As a land–atmosphere coupling “hot spot”, the northern China climate transition zone has a sharp spatial gradient of hydrothermal conditions, which plays an essential role in shaping the spatial and temporal pattern of evapotranspiration-precipitation coupling, but whose mechanisms still remain unclear. This study analyzes the spatial and temporal variation in land–atmosphere coupling strength (CS) in the climate transitional zone of northern China and its relationship with soil moisture and air temperature. Results show that CS gradually transitions from strong positive in the northwest to negative in the southeast and northeast corners. The spatial distribution of CS is closely related to climatic hydrothermal conditions, where soil moisture plays a more dominant role: CS increases first, and then decreases with increasing soil moisture, with the threshold of soil moisture at 0.2; CS gradually transitions from positive to negative at soil moisture between 0.25 and 0.35; CS shows an exponential decreasing trend with increasing temperature. In terms of temporal variation, CS is strongest in spring and weakens sequentially in summer, autumn, and winter, and has significant interdecadal fluctuations. The trend in CS shifts gradually from significantly negative in the west to a non-significant positive in the east. Soil moisture variability dominates the intra-annual variability of CS in the study regions, and determines the interannual variation of CS in arid and semi-arid areas. Moreover, the main reason for the positive and negative spatial differences in CS in the study area is the different driving regime of evapotranspiration (ET). ET is energy-limited in the southern part of the study area, leading to a positive correlation between ET and lifting condensation level (LCL), while in most of the northern part, ET is water-limited and is negatively correlated with LCL; LCL has a negative correlation with P across the study area, thus leading to a negative ET-P coupling in the south and a positive coupling in the north.

Evapotranspiration (ET) is an essential component of the land–atmosphere water cycle. In this work, the trend of ET and its dominant factors during 1982 to 2011 are investigated in the northern drought-prone belt of China (NDPB) based on five datasets, including the gridded FLUXNET, using the Pearson correlation and linear regression methods. Specially, we focus on the increasing contribution of vegetation in the change of ET. During 1982–2011, summer ET significantly increased at the rate of 0.33 mm/year (p < 0.05) in the NDPB. However, similar to global-mean ET, the ET in NDPB also experienced a pronounced fluctuation during 1999 and 2002. The role of water supply differed remarkably before and after the fluctuation while the atmospheric demand maintained weak constraint on ET. Before the fluctuation (during 1982–2000), ET correlated significantly (p < 0.01) and positively with soil moisture, indicating ET was primarily limited by water supply. However, their correlation weakened remarkably after the fluctuation when soil moisture decreased to the lowest level for the past thirty years, indicating that neither moisture supply nor atmospheric demand dominated the ET during this period. In contrast, vegetation leaf area index (LAI) maintained consistent significant (p < 0.01) and positive correlation with ET before and after the fluctuation in the NDPB, and it reflected over 60% of the change in ET. Moreover, the LAI in NDPB increased by 19.6% which was more than double of the global-mean increase. The ET increase due to rising LAI offset the ET decrease due to reduction of soil moisture, and vegetation became the primary constraint on ET during 2001–2011. The expansion of vegetation may intensify the risk of drought and cause conflicting demands for water between the ecosystem and humans in the NDPB, especially in the case of weak summer monsoon.

The Qinghai–Tibet Plateau (QTP) is a crucial component of the global climate system, influencing the regional and global climate through complex thermal and dynamic mechanisms. The high-altitude region, which is the largest part of the extra-polar cryosphere, encompasses extensive mountain glaciers, permafrost, and seasonally frozen land, making it highly sensitive to global climate change. However, the challenging environmental conditions, such as the harsh terrain and high altitude, coupled with sparse weather station distribution and weak observatory representation, make it difficult to accurately quantify the atmospheric conditions and land–atmosphere coupling systems and their effects on the surrounding areas. To address these challenges, we utilized the Weather Research and Forecasting (WRF) model and a three-dimensional variational (3DVAR) assimilation method to create a high-resolution assimilated dataset (HRAD). The QTP-HRAD, covering the spatial range of 70 to 110°E and 25 to 40°N, was validated using both surface weather station observations and the European Center for Medium-Range Weather Forecasts Reanalysis V5, and can now be utilized for further studies on land–atmosphere interactions, water cycling and radiation energy transfer processes, and extreme weather events in the region.

This paper documents a windshear case for an airport in the Qinghai-Tibet Plateau and explores, for the first time, the capability for high-resolution numerical weather simulation of the wind shear features. The windshear appears to be associated with pulses of the wind speed in a low-level easterly jet. The features are basically reproduced quite well with the high-resolution numerical model, though some discrepancies are identified, such as the maximum wind speed of the easterly jet and the magnitude of the eddy dissipation rate as compared with the actual Doppler LIDAR observations. Statistical analysis has been performed between the observation and the simulation results. The sensitivity of the modeling result to the choice of turbulence parameterization scheme has also been studied. The study result shows that it is possible to forecast the windshear feature using a high-resolution numerical weather prediction model for an airport in the complex terrain of the Plateau.

Reducing anthropogenic fossil fuel CO₂ (FFCO₂) emissions in urban areas is key to mitigating climate change. To better understand the spatial characteristics and temporal variations in urban CO₂ levels in the Beijing (BJ) region, we conducted a long-term CO₂ simulation study by using the Weather Research and Forecasting WRF-Chem model and CO₂ observation data. To assess the model performance, three representative sites with high-precision CO₂ observation data were chosen in this study: the rural regional background Shangdianzi (SDZ) site, the suburban Xianghe (XH) site, and the urban BJ site. The simulation results generally captured the observed variations at these three sites, but the model performed much better at the SDZ and XH sites, with mean biases of −0.7 ppm and −2.3 ppm, respectively, and RMSE of 12.3 ppm and 21.4 ppm, respectively. The diurnal variations in the model results agreed well with those in the observed CO₂ concentrations at the SDZ and XH sites during all seasons. In the meanwhile, the diurnal variations in the modeled FFCO₂ were similar to those in the CO₂ observation with a positive bias at the BJ site, which may have been caused by higher emissions especially in winter. Moreover, both the modeled FFCO₂ and biospheric CO₂ (BIOCO₂) have positive correlations with the observed CO₂ concentration, whereas the planetary boundary layer height (PBLH) and observed CO₂ concentration exhibited negative correlations at all sites. In addition, the contributions of FFCO₂ and BIOCO₂ to CO₂ varies depending on the seasons and the location of sites.