###### Abstract
Currently, scientists focus the numerical simulation research on typhoons within two primary domains. One approach emphasizes simulating complex physical processes based on fluid dynamics and thermodynamics, valued for its high accuracy. However, this method is computationally intensive. The Weather Research and Forecasting (WRF) model and the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5) are commonly used tools for such research. Scientists have used the WRF and MM5 models for typhoon numerical simulations, validating their accuracy and conducting sensitivity analyses on various simulation parameter schemes [6; 7; 8; 9; 10]. Another method for typhoon simulation relies on theoretical and empirical formulas, or a combination of both, to calculate typhoon wind fields. Since the 1960s, numerous empirical parametric typhoon models have been developed by scholars, characterized by their relatively low computational demand [11; 12; 13; 14]. Scientists have conducted a series of studies using these empirical parameterized typhoon models, including driving ocean models with the generated wind fields, comparing and blending them with reanalysis wind fields, and analyzing them alongside other wind field models [15; 16; 17]. The development of numerical simulation methods for super typhoons is ongoing. For instance, the Weather Research and Forecasting (WRF) model has been employed to numerically simulate the intensity and structure of super typhoons. The accuracy of these simulations is then validated using observational data [18; 19]. Scientists have also been employing numerical simulation methods to investigate the factors contributing to the intensification of super typhoons. These factors include sea surface temperature (SST), sea-atmosphere interaction coefficients, and surface heat flux [20; 21; 22]. Typhoon-induced waves are among the most destructive oceanic hazards generated by intense typhoons. With advancements in computing technology, scientists have turned to numerical simulations to study typhoon wave patterns. Widely used models in this research include the Simulating WAves Nearshore (SWAN) model and the WaveWatchIII (WW3) model et al. [23, 24, 25, 26]. The driving wind fields of wave models significantly impact the accuracy of simulating parameters such as significant wave height during super typhoons. To enhance simulation accuracy, researchers have employed various wind field data sources. For instance, the Climate Forecast System version 2 (CFSV2), Cross-Calibrated Multi-Platform (CCMP) wind fields, and Global Data Assimilation System (GDAS) 10 m wind field data have been utilized, empirical parameterized typhoon model wind fields have been utilized, either individually or in combination [27, 28, 29]. In the current research landscape, comparisons of empirical parametric typhoon models and dynamic models in simulating typhoons primarily focus on moderate wind speeds [30, 31, 32] (below 50 m/s). In contrast, studies comparing and evaluating simulation performance at high wind speeds (above 50 m/s) remain relatively scarce. High wind speeds can directly impact structures such as ocean platforms, bridges, and offshore wind farms, causing damage. Additionally, the waves and storm surges induced by high wind speeds can severely affect port operations, leading to significant economic and personnel losses. Within the scope of the Northwest Pacific, the areas surrounding Taiwan and the Philippines are located at the heart of the typhoon tracks in the Northwest Pacific, making them regions that are widely and severely affected by typhoons. Furthermore, considering the completeness of typhoon data observed through satellite, this study selects two super typhoons, Typhoon Surigae (2021) and Typhoon Neparatk (2016), as cases for examining high wind-speed simulations. We employ both the WRF model and empirical parametric typhoon models to conduct these simulations.