Observations and modeling of areal surface albedo and surface types in the Arctic

The spread of climate model results quantifying the snow–ice surface albedo feedback is partly caused by the significant sensitivity of the simulated sea ice surface albedo with respect to surface warming. Therefore, the accurate representation of the Arctic sea ice and its evolution throughout the year, particularly in the melting period, is crucial to obtain reliable climate model projections.

Here we evaluate the results of the surface albedo scheme of the coupled regional climate model HIRHAM–NAOSIM against airborne and ground-based measurements. The corresponding observations were conducted during the MOSAiC expedition in 2020 and during five aircraft campaigns within the framework of the (AC)³ project in different seasons between 2017 and 2022.  

The comparison of measured and modeled surface albedo was based on observed fractions of four surface types (melt ponds, snow, sea ice, bare ice), which were classified using fisheye camera imagery and the measured skin temperatures along the flight track. From the modeling side, we applied the full surface albedo scheme, together with the ice sub-type fractions. We found a seasonal-dependent degree of agreement between measured and modeled surface albedo for cloud-free and cloudy situations. The current albedo scheme has projected an earlier onset of melting and a more realistic width of surface albedo frequency distributions in summer than the former albedo scheme. In spring, however, the cloud effect on surface albedo was overestimated by the model, while the albedo scheme for cloudless cases showed a smaller bias than the former scheme without cloud-depending parameters.