Seasonal predictability of the minimum sea ice extent (SIE) in the Laptev Sea is investigated using winter coastal divergence as a predictor. From February to May, the new ice forming in wind-driven coastal polynyas grows to a thickness approximately equal to the climatological thickness loss due to summer thermodynamic processes. Estimating the area of sea ice that is preconditioned to melt enables seasonal predictability of the minimum SIE. Wintertime ice motion is quantified by seeding passive tracers along the coastlines and advecting them with the Lagrangian Ice Tracking System (LITS) forced with sea ice drifts from the Polar Pathfinder dataset for years 1992–2016. LITS-derived landfast ice estimates are comparable to those of the Russian Arctic and Antarctic Research Institute ice charts. Time series of the minimum SIE and coastal divergence show trends of −24.2% and +31.3% per decade, respectively. Statistically significant correlation ( r = −0.63) between anomalies of coastal divergence and the following September SIE occurs for coastal divergence integrated from February to the beginning of May. Using the coastal divergence anomaly to predict the minimum SIE departure from the trend improves the explained variance by 21% compared to hindcasts based on persistence of the linear trend. Coastal divergence anomalies correlate with the winter mean Arctic Oscillation index ( r = 0.69). LITS-derived areas of coastal divergence tend to underestimate the total area covered by thin ice in the CryoSat-2/SMOS (Soil Moisture and Ocean Salinity) thickness dataset, as suggested by a thermodynamic sea ice growth model.
Observations show predictive skill of the minimum sea ice extent (Min SIE) from late winter anomalous offshore ice drift along the Eurasian coastline, leading to local ice thickness anomalies at the onset of the melt season—a signal then amplified by the ice–albedo feedback. We assess whether the observed seasonal predictability of September sea ice extent (Sept SIE) from Fram Strait Ice Area Export (FSIAE; a proxy for Eurasian coastal divergence) is present in global climate model (GCM) large ensembles, namely the CESM2-LE, GISS-E2.1-G, FLOR-LE, CNRM-CM6-1, and CanESM5. All models show distinct periods where winter FSIAE anomalies are negatively correlated with the May sea ice thickness (May SIT) anomalies along the Eurasian coastline, and the following Sept Arctic SIE, as in observations. Counterintuitively, several models show occasional periods where winter FSIAE anomalies are positively correlated with the following Sept SIE anomalies when the mean ice thickness is large, or late in the simulation when the sea ice is thin, and/or when internal variability increases. More important, periods with weak correlation between winter FSIAE and the following Sept SIE dominate, suggesting that summer melt processes generally dominate over late-winter preconditioning and May SIT anomalies. In general, we find that the coupling between the winter FSIAE and ice thickness anomalies along the Eurasian coastline at the onset of the melt season is a ubiquitous feature of GCMs and that the relationship with the following Sept SIE is dependent on the mean Arctic sea ice thickness.
more » « less- NSF-PAR ID:
- 10495139
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Journal of Climate
- Volume:
- 37
- Issue:
- 7
- ISSN:
- 0894-8755
- Format(s):
- Medium: X Size: p. 2361-2377
- Size(s):
- ["p. 2361-2377"]
- Sponsoring Org:
- National Science Foundation
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