# Characterization of Tropical Cyclone Intensity Using the HY-2B Scatterometer Wind Data
## 5 Discussion and Conclusions  
Satellite scatterometers are able to obtain accurate stream line features [32] in the presence of TCs, such that they have been widely used in TC monitoring, notably for the monitoring of the TC center location. However, the scatterometer-derived extreme winds usually present larger uncertainties due to signal saturation and rain contamination effects (the latter is mostly for Ku-band systems), limiting the application of its data in determining the TC intensity. Following the unique pattern of wind stress divergence and curl near the TC core, a new method is developed to determine the TC center location, and to estimate the azimuthally averaged radius of 17 m/s scatterometer winds. Although this article ignored the QC flag when calculating the R17, [PERSON] and [PERSON] [33] mentioned a new indicator for the Ku-band QC which can improve the QC of rain in the Ku-band wind scatterometer, and we may apply multiple QC indicators to improve the R17 calculation in the near future.  
The best-track database was used as another metric to verify the TC center location and R17. The correlation between the estimated wind radii and the best-track MSW/MSLP is analyzed, and it proves that the estimated R17 value is a better proxy for TC intensity than the maximum wind speed of the Ku-band HSCAT. However, the correlation between R17 and MSW is still rather low (r = 0.54) to develop a universal TC intensity prediction model. Through a case by case study, we find that the R17 value is highly correlated with the best-track MSW for each single TC event and their correlation coefficient is up to 0.86. This finding implies that the scatterometer wind radii are useful for estimating TC intensity when limiting the spatial and temporal context in which the analysis is performed. Moreover, this method can be also applied to the other scatterometers onboard the HY-2 satellite series (e.g., HSCAT-C and -D), hence it is useful to improve the monitor of TC intensity using the HY-2 satellites observations.  
Note that the illustrated TCs are generally at the growing phases. The correspondence between R17 and MSW becomes more complicated when a TC is at the weakening stage. That is, the 17-m/s wind radius may keep growing before it approaches a saturated value, even though the TC intensity has gradually decreased. Nonetheless, for nowcasting or short-range forecasting purposes, the scatterometer R17 value is still quite useful in  
Figure 7: The correspondence between ASCAT R17 and best-track MSW (**a**) and MSLP (**b**), respectively.  
assessing the evolution of TC intensity, particularly with the joint observations from the HSCAT constellation.  
Conceptualization, W.L. and M.P.; methodology, S.L. and W.L.; software and validation, S.L. and Z.W.; formal analysis, W.L., M.P. and S.L.; writing--review and editing, S.L., W.L. and M.P. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, grant number 42027805.  
Not applicable.  
The NSOAS HSCAT L2B data are available at [[https://osdds.nsoas.org.cn/](https://osdds.nsoas.org.cn/)]([https://osdds.nsoas.org.cn/](https://osdds.nsoas.org.cn/)) (last accessed on 30 January 2022). The ASCAT L2B data are provided by EUMETSAT OSI SAF. The CMA best-track data are available at [[http://tcdata.typhoon.org.cn/](http://tcdata.typhoon.org.cn/)]([http://tcdata.typhoon.org.cn/](http://tcdata.typhoon.org.cn/)) (last accessed on 30 January 2022).  
The authors would like to acknowledge NSOAS for straightforward and rapid access to the HY-2B data. We would also like to acknowledge the EUMETSAT NWP SAF for EUMETSAT OSI SAF for providing the ASCAT data.  
The authors declare no conflict of interest.