# Feasibility of Wave Simulation in Typhoon Using WaveWATCH-III Forced by Remote-Sensed Wind
## 4 Conclusions  
Remote-sensed wind and wave products are operationally provided by multiple satellites, i.e., ASCAT [43], HY-2B [44], and CFOSAT [45]. Although the spatial resolution of these products is 12.5 km for winds and \(\sim\)10 km for waves, they are valuable sources of data for oceanography during extreme sea states [46], e.g., typhoons and hurricanes. As mentioned above, the wind field simulated using atmospheric models such as ERA-5 during typhoons is significantly underestimated. The purpose of this study is to address the issue of whether assembling winds from satellites is valuable as a forcing field in wave simulation via the WW3 model. Although the advantage of the proposed approach is that TC intensity is considerable, the uncertainty of remote-sensed products is inherent in assembling winds. In our study, wind products from the scatterometers and radiometers during the typhoon season in 2021 and 2022 were assembled using the Cressman interpolation method. The statistical analysis of the maximum wind speed \(V_{max}\) in 30 typhoons from assembling winds compared with the measurements from NHC showed an RMSE of 4.79 m/s and an SI of 0.20. In addition, the comparison between assembling wind speeds and ERA-5 data proved that underestimation exists in the result from the numerical weather prediction model. This indicates that assembling winds could illustrate the intensity of the typhoon. The 0.125\({}^{\circ}\) gridded assembling wind speeds with intervals of 12 h, daily CMES currents, and daily CMES sea levels at 0.08\({}^{\circ}\) grids which were applied as the forcing fields in the WW3 wave simulations during 30 typhoons. The WW3-simulated waves for June-October 2022 were validated against the measurements from SWIM onboard CFOSAT, yielding a Cor of wave spectrum of 0.80 with an Err of 0.49, an RMSE of SWHs of 0.48 m with an SI of 0.25, and an RMSE of PWP of 0.95 s with an SI of 0.10. Furthermore, an error  
Figure 9: Bias of SWH versus the measurement of SWIM SWH, in which the red error bar represents the bias of SWH (simulated from the WW3 model with the assembling wind forcing minus that measured by SWIM), and the black error bar is the bias of SWH (simulated from the WW3 model with the ERA-5 wind forcing minus that measured by SWIM). analysis between the bias of SWHs (WW3 minus ERA-5) concerning the bias of wind speeds (assembling minus ERA-5) was conducted. It was observed that the WW3-simulated SWHs forced by the assembling wind fields was higher than that by ERA-5, i.e., the positive bias of SWHs at a wind speed bias greater than 5 m/s. With the increasing bias of wind speeds, the bias of SWHs gradually increased; in particular, the bias of SWHs reached up to 4 m as the wind speed bias was greater than 30 m/s, which was caused by the linear relation between winds and waves. Furthermore, the comparison also showed that assembling winds derived from multiple remote-sensed products had better performance for typhoon-induced wave simulations using WW3 than that using the ERA-5 winds. In particular, the error reduced from 6 m with ERA-5 winds to 3 m with assembling winds in an extreme sea state. It was concluded that assembling winds derived from multiple remote-sensed products is reliable for typhoon-induced wave simulations using WW3, in which the underestimation of ERA-5 in typhoons is significantly reduced. TC winds and waves can be inverted from SAR images with fine spatial resolution, i.e., TerraSAR-X [47; 48], Gaofen-3 [49], RADARSAT-2 [50], and Sentinel-1 [51; 52]. In the near future, SAR-derived TC winds and waves will be assimilated with other remote-sensed wind products. Otherwise, by assembling winds using the interpolation method, we need to consider the asymmetric of the typhoon winds [53]. The collocated wind and wave data are useful for improving the parametrizations of the drag coefficient and wave breaking in WW3 to enhance the accuracy of the wave simulation. Conceptualization, W.S. and R.Y. ; methodology, W.S. and M.W. ; validation, W.S. and Y.Z. ; formal analysis, W.S., M.W.