# Blending Sea Surface Winds from the HY-2 Satellite Scatterometers Based on a 2D-Var Method
## 3 Data Verification  
Before blending the HSCATs winds with the ERA5 background data based on the 2D-Var method, the differences among HSCATs, ERA5, and buoy winds are evaluated in order to verify the consistency of the used data sources. In particular, the SD difference between HSCATs and buoy winds is assessed for different collocation windows, with the objective of accounting for the temporal representativeness errors in the blending analysis.  
Figure 3 shows the contour plots of HSCATs versus ERA5 winds. Here, the time difference between HSCATs and ERA5 is less than 30 min, and only the data accepted by the quality control scheme are used in the analysis. The upper left corner of each panel illustrates the correlation coefficient (cc), the bias, and the SD values of HSCATs with respect to (with regards to) ERA5 winds. Compared with the ERA5 background field, the bias of HSCATs winds is negligible, and the SD differences of wind speed and direction are generally less than 0.95 m/s and 10\({}^{\circ}\), indicating that the observational data are of excellent consistency with the background fields. In addition, winds derived from the three HSCATs  
Figure 2: The background error correlation functions used in the 2D-Var analysis. Gaussian structure functions (GSF) are in solid curves (thin curve for Tropics and bold curve for extratropics), and empirical background error correlation (EBEC) functions are in dashed curves (thin curve for velocity potential and bold curve for stream function). Figure is adapted from ref. [19] with permission.  
are with similar statistical scores with regards to. ERA5, such that it is not necessary to perform a bias correction before the 2D-Var analysis.  
Figure 4 verifies the consistency between the ERA5 wind and the collocated buoy winds. Note that the moored buoy data have been already assimilated into the ERA5 model, such that the verification is indeed not independent in terms of quality assessment. Nonetheless, statistical scores of the ERA5 winds with respect to buoy measurements are  
Figure 3: Contour plots of HSCATs versus ERA5 winds. Left panels (**a**,\(c\),**e**) and right panels (**b**,\(d\),**f**) show the comparison of wind speeds and directions separately. The upper, middle, and lower panels correspond to HSCAT-B, -C and -D, respectively.  
shown in the upper-right corner of each panel, which indicates that the two wind data sets are consistent with each other.  
Eventually, the collocated HSCAT-buoy data sets are segregated into six categories according to the time difference between the two data sources, i.e., 0-0.5 h, 0.5-1.0 h,..., and 2.5-3.0 h. The statistical scores between HSCATs and buoy winds are evaluated for each category and summarized in Tables 2 and 3. Note that, the bias of HSCATs winds (with regards to. buoy) does not show a clear dependency on the temporal window (see Table 2), while the SD difference does increase as the time difference increases (see Table 3). Consequently, it is not necessary to do a time-dependent bias correction for the HSCATs observations. However, the temporal representativeness errors, which are induced by the time difference between **O** and **B**, should be considered in the 2D-Var cost function. In practice, the ratio of observation to background error, rather than their absolute values, impacts the 2D-Var cost function. Following the results of Figure 4 and Table 3, a time-dependent observation-to-background error ratio is used in the following study, as shown in Table 4. Regarding that the buoy observations are not independent for the verification of ERA5 wind quality, the actual error ratio in Table 4 may be even smaller, which could be tested further once an independent data source is available.  
Figure 4: The scatter plots of ERA5 wind components versus buoy measurements: (**a**) wind speed, (**b**) direction, (**c**) u components and (**d**) v components.