Annular Variability and Eddy–Zonal Flow Interactions in a Simplified Atmospheric GCM. Part I: Characterization of High- and Low-Frequency Behavior

Abstract

Experiments have been performed using a simplified, Newtonian forced, global circulation model to investigate how variability of the tropospheric jet can be characterized by examining the combined fluctuations of the two leading modes of annular variability. Eddy forcing of this variability is analyzed in the phase space of the leading modes using the vertically integrated momentum budget. The nature of the annular variability and eddy forcing depends on the time scale. At low frequencies the zonal flow and baroclinic eddies are in quasi equilibrium and anomalies propagate poleward. The eddies are shown primarily to reinforce the anomalous state and are closely balanced by the linear damping, leaving slow evolution as a residual. At high frequencies the flow is strongly evolving and anomalies are initiated on the poleward side of the tropospheric jet and propagate equatorward. The eddies are shown to drive this evolution strongly: eddy location and amplitude reflect the past baroclinicity, while eddy feedback on the zonal flow may be interpreted in terms of wave breaking associated with baroclinic life cycles in lateral shear.

Propagating Annular Modes: Empirical Orthogonal Functions, Principal Oscillation Patterns, and Time Scales

“…The EOF structures are similar to those seen in Southern Hemisphere data (e.g., Lorenz and Hartmann 2001;Fig. 11, below) and in models of this type (Son and Lee 2006;Sparrow et al 2009;A. Sheshadri and R. A. Plumb 2016, unpublished manuscript): EOF1 is primarily a dipole straddling the midlatitude jet; EOF2 is also predominantly dipolar, but with its central extremum coincident with the latitude of the jet.…”

“…Periods of both propagation and nonpropagation are evident, in all seasons; propagating anomalies typically appear in low latitudes and migrate generally poleward over the course of 2-3 months, although there are some instances of equatorward propagation. In terms of the leading EOFs, propagation is manifested through nonzero lag correlations between the two corresponding principal components (Lorenz and Hartmann 2001;Son and Lee 2006;Watterson 2007;Sparrow et al 2009). For the examples shown in Fig.…”

The Aqua-Planet Experiment (APE): CONTROL SST Simulation

“…This is generally due to a subtle poleward or equatorward shift of the jet in the individual models (seen as a dipole structure in differences from the multi-model mean in the ATLAS) rather than to a widening or narrowing of the jet. The peak in standard-deviation is aligned vertically on the poleward flank of the jet but tilts poleward with height on the equatorward side, reminiscent of the structure of the leading mode of annular variability found in dynamical core simulations, which describes latitudinal displacements of the jet (see e.g., Sparrow et al 2009). The standard deviation at the jet maximum is around 3 m s -1 .…”

The Impact of the State of the Troposphere on the Response to Stratospheric Heating in a Simplified GCM

“…The first and second empirical orthogonal functions (EOFs) account for most of the variability in the zonal-mean zonal wind with the first EOF representing a poleward shift of the midlatitude jet and the second EOF representing a weakening/strengthening and broadening/narrowing of the jet (see Fig. 1 of Sparrow et al 2009). Figure 6b shows the projection of the zonal wind response onto the first and second EOFs (calculated following Baldwin et al 2009) of the zonal-mean zonal wind variability of the NH and the SH of the R runs.…”

“…This arises because, although the dominant variability is of rather short time scale, there is an underlying low frequency variability with regime shifts in which the jet may remain at an anomalously high or low latitude for an extended period of time. The model's annular variability therefore exhibits a wide range of time scales (Sparrow et al 2009). Long integrations are required both to accurately characterize the control run variability and to determine the response to a forcing when that response is comparable to, or smaller than, the intrinsic variability.…”