Uncertainty of the satellite-retrieved sea-ice area record and its trend

This study quantifies uncertainties of the observed Arctic and Antarctic Sea-Ice Area (SIA). Uncertainties in SIA estimates are derived from a single product, using a refined method to propagate local sea-ice concentration (SIC) uncertainties to hemispheric SIA estimates. The method accounts for spatial and temporal error correlations. The SIA uncertainty time-series based on the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) SIC record is relatively stable over time, even though SIA itself shows notable seasonal and long-term variability. The seasonal cycle of the uncertainty is instead linked largely to the distribution of the ice. In the growing season, the SIC fields are more compact with a shorter sea-ice edge separating high and low sea ice concentrations. In the melting season the sea-ice edge is in comparison more diffuse. This seasonal evolution of the sea-ice edge leads to a relatively large SIA uncertainty in the melting season and a smaller uncertainty in the growing season. The new single-product time series is compared with the spread across several SIA satellite products. The spread in the latter is characterized by seasonally varying biases. After accounting for these biases, the remaining differences are consistent with our new single-product SIA uncertainty. The two approaches are complementary: The inter-product approach provides insights into the influence of the product development while the new single-product SIA uncertainty allows for dynamic daily and monthly estimates which do not rely on the selection and availability of other products. It represents the non-systematic (bias-free) component of the uncertainties, which, among other things, determines the significance of new SIA extremes. The single-product, non-systematic uncertainties in SIA trends from 1979 to 2025 are estimated to be 11⋅103 km2 per decade (Arctic) and 14⋅103 km2 per decade (Antarctic). Our analysis shows that systematic uncertainties are present in the SIA trend estimates. This indicates that a longer time-series will not be sufficient to remove trend uncertainties. For an extensive uncertainty quantification, systematic uncertainties should be represented explicitly. These uncertainties are related to methodological choices in the SIC product development, such as the homogenization across passive microwave sensors, applied masks, corrections and interpolations. The respective influence of these choices on SIA trend observations requires further research.