The leading mode of wintertime variability in Northern Hemisphere sea level pressure (SLP) is the Arctic Oscillation (AO). It is usually obtained using linear principal component analysis, which produces the optimal, although somewhat restrictive, linear approximation to the SLP data. Here we use a recently introduced nonlinear principal component analysis to find the optimal nonlinear approximation to SLP data produced by a 1001 year integration of the CCCma coupled general circulation model (CGCM1). This approximation's associated time series is strongly bimodal and partitions the data into two distinct regimes. The first and more persistent regime describes a standing oscillation whose signature in the mid-troposphere is alternating amplification and attenuation of the climatological ridge over Northern Europe, with associated decreasing and increasing daily variance over Northern Eurasia. The second and more episodic regime describes a split-flow south of Greenland with much enhanced daily variance in the Arctic. In a 500 year integration with atmospheric CO2 stabilized at concentrations projected for year 2100, the occupation statistics of these preferred modes of variability change, such that the episodic split-flow regime occurs less frequently while the standing oscillation regime occurs more frequently. ¿ 2000 American Geophysical Union