Tracing the second stage of Antarctic ozone hole recovery with a "big data" approach to multi-variate regressions

This study presents a sensitivity analysis of multi-variate regressions of recent springtime Antarctic vortex ozone trends using a "big data" ensemble approach. Multi-variate regression methods are widely used for studying the variability and detection of ozone trends. Based on multi-variate regression analysis of total Antarctic springtime vortex ozone it has been suggested that the observed increase of ozone since the late 1990s is statistically significant and can be attributed to decreasing stratospheric halogens (Salby et al., 2011, 2012; Kuttippurath et al., 2013). We find that, when considering uncertainties that have not been addressed in these studies, this conclusion on ozone recovery is not warranted. An ensemble of regressions is constructed based on the analysis of uncertainties in the applied ozone record as well as of uncertainties in the various applied regressors. The presented combination of ensemble members spans up the uncertainty range with about 35 million different regressions. The poleward heat flux (Eliassen–Palm Flux) and the effective chlorine loading explain, respectively, most of the short-term and long-term variability in different Antarctic springtime total ozone records. The inclusion in the regression of stratospheric volcanic aerosols, solar variability, the Quasi-Biennial Oscillation and the Southern Annular Mode is shown to increase rather than to decrease the overall uncertainty in the attribution of Antarctic springtime ozone because of large uncertainties in their respective records. Calculating the trend significance for the ozone record from the late 1990s onwards solely based on the fit of the effective chlorine loading should be avoided, as this does not take fit residuals into account and thereby results in too narrow uncertainty intervals. When taking fit residuals into account, we find that less than 30% of the regressions in the full ensemble result in a statistically significant positive springtime ozone trend over Antarctica from the late 1990s to either 2010 or 2012. Analysis of choices and uncertainties in time series show that, depending on choices in time series and parameters, the fraction of statistically significant trends in parts of the ensemble can range from negligible to more than 90%. However, we were unable to detect a robust statistically significant positive trend in Antarctic springtime vortex ozone in the ensemble.