This study presents a sensitivity analysis of multivariate regressions of recent springtime Antarctic vortex ozone trends using a "big data" ensemble approach.
Our results indicate that the poleward heat flux (Eliassen–Palm flux) and the effective chlorine loading respectively explain 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 and the quasi-biennial oscillation is shown to increase rather than 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 is not recommended, as this does not take fit residuals into account, resulting in too narrow uncertainty intervals, while the fixed temporal change of the effective chlorine loading does not allow for any flexibility in the trends.
When taking fit residuals into account in a piecewise linear trend fit, we find that approximately 30–60% of the regressions in the full ensemble result in a statistically significant positive springtime ozone trend over Antarctica from the late 1990s onwards. 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 a complete 100% significance. We also find that, consistent with expectations, the number of statistically significant trends increases with increasing record length.
Although our results indicate that the use multivariate regressions is a valid approach for assessing the state of Antarctic ozone hole recovery, and it can be expected that results will move towards more confidence in recovery with increasing record length, uncertainties in choices currently do not yet support formal identification of recovery of the Antarctic ozone hole.
ATJ de Laat, RJ van der A, M van Weele. Tracing the second stage of Antarctic ozone hole recovery with a “big data” approach to multi-variate regressions
published, Atm. Chem. Phys., 2015