Near-surface wind measurements obtained with five 100-m meteorology towers, 39 regional automatic stations, and simulations by the Weather Research and Forecasting (WRF) model were used to investigate the spatial structure of topography-driven flows in the complex urban terrain of Urumqi, China. The results showed that the wind directions were mainly northerly and southerly within the reach of 100 m above ground in the southern suburbs, urban area, and northern suburbs, which were consistent with the form of the Urumqi gorge. Strong winds were observed in southern suburbs, whereas the winds in the urban, northern suburbs, and northern rural areas were weak. Static wind occurred more frequently in the urban and northern rural areas than in the southern suburbs. In the southern suburbs, wind speed was relatively high throughout the year and did not show significant seasonal variations. The average annual wind speed in this region varied among 1.9–5.5, 1.1–3.6, 1.2–4.3, 1.2–4.3, and 1.1–3.5 m s ⁻¹ within the reach of 100 m above ground at Yannanlijiao, Shuitashan, Liyushan, Hongguangshan, and Midong, respectively. The flow characteristics comprised more airflows around the mountain, where the convergence and divergence were dominated by the terrain in eastern and southwestern Urumqi. Further analysis showed that there was a significant mountain–valley wind in spring, summer, and autumn, which occurred more frequently in spring and summer for 10–11 h in urban and northern suburbs. During daytime, there was a northerly valley wind, whereas at night there was a southerly mountain wind. The conversion time from the mountain wind to the valley wind was during 0800–1000 LST (Local Standard Time), while the conversion from the valley wind to the mountain wind was during 1900–2100 LST. The influence of the mountain–valley wind in Urumqi City was most obvious at 850 hPa, according to the WRF model.

Using data from the Integrated Global Radiosonde Archive Version 2 (IGRA2) and the Multi Model Ensemble (MME) of four global climate models (GCMs), named CanESM5, IPSL-CM6A-LR, MIROC6, and MRI-ESM2-0, within the framework of phase 6 of the Coupled Model Intercomparison Project (CMIP6), we analyzed the changes in atmospheric total column water vapor (TCWV) over Central Asia in the future (2021–2100) under SSP-RCPs scenarios: SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5, relative to baseline period (1986–2005). Results showed that the annual mean TCWV from IGRA2 was consistent with the model output from 1979 to 2014 in Central Asia. Besides, the spatial distribution of TCWV in Central Asia during the baseline period was consistent between the models. The regional average value of Central Asia was between 10.8 mm and 12.4 mm, and decreased with elevation. TCWV will increase under different SSP-RCPs from 2021 to 2040, but showed different trends after 2040. It will increase under SSP1-1.9 and SSP1-2.6 scenarios from 2021 to 2050, and decrease after that. It will grow from 2021 to 2055 under SSP4-3.4 scenario, and then stay essentially constant. Under SSP2-4.5 and SSP4-6.0 scenarios, TCWV will rise rapidly during 2021–2065, but the growth will decline from 2065 to 2100. TCWV will continue to increase under SSP3-7.0 and SSP5-8.5 scenarios, and the largest increase is projected under SSP5-8.5 scenario. Change in near-surface temperature (Ts) matched the change in TCWV, but changes in precipitation and evapotranspiration are not significant during 2021–2100. In spite of the large variations in TCWV under different SSP-RCPs, the dominant characteristic in all scenarios shows that a large TCWV increase is demonstrated over areas with small TCWV amounts during the baseline period. On the contrary, increases will be small where the TCWV amounts had been large during the baseline period. The change in TCWV is highly correlated to the increase in Ts in Central Asia. Under SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5 scenarios, the higher the temperature due to higher radiative forcing, the steeper the regression slope between TCWV and Ts change. It is closest to the theoretical value of the Clausius-Clapeyron equation under SSP3-7.0 and SSP5-8.5 scenarios, but not presented under other scenarios. Spatially, steeper regression slopes during 2021–2100 have been found around the Caspian Sea in the southwest and in the high-elevation areas in the southeast of Central Asia, which is likely related to the abundant local water supply for evaporation.

Field observations made with unmanned aerial vehicles of the particulate matter (PM) concentration from the ground to a height of 500 m were conducted at Xiaotang and Tazhong in the Taklimakan Desert (TD), China, from 7 to 15 November 2019. The vertical structures of the PM concentrations were studied. Pulsed lidar observations showed that dust aerosols in the TD can reach heights of 4 km. Within 500 m above the ground, the PM_1.0, PM_2.5, and PM₁₀ concentrations were <100, <201, and <764 µg∙m⁻³, respectively, in the TD. On days containing sand-blowing periods (e.g., at 18:00 on 11 November), the PM_1.0, PM_2.5, and PM₁₀ concentrations were 10–17.7 times higher than on clear days. The northern margin of the TD (Xiaotang) was dominated by fine particles, while the hinterland (Tazhong) was dominated by coarse particles, because there was sparse vegetation around Xiaotang and the surface was sand and clay, while there was no vegetation around Tazhong and the surface was sand. During floating dust periods, the boundary layer was dominated by fine particles. The average PM_1.0/PM_2.5 ratios were 0.25–0.65 and 0.40–0.80 at Tazhong and Xiaotang, respectively, while, during sand blowing periods, these ratios were 0.40–0.55 and 0.40–0.45, respectively. The critical condition in the atmospheric boundary layer for PM concentration was revealed with the enhanced momentum flux and sensible heat flux up to 0.52 kg∙m⁻¹∙s⁻², 0.69 m∙s⁻¹, and 6.7 W∙m², respectively, and the low mixed layer was high in the lower atmosphere.

An observational data set of the year 2010 at a site in the northern marginal zone of the Taklimakan Desert (TD) was used to analyse the key surface parameters in land–atmospheric interactions in the desert climate of northwest China. We found that the surface albedo (α) and emissivity (ε) were 0.27 and 0.91, respectively, which were consistent with the values obtained based on observations in the hinterland of the TD as well as being similar to the dry parts of the Great Basin desert in North America, where they were comparable to the α and ε values retrieved from remote sensing products. Peak frequency value of z_0m was 5.858 × 10⁻³ m, which was similar to the Mojave Desert, Peruvian desert, Sonoran Desert, HEIFE (Heihe region) Desert, and Badain Jaran Desert. The peak frequency value of z_0h was 1.965 × 10⁻⁴ m, which was different from those obtained in the hinterland of the TD. The average annual value of excess resistance to heat transfer (kB⁻¹) was 2.5, which was different from those obtained in the HEIFE Gobi and desert, but they were similar to those determined for the Qinghai–Tibetan Plateau and HAPEX-Sahel. Both z_0m and z_0h varied less diurnally but notably seasonally, and kB⁻¹ exhibited weak diurnal and seasonal variations. We also found that z_0m was strongly influenced by the local wind direction. There were many undulating sand dunes in the prevailing wind and opposite to the prevailing wind, which were consistent with the directions of the peak z_0m value. The mean values calculated over 24 h for C_d and C_h were 6.34 × 10⁻³ and 5.96 × 10⁻³, respectively, which were larger than in the Gobi area, hinterland of the TD and semiarid areas, but similar to HEIFE desert. Under the normal prevailing (NNE–ESE) wind, the mean bulk transfer coefficient C_d and C_h were of the same order of magnitude as expected based on similarity theory. Using the data obtained under different wind directions, we determined the relationships between C_d, C_h, the wind speed U, and stability parameter z/L, and the results were different. C_d and C_h decreased rapidly as the wind speed dropped below 3.0 m s⁻¹ and their minimum values reached around 1–2 m s⁻¹. It should also be noted that the ε values estimated using the sensible heat flux (H) were better compared with those produced using other estimation methods.