## 4 Discussion  
For further analysis, the time series of overall accuracy of sea ice monitoring is computed using all the available data from January 2015 to December 2018 (Figure 8). The overall accuracy of the Arctic region is significantly lower in September 2016 since the sea ice melts in this season, while the changing trend of the Antarctic region is reverse as the seasonal alternation between the Arctic and Antarctic is opposite. To analyze the impact of each variable, the relative importance of variables for sea ice monitoring is shown in Figure 9. REWD is used at all nodes in the DT algorithm, which results in a relatively high contribution to sea ice monitoring. REWI is useful as it can be used to distinguish sea ice from water with very low error. The REWD is the most important parameter, followed by REWI, RESI, RESD, RESC and REWC in the DT algorithm. Like the DT algorithm, REWC is of the least significance for monitoring sea ice in the RF algorithm. Figure 8: The time series of producer and user accuracies of sea ice monitoring results over the (**a**) Arctic and (**b**) Antarctic regions using decision tree (DT) and random forest (RF) algorithms. Figure 9: Relative importance of variables to sea ice monitoring using decision tree (DT) and random forest (RF) algorithms over the (**a**) Arctic and (**b**) Antarctic regions. The RF-based GNSS-R sea ice monitoring results in March and September 2018 are mapped with the OSISAF SIE data in Figure 10. The white and dark gray edge (partly marked by a rounded rectangle with a red dotted line) represent the minimum and maximum ice extent for March and September in 2018, respectively. In March, the sea ice extent of Arctic region reaches the minimum and maximum on 6 and 14 March, respectively, while the minimum and maximum sea ice extent of Antarctic region appear on 1 and 31 March respectively. As shown in Figure 5d, the data are not available every day in September 2018. From 1 to 17 September, the maximum and minimum sea ice extent of Arctic region occur on 2 and 17 September, respectively, while the sea ice extent of Antarctic region reaches the minimum and maximum on 13 and 17 September, respectively. The scatter points are ground tracks of TDS-1 data with the peak SNR above \(-3\) dB, which results in some gaps in the GNSS-R ground-tracks. In the figures, the presence of sea ice monitored using GNSS-R is illustrated by magenta points, whereas the presence of GNSS-R sea water is depicted by the blue points. As shown in Figure 10b,c, the detected sea ice and water overlaps in some areas. This is because the GNSS-R data span over one month and the ice extent changes rapidly during the melting season in the Arctic and Antarctic regions respectively. Figure 10: RF-based GNSS-R sea ice monitoring results in March and September 2018 are mapped with the OSISAF SIE for the Arctic and Antarctic regions: (**a**) March 2018 for the Arctic region. (**b**) September 2018 for the Arctic region. (**c**) March 2018 for the Antarctic region. (**d**) September 2018 for the Antarctic region. The dark gray (partly marked by a rounded rectangle with a red dotted line) and white edge represent the maximum and minimum ice extent in each month. The magenta points represent the ground tracks of GNSS-R sea ice, while the blue points stand for those of GNSS-R sea water. The examples of monitoring sea ice around Greenland using four different methods are presented in Figure 11. The sea ice monitoring results are compared with the ASI SIC data. Two simple thresholding methods based on REWD (i.e., REWD \(>\) 0.38 for sea water and REWD \(<\) 0.38 for sea ice) and REWI (i.e., REWD \(>\) 0.62 for sea water and REWD \(<\) 0.62 for sea ice) used in [28] are adopted to monitor sea ice (Figure 11a,b). The simple thresholding methods result in some false monitoring of sea ice; sea ice is identified as sea water or sea water is regarded as sea ice.