## 1 Introduction  
In the past several decades, remote sensing techniques operating at microwave frequencies have been well developed and aimed at sea surface dynamic monitoring. Sea surface waves play a critical role in oceanic dynamics for determining the heat and motion exchange at the air\(-\)sea layer. Nowadays, remote-sensed products, including sea surface wind and waves, are operationally released with a 1-2 day delay, and they are valuable sources for analyzing sea climates [1]. With more and more earth observation satellites launching, there is particular importance in their marine applications using remote-sensed data, especially for forecasting and hindcasting atmospheric and oceanic dynamics. Until now, all-weather winds over global seas have been measured by satellites carrying active microwave scatterometers [2], i.e., quick scatterometers (QuikSCATs) [3], advanced scatterometers (ASCATs) onboard the Metop-A/B/C [4], scatterometers onboard the Haiyang-2B/C/D (HY-2B/2C/2D) satellites [5], and the Chinese-French Oceanography SATellite (CFOSAT) [6], as well as microwave radiometers, such as WindSAT [7]. The spatial resolution of standard ocean wind products is 12.5 km, with a swath of approximately 100 km, and thus, there are gaps on the surface of the ocean. The limitation of scatterometer wind is undetectable under extreme meteorological conditions (\(>\)25 m/s), such as tropical cyclones (TCs), because the backscattering signals from sea surfaces suffer a saturation problem similar to synthetic aperture radars (SARs) during co-polarization [8; 9]. This is due to both scatterometers and SARs utilizing the same geophysical model function (GMF) for wind retrieval [10; 11]. Validation against moored buoys has shown that the accuracy of scatterometer-measured wind speed is approximately 1 m/s [12]. In addition, the space-borne polarimetric microwave radiometer WindSAT, developed by the Naval Research Laboratory (NRL), has the ability to measure 0.25\({}^{\circ}\) gridded sea surface wind vectors with a swath coverage of 350 km [13]. The advantage of WindSAT is that the maximum wind speed could reach 40 m/s in a TC [14]. The wave products (i.e., SWHs) are operationally released by altimeters, i.e., the Topography Experiment (TOPEX)/Poseidon [15], the [PERSON] family [16; 17], and the Sentinel-3A/3B [18]. Although altimeter-measured waves are reliable for large-scale analyses, the spatial resolution of approximately 10 km following the satellite footprints does not satisfy the requirement for regional seas. An SAR could provide the wave spectrum with a fine spatial resolution (approximately 3 km), with a swath coverage of 100-300 km [19], and the Surface Wave Investigation and Monitoring (SWIM) [20] module onboard the CFOSAT is designed to obtain the wave spectrum with a spatial resolution of 18 km over global seas, and it also operates in TCs [21; 22]. The validation of remote-sensed wind and wave products has been systematically studied; however, the applications for using these data are worthy of further study. Oceanic modeling is a useful technique for research on oceanography. Several numeric models have been developed, i.e., a wave model called the WAve Model (WAM) [23], as have hydrodynamic models, including the Finite-Volume Community Ocean Model (FVCOM) [24], the Stony Brook Parallel Ocean Model (sbPOM) [25], and the Hybrid Coordinate Ocean Model (HYCOM) [26]. The sea surface wind field is the main driving force of sea surface dynamics, i.e., ocean waves, circulation, and eddies. Under this circumstance, a well-calibrated wind field is crucial for oceanic modeling. Several types of wind data derived from meteorological numerical models are convenient to use, i.e., the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim (ERA-Interim) data [27], the Cross-Calibrated Multi-Platform (CCMP) from Remote Sensing Systems (RSS) data [28], and the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) data [29].