This study aimed to find a boundary layer parameter scheme suitable for typhoons in the South China Sea based on a comparison with the aircraft detection data from Typhoon Nida (2016). We simulated the typhoon boundary layer wind field in different boundary layer schemes, such as YSU, MYNN, BouLac, and Shin-Hong, and with a no-boundary-layer parametrization scheme. The results were as follows: (1) In the eye and eyewall area, the YSU and MYNN schemes could better simulate the east–west wind characteristics and the YSU scheme could also simulate the jet current of the southerly wind component in the boundary layer in the eyewall. (2) Compared with the eye area, the easterly wind in the eyewall area was strong, and the overall vertical movement was weak. (3) The YSU and MYNN schemes had similar turbulent kinetic energies that were also similar to those from aircraft observations; the turbulent kinetic energy in the simulations of several schemes in the boundary layer was evidently lower than that in the aircraft observations. Thus, the MYNN and the YSU schemes yielded better simulations for the eye and eyewall areas, and the YSU scheme was more similar to the boundary layer observations.

An improved understanding of the environmental factors influencing tropical cyclones (TCs) is vital to enhance the accuracy of forecasting TC intensity. More than half of TCs that were substantially affected by environmental factors were predominantly affected by low-level environmental relative vorticity (hereafter, VOR TCs). In this study, the seasonal variation and related physical features of VOR TCs from 2003–2017 during TC seasons in summer and autumn over the western North Pacific were analyzed. Autumn VOR TCs exhibited the strongest intensity among all TCs over the western North Pacific. The enhanced environmental relative vorticity during the TC intensification period was larger and more favorably distributed for VOR TC development in autumn. The vorticity diagnostic analysis showed that the convergence was the positive source of environmental relative vorticity of VOR TCs, while the contribution of convergence was larger in autumn than in summer. The increased convergence was related to seasonal variation in larger-scale systems, especially the higher environmental pressure gradient, which reflected the larger subtropical high and the compressed East Asian summer monsoon trough in autumn. In addition, the East Asian summer monsoon trough was also somewhat stronger during the intensification period of VOR TCs, especially in autumn.

Predicting tropical cyclone (TCs) tracks is a primary concern in TC forecasting. Some TCs appear to move in a direction favorable for their development, beyond the influence of the steering flow. Thus, we hypothesize that TCs move toward regions with high water-vapor content in the lower atmosphere. In this study, four numerical experiments, including a control experiment and three sensitivity experiments, were performed using the Weather Research and Forecasting Model, to analyze the relationship between water vapor distribution and the track of Severe Typhoon Hato (2017). Observations validated the features reproduced in the control experiment. The sensitivity experiments were conducted to explore variations in the TC track under different water vapor environments. Results indicate that the horizontal distribution of water-vapor content exerted a greater impact on the TC track than the steering flow when both factors were significant. Further analysis revealed that the TC’s movement vector was between the direction of the steering flow and the direction toward the peak of vorticity increasing area. The peaks of vorticity increasing area were close to the peaks of water vapor increasing area, which also proved the effect of water vapor distribution on the TC track. These results are expected to improve TC track analysis and forecasting.

Sea fog significantly impacts harbor operations, at times even causing navigation to cease. This study examines two harbors in the north of the South China Sea, analyzing the feasibility of increasing each harbor’s sea fog early warning capability to 6 h in advance. Although the harbors are separated by only about 100 km, analysis of their backward trajectories reveals differences in the incoming flow and sea fog types. Concerning the types, at Xuwen harbor, warm advection fog represents 49.56% of the cases, cold advection representing 48.03%. At Zhanjiang harbor, 37.06% are warm advection fog, with 58.33% cold advection fog cases. We propose different monitoring and early warning schemes for the harbors. For Xuwen, we suggest eight visibility lidars located on the north and south sides of Qiongzhou Strait (two on the north, six on the south). Here, such a setup would give warning probabilities of sea fog of 87.50, 66.23, and 49.78% for advance times of 2, 3, and 4 h. For Zhanjiang, we suggest two visibility lidars and four buoys at the east side of the harbor. The corresponding warning probabilities are 83.77, 64.47, and 47.15% for the same advance times. For 5–6 h in advance, the early warning probabilities of both harbors drop quickly. We also suggest a flow chart for the early warning and monitoring scheme at each harbor.