## 4 Conclusions  
The number of satellite scatterometers is increasing, and consistencies of their sea surface wind products are critically important for data applications. In this study, we focus on the recently developed Chinese spaceborne scatterometer constellation, i.e., the Ku-band rotating pencil-beam scatterometer onboard the HY-2 series satellites. Three methods are presented and performed to achieve the intercalibration of backscatter measurements among the HY-2 scatterometers, which include: (1) direction comparison using the collocated backscatter measurements, in which the nonlinear calibrations can also be derived by using the CDF matching technique; (2) intercalibration over the Amazon rainforest; (3) and the double-difference technique based on backscatter simulations over global oceans, which essentially employs the calibration method called NOC.  
In performing the direct collocation, a large number of collocations between HY-2 scatterometers are used over land, ice, and ocean and with a temporal difference less than 60 min. For the rainforest, considering the annual, seasonal, and diurnal variations in \(\sigma^{0}\) data over masked Amazon rainforest, the scatterometer measurements that are used are limited from 5:00 to 7:00 and 17:00 to 19:00 according to local solar time. NOC is performed based on wind vector cells with a spatial size of 25 \(\times\) 25 km\({}^{2}\) instead of the original \(\sigma^{0}\) data contained in L1B products.  
The results among the three methods are quite close, and, when using the direct collocation method as reference, the differences are within 0.1 dB. To verify the results, scatterometer wind speeds are compared with the ECMWF model forecasts. It is shown that the curves of wind speed biases among HY-2 scatterometers are extremely close for wind speeds above 4 m/s and below 20 m/s. It is clear that the consistency of sea surface wind speeds among HY-2B, HY-2C, and HY-2D is well-established. Next, we can investigate the potential capability of these three methods to extend to all the spaceborne scatterometers and compare with cone metrics [16].  
Conceptualization, [PERSON]; methodology, [PERSON], J.Z. and W.L.; software, [PERSON] and B.M.; validation, [PERSON] ([PERSON]); formal analysis, [PERSON]; investigation, [PERSON] and Y.Z. ([PERSON]); resources, Y.H. and M.L.; data curation, Q.F. and J.Z.; writing--original draft preparation, [PERSON]; writing--review and editing, [PERSON] and A.S.; visualization, [PERSON]; supervision, [PERSON]; project administration, [PERSON], Q.F. and J.Z.; funding acquisition, Y.H. and M.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China, grant number 41906153, and partly by Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), grant number GML2019 ZD0302. [PERSON] is supported by the EUMETSAT OSI SAF.  
Not applicable.  
The NSOAS ASCAT L1B data products are available at [[https://osdds.nsoas.org.cn/](https://osdds.nsoas.org.cn/)]([https://osdds.nsoas.org.cn/](https://osdds.nsoas.org.cn/)) (accessed on 1 September 2021). The QuikSCAT and ISS L2A data products are accessed from NASA PO.DAAC.  
The authors would like to thank [PERSON], who is working on scatterometry at KNMI, for details and discussions in performing the CDF matching technique.  
The authors declare no conflict of interest.