## 5 Discussion
The diffused echoes from the old ice were found to be similar to those of the seawater. Figure 19: Distributions of the classification errors of the three methods in the Antarctic region: Figure 19A,E,J and C, G, K indicate the C Band results of the HY-2A/B, respectively; Figure 19B,F,J and D, H, L indicate the Ku Band results of the HY-2A/B, respectively. Note: The color boundaries of the different types ice in the Figure 19A–L are consistent with the classifications in the ice chart. Figure 18: Distributions of the classification errors of the three methods in the Arctic regions: Figure 18A,E,J and C, G, K indicate the C Band results of the HY-2A/B, respectively; Figure 18B,F,J and D, H, L indicate the Ku Band results of the HY-2A/B, respectively. Note: The color boundaries of the different types of ice in the Figure 18A–L are consistent with the classifications in the ice chart. In the Antarctic regions, an almost complete correct identification of the seawater had been achieved in the areas with no ice using the KNN with the threshold method. However, there were many misclassifications in areas with sea ice, as illustrated in Figure 19. It was found that the noise from the ice floes had impacted the classification results. Since November was the summer season in the Antarctic regions at the local time, the ice had been melting. The errors of the threshold were found to be mainly distributed in the areas containing many sea ice floes, as illustrated in Figure 20 (Weddell Sea, Pulitzer Sea, and Ross Sea). In the present study, it was found that the results of the LIBSVM were so inaccurate that the errors had been distributed in all of the orbits of the Antarctic regions. In addition, in the large footprint of the altimeter, there tended to be a large number of non-singular ground signals which had introduced many mixed signals. Meanwhile, it was also determined that the OSI-SAF ICETYPE dataset was not exactly correct. The spatial resolution of the dataset was 10 km, which was far greater than the sizes of the ice floes. Therefore, it was not able to accurately present the distributions of the ice floes. The large footprints only allows a detection of large-scale changes in surface structure and signal strength. This further limits the possibility of distinguishing between surface types. A more detailed study is needed to analyze the impact of the different resolutions as well as the influence of snow and roughness on the HY-2A/B ALT echoes. The waveforms of radar altimeter are sensitive to the electrical properties [30] and surface roughness [31] and so on. [PERSON] [30] found that the snow influence on the reflected radar signals from the snow-ice interface can be neglected when the snow is dry and cold based on the laboratory experiments. The Arctic in November is winter, while the season is summer in the Antarctic regions. The environment of Antarctic was not as dry and cold as the Arctic in November. The Antarctic sea ice had been melting in November. [PERSON] [32] further found the dominant scattering surface was not always the snow-ice interface for the Antarctic sea ice surveyed based on a sled-borne radar during the summer seasons. The mean depth of the dominant scattering surface of the radar was only around 50% of the mean measured snow depth. Thus, the snow depth has a not negligible influence on the formation of \"ocean-like\" echoes in the centers of the large ice floes. Due to the melting processes, the ice in the Antarctic low sea ice concentration was very loose. From the scale of the altimeter footprint, the surface of these areas is not so smooth. The snow cover and the changes in the surface roughness of the ice zones generate a significant difference in the echoes. These influences brought difficulties to the separation of sea ice and seawater in the Antarctic. Meanwhile, there are differences between the echoes of band C and band Ku (Figures 10-12). The band C and Ku have different abilities to penetrate snow and ice as they have different wavelengths.