Comparing seasonal cycle and trend-based emergent constraints on future sea ice albedo feedback

One of the largest sources of uncertainty in projections of Arctic climate change is the surface albedo feedback, particularly the feedback stemming from sea ice retreat and thinning (i.e., sea ice albedo feedback; SIAF). In prior work, we demonstrated that intermodel spread in SIAF can be reduced through an emergent constraint (EC) using an observable analog for SIAF derived from climatological summer sea ice retreat. This seasonal cycle metric was chosen for its resemblance to the established snow albedo feedback EC, but it is possible that other types of seasonal or trend metrics may prove to be even more robustly tied to SIAF. Here, we use CMIP5 and CMIP6 models to explore the potential value of these other metrics for constraining Arctic SIAF. We find that the maximum seasonal SIAF (where SIAF is calculated each summer over recent decades) and the trend in summer SIAF across the high-Arctic (>80°N) are particularly strong predictors of future SIAF. This geographical difference tells us that the trend-based metric seems to be picking up on the historical albedo decline stemming from sea ice thinning rather than the albedo decline driven by ice retreat. Lastly, we seek to combine these new constraints with those from past work to update our best estimate of future summer SIAF.