Observed Atmospheric Response to Cold Season Sea Ice Variability in the Arctic

Abstract

The relation between weekly Arctic sea ice concentrations (SICs) from December to April and sea level pressure (SLP) during 1979–2007 is investigated using maximum covariance analysis (MCA). In the North Atlantic sector, the interaction between the North Atlantic Oscillation (NAO) and a SIC seesaw between the Labrador Sea and the Greenland–Barents Sea dominates. The NAO drives the seesaw and in return the seesaw precedes a midwinter/spring NAO-like signal of the opposite polarity but with a strengthened northern lobe, thus acting as a negative feedback, with maximum squared covariance at a lag of 6 weeks. Statistical significance decreases when SLP is considered in the whole Northern Hemisphere but it increases when North Pacific SIC is included in the analysis. The maximum squared covariance then occurs after 8 weeks, resembling a combination of the NAO response to the Atlantic SIC seesaw and the Aleutian–Icelandic low seesaw-like response to in-phase SIC changes in the Bering and Okhotsk Seas, which is found to lag the North Pacific SIC. Adding SST anomalies to the SIC anomalies in the MCA leads to a loss of significance when the MCA is limited to the North Atlantic sector and a slight degradation in the Pacific and hemispheric cases, suggesting that SIC is the driver of the midwinter/spring atmospheric signal. However, North Pacific cold season SST anomalies also precede a NAO/Arctic Oscillation (AO)-like SLP signal after a shorter delay of 3–4 weeks

Arctic sea ice and Eurasian climate: A review

“…They suggested that longer and more reliable datasets are needed before conclusions can be properly drawn on the impacts and feedback processes between autumn Arctic sea ice and the following winter's NAO. The interaction between the NAO and a sea-ice concentration seesaw between the Labrador Sea and the Greenland-Barents Sea has also been revealed by Frankignoul et al (2014), by using the SIC from the National Snow and Ice Data Center and SLP anomalies obtained from the NCEP Climate Forecast System Reanalysis. The NAO drives the seesaw and in return the seesaw precedes a midwinter/spring NAO-like signal of opposite polarity but with a strengthened northern lobe, thus acting as a negative feedback, with maximum squared covariance at a lag of 6 weeks.…”

“…Simmonds and Keay (2009) suggest that low Arctic sea-ice extent conditions in September provide additional energy for cyclonic systems, which could further exert greater mechanical forcing to move more sea ice into warmer waters and result, in turn, in less sea-ice extent. The wintertime sea-ice cover variability shows a seesaw pattern between the Labrador Sea and the GreenlandBarents Seas (Gerdes, 2006), which is driven by the NAO through wind forcing, oceanic heat transport, and surface heat exchanges (Frankignoul et al, 2014). Koenigk et al (2009) suggest that negative-phase NAO leads to anomalous high pressure over Novaya Zemlya and anomalous low pressure over Svalbard, strengthening the winds across the northern border of the Barents Sea, and thus the sea-ice transport into the Barents Sea increases.…”

Wind-Driven Atlantic Water Flow as a Direct Mode for Reduced Barents Sea Ice Cover

“…The diminishing ice cover and the associated impacts have deservedly received a lot of attention (e.g., Serreze et al 2007;Comiso 2012;Parkinson and Cavalieri 2012). Variable air-sea heat fluxes caused by a changing sea ice cover may act as important drivers of large-scale atmospheric circulation variability (Screen et al 2013;Frankignoul et al 2014;Cohen et al 2014) and have been considered a cause for the midlatitude cold winters in recent years (e.g., Petoukhov and Semenov 2010;Vihma 2014;Cohen et al 2014;Mori et al 2014) and changes to the circulation in the upper troposphere (Schlichtholz 2014); they have been connected to surface temperature in midlatitudes (Schlichtholz 2016), although the causal relationship is complex (Sorokina et al 2016). Changes in the sea ice cover also impact regional marine resources and ecosystems, including species distributions, abundances, and interactions (Fossheim et al 2015); availability of light (Varpe et al 2015); and commercial offshore activity, such as shipping and fossil fuel extraction [e.g., Arctic Climate Impact Assessment (ACIA 2005)].…”

On the Predictability of the Winter Euro-Atlantic Climate: Lagged Influence of Autumn Arctic Sea Ice

“…Observational and modeling studies have largely focused on evaluating the winter atmospheric response to winter sea ice anomalies (e.g., Alexander et al 2004;Strong et al 2009;Frankignoul et al 2014;Liptak and Strong 2014). Early atmospheric general circulation model (AGCM) experiments showed that prescribing winter Arctic sea ice reduction trends leads to a negative NAO-like response , which is largely controlled by the transient-eddy feedback (Deser et al , 2007.…”