Detecting ozone- and greenhouse gas-driven wind trends with observational data

July 29, 2013

Earth’s climate is characterized by persistent westerly jets (eastward flow) in the upper troposphere, located in the mid-latitudes of the Northern and Southern Hemisphere, which are associated locally with strong weather systems. The location of these jets is of paramount importance to human societies, as these are collocated with maximum in precipitation rates and surface winds in the extratropical regions. Any changes in the location of these jets on seasonal to centennial time-scales can have a strong impact on water availability on land or the rate of carbon dioxide uptake by the ocean. Observational data of Earth’s climate have shown that westerly jets have shifted poleward for at least the past 30 years. This shift is consistent with a dynamical response of the atmosphere to an increase in greenhouse gases (GHG) concentrations in comprehensive General Circulation Models (GCM) simulations. Yet other factors can lead to a poleward shift.  In particular, depletion in stratospheric ozone by CFCs in the Southern Hemisphere could also lead to the poleward trend. 

While it is possible to disentangle the relative importance of changes in GHGs and stratospheric ozone concentration in GCMs, such methods do not necessarily apply to Earth’s observations. Instead, Lee and Feldstein (2013) attempt to directly evaluate climate sensitivity of the westerly jets using an empirical statistical method. Their method captures most of the daily variability using a limited number of empirically derived modes. Using this statistical method, Lee and Feldstein shows that the variability observed in the observations on a wide range of time-scales, from daily to multi-decadal, is well captured by only 4 modes with weekly to monthly variability. Lee and Feldstein finds that the dynamical pattern of these modes are reminiscent of other modes of variability of much longer timescales, from interannual modes (e.g., ENSO [El Nino-Southern Oscillation] or SAM [Southern Annular Mode]) to multi-decadal modes (e.g., induced by changes in GHGs or ozone concentrations). In particular, long-term changes in GHGs or ozone concentrations each produces a dynamical pattern projecting almost entirely on 1 of the 4 empirical modes: a time-series of these modes then provide a direct estimate of the relative importance of changes in GHGs and ozone concentrations in driving climate change. Applying this modal decomposition to the poleward shift of the westerly jet, Lee and Feldstein finds that its sensitivity to changes in ozone and GHG concentration is consistent with the indirect estimates obtained in previous GCM studies.

The study is quite significant as Lee and Feldstein suggests that high frequency modes, on weekly to monthly timescales, could imprint itself on low-frequency modes, from interannual to centennial timescales. If true, this study may imply that the effect of global warming on the large-scale dynamics can be quantitatively constrained from even a short-term observational record, thus providing a powerful way to check climate sensitivities derived from GCM simulations of 21st century climate change.

Citation: Lee, S. and S. B. Feldstein, 2013: Detecting ozone- and greenhouse gas–driven wind trends with observational data. Nature, 339, 563–567.