Recent record lows of Arctic summer sea ice extent are found to be triggered by the Arctic atmospheric Dipole Anomaly (DA) pattern. This local, second–leading mode of sea–level pressure (SLP) anomaly in the Arctic produced a strong meridional wind anomaly that drove more sea ice out of the Arctic Ocean from the western to the eastern Arctic into the northern Atlantic during the summers of 1995, 1999, 2002, 2005, and 2007. In the 2007 summer, the DA also enhanced anomalous oceanic heat flux into the Arctic Ocean via Bering Strait, which accelerated bottom and lateral melting of sea ice and amplified the ice–albedo feedback. A coupled ice–ocean model was used to confirm the historical record lows of summer sea ice extent.

In this study, temporal and spatial variability of ice cover in the Great Lakes are investigated using historical satellite measurements from 1973 to 2010. The seasonal cycle of ice cover was constructed for all the lakes, including Lake St. Clair. A unique feature found in the seasonal cycle is that the standard deviations (i.e., variability) of ice cover are larger than the climatological means for each lake. This indicates that Great Lakes ice cover experiences large variability in response to predominant natural climate forcing and has poor predictability. Spectral analysis shows that lake ice has both quasi-decadal and interannual periodicities of ~8 and ~4 yr. There was a significant downward trend in ice coverage from 1973 to the present for all of the lakes, with Lake Ontario having the largest, and Lakes Erie and St. Clair having the smallest. The translated total loss in lake ice over the entire 38-yr record varies from 37% in Lake St. Clair (least) to 88% in Lake Ontario (most). The total loss for overall Great Lakes ice coverage is 71%, while Lake Superior places second with a 79% loss. An empirical orthogonal function analysis indicates that a major response of ice cover to atmospheric forcing is in phase in all six lakes, accounting for 80.8% of the total variance. The second mode shows an out-of-phase spatial variability between the upper and lower lakes, accounting for 10.7% of the total variance. The regression of the first EOF-mode time series to sea level pressure, surface air temperature, and surface wind shows that lake ice mainly responds to the combined Arctic Oscillation and El Niño–Southern Oscillation patterns.

No abstract

[1] The impacts of North Atlantic Oscillation (NAO) and El Niño-Southern Oscillation (ENSO) on Great Lakes ice cover were investigated using lake ice observations for winters 1963-2010 and National Centers for Environmental Prediction reanalysis data. It is found that both NAO and ENSO have impacts on Great Lakes ice cover. The Great Lakes tend to have lower (higher) ice cover during the positive (negative) NAO. El Niño events are often associated with lower ice cover. The influence of La Niña on Great Lakes ice cover is intensity-dependent: strong (weak ) La Niña events are often associated with lower (higher) ice cover. The interference of impacts of ENSO and NAO complicates the relationship between ice cover and either of them. The nonlinear effects of ENSO on Great Lakes ice cover are important in addition to NAO effects. The correlation coefficient between the quadratic Nino3.4 index and ice cover (À0.48) becomes significant at the 99% confidence level. The nonlinear response of Great Lakes ice cover to ENSO is mainly due to the phase shift of the teleconnection patterns during the opposite phases of ENSO. Multiple-variable nonlinear regression models were developed for ice coverage. Using the quadratic Nino3.4 index instead of the index itself can significantly improve the prediction of Great Lakes ice cover (the correlation between the modeled and observed increases from 0.35 to 0.51). Including the interactive term NAOÁNino3.4 2 further improves the prediction skill (the correlation increases from 0.51 to 0.59). The analysis is also applied to individual lakes. The model for Lake Michigan has the highest prediction skill, while Lake Erie has the smallest skill.Citation: Bai, X., J. Wang, C. Sellinger, A. Clites, and R. Assel (2012), Interannual variability of Great Lakes ice cover and its relationship to NAO and ENSO,