Despite frequent tropical cyclone (TC) activity over the western North Pacific (WNP), scarce offshore observational data hinder precise assessment of TC-induced wind hazards. This study used the Satellite-Analyzed Tropical Cyclone Size Dataset (V3.0), developed by the Shanghai Typhoon Institute of China Meteorological Administration (CMA/STI), to reconstruct 0.5° × 0.5° gridded wind fields from 1981 to 2020, and a vortex destructiveness index (VDI) and grid-based potential destructiveness index (PDI_g) were proposed to analyze spatiotemporal changes in TC activities and hazards. The main findings are as follows: (1) TC genesis and landfall frequency have declined since 1980, with landfall locations shifting notably north-eastward, and lifetime maximum and landfall intensities rising by ~0.8 and 3.8 m s⁻¹ after 2000, respectively. (2) Mean radii of maximum winds (R_max) and Beaufort scale winds of grades 8, 10, and 12 (R₈, R₁₀, R₁₂) were 48, 179, 100, and 65 km, with R₈ exhibiting the most pronounced asymmetry. (3) TC impacts and maximum winds rose at higher latitudes and the Chinese mainland, with a 0.5–0.6 probability of winds ≥ 32.7 m s⁻¹ from the Yangtze River estuary to southern Taiwan Strait. (4) China’s offshore 50- and 100-yr return period wind speeds (V_p) exceeded 45 and 50 m s⁻¹, respectively, and V_p in some southern coastal cities (e.g., Wenzhou and Fuzhou) exceeded engineering design criteria. (5) VDI peaked east of Taiwan Island, with a secondary high off Zhejiang, while the South China Sea and Pearl River Delta exhibited significant uptrends. (6) TC structural asymmetry was most pronounced at high latitudes and nearshore, enhancing hazards in the southern semicircle off Southeast China and western semicircle off East China. (7) Despite fewer landfalls, stronger TC intensity and northward-shifted activity have heightened wind risks and potential destructiveness across northern coastal and inland regions. These findings provide a scientific basis for China’s long-term disaster prevention and climate-resilient financial planning.

Accurate tropical cyclone (TC) risk assessment is challenged by limited historical TC records. In this paper, a statistical–dynamical model is developed to generate a large TC hazard dataset over the western North Pacific (WNP) basin for risk assessment. The model integrates three core components: a fully statistical TC genesis model, an environment-dependent beta-advection TC track model (BAM) for trajectory simulation, and a set of nonlinear differential equations governing TC intensification rates. Using this model, a 10,000-yr synthetic TC dataset is generated and systematically validated against observational records. The results show that the model reproduces observed TC climatology, including seasonal cycle, genesis statistics, track density, and intensity distribution. Regional TC hazard analysis via landfall intensity return period curves across the WNP shows reasonable model performance. It is thus believed that the proposed statistical–dynamical model has the potential to be used for supporting TC risk assessments in coastal regions, including those with limited observational data.

Accurate calculation of land surface heat fluxes is scientifically significant and practically valuable for understanding land-atmosphere interaction and improving capabilities of weather forecast. The methods commonly used for calculating land surface heat fluxes in current numerical weather forecast models are based on the Monin-Obukhov Similarity Theory (MOST). These methods have some limitations and it is hard to further improve them. Meanwhile, a method based on maximum entropy production (MEP) model is proposed to calculate land surface heat fluxes in recent years. This method demonstrates great advantages and yields good results and has been increasingly applied in the study of land-atmosphere exchange. This study introduces the MEP model into the operational weather forecast numerical model (CMA-BJ model) in Beijing Meteorological Service to replace the existing MOST-based method in the model for the calculation of land surface sensible heat flux, latent heat flux and ground heat flux. Simulation experiments over the period from June to August 2022 are conducted to evaluate the performance of the operational numerical model system with the MEP model on predicting land surface and atmospheric meteorological elements and precipitation. Results show that the use of MEP model in CMA-BJ model can significantly improve the simulation of surface energy balance and thermodynamic processes of land surface and boundary layer. It also enhances the ability of the model for the simulation of air temperature, humidity and wind in the boundary layer, and ultimately increases the accuracy of precipitation prediction, especially for heavy rainfall prediction. The TS (threat scores) of rainstorm forecasts in North China and Yangtze river basin have increased by 20% and 10%, respectively. The predicted diurnal precipitation variation is also more consistent with observations with higher correlation coefficient. These results show that it is feasible to use MEP model in numerical weather forecast models and operational systems.