- Internal variability in twenty-first-century summer Arctic sea ice loss and its relationship to the large-scale
atmospheric circulation is investigated in a 39-member Community Climate System Model, version 3 (CCSM3)
ensemble for the period 2000–61. Each member is subject to an identical greenhouse gas emissions scenario and
differs only in the atmospheric model component’s initial condition.
September Arctic sea ice extent trends during 2020–59 range from -2.0 x 10⁶ to -5.7 x 10⁶ km² across the 39
ensemble members, indicating a substantial role for internal variability in future Arctic sea ice loss projections.
A similar nearly threefold range (from -7.0 x 10³ to -19 x 10³ km³) is found for summer sea ice volume trends.
Higher rates of summer Arctic sea ice loss in CCSM3 are associated with enhanced transpolar drift and
Fram Strait ice export driven by surface wind and sea level pressure patterns. Over the Arctic, the covarying
atmospheric circulation patterns resemble the so-called Arctic dipole, with maximum amplitude between
April and July. Outside the Arctic, an atmospheric Rossby wave train over the Pacific sector is associated with
internal ice loss variability. Interannual covariability patterns between sea ice and atmospheric circulation are
similar to those based on trends, suggesting that similar processes govern internal variability over a broad
range of time scales. Interannual patterns of CCSM3 ice–atmosphere covariability compare well with those in
nature and in the newer CCSM4 version of the model, lending confidence to the results. Atmospheric teleconnection
patterns in CCSM3 suggest that the tropical Pacific modulates Arctic sea ice variability via the
aforementioned Rossby wave train. Large ensembles with other coupled models are needed to corroborate
these CCSM3-based findings.
- Wettstein, Justin J., Clara Deser, 2014: Internal Variability in Projections of Twenty-First-Century Arctic Sea Ice Loss: Role of the Large-Scale Atmospheric Circulation. Journal of Climate, 27, 527–550. doi:10.1175/JCLI-D-12-00839.1
|Funding Statement (additional comments about funding)
- We made extensive use of the
NCAR Command Language (NCL) and would like to
acknowledge the National Science Foundation for their
sponsorship of this effort and especially Dennis Shea for
his support and guidance. J. W. was supported by a grant
from the National Science Foundation Arctic Sciences