundary-layer mixing in coastal air-quality forecasting, chemical transport modeling, and regional pollution mitigation.