###### Abstract  
As extreme forms of tropical cyclones (TCs), typhoons pose significant threats to both human society and the natural environment. To better understand and predict their behavior, scientists have relied on numerical simulations. Current typhoon modeling primarily falls into two categories: (1) complex simulations based on fluid dynamics and thermodynamics, and (2) empirical parameterized models. Most comparative studies on these models have focused on wind speed below 50 m/s, with fewer studies addressing high wind speed (above 50 m/s). In this study, we design and compare four different simulation approaches to model two super typhoons: Typhoon Surigae (2102) and Typhoon Nepartak (1601). These approaches include: (1) The Weather Research and Forecasting (WRF) model simulation driven by NCEP Final Operational Global Analysis data (FNL), (2) WRF simulation driven by the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA5), (3) the empirical parameterized Holland model, and (4) the empirical parameterized Jelesnianski model. The simulated wind fields were compared with the measured wind data from The Soil Moisture Active Passive (SMAP) platform, and the resulting wind fields were then used as inputs for the Simulating WAves Nearshore (SWAN) model to simulate typhoon-induced waves. Our findings are as follows: (1) for high wind speeds, the performance of the empirical models surpasses that of the WRF simulations; (2) using more accurate driving wind data improves the WRF model's performance in simulating typhoon wind speeds, and WRF simulations excel in representing wind fields in the outer regions of the typhoon; (3) careful adjustment of the maximum wind speed radius parameter is essential for improving the accuracy of the empirical models. WRF; Holland model; Jelesnianski model; SWAN; typhoon simulation  
2020 IEEE/RSJ International Conference on Intelligent Systems and Systems (IEEE)  
surrounding Taiwan Island and the Philippines Peninsula experience significant loss of life and property each year due to typhoon events. According to the national standard for \"Tropical Cyclone Categories\" set by the China Meteorological Administration, typhoons are classified into six intensity levels: Tropical Depression (TD), Tropical Storm (TS), Severe Tropical Storm (STS), Typhoon (TY), Severe Typhoon (STY), and Super Typhoon (SuperTY). Among these, Super Typhoons are rare yet highly destructive natural disasters. Although their frequency of occurrence is relatively low, each event can cause significant damage to the affected areas. In particular, the impact of Super Typhoons is pronounced in the regions of Taiwan Island and the Philippine Peninsula, as well as their surrounding areas. Strong winds can lead to widespread crop damage and destruction of fishing facilities, while heavy rainfall may trigger flash floods that wash away roads and houses. These events severely disrupt the lives and economic development of residents. Given their immense potential for destruction and significant impact on human society, Super Typhoons must be given high priority and subjected to thorough research. The study of typhoons has a long history, with its origins traceable to ancient times when people primarily relied on observing changes in wind direction to predict weather patterns. However, modern scientific research on typhoons began in the early 20 th century. As the field of meteorology advanced, particularly with the widespread application of satellite remote sensing technology, humanity's understanding of typhoons improved significantly [1; 2; 3]. The rapid development of computer technology in the 1970s further advanced numerical weather prediction models, leading to more precise forecasts of typhoon trajectories and intensities [4; 5]. These developments have greatly improved the accuracy and reliability of typhoon forecasts, providing robust scientific support for disaster prevention and mitigation efforts.