## 4 Discussion
Generally, it is debatable whether an overfrozen lead should be shown as reduced SIC, as strictly speaking the SIC should be 100% instantly when the lead starts to refreeze. For most applications, e.g., heat flux calculation or navigation, the presence of leads is very relevant. A calculation in [24] shows that for thick ice the heat flux would be \(\sim\)9 Wm\({}^{-2}\) for 99% SIC and 5 Wm\({}^{-2}\) for 100% SIC. In a 1 km grid cell of our dataset, this would correspond to a difference of 4 MW. We see this and the importance of leads for navigation as a sufficient argument for keeping the leads as reduced SIC in our merged dataset. The benefit of keeping the leads is also reflected in the higher open-water extent of the merged and MODIS SIC compared to the AMSR2 SIC. For lead retrieval only, the MODIS SIC would be more suitable than the merged SIC. However, our main goal is to have a dataset which does not only allow lead identification, but also offers spatial continuity. We therefore see our dataset as a compromise where a part of the lead information from the MODIS data is lost, but we judge the spatial continuity as valuable enough to accept this as a trade-off. For users who are mainly interested in leads, the MODIS SIC will be provided along with the merged SIC in a future version of our dataset. Both MODIS and AMSR2 SIC are strongly influenced by melt ponds. We do not consider this relevant for our study here since we do not cover the melt season, but it makes MODIS SIC retrieval in summer impossible, especially if we discard pixels with ice tie-points above 266.5 K as derived in Section 3.3. The merged SIC are thus only available between October and May. We do not compare our merged SIC to passive microwave SIC. The reason for this is that the main advantage of our product over the well-established passive microwave SIC algorithms is the finer resolution. As the ASI-AMSR2 SIC have the finest spatial resolution of all passive microwave SIC algorithms, we expect the ASI-AMSR2 SIC to yield an open-water extent (the metric which we use to show the advantages of the merged SIC) which is closer to that of the Sentinel-2 reference SIC than for the other passive microwave algorithms. Showing that the open-water extent of our merged SIC is closer to the Sentinel-2 open-water extent than that of the ASI-AMSR2 SIC does thus immanently show that the merged SIC are also better compared to the other passive microwave SIC with their even coarser spatial resolution. As we preserve the mean of the ASI-AMSR2 SIC, previous comparisons of ASI-AMSR2 SIC to alternative SIC products [24; 25; 26; 27] are also valid for our product in terms of potential biases, although the variability might be different. The selection of Sentinel-2 scenes for evaluation could introduce a bias into our dataset as we are (a) limited to daylight conditions, (b) limited to the marginal seas and (c) limited to temporally unevenly sampled scenes. Our results are thus only representative for these conditions and regions, they should not be interpreted as an assessment of the Arctic-wide SIC transition from late Winter to early Summer. However, the 66 reference scenes cover a fair amount of different ice conditions and a higher than average percentage of intermediate ice concentrations due to their location in the marginal seas. Low and intermediate SIC retrievals are in general more challenging and have higher uncertainties than the close to 100% SIC in the central Arctic. Thus, we do not expect worse results for such cases. For evaluation, the authors of [15] compare the MODIS SIC with SIC derived from aircraft measurements and find an error of \(\pm\)10% in April. Comparison with SSM/I data, also done by [15], yields a linear regression error of \(\pm\)7%. The MODIS SIC uncertainties derived by us are on average lower than the ones from the work in [15], but are larger (up to 20%) in some cases. In May, they range from 10% to 35%, i.e., they are larger than the ones in [15].