Dust aerosols pose non‐negligible impacts on regional and global climate, particularly over northwest China (NWC), where dust events frequently occur. Here, six dust events with different intensities occurred from 2014 to 2019 in NWC were simulated by the Weather Research and Forecasting model coupled to Chemistry (WRF‐Chem) to quantitatively evaluate the contributions of dust aerosols to radiation fluxes, surface energy, and meteorology, with specific consideration to the distinctions between daytime and nighttime. The results show that the contributions of dust aerosols to surface energy and meteorology were significantly affected by dust concentrations and dust layer heights and exhibited diurnal variation. In the case with high dust concentration and low dust layer height, dust aerosols increased the surface energy during the nighttime but decreased in the daytime, and the increase was much greater than the decrease. As a result, dust aerosols increase surface energy (0.06 W/m² in the dust source region; 0.13 W/m² in the dust affected region (DAR)) and surface temperature (0.0088°C in the DSR; 0.0781°C in the DAR) and decrease surface relative humidity (−0.053% in the DSR; −0.205% in the DAR) throughout the whole day. In contrast, dust causes opposite impacts on surface meteorology throughout the whole day due to the nighttime warming effect from the dust events with low dust concentration and high dust layer height is lesser than the daytime cooling effect. The study provides scientific insights for improving our understanding of dust aerosols‐regional meteorology interaction.

Dust aerosols substantially impinge on the Earth’s climate by altering its energy balance, particularly over Northwest China, where dust storms occur frequently. However, the quantitative contributions of dust aerosols to direct radiative forcing (DRF) are not fully understood and warrant in-depth investigations. Taking a typical dust storm that happened during 9–12 April 2020 over Northwest China as an example, four simulation experiments based on the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) were designed, including a real scenario with dust emissions and three hypothetical scenarios without dust emissions, with dust emissions doubled, and with dust emissions reduced by half, to quantitatively evaluate the contributions of dust aerosols to DRF and then to surface temperature, with particular attention to the differences between daytime and nighttime. Moreover, multi-satellite observations were used to reveal the behavior of dust events and to evaluate the model performance. During the daytime, the net dust radiative forcing induced by dust aerosols was −3.76 W/m² at the surface (SFC), 3.00 W/m² in the atmosphere (ATM), and −0.76 W/m² at the top of the atmosphere (TOA), and thus led to surface air temperature cooling by an average of −0.023 °C over Northwest China. During the nighttime, the net dust radiative forcing was 2.20 W/m² at the SFC, −2.65 W/m² in the ATM, and −0.45 W/m² at the TOA, which then resulted in surface temperature warming by an average of 0.093 °C over Northwest China. These results highlight that the contribution of dust aerosols to DRF is greater during the daytime than that during the nighttime, while exhibiting the opposite impact on surface temperature, as dust can slow down the rate of surface temperature increases (decreases) by reducing (increasing) the surface energy during the daytime (nighttime). Our findings are critical to improving the understanding of the climate effects related to dust aerosols and provide scientific insights for coping with the corresponding disasters induced by dust storms in Northwest China.

The evolution of lightning generation and extinction is a nonlinear and complex process, and the nowcasting results based on extrapolation and numerical models largely differ from the real situation. In this study, a multiple-input and multiple-output lightning nowcasting model, namely Convolutional Long- and Short-Term Memory Lightning Forecast Net (CLSTM-LFN), is constructed to improve the lightning nowcasting results from 0 to 3 h based on video prediction methods in deep learning. The input variables to CLSTM-LFN include historical lightning occurrence frequency and physical variables significantly related to lightning occurrence from numerical model products, which are merged with each other to provide effective information for lightning nowcasting in time and space. The results of batch forecasting tests show that CLSTM-LFN can achieve effective forecasts of 0 to 3 h lightning occurrence areas, and the nowcasting results are better than those of the traditional lightning parameterization scheme and only inputting a single data source. After analyzing the importance of input variables, the results show that the role of numerical model products increases significantly with increasing forecast time, and the relative importance of convective available potential energy is significantly larger than that of other physical variables.

Different aerosol types exhibit distinct radiative effects in different regions, attributed to their unique optical characteristics and regional distributions. This study focuses on North China, which is impacted by both natural and anthropogenic aerosols with high concentrations and a variety of aerosol types. While many studies on aerosol direct radiative effects have been conducted in this region, the majority have focused on a specific type of aerosol or overall aerosol, leaving limited research on the direct radiative effects and contributions of different aerosol types. In this study, we use CALIPSO satellite data from 2011 to 2020 to investigate concentrations and distributions of different aerosol types. The results reveal that dust, polluted dust, polluted continental/smoke, and elevated smoke are the dominant aerosol types in North China. Based on the radiative closure experiment, we systematically calculate the radiative effects of different aerosol types and their corresponding contributions to the energy budget by combining satellite data with the Fu–Liou radiative transfer model. The annual average net aerosol direct radiative effect (ADRE) of North China is −6.1 and −13.43 W m⁻² at the TOA and surface, respectively, causing a net warming effect of 7.33 W m⁻² in the atmosphere. For each main aerosol type, dust contributes 93% to the shortwave ADRE in the western dust source region, while polluted dust mainly contributes 31% and 45% of the total ADRE, in Northwest China and North China Plain, respectively. Anthropogenic pollutant aerosols account for 58% of the total ADRE in Northeast China. This study holds great significance in elucidating the dominant aerosol types and their concentrations in North China, comprehending the impacts of different aerosol types on the local energy balance.

This study focuses on the critical issue of low-altitude wind shear, which is vital for aircraft safety during takeoff and landing. Using the WRF–CALMET model, we assess the impact of topography on low-level wind shear at Zhongchuan Airport. CALMET outperforms WRF, showing improved simulation accuracy. CALMET's simulation highlights diurnal variations in vertical wind shear, which are especially pronounced from 13:00 to 24:00 CST (China standard time, UTC+8). Notably, CALMET indicates wind shear that is one to two hazard levels higher for aircraft operations compared to WRF over a significant area. Terrain sensitivity experiments reveal CALMET's responsiveness to terrain changes during high-wind-shear periods, with reduced impact at higher altitudes. CALMET's incorporation of kinematic terrain influences, blocking effects, slope flow, and strengthened diversion of near-surface airflow on complex terrain contribute to these findings. This study confirms the efficacy of CALMET in simulating low-altitude wind shear, emphasizing its superiority in capturing terrain influences and reducing the aviation safety threat posed by low-altitude wind shear.