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

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 degrees 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.