Reply on RC2

Abstract

We use the TOMCAT 3-dimensional (3D) off-line chemical transport model (CTM) forced by two different meteorological reanalysis datasets (ERA-Interim and ERA5) from the European Centre for Medium-Range weather Forecasts (ECMWF) to study stratospheric ozone trends and variability. The model-simulated ozone variations are evaluated against two observation-based data sets. For total column ozone (TCO) we use the Copernicus Climate Change Service (C3S) data (1979–2019), while for ozone profiles we use the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) database (1984–2019). We find that the CTM simulations forced by ERA-Interim (A_ERAI) and ERA5 (B_ERA5) can both successfully reproduce spatial and temporal variations in stratospheric ozone. Modelled TCO anomalies from B_ ERA5 show better agreement with C3S than A_ERAI, especially in northern hemisphere (NH) mid-latitudes, except that it produces large positive biases (> 15 DU) during winter-spring seasons. Ozone profile comparisons against SWOOSH data show larger differences between the two simulations. In the lower stratosphere, which controls the TCO, these are primarily due to differences in transport, whereas in the upper stratosphere they can be directly attributed to the differences in temperatures between the two reanalysis data sets. Although TCO anomalies from B_ERA5 show better agreement with C3S compared to A_ERAI, comparison with SWOOSH data does not confirm that B_ERA5 performs better in simulating the stratospheric ozone profiles. We employ a multi-variate regression model with piecewise linear trends (PWLT) to quantify ozone trends before and after peak stratospheric halogen loading in 1997. This model shows that compared to C3S, TCO recovery trends (since 1998) in simulation B_ERA5 are significantly overestimated in the southern hemisphere (SH) mid-latitudes, while for A_ERAI in the NH mid-latitudes simulated ozone trends remain negative. Similarly, in the lower stratosphere B_ERA5 shows positive ozone recovery trends for both NH and SH mid-latitudes. In contrast, both SWOOSH and A_ERAI show opposite (negative) trends in the NH mid-latitudes. We analyse Age-of-Air (AoA) trends to diagnose transport differences between the two reanalysis data sets. Simulation B_ERA5 shows a positive AoA trend after 1998 and somewhat older age in the NH lower stratosphere compared to A_ERAI, indicating a slower Brewer-Dobson circulation does not translate into reduced wintertime ozone build-up in the NH extratropical lower stratosphere. Overall, our results show that models forced by the most recent ERA5 reanalyses may not yet be capable of reproducing observed changes in stratospheric ozone, particularly in the lower stratosphere.