期刊
JOURNAL OF CLIMATE
卷 25, 期 8, 页码 3025-3038出版社
AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-11-00209.1
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资金
- Ecole des Ponts ParisTech, Marne-la-Vallee (France)
- Total RD
- European Commission [GOCE-CT-2003-505539]
The intrinsic seasonal predictability of Arctic sea ice is investigated in a 400-yr-long preindustrial simulation performed with the Centre National de Recherches Meteorologiques Coupled Global Climate Model, version 3.3 (CNRM-CM3.3). The skill of several predictors of the pan-Arctic sea ice area was quantified: the sea ice area itself, the pan-Arctic sea ice volume, and some areal predictors built from the subgrid ice thickness distribution (ITD). Sea ice area provides a potential predictability of about 3 months, which is consistent with previous studies using model and observation data. Sea ice volume predictive skill for winter sea ice area prediction is weak. Nevertheless, there is a higher potential to predict the September ice area with the June volume anomaly than with the June area anomaly. Using ITD-based predictors, two regimes of predictability were highlighted. The first one, a persistence regime, applies to winter/early spring sea ice seasonal predictability. The winter sea ice cover can be predicted in late fall/early winter from the amount of young ice formed since the freeze-up onset in the margins. However, sea ice area itself is potentially the best predictor of winter sea ice area at seasonal time scales. The second regime is a memory regime. It applies to the predictability of summer sea ice area. An ice area anomaly in September is potentially predictable up to 6 months in advance, using the area covered by ice thicker than a critical thickness lying between 0.9 and 1.5 m. Results of this study are preliminary; however, they provide information for the design of future prediction systems and highlight the need for observations and a state-of-the-art sea ice model.
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