Palaeoclimate constraints narrow uncertainty in future Arctic winter sea ice projections

Abstract

Abstract Arctic sea ice decline has been observed across all seasons and is projected to continue in the future. Relative to historical observations, climate models show their largest biases and uncertainties during winter, when ice cover strongly regulates air–sea heat exchange, ocean mixing and atmospheric circulation. Palaeoclimate records offer opportunities to evaluate model performance beyond the historical period, but applications have remained largely qualitative. Here we compile an Arctic-wide database of mid-Holocene (5–7 thousand years ago) biomarkers to assess sea ice simulations of this past warm period. Using a recently developed proxy system model, we present a Bayesian palaeoclimate model weighting scheme that refines the multi-model mean winter sea ice extent through fully quantitative proxy-model comparisons, accounting for model interdependence and non-stationary proxy seasonality. We demonstrate that, by adjusting the contribution of each model to the ensemble mean based on proxy evidence, model weights can eliminate biases and reduce uncertainties by 85%, to the level of interannual variability. Weighted projections using the same climate models indicate that future winter sea ice extent may be nearly 1 million km 2 lower than prior estimates across forthcoming decades and possible emissions scenarios, with broad implications for Arctic ecosystems, mid-latitude weather, and cryosphere stability.