## 3 Results
### Sea-Ice Concentration Uncertainties
#### 3.3.2 Uncertainty Time Series  
In Figure 13, we show the mean merged, AMSR2 and MODIS SIC uncertainties for the time between February 22 nd and May 27 th. Only pixels where MODIS and AMSR2 data are available are considered. The MODIS SIC uncertainty increases with time as the main uncertainty contributor, the dynamic range, decreases. It is important to note that the dynamic range starts to decrease in April (see Figure 4, an increase in ice tie-point means a decrease in dynamic range), while the MODIS SIC uncertainty only increases in May. We explain this by the nonlinear increase of the single MODIS SIC uncertainty components (see Equations (6) and (7)) for a linearly decreasing dynamic range. Therefore, a decrease of the dynamic range by for example 1 K has a stronger effect on the uncertainty in May, already starting at a smaller dynamic range than in April.  
The increase of the MODIS SIC uncertainty also causes the uncertainty of the merged SIC to increase with time. In fact, the temporal evolution of the MODIS and merged SIC is nearly identical as the AMSR2 SIC is quite constantly between 6% and 8% over the entire period. Again, note the much simpler assumption for the AMSR2 SIC uncertainty we are applying, which, e.g., does not take atmospheric variability into account. Therefore, the temporal variability of the MODIS SIC directly propagates into the merged SIC. The comparably constant uncertainty of the AMSR2 SIC is because our selection of Sentinel-2 scenes comprises mainly scenes with high SIC and the AMSR2 uncertainty is expressed as a function of SIC. It should therefore not be interpreted as an assessment of the AMSR2 uncertainty under different conditions.  
The benefit of the merged dataset over the MODIS SIC with regard to uncertainties is best demonstrated by the difference between their respective uncertainties. Figure 13b shows that the uncertainty is reduced in most cases by including the AMSR2 data. Until April, this is mostly reflected in single scenes in which the MODIS SIC uncertainty is between 10% and 18%, while the merged SIC uncertainty is between 8% and 14%. Apart from these single scenes, the MODIS SIC uncertainty is mostly between 5% and 8%, while the merged SIC uncertainty is between 5% and 6%. In May, the uncertainties of the merged and MODIS SIC start to increase. The increase of the merged SIC uncertainty is less pronounced than that of the MODIS SIC uncertainty. This means that the effect  
Figure 13: The mean uncertainty of the merged, AMSR2 and MODIS SIC is shown in panel (**a**). Panel (**b**) shows the difference between the MODIS SIC and the merged SIC uncertainty, the monthly mean difference is shown as solid horizontal line. The uncertainty is given as a fraction of 1. The x-axis shows the date, the vertical lines mark the days with Sentinel-2 scenes.  
of including the AMSR2 data reduces the uncertainties stronger for higher uncertainties. By the end of May, the mean uncertainty of the merged SIC is 18%, while the MODIS SIC uncertainty is 25%. When interpreting these numbers, the reader should keep in mind that there are large scene-to-scene fluctuations of up to 10% (merged SIC uncertainty) and up to 15% (MODIS SIC uncertainty). Considering the entire time-series, the uncertainty of the merged dataset is 8.9%, while that of the MODIS SIC is 10.6%. If only May is considered the mean uncertainties of the merged and the MODIS SIC are 11.6% and 14.9%.