The three-dimensional structure of thermally and eddy-driven midlatitude jet variability

Previous work (Li and Wettstein, 2012) has demonstrated that indices of two fundamental processes in the atmospheric general circulation (iT: thermal driving in the tropics and iE: momentum flux convergence in the midlatitudes) are associated both with simple reorganizations of storm track / jet covariability and with familiar leading patterns of climate variability in the Northern Hemisphere. North Atlantic zonal wind variability is mainly associated with eddy momentum flux convergence (NAO-like variability), whereas zonal wind variability over the Pacific is associated with both driving processes, providing evidence the North Pacific jet is both thermally-driven (PNA-like variability) and eddy-driven (WP-like). The present study uses both reanalysis and model simulations to expand on previous work by illustrating that the driving processes are associated with coherent three-dimensional zonal wind variability structures in both hemispheres, particularly in the vertical. Zonal wind variability is analyzed on pressure surfaces chosen to emphasize one or the other of the thermal or eddy-driven processes. For example, the leading Northern Hemisphere pattern of extratropical zonal wind variability in the lower troposphere (850 hPa) is an NAO-like pattern of zonal wind variability that resides almost exclusively in the (eddy-driven) North Atlantic. Conversely, the leading Southern Hemisphere pattern of extratropical zonal wind variability near the tropopause (200 hPa) is a Pacific South America-like pattern of zonal wind variability that resides almost exclusively in the (thermally-driven) South Pacific. An eddy-driven Southern Annular Mode-like pattern of zonal wind variability concentrated in the South Indian Ocean is the second leading pattern of 200 hPa zonal wind variability in the Southern Hemisphere. Choosing different variables (e.g., geopotential height) and pressure levels for analysis will emphasize or distort relatively clear patterns of variability associated with iT and iE. The three-dimensional (and especially vertical) structure of zonal wind covariance associated with the leading patterns of climate variability corroborate these results.