Seasonal to interannual Arctic sea ice predictability in current global climate models

Abstract

We establish the first intermodel comparison of seasonal to interannual predictability of present-day Arctic climate by performing coordinated sets of idealized ensemble predictions with four state-of-the-art global climate models. For Arctic sea ice extent and volume, there is potential predictive skill for lead times of up to 3 years, and potential prediction errors have similar growth rates and magnitudes across the models. Spatial patterns of potential prediction errors differ substantially between the models, but some features are robust. Sea ice concentration errors are largest in the marginal ice zone, and in winter they are almost zero away from the ice edge. Sea ice thickness errors are amplified along the coasts of the Arctic Ocean, an effect that is dominated by sea ice advection. These results give an upper bound on the ability of current global climate models to predict important aspects of Arctic climate.

Mechanisms influencing seasonal to inter-annual prediction skill of sea ice extent in the Arctic Ocean in MIROC

“…This is primarily because of the persistence of ice thickness anomalies from summer to summer and the persistence of sea surface temperature anomalies from the melt to growth seasons (BlanchardWrigglesworth et al, 2011a;Guemas et al, 2014). These features are also found in the results of experiments comparing multiple climate models (Day et al, 2014b;Tietsche et al, 2014). The observed detrended Arctic sea ice extent, based on ensemble hindcasts can be predicted up to 2-7 and 5-11 months ahead for summer and winter, respectively (e.g., Chevallier et al, 2013;Sigmond et al, 2013;Wang et al, 2013;Msadek et al, 2014;Peterson et al, 2015;Guemas et al, 2016;Sigmond et al, 2016).…”

Comparison of viscoelastic‐type models for ocean wave attenuation in ice‐covered seas

“…The magnitude and trends of such changes can only be partially captured by contemporary climate models [Stroeve et al, 2007;Jeffries et al, 2013;Tietsche et al, 2014], suggesting that important physical processes are being neglected. Recent evidence has shown that ocean waves play an important role in controlling the morphology of polar sea ice, caused by larger expanses of open water opening up in the Arctic Basin where stronger winds can then create more energetic waves over increasing fetches [Young et al, 2011;Thomson and Rogers, 2014].…”

“…The WS model has only been calibrated with data from laboratory experiments by Zhao and Shen [2015], which cannot capture the full complexity of wave-ice interactions in ice-infested seas generally. This notwithstanding, it has been implemented in WAVEWATCH III V R to describe the effect of sea ice on ocean wave attenuation [Tolman and The WAVEWATCH III V R Development Group, 2014].…”

Arctic Sea Ice: Decadal Simulations and Future Scenarios Using BESM-OA

“…However, when considering only SIE, the information related to spatial pattern is lost. Analyzing spatial patterns avoids overconfidence in the predictions and excludes compensation of errors of opposite sign in different regions [48]. Cavalieri and Parkinson [49] also show the importance of evaluating the Arctic Ocean by regions.…”