# Ice Production in Ross Ice Shelf Polynyas during 2017-2018 from Sentinel-1 SAR Images
## 6 Conclusions  
In this study, the high spatial and temporal resolution of Sentinel-1 SAR data are used to derive the wind-driven ice production of Ross Sea polynynas in 2017 and 2018.  
Based on the Sentinels SAR imagery, the wind-driven polynynas occurred from the middle of March to the middle of November. There were 90 wind-driven polynya events in 2017 (64 in RISP and 26 in MSP) and 114 events in 2018 (84 in RISP and 30 in MSP), the yearly cumulative polynya area were 1,159,847 km\({}^{2}\) in 2017 and 1,101,588 km\({}^{2}\) in 2018, and the yearly cumulative polynya ice productions were 202 km\({}^{3}\) in 2017 and 196 km\({}^{3}\) in 2018. The polynya event frequency in 2017 was less than that in 2018, but the yearly cumulative polynya area and ice production were similar to those in 2018. The more frequent events mean the shorter time for ice growth in polynya, then the smaller ice thickness.  
The yearly cumulative SIP volume is only 1/2-2/3 of those reported from previous results. The reason for this difference may come from the different methods and the uncertainties of each method. In the method of this study, every polynya event was derived using manually digitization based on the SAR images, and the events occurred from the middle of March to the middle of November. This is different from the definition in the PMW method in which the polynya area was the mean daily area with an ice thickness of less than 20 cm for the period of March to October. The ice volume in this study was calculated through multiplying the polynya area and the ice thickness estimated from AMSR2. For the PMW method, the ice production was estimated by the heat flux model. The estimation algorithm of ice thickness and the inputs of the heat flux model could also bring in uncertainties in the ice production estimation. The results in this study imply that the previous studies might have significantly overestimated the ice production in the RSP. However, due to the limited image data in 2017 and the short time (only 2 years) of data, some uncertainties still exist. We hope the longer time series of ice productions will be obtained in the future to further assess this method.  
Methodology, L.D., H.X.; Supervision, H.X., S.F.A.; Writing-original draft, L.D.; Writing-review & editing, H.X., S.F.A. and A.M.M.-N. All authors have read and agreed to the published version of the manuscript.  
[PERSON] was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (no. XDA19070101) and the National Natural Science Foundation of China (no. 41771389). Supports for [PERSON], [PERSON], and [PERSON] were provided by the U.S. National Science Foundation (no. 134717 and 1835784) and U.S. National Aeronautics and Space Administration (NASA) (no. 80 NSSC19M0194).  
[PERSON] thanks the China Scholarship Council for funding her 2016-2017 visit to the University of Texas at San Antonio. The European Space Agency (ESA) provided Sentinel-1 SAR data, NASA provided AMSR2 brightness temperature and sea ice concentration data. Critical reviews from three anonymous reviewers to substantially improve the paper are greatly appreciated.  
The authors declare no conflict of interest.