## 4 Results  
### Waveform Parameter Statistics  
The first step of our analysis focusses on the altimeter waveform and SAR image parameters of different ice types. Figure 4 shows the waveform parameter statistics (a-c) and HV backscatter coefficient (d) of FYI, MYI and large leads accumulated over the three winter seasons 2015/16, 2016/17 and 2017/18. The three ice types are clearly distinguished by the waveform parameters, but the distributions also show a large overlap. FYI waveforms have a large PP, i.e., most of the backscattered power is located in the maximum peak, and a low SSD value, i.e., the contributions to the multi-looked waveform are confined to a smaller incidence angle range. Furthermore, FYI waveforms have a larger mean power compared to MYI as shown by the low values of IMP. MYI waveforms contain energy from a larger range of incidence angles, i.e., high SSD value, and the low PP indicates a smoother distribution of backscattered energy over the entire waveform. Leads are characterized by the highest PP, low SSD and high mean power. IMP enhances the contrast for FYI and MYI but reduces it for FYI \begin{table}
\begin{tabular}{l c c c} \hline \hline
**Season** & **Number of FYI Samples** & **Number of MYI Samples** & **Number of Large Leads Samples** \\ \hline
2015/2016 & 789 & 4048 & 837 \\
2016/2017 & 4217 & 1782 & 10 \\
2017/2018 & 2582 & 5033 & 86 \\ Total & 7588 & 10862 & 933 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Numbers of FYI, MYI and large leads samples for the different seasons. Figure 3: Example of waveform evolution over a multiyear sea ice floe 2018-02-18. (**a**) HV SAR image with altimeter footprint in blue rectangles [Contains Copernicus Sentinel data 2018] and (**b**) waveforms in different colors for distinction and freeboard as a solid black line. and leads. FYI and MYI are well separated by the mean backscatter coefficient of the SAR image since the age of sea ice has a significant impact on the SAR backscatter intensity [24]. Large leads have a bimodal distribution of HV backscatter intensities that largely overlaps with the FYI values. The lower peak is caused by leads of new ice whereas the second peak at higher backscatter values represents leads that have started to form thicker ice but still contain areas of thin ice that cause a highly peaked response in the altimeter. The robustness of these characteristics can be checked by investigating their temporal variability for each ice type. Figures 5 and 6 show the variation of waveform parameters and HV backscatter for FYI and MYI in the three different winter seasons. FYI shows a larger variability between the different years for PP and SSD waveform parameters, while the cross-polarization backscatter coefficient is relatively stable. IMP of FYI is less variable then for MYI because of generally higher peak power in FYI waveforms. The larger tail of PP in the winter 2015/16 represents waveforms with higher peak power. Part of the observed variability is probably induced by the fact that FYI is much more variable in surface appearances that affect the scattering process. For MYI the PP varies very little and only the winter 2016/17 shows a deviation for SSD and IMP. The peak at lower IMP originates from waveforms over MYI in the beginning of November 2016, and therefore relatively early in the season. Slightly more texture is visible in the SAR image and refrozen melt ponds could have increased the specular component. It should be noted here that the limitation to near-coincidental altimeter data and manual sample selection also introduce variabilities to the waveform parameters. The complexity of altimeter interaction with the sea ice surface and the dependence of altimeter waveforms on small-scale specular scatterers in the footprint, e.g., [25], make it difficult to assess the reasons of certain waveform changes based on the available SAR imagery. A more in-depth analysis of potential causes in yearly variability is therefore not feasible in this study.