## 5 Conclusions  
At present, sea surface dynamics, i.e., wind and waves, are operationally monitored using remote-sensed techniques, i.e., scatterometers, polarimetric microwave radiometers, and SAR and CFOSAT. The accuracy of these products was systematically investigated. Oceanic modeling primarily relies on atmospheric numerical simulations, and thus, the inherent error for the winds is inevitably included in the modeling techniques, e.g., the under-estimation by ECMWF for TCs [55]. With the abundant remote-sensed data, an interesting question is whether remote-sensed products in near real time could be applied to forecasting and hindcasting, as these do not rely on atmospheric numerical simulations. There is little research on fusion wind from remote-sensed products used in forcing numeric wave models, i.e., WW3 and SWAN. The main purpose of our work was to classify the above issue through conducting an experiment in 2019 - 2020. In our work, the wind products from the ASCATs onboard the Metop-A/B/C satellites, the HY-2B scatterometer, and the WindSAT spaceborne polarimetric microwave radiometer for the period November 2019 to October 2020 were fused by using the classic interpolation method, denoted as Cressman interpolation. The validation of the fusion wind speed against the on-scene observations from the NDBC buoys showed a 1.66 m/s RMSE with a 0.81 COR; therefore, the fusion wind derived from the remote-sensed products was reliable for this study. However, gaps and swath patterns for the Southern Hemisphere were still observed in the fusion data, which could be further improved by using more  
Figure 13: Analysis of the monthly average errors between the WW3 results and the altimeter data for (**a**) March 2020, (**b**) June 2020, (**c**) September 2020, and (**d**) December 2019.  
products from other scatterometers onboard satellites (e.g., the CFOSAT satellite) and Soil Moisture Active Passive (SMAP) radiometers. The 0.125\({}^{\circ}\) gridded wind at 12 h intervals, daily CMEMS currents, and sea levels at 0.08\({}^{\circ}\) grids were treated as the forced fields in the wave simulations by the WW3 and SWAN models. Comparisons of the SWHs for June\(-\)September 2020 between the simulations of the two models and the NDBC observations showed that a \(<\) 0.5 m RMSE with a COR of \(>\) 0.8 was achieved by the WW3 and SWAN models. The wave products from the HY-2B and Jason-3 altimeters were also collected. The simulations by the WW3 model were compared with the monthly average values from the HY-2B and Jason-3 altimeters over global seas. The seasonal analysis of the monthly average error showed that the differences in the SWHs (the altimeter data minus the WW3 results) were within \(\pm\) 1.5 m for March and June. However, the differences were quite significant for December, especially for latitude \(>\) 40\({}^{\circ}\)N and latitude \(<\) 40\({}^{\circ}\)S. It was concluded that the fusion wind data derived from multiple remote-sensed products were potential sources for hindcasting waves using numeric wave models. It is necessary to figure out whether the distortion caused by environmental factors (i.e., SST anomaly) should be further considered so as to improve the accuracy of fusion wind. Since 2018, the HY-2 satellite constellation has provided synchronous wind products from scatterometers and microwave radiometers. In the near future, the measurements from the HY-2 satellite constellation will be assimilated with TC wind data provided by numeric models and SAR retrieval results [56; 57], and this will consider the asymmetrical and eccentrical patterns of the horizontal winds. Furthermore, the assimilated wind field will be further tested for TC wave simulations by the WW3 and SWAN models. Conceptualization, J.S., W.S., Y.H. and Y.Z. ; methodology, J.S., Y.H., S.S. and W.S. ; validation, Y.H. and W.S. ; formal analysis, Y.H., S.S., Y.Z. and W.S. ; investigation, Y.H. ; resources, J.S. and S.S.; writing--original draft preparation, W.S., T.J. and S.S.; writing--review and editing, Y.Z.