Abstract
AbstractSeasonal forecast systems can skillfully predict summer Arctic sea ice up to 4 months in advance. For some regions, however, there is a springtime predictability barrier that causes forecasts initialized prior to May to be less skillful. Since this barrier has only been documented in a few general circulation models (GCMs), we evaluate GCMs participating in phase 5 of the Coupled Model Intercomparison Project. We first show sea ice volume skillfully predicts summer sea ice area (SIA) and has similar skill to a perfect model experiment. Given this result, we assess regional SIA predictability across each GCM and find a universal predictability barrier in late spring. For SIA at each summer target month in the marginal seas of the Arctic basin, a notable drop in prediction skill occurs from June to May in each GCM. This suggests summer sea ice forecasts initialized after 1 June will have substantially better prediction skill than forecasts initialized before.
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