Effects of reanalysis forcing fields on ozone trends and age of air from a chemical transport model

Abstract

Abstract. We use TOMCAT, a 3-dimensional (3D) offline chemical transport model (CTM) forced by two different meteorological reanalysis data sets (ERA-Interim and ERA5) from the European Centre for Medium-Range weather Forecasts (ECMWF) to analyse seasonal behaviour and long-term trends in stratospheric ozone and mean age of air. The model-simulated ozone variations are evaluated against two observation-based data sets. For total column ozone (TCO) comparisons, 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) data set (1984–2019). We find that the CTM simulations forced by ERA-Interim (A_ERAI) and ERA5 (B_ERA5) can both successfully reproduce the spatial and temporal variations in stratospheric ozone. Also, modelled TCO anomalies from B_ERA5 show better agreement with C3S than A_ERAI, especially in Northern Hemisphere (NH) mid latitudes, except that it gives somewhat larger positive biases (> 15 DU, Dobson units) during winter–spring seasons. Ozone profile comparisons against SWOOSH data show larger differences between the two simulations. In the lower stratosphere, ozone differences can be directly attributed to the representation of dynamical processes, whereas in the upper stratosphere they can be directly linked to the differences in temperatures between ERAI and ERA5 data sets. Although TCO anomalies from B_ERA5 show relatively better agreement with C3S compared to A_ERAI, a comparison with SWOOSH data does not confirm that B_ERA5 performs better at simulating the variations in the stratospheric ozone profiles. We employ a multivariate regression model to quantify the TCO and ozone profile trends before and after peak stratospheric halogen loading in 1997. Our results show 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. Furthermore, 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 that a slower Brewer–Dobson circulation does not translate into reduced wintertime ozone buildup 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.

Investigating Zonal Asymmetries in Stratospheric Ozone Trends From Satellite Limb Observations and a Chemical Transport Model

“…A possible reason for the discrepancy between TOMCAT and SCIA + OMPS in the lower stratosphere is related to ERA5 forcing, as pointed out by Li et al. (2022, 2023). In comparison to the long‐term 2000–2020 ozone trends shown in Godin‐Beekmann et al.…”

“…The detection of negative trends in the lower tropical and extra-tropical stratosphere has been extensively debated (Ball et al, 2018;Chipperfield et al, 2018). A possible reason for the discrepancy between TOMCAT and SCIA + OMPS in the lower stratosphere is related to ERA5 forcing, as pointed out by Li et al (2022Li et al ( , 2023. In comparison to the long-term 2000-2020 ozone A TOMCAT simulation with a higher spatial resolution (1.4°× 1.4°× 0.75 km grid) was run to investigate whether the discrepancies between the CTM and SCIA + OMPS could be reduced.…”

Using machine-learning to construct TOMCAT model and occultation measurement-based stratospheric methane (TCOM-CH4) and nitrous oxide (TCOM-N2O) profile data sets

“…The CTM setup is therefore similar to the control simulations used in our recent studies such as Dhomse et al (2022) andLi et al (2022). The model simulation is performed at a 2.8 • × 2.8 • horizontal resolution with 32 hybrid sigma-pressure levels (surface to about 60 km) and is forced with ERA5 (and ERA5.1) reanalysis meteorology (Hersbach et al, 2020).…”

“…Inter-hemispheric asymmetry in the CH 4 bias correction also indicates significant differences in representation of BD circulation in ERA5 data (e.g. Li et al, 2022).…”