The interaction between internal waves and submarine seamounts is three-dimensional (3D). In this work, we conduct laboratory experiments to investigate the role of the three-dimensional seamount on the reflection of internal waves. Experimental results show that the energy of internal waves is focused after the reflection and the phase of the internal wave front become curved. The energy of the focusing region was nearly 2 times as that of the scattering region. There is a strong internal wave induced mean flow whose strength is nearly as high as 50% of that of the reflected internal wave. The mean flow was generated by the variation of the velocity amplitude in both the x axis and y axis. These results indicate that the reflection from the 3D seamount could lead to a complex spatial distribution of the internal wave and a different energy conversion process.

Particle size distribution, water soluble ions, and black carbon (BC) concentration in a long-term haze-fog episode were measured using a wide-range particle spectrometer (WPS), a monitor for aerosols and gases (MARGA), and an aethalometer (AE33) in Nanjing from 16 to 27 November, 2018. The observation included five processes of clean, mist, mix, haze, and fog. Combined with meteorological elements, the HYSPLIT model, and the IMPROVE model, we analyzed the particle size distribution, chemical composition, and optical properties of aerosols in different processes. The particle number size distribution (PNSD) in five processes differed: It was bimodal in mist and fog and unimodal in clean, mix, and haze. The particle surface area size distribution (PSSD) in different processes showed a bimodal distribution, and the second peak of the mix and fog processes shifted to a larger particle size at 480 nm. The dominant air masses in five processes differed and primarily originated in the northeast direction in the clean process and the southeast direction in the haze process. In the mist, mix, and fog processes local air masses dominated. NO₃⁻ was the primary component of water soluble ions, with the lowest proportion of 45.6% in the clean process and the highest proportion of 53.0% in the mix process. The ratio of NH₄⁺ in the different processes was stable at approximately 23%. The ratio of SO₄²⁻ in the clean process was 26.2%, and the ratio of other processes was approximately 20%. The average concentration of BC in the fog processes was 10,119 ng·m⁻³, which was 3.55, 1.80, 1.60, and 1.46 times that in the processes of clean, mist, mix, and haze, respectively. In the different processes, BC was primarily based on liquid fuel combustion. NO₃⁻, SO₄²⁻, and BC were the main contributors to the atmospheric extinction coefficient and contributed more than 90% in different processes. NO₃⁻ contributed 398.43 Mm⁻¹ in the mix process, and SO₄²⁻ and BC contributed 167.90 Mm⁻¹ and 101.19 Mm⁻¹, respectively, during the fog process.

To clarify the aerosol optical properties under different pollution levels and their impacting factors, hourly organic carbon (OC), elemental carbon (EC), and water-soluble ion (WSI) concentrations in PM_2.5 were observed by using monitoring for aerosols and gases (MARGA) and a semicontinuous OC/EC analyzer (Model RT-4) in Wuhan from 9 to 26 January 2018. The aerosol extinction coefficient (b_ext) was reconstructed using the original Interagency Monitoring of Protected Visual Environment (IMPROVE) formula with a modification to include sea salt aerosols. A good correlation was obtained between the reconstructed b_ext and measured b_ext converted from visibility. b_ext presented a unimodal distribution on polluted days (PM_2.5 mass concentrations > 75 μg⋅m⁻³), peaking at 19:00. b_ext on clean days (PM_2.5 mass concentrations < 75 μg⋅m⁻³) did not change much during the day, while on polluted days, it increased rapidly starting at 12:00 due to the decrease of wind speed and increase of relative humidity (RH). PM_2.5 mass concentrations, the aerosol scattering coefficient (b_scat), and the aerosol extinction coefficient increased with pollution levels. The value of b_ext was 854.72 Mm⁻¹ on bad days, which was 4.86, 3.1, 2.29, and 1.28 times of that obtained on excellent, good, acceptable, and poor days, respectively. When RH < 95%, b_ext exhibited an increasing trend with RH under all pollution levels, and the higher the pollution level, the bigger the growth rate was. However, when RH > 95%, b_ext on acceptable, poor and bad days decreased, while b_ext on excellent and good days still increased. The overall b_ext in Wuhan in January was mainly contributed by NH₄NO₃ (25.2%) and organic matter (20.1%). The contributions of NH₄NO₃ and (NH₄)₂SO₄ to b_ext increased significantly with pollution levels. On bad days, NH₄NO₃ and (NH₄)₂SO₄ contributed the most to b_ext, accounting for 38.2% and 27.0%, respectively.

The icing environment is an important threat to aircraft flight safety. In this work, the icing index is calculated using linear interpolation and based on temperature and relative humidity (RH) curves obtained from radiosonde observations in China. The results show that: (1) there are obvious differences in icing index distribution in parameter over various climatic regions of China. The differences are reflected in duration, main altitude, and ice intensity. The reason for the differences is related to the temperature and humidity environment. (2) Before and after the summer rainfall process, there are obvious changes in the ice accretion index in the 4–6 km altitude area of Northeast China, and the areas with serious ice accretion are coincident with areas with large rainfall estimates. (3) In the process of snowfall in winter, the ground snow has an impact on the ice accumulation index in the east of China. When it is snowing, ice accumulation in low altitudes is serious. The results of this study offer a theoretical basis for prediction and early warning of aircraft icing.

In order to avoid accidents due to aircraft icing, an algorithm for identifying supercooled water was studied. Specifically, a threshold method based on millimeter wave radar, lidar, and radiosonde was used to retrieve the coverage area of supercooled water and a fuzzy logic algorithm was used to classify the observed meteorological targets. The macrophysical characteristics of supercooled water could be accurately identified by combing the threshold method with the fuzzy logic algorithm. In order to acquire microphysical characteristics of supercooled water in a mixed phase, the unimodal spectral distribution of supercooled water was extracted from a bimodal or trimodal spectral distribution of a mixed phase cloud, which was then used to retrieve the effective radius and liquid water content of supercooled water by using an empirical formula. These retrieved macro- and micro-physical characteristics of supercooled water can be used to guide aircrafts during takeoff, flight, and landing to avoid dangerous areas.