# Ice Production in Ross Ice Shelf Polynyas during 2017-2018 from Sentinel-1 SAR Images
## 5 Discussion  
The polynya area and polynya ice production estimated in this study are different from those in previous studies. The reasons for this difference are analyzed in this section. The method to derive wind-driven polynya and ice production is different from the PMW method. For the PMW method, thin ice thickness (<20 cm) was first estimated from PMW based on PR36 and PR85 or the ice concentration less than 75%, and then the sea ice production was calculated by the heat flux model based on the thin ice thickness data from March to October [23]. Therefore, it was not possible to identify individual polynya events, (i.e., neither it was possible to compute individual event area or volume). Previous studies in Table 1 present the average polynya area, which was the mean thin ice area of all days from March to October. This mean ice area was then used to generate ice production volume based on the heat flux calculation. Furthermore, in the PMW method, the difference in the definition of polynya (based on ice thickness or ice concentration) might directly influence the ice production results, therefore, papers showed different results even for the same year [19; 39]. In this study, Sentinel-1 SAR data is used to obtain the individual wind-driven polynya ice production events and their corresponding areas, with very fine spatial and temporal resolutions. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Year** & \multicolumn{2}{c}{**2017**} & \multicolumn{2}{c}{**2018**} \\ \hline
**Polynyas** & **RISP** & **MSP** & **RISP** & **MSP** \\ \hline Event times & 64 & 26 & 84 & 30 \\ Cumulative area (km\({}^{2}\)) & 1,066,520 & 93,327 & 1,013,906 & 87,682 \\ Mean event area (km\({}^{2}\)) & 16,159 & 3590 & 12,070 & 2923 \\ Cumulative Volume (km\({}^{3}\)) & 188 & 14 & 179 & 17 \\ Mean daily area from AMSR2 (km\({}^{2}\)) & 23,617 & 1782 & 25,901 & 1874 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Statistics of wind–driven polynya ice production events in the Ross Ice Shelf polynya (RISP) and McMurdo Sound polynya (MSP) during 2017 and 2018. The mean ice production event areas derived from AMSR-2 (ice thickness < 20 cm) are also included for comparison. For example, from the SAR images, the wind-driven polynynas occurred 2 times in November 2017 and 5 times in November 2018, while in the PMW method, the ice production was only accounted for the period of March-October. In terms of ice thickness for the ice volume calculation in this study, the last ice thickness from the PMW in the day before the next wind-driven event is used. The PMW method, however, cannot determine such information for individual ice production events. Furthermore, in previous studies, the polynyna area was thought of as the thin ice area, and the ice production had a very high correlation with the polynyna area (0.89) [21]. However, it can be seen from Sentinel-1 SAR data (e.g., Figure 6) that some areas exhibit an ice thickness of more than 20 cm within the polynynas, while the PMW method would not count as ice production. This could result in underestimates of ice production. On the other hand, the fast ice area was very likely misclassified as the polynyna area by PMW method, due to the potential underestimation in fast ice thickness (Figure 2f). This uncertainty was pointed out by [52] in which they developed a new fast-ice mask method to improve the sea ice production calculation from AMSR-E. Compared with previous studies performed based on PMW and heat flux model, the results of this study show much lower ice production estimates in the RISP. It is worth noting that the PMW method usually has large uncertainties in estimating the polynyna area. The annual ice production in the RISP and MSP vary from 160 km\({}^{3}\) to 600 km\({}^{3}\) (Table 1). Even for similar time periods, different papers obtained different results like in [25] and [8]. The former paper calculated the ice production from 1992 to 2002, and the latter one from 1992 to 2001.