## 5 Discussion  
Near-coincidental high-resolution SAR imagery significantly aids the interpretation of altimeter waveforms in particular for small-scale features in the sea ice cover. Waveform derived parameters such as PP, IMP and SSD can principally discern between FYI, MYI and leads. The sensitivity of altimeters waveforms to smooth areas within the footprint, however, complicates the classification task. We introduced the IMP parameter to improve the separability between FYI and MYI for cases where  
Figure 11: Waveform evolution and SAR imagery over a small MYI floe embedded in FYI on 2018-02-24 with time separation of about 10 min. The small MYI floe is split in two by a high backscatter FYI feature. (**a**) SAR HV image with blue rectangles marking the altimeter footprints, (**b**,**c**) HH and HV mean backscatter with standard deviation interval in light blue and minimum and maximum values in grey, (**d**) waveforms, (**e**) mean inverse power and freeboard and (**f**) SSD and PP. [Contains Copernicus Sentinel data 2018]the peak power of the two ice types are similar (see Figure 4). Large temporal and spatial variability of these parameters, however, impedes the establishment of universally valid thresholds. Spatio-temporal changes can have a multitude of sources, e.g., differences in snow depth and composition [30; 31], changes in surface roughness in the order of the radar wavelength [24] or temperature variations [32]. To circumvent this problem, adaptive thresholding has been proposed for larger scale assessments of ice type variability from altimeter data [7]. For small-scale investigations, the relative spatial evolution of waveforms corresponds well to changes of sea ice surface types as determined from SAR imagery (see Figures 8-11). Therefore, usage of SAR imagery offers possibilities to assess the reasons of sea ice type misclassification from CryoSat-2 data [7; 8] and inconsistencies in the spatial distribution of waveform parameters and sea ice type products [6] left unanswered in previous studies. From the comparison of the altimeter data with the SAR images we observed that in areas of predominantly FYI, waveforms with high PP and peak power are common that are not linked to visible features in the SAR data. The increased peak power can be attributed to sub-resolution specular reflectors, e.g., thin smooth ice and leads that dominate the waveform. These findings are in line with observations from conventional (non-SAR) altimetry over the marginal ice zone [33]. Similarly, we found that in mixtures of FYI and MYI, waveforms tend to be more similar to FYI waveforms. The return from the smoother components are still strong enough to dominate the waveform in those cases. Difficulties in waveform interpretation over non-homogeneous surfaces are in accordance with earlier observations from Seasat data [15; 34]. The complexity of altimeter waveform interpretation of mixed surfaces also showed an impact on freeboard estimates. Close to boundaries of distinct MYI floes in FYI, mixtures of ice types within a floe or small floes of MYI in FYI, freeboard estimates are lower compared to the interior of a homogeneous floe and similar to FYI freeboard measurements. While freeboard may vary over such a floe, this behavior is observed for nearly all floes in our study. Thus, the measurements most likely reflect the range to the thinner component either at nadir or off-nadir positions [35]. The latter ones often cause highly negative freeboard values because the range estimate is no longer associated with the nadir return. Underestimation of freeboard for mixed ice cases has been demonstrated in a simulation study based on CryoSat-2 parameters [36]. To reduce biases in freeboard retrievals due to ambiguous waveforms, returns with increased PP and peak power over FYI or waveforms with widened leading edge are usually discarded for sea ice thickness retrievals in standard gridded products [3; 37].