Anomalous Arctic surface wind patterns and their impacts on September sea ice minima and trend

Abstract

We used monthly mean surface wind data from the National Centers for Environmental Prediction/National Centers for Atmospheric Research (NCEP/NCAR) reanalysis dataset during the period 1979–2010 to describe the first two patterns of Arctic surface wind variability by means of the complex vector empirical orthogonal function (CVEOF) analysis. The first two patterns respectively account for 31 and 16% of its total anomalous kinetic energy. The leading pattern consists of the two subpatterns: the northern Laptev Sea (NLS) pattern and the Arctic dipole (AD) pattern. The second pattern contains the northern Kara Sea (NKS) pattern and the central Arctic (CA) pattern. Over the past two decades, the combined dynamical forcing of the first two patterns has contributed to Arctic September sea ice extent (SIE) minima and its declining trend. September SIE minima are mainly associated with the negative phase of the AD pattern and the positive phase of the CA pattern during the summer (July to September) season, and both phases coherently show an anomalous anticyclone over the Arctic Ocean. Wind patterns affect September SIE through their frequency and intensity. The negative trend in September SIE over the past two decades is associated with increased frequency and enhanced intensity of the CA pattern during the melting season from April to September. Thus, it cannot be simply attributed to the AD anomaly characterised by the second empirical orthogonal function mode of sea level pressure north of 70°N. The CA pattern exhibited interdecadal variability in the late 1990s, and an anomalous cyclone prevailed before 1997 and was then replaced by an anomalous anticyclone over the Arctic Ocean that is consistent with the rapid decline trend in September SIE. This paper provides an alternative way to identify the dominant patterns of climate variability and investigate their associated Arctic sea ice variability from a dynamical perspective. Indeed, this study investigates only the role of surface wind dynamical forcing in resulting September SIE minima and trend in terms of CVEOF, without even considering contributions from other factors

Synoptic activity associated with sea ice variability in the Arctic

“…Patterns within the High Pressure Bridges, Eurasian Highs‐Icelandic/Aleutian Lows, and Beaufort Highs/Eurasian Lows groups, for example, show, in some cases, stronger correlations to these sea ice metrics than do modes of atmospheric circulation variability that are commonly used to diagnose sea ice variability: the AO and NAO [ Rigor et al , ; Stroeve et al , ], and the AD [ Wu et al , ], highlighting the SOMs as a complimentary tool in understanding ice variability. Correlations with indices of these patterns are shown in Figure .…”

“…The pressure gradients associated with the Beaufort High patterns in the group are consistent with shuttling ice into the Chukchi Sea and toward the Barents Sea and North Atlantic where it can melt. Many studies have suggested the 2007 record‐setting September sea ice minimum can be attributed to a persistence of Beaufort Highs and Eurasian Lows, the so‐called “dipole anomaly” [ L'Heureux et al , ; Wu et al , ]. The group exhibits the most spatial similarities to the mean May, June, and July (MJJ) pressure pattern during ILYs ( Screen et al [, their Figure ] and adapted here in Figure ), occurring ~29 days during ILYs in AMJ and ~31 days during IGYs, with an overall mean frequency of occurrence of 29 days (Figure ).…”

Predictability of winter temperature in China from previous autumn Arctic sea ice

“…Observational evidence shows that the Arctic sea ice cover has rapidly declined in the past three decades (Bader et al 2011), and this decline has been accelerating since the late 1990s (Comiso et al 2008;Comiso 2012), which is dynamically consistent with decadal changes in the Arctic surface wind pattern in summer and previous spring and winter (Ogi et al 2010;Wu et al 2012). Observational and numerical studies have demonstrated that the Arctic sea ice decline could exert substantial impact on the remote largescale atmospheric circulation and surface weather and climate in the extratropical Northern Hemisphere (Budikova 2009;Bader et al 2011;Vihma 2014;Gao et al 2015).…”

Anomalous winter moisture transport associated with the recent surface warming over the Barents–Kara seas region since the mid‐2000s

“…Many previous studies have suggested that reduction of autumn sea‐ice extent can drive atmospheric circulation change during following winter (Honda et al ., ; Wu et al ., ; Liu et al ., ; Wu et al ., ). The Arctic sea ice in the Siberian marginal seas of the Arctic Ocean decreased accelerate recently (Comiso et al ., ; Wu et al ., ), which may lead to change in the atmospheric circulation (Wang and Chen, ; Wu, ). Apart from the Arctic sea ice, the SST cooling in the tropical Pacific may also influence the inter‐decadal change of winter atmospheric circulation occurred in the mid‐2000s (Wu, ).…”