Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Atmos. Chem. Phys., 19, 425-446, 2019
https://doi.org/10.5194/acp-19-425-2019
Atmos. Chem. Phys., 19, 425-446, 2019
https://doi.org/10.5194/acp-19-425-2019

Research article 11 Jan 2019

Research article | 11 Jan 2019

# Structural changes in the shallow and transition branch of the Brewer–Dobson circulation induced by El Niño

Shallow and transition branch of the BDC responses to El Niño
Mohamadou Diallo1,2, Paul Konopka1, Michelle L. Santee3, Rolf Müller1, Mengchu Tao1, Kaley A. Walker4, Bernard Legras2, Martin Riese1, Manfred Ern1, and Felix Ploeger1,5 Mohamadou Diallo et al.
• 1Institute of Energy and Climate Research, Stratosphere (IEK–7), Forschungszentrum Jülich, 52425 Jülich, Germany
• 2Laboratoire de Météorologie Dynamique, UMR8539, IPSL, UPMC/ENS/CNRS/Ecole Polytechnique, Paris, France
• 3Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
• 4Department of Physics, University of Toronto, Toronto, Ontario, Canada
• 5Institute for Atmospheric and Environmental Research, University of Wuppertal, Wuppertal, Germany
Abstract

The stratospheric Brewer–Dobson circulation (BDC) determines the transport and atmospheric lifetime of key radiatively active trace gases and further impacts surface climate through downward coupling. Here, we quantify the variability in the lower stratospheric BDC induced by the El Niño–Southern Oscillation (ENSO), using satellite trace gas measurements and simulations with the Lagrangian chemistry transport model, CLaMS, driven by ERA-Interim and JRA-55 reanalyses. We show that despite discrepancies in the deseasonalized ozone (O3) mixing ratios between CLaMS simulations and satellite observations, the patterns of changes in the lower stratospheric O3 anomalies induced by ENSO agree remarkably well over the 2005–2016 period. Particularly during the most recent El Niño in 2015–2016, both satellite observations and CLaMS simulations show the largest negative tropical O3 anomaly in the record. Regression analysis of different metrics of the BDC strength, including mean age of air, vertical velocity, residual circulation, and age spectrum, shows clear evidence of structural changes in the BDC in the lower stratosphere induced by El Niño, consistent with observed O3 anomalies. These structural changes during El Niño include a weakening of the transition branch of the BDC between about 370 and 420 K (∼100–70 hPa) and equatorward of about 60 and a strengthening of the shallow branch at the same latitudes and between about 420 and 500 K (∼70–30 hPa). The slowdown of the transition branch is due to an upward shift in the dissipation height of the large-scale and gravity waves, while the strengthening of the shallow branch results mainly from enhanced gravity wave breaking in the tropics–subtropics combined with enhanced planetary wave breaking at high latitudes. The strengthening of the shallow branch induces negative tropical O3 anomalies due to enhanced tropical upwelling, while the weakening of the transition branch combined with enhanced downwelling due to the strengthening shallow branch leads to positive O3 anomalies in the extratropical upper troposphere–lower stratosphere (UTLS). Our results suggest that a shift in the ENSO basic state toward more frequent El Niño-like conditions in a warmer future climate will substantially alter UTLS trace gas distributions due to these changes in the vertical structure of the stratospheric circulation.

1 Introduction

The lower stratosphere (10–25 km) is a key region in a changing climate. In this region, the amount of key greenhouse gases, such as water vapour and ozone, which radiatively impact temperatures both locally and globally, is regulated by advection, mixing, and chemistry (Dessler et al.2013; Forster and Shine1999, 2002; Riese et al.2012; Solomon et al.2010). Ozone is a greenhouse gas, which is mainly produced in the stratosphere (10–50 km), and is directly regulated by the upwelling strength of the stratospheric circulation in the tropics.

The stratospheric mean meridional circulation, the so-called Brewer–Dobson circulation (Brewer1949; Butchart2014), is defined as a slow circulation in which air parcels rising in the tropics drift poleward in the stratosphere and are transported downward at high latitudes via its shallow and deep branches . Driven by wave breaking in the stratosphere and varying on subseasonal to decadal timescales, the BDC is modulated by natural variability , including the El Niño–Southern Oscillation (ENSO) .

ENSO is a coupled atmosphere–ocean phenomenon occurring in the equatorial Pacific Ocean with drastic changes in regional sea surface temperatures (SSTs), impacting surface weather and climate (Bjerknes1969; Cagnazzo and Manzini2009; Wang et al.2016). ENSO alternates between anomalously warm (El Niño) and cold (La Niña) conditions in the tropical eastern or central Pacific Ocean at intervals of 2–8 years . El Niño and La Niña events are associated with variations in tropical SSTs, convection, and atmospheric temperature as well as in the circulation throughout the global troposphere . During El Niño, the eastern equatorial or central Pacific Ocean is anomalously warm and convection is shifted towards this region (Avery et al.2017). During La Niña, in contrast, the highest SSTs and most intense convection occur in the western Pacific. In either phase, the fluctuations associated with ENSO usually last for a little longer than 1 year. The oscillations in SSTs of the Pacific Ocean are accompanied by displacements of tropospheric temperature and precipitation patterns around the globe .

ENSO is also a major mode of climate variability that affects the variability of the BDC. Most of the previous research on ENSO influences on the stratosphere has concentrated on tropical and extratropical temperatures as well as on planetary waves in the extratropics and on polar vortex stability during El Niño based on global circulation models and observations (Butler et al.2014; Calvo et al.2008; Garcia-Herrera et al.2006; Garfinkel and Hartmann2007; Ineson and Scaife2009; Manzini et al.2006; Sassi et al.2004; Taguchi and Hartmann2006). A substantial part of the interannual variability in the lower stratosphere turns out to be related to ENSO . El Niño events directly warm the troposphere and cool the tropical lower stratosphere with a node near the tropopause, suggesting a tropical coupling of the tropospheric and stratospheric variability . Analyses of atmospheric temperatures from satellite observations indicated an overall warming of the tropical troposphere superimposed on equatorially symmetric subtropical Rossby wave gyres during El Niño events . Using a comprehensive high-top general circulation model to investigate the dynamical mechanisms involved during ENSO winters, concluded that the response in tropical upwelling is predominantly driven by anomalous transient synoptic-scale wave drag in the Southern Hemisphere subtropical lower stratosphere. Based on zonally averaged satellite observations, found negative ozone and temperature anomalies in the tropical lower stratosphere attributed to strengthening tropical upwelling of the BDC during El Niño events. In contrast, La Niña events induce an opposite zonal mean effect (Calvo et al.2010; Konopka et al.2016). Climate models show that the ENSO modulations of the tropical upwelling appear to be linked to different propagation and dissipation patterns of parameterized gravity waves during winter . According to , the variability of tropical upwelling in the lower stratosphere shows strong regional variations in the zonally resolved picture, especially during strong La Niña years when planetary wave activity at levels directly above the tropical tropopause is enhanced and the subtropical jets are significantly disturbed.

Most previous studies of direct ENSO influence on the BDC have focused on changes in the strength of the tropical upwelling and on the mechanisms (wave–mean flow interaction) that produce its acceleration or deceleration . Here, we investigate the detailed changes in the vertical structure of different BDC branches based on satellite observations and simulations with the Chemical Lagrangian Model of the Stratosphere (CLaMS) . found a separation in the residual circulation transit times (RCTT) between the shallow and deep branches of the BDC. In particular, they found much smaller transit times into the mid-latitude than into the polar lowermost stratosphere. Based on these findings, the shallow branch is found in the tropical stratosphere and in the lower mid-latitudinal stratosphere equatorward of about 60 below 500 K (∼30hPa), whereas the deep branch is found throughout the high-latitude stratosphere poleward of 70 and above 500 K. In addition, further separated the shallow branch defined by into two sub-branches: the transition branch (i.e. between 370 and 420 K (100–70 hPa)) and the shallow branch (i.e. between 420 and 500 K (70–30 hPa)). Here, we use this definition of the branches to identify the “fingerprints” of the ENSO-induced variability in the structure of the BDC. We disentangle the changes in each branch of the BDC related to ENSO using multiple regression analysis of different diagnostic quantities derived from the satellite observations, CLaMS simulations, and meteorology of two modern reanalysis products included in the SPARC Reanalysis Intercomparison Project (S-RIP) . A description of the satellite observations, model data, and the multiple regression technique is included in Sect. 2. Section 3 shows the ENSO impact on simulated and observed ozone mixing ratios in the lower stratosphere. Section 4 presents an analysis of the ENSO-induced changes in the vertical structure of the BDC in the lower stratosphere, based on mean age of air, vertical velocity, residual circulation, and age spectrum diagnostics. Finally, we discuss a possible dynamical mechanism for these changes in the vertical structure of the circulation and potential impacts on decadal and long-term changes (Sect. 5).

2 Data and methodology

## 2.1 Description of the CLaMS model

The Chemical Lagrangian Model of the Stratosphere (CLaMS) is a Lagrangian transport model with trace gas transport based on the motion of 3-D forward trajectories and an additional parameterization of subgrid-scale atmospheric mixing . The CLaMS model allows ozone concentrations to be simulated through a simplified formulation of stratospheric chemistry . The lower boundary values for the ozone mixing ratio are set to zero in the lowest model layer (roughly the boundary layer), while the upper boundary condition (∼500K) is imposed based on mean climatological satellite fields. For this study, we carried out simulations with the CLaMS model driven by 6-hourly horizontal winds and diabatic heating rates both from ERA-Interim (ERA-I) and Japanese 55-year Reanalysis (JRA-55) reanalyses, respectively provided by the European Centre for Medium-Range Weather Forecasts and the Japan Meteorological Agency. For the wind and temperature fields, CLaMS uses $\mathrm{1}{}^{\circ }×\mathrm{1}{}^{\circ }$ for the horizontal resolution and the native reanalysis vertical resolution. The mean vertical resolution of air parcels in the CLaMS Lagrangian model is about 400 m near the tropopause. The simulation driven by ERA-I covers the 1979–2016 period, whereas the simulation driven by JRA-55 covers the 1979–2013 period. Both reanalyses are described in detail by for the S-RIP project, which is a coordinated inter-comparison of modern global atmospheric reanalyses.

## 2.2 Lower stratospheric O3 from CLaMS and Aura-MLS

To analyse the response of the BDC to ENSO variability, we use ozone (O3) mixing ratios and different diagnostics of the stratospheric circulation strength, as described in the following. The simulated O3 mixing ratios from the CLaMS set-up used in this work were previously analysed by for validation of the CLaMS simulations. In addition, the O3 mixing ratios from CLaMS simulations driven by ERA-I and JRA-55 are sampled at the MLS measurement geolocations to avoid sampling bias during the inter-comparisons. Reliable agreement with satellite observations has been found regarding seasonality as well as variability related to the Quasi-Biennial Oscillation (QBO). The first part of the present analysis is a further validation of CLaMS' ability to reproduce interannual stratospheric variability related to ENSO.

The observational data used for comparison with CLaMS simulations are monthly mean O3 mixing ratios in the lower stratosphere from the Aura Microwave Limb Sounder (MLS), covering the period 2005–2016 . The MLS instrument, flying aboard the EOS-Aura satellite, is designed to measure a wide range of physical and chemical quantities, including O3 . The version 4.2 abundances MLS data were produced with improved retrieval algorithms, which substantially reduced the occurrence of unrealistically small O3 values at 215 hPa in the tropics observed in the previous version 2.2 MLS product . Note that the version 4.2 MLS O3 data used here are not significantly different from the previous version MLS observations at pressures less than 100 hPa, but show less oscillatory behaviour and fewer retrieval artifacts induced by cloud contamination in the tropical upper troposphere and lower stratosphere. The version 4.2 O3 data are characterized by a vertical resolution of 2.5–3.5 km, a precision of ±0.02–0.04 ppmv, a systematic uncertainty of ±0.02–0.05 ppmv+±5–10 %, and a lowest recommended level of 261 hPa for individual profile measurements with a horizontal resolution in the UTLS of ∼300–400 km along the orbital-track line of sight . The regression results will not be affected by these intrinsic uncertainties since they apply to the O3 mixing ratios and not the anomalies. Additional detailed information on the quality of MLS O3 in the upper troposphere–stratosphere in previous versions can be found in dedicated validation papers .

## 2.3 Metrics of the BDC

In addition to the trace gas diagnostics, the strength of the BDC is commonly deduced from age of air related diagnostics, including the mean age of air (AoA) and the age spectrum, and also the residual vertical velocity ($\stackrel{\mathrm{‾}}{{w}^{\ast }}$), the residual circulation transit time (RCTT), and the residual circulation mass stream function (ψ) . Mean AoA is defined as the average transit time for an air parcel since entering the stratosphere, and is therefore the first moment of the full transit time distribution termed the age spectrum. As shown by , mean AoA can be calculated in a model from a “clock tracer” that is an inert tracer with a linear increase in the troposphere or at the surface. Note that we calculate mean AoA and age spectrum relative to the lowest model level following the surface, as this is a common choice in global models .

The age spectrum includes the detailed transit time information and is advantageous for investigating different transport pathways (Ploeger and Birner2016). In the CLaMS model, the age spectrum is calculated using a total of 60 different boundary pulse tracers, with pulses released in the lowest model layer in the tropics between 15 S and 15 N, constituting the pulse source region Ω at source times t. Note that releasing the pulses only in the tropics between 15 S and 15 N might bias the age spectrum results in the lowermost stratosphere. It is likely that a substantial amount of air originating in the extratropics crosses the tropopause near the subtropical jets, especially during summer and autumn in the Northern Hemisphere. Since this air is not taken into account, the young portion of the age spectrum is likely being underestimated. For each pulse, the tracer mixing ratio χi(r,t) is set to unity in Ω for 30 days, and is set to zero in Ω otherwise. These pulses are released every 2 months. For instance, the first tracer pulse has its source time in January 1979, the second tracer pulse in March 1979, and so on. The age spectrum is Green's function or a boundary propagator, G, that solves the continuity equation for the mixing ratio of a conserved and passive tracer . As a function of transit time (elapsed time) $\mathit{\tau }=t-{t}_{i}^{\prime }$, the age spectrum is constructed from these N pulse tracers at each sample field time t and sample region r as $G\left(r,t|\mathrm{\Omega },t-{\mathit{\tau }}_{i}\right)={\mathit{\chi }}_{i}\left(r,t\right)$. For more details about the set-up and calculations, see .

The residual circulation transit time (RCTT) is a 2-D diagnostic defined as the transit time of an air parcel through the stratosphere, if it were advected only by the residual circulation, and measures the strength of the residual circulation . RCTTs are calculated from 2-D CLaMS backward trajectories driven by the mass-weighted isentropic zonal mean diabatic circulation, and the reference level is set to the 340 K isentrope in the tropics to include transport in the tropical tropopause layer . For more details about the RCTT calculations see . In addition, we analyse the strength of the tropical upwelling related to ENSO using $\stackrel{\mathrm{‾}}{{w}^{\ast }}$, calculated from the transformed Eulerian mean (TEM) circulation standard formula in geometric coordinates (Andrews et al.1987) and the diabatic heating rate from both reanalyses. In contrast to the integrated residual circulation transit time along the trajectory of an air parcel, $\stackrel{\mathrm{‾}}{{w}^{\ast }}$ is a local 2-D quantity.

## 2.4 Multiple regression model

To properly disentangle the ENSO impact on these metrics of the BDC from the other sources of natural variability, the monthly zonal mean O3 mixing ratios and other diagnostic quantities are analysed by using a multiple regression model as a function of latitude (ϕ) and altitude (z). This regression method is an established method and appropriate to disentangle the relative influences of the considered climate indices on BDC variability, as it includes time-lag coefficients as a function of ϕ and z for each proxy, including the ENSO signal. For more details about the method and its further applications, see . The regression method decomposes the temporal evolution of a monthly zonal mean parameter, χ, in terms of a long-term linear trend, seasonal cycle, QBO, ENSO, volcanic aerosol, and a residual. The model yields for a given parameter, χ (herein O3, AoA, $\stackrel{\mathrm{‾}}{{w}^{\ast }}$, RCTT, Ψ, age spectrum, air mass fraction, temperature, zonal mean wind, Eliassen–Palm flux, and its divergence),

$\begin{array}{ll}& \mathit{\chi }\left(t,\mathit{\varphi },z\right)=a\left(\mathit{\varphi },z\right)\cdot t+C\left(t,\mathit{\varphi },z\right)+\sum _{k=\mathrm{1}}^{\mathrm{3}}{b}_{k}\left(\mathit{\varphi },z\right)\\ \text{(1)}& & \cdot {P}_{k}\left(t-{\mathit{\tau }}_{k}\left(\mathit{\varphi },z\right)\right)+\mathit{ϵ}\left(t,\mathit{\varphi },z\right),\end{array}$

where Pk represents the predictors or proxies of different atmospheric sources of variability. Thus, P1 is a normalized QBO index (QBOi) from CDAS/Reanalysis zonally averaged winds at 50 hPa, P2 is the normalized Multivariate ENSO Index (MEI) and P3 is the Aerosol Optical Depth (AOD) from satellite data . The coefficients are a linear trend a, the annual cycle $C\left(t,\mathit{\varphi },z\right)$, the amplitude b1 and the lag τ1(ϕ,z) associated with the QBO, the amplitude b2 and the lag τ2(ϕ,z) associated with ENSO and the amplitude b3 and the lag τ3(ϕ,z) associated with AOD. The constraint applied to determine the parameters a, b1, b2, b3, τ1(ϕ,z), τ2(ϕ,z), τ3(ϕ,z) and C is to minimize the residual $\mathit{ϵ}\left(t,\mathit{\varphi },z\right)$ in the least squares sense. Because of the presence of lags in the QBO, ENSO and AOD terms in Eq. (1), the problem is nonlinear and the residual may have multiple minima as a function of the parameters. In order to determine the optimal values of τ1(ϕ,z), τ2(ϕ,z) and τ3(ϕ,z), the residual is first minimized at fixed lag and then sorted out over a range of lags. This is done in sequence for QBO, ENSO and AOD. Here we neglect solar forcing, because our data set covers only one solar period. Uncertainty estimates for the statistical fits are calculated using a Student's t-test technique .

Figure 1Time evolution of the tropical O3 anomalies from CLaMS simulations sampled at the MLS measurement geolocations together with MLS satellite observations in percent change from the monthly zonal mean climatology and averaged between 380 and 425 K for the 2005–2016 period. Panel (a) shows the 10 S–10 N deseasonalized O3 for CLaMS driven by ERA-I (red); CLaMS driven by JRA-55 (blue) and MLS (dashed black). Panel (b) shows the ENSO-induced O3 anomalies in the tropics for CLaMS driven by ERA-I (red); CLaMS driven by JRA-55 (blue) and MLS (dashed black) derived from the multiple regression fit. Panel (c) shows the Multivariate ENSO Index (MEI: blue). Note that there is a factor of 2 difference in the legend in (a) and (b), reflecting the difference in the magnitude of the deseasonalized O3 mixing ratio between CLaMS and MLS. Vertical black dashed line indicates February 2015 for the warm ENSO onset.

3 ENSO impact on lower stratospheric O3

Figure 1a shows the interannual variability of the deseasonalized O3 from CLaMS simulations driven by ERA-I and JRA-55 sampled at the MLS measurement geolocations together with MLS observations averaged in the tropical lower stratosphere between 380 and 425 K as a percentage change relative to the climatological monthly mean mixing ratio during the 2005–2016 period. Generally, a consistent picture of O3 interannual variability emerges between observations and model simulations driven by ERA-I and JRA-55. Note that the CLaMS O3 values are 2 times as large as the MLS O3 values, and this difference in the magnitude of the O3 anomalies is not due to a sampling bias. The factor of 2 difference in the zonal mean magnitude between CLaMS and MLS O3 anomalies is likely due to the lack of tropospheric O3 chemistry and the O3 lower boundary condition being set to zero in CLaMS, combined with tropical upwelling being too strong and tropical–extratropical exchange being too weak in the model. These different possible reasons for the factor of 2 difference are further discussed in Sect. 5. The deseasonalized tropical O3 time series exhibit seasonal variations in both model simulations and observations, which are negatively correlated with the Multivariate ENSO Index (MEI) (Fig. 1a, c). In particular, during the 2015–2016 period, the deseasonalized O3 shows negative anomalies in the tropical lower stratosphere due to the enhanced tropical upwelling caused by both the extreme El Niño event and the QBO disruption (e.g. easterly wind shear at 100–40 hPa) .

However, the overall O3 interannual variability is challenging to interpret because of its regulation by the complex interplay between the ENSO- and QBO-induced variability (Diallo et al.2018; Liess and Geller2012; Neu et al.2014; Taguchi2010), by the climate change impact (Ball et al.2018; Bekki et al.2013; Iglesias-Suarez et al.2018; Wargan et al.2018), and by the emissions of ozone depletion substances (Chipperfield et al.2018; Dhomse et al.2018; Montzka et al.2018). Therefore, to elucidate the ENSO impact on the stratospheric O3 anomalies, the multiple regression is performed both without and with explicit inclusion of the ENSO signal. The difference between the residual (ϵ in Eq. 1) without and with explicit inclusion of the ENSO signal gives the ENSO-induced impact on stratospheric O3 anomalies. This approach of differencing the residuals is similar to direct calculations, projecting the regression fits onto the ENSO basis functions herein termed the amplitude variation (b2×SD(MEI), i.e. term b2 in (1) normalized by the standard deviation of the MEI). For illustration, please see supplementary Figs. 2 and 4 in and also .

Figure 1b shows time series of the O3 changes induced by ENSO variability in the tropical lower stratosphere averaged between 380 and 425 K and estimated from the difference between the residual (ϵ in Eq. 1) with and without explicit inclusion of the ENSO signal for the 2005–2016 period. The ENSO-induced variability in lower stratospheric O3 mixing ratios shows a good agreement between CLaMS simulations driven by both reanalyses and MLS observations, though again with a factor of 2 difference in the magnitude. These O3 anomalies show a strong negative correlation with the MEI, reaching 77.9 % for CLaMS driven by ERA-I, 70 % for CLaMS driven by JRA-55, and 85.7 % for MLS.

Figure 2Latitude–time evolution of the ENSO impact on lower stratospheric O3 from (a) CLaMS simulations driven by ERA-I; (b) CLaMS simulations driven by JRA-55 and (c) MLS satellite observations in percent change from the monthly zonal mean climatology derived from the multiple regression fit and averaged between 380 and 425 K for the 2005–2016 period. Note that there is a factor of 2 difference in the colour scales in (a), (b), and (c), reflecting the difference in the magnitude of the deseasonalized O3 mixing ratio between CLaMS and MLS. Panel (d) shows the MEI in blue. Vertical black dashed line indicates February 2015 for the warm ENSO onset.

Figure 2a–c show latitude–time series of the ENSO-induced variability in monthly mean O3 mixing ratios in the lower stratosphere and estimated from the difference between the residual (ϵ in Eq. 1) with and without explicit inclusion of the ENSO signal for the 2005–2016 period. The patterns of ENSO-induced variability in the CLaMS O3 driven by both reanalyses and MLS observations agree very well, though again with a factor of 2 difference in the magnitude related to the high-biased O3 variability in CLaMS consistent with Fig. 1a, b. In addition, the gradient in the MLS and JRA-55 O3 anomalies between the tropics and extratropics in the Southern Hemisphere is smoother than that in CLaMS simulations driven by ERA-I, likely due to its too strong tropical upwelling . The CLaMS and MLS O3 anomalies are negative in the lower stratosphere during El Niño years (e.g. 2006–2007, 2010–2011, 2015–2016) and positive during La Niña years (e.g. 2008–2009, 2011–2012, 2013–2014), consistent with previous studies . In particular, the most recent El Niño event produces an extremely large negative O3 anomaly in the lower stratosphere, inducing a record anomaly of 15 % in the tropics for MLS (twice as large for CLaMS), consistent with . This strong increase in the magnitude of negative O3 anomalies is interpreted as a manifestation of the strengthening of the tropical upwelling induced by El Niño (see Sect. 4) . These substantial O3 anomalies are consistent with recently published strong ozone and water vapour anomalies during the 2015–2016 El Niño . The two consecutive La Niña events in 2011–2012 exhibit the largest positive O3 anomalies in decadal satellite records.

Figure 3Zonal mean distribution of the ENSO impact on stratospheric O3 variability from (a) CLaMS simulations driven by ERA-I; (b) CLaMS simulations driven by JRA-55 and (c) MLS satellite observations in percent change relative to the climatological monthly mean mixing ratios. The amplitude of the O3 variations (term b2×SD(MEI)) attributed to ENSO is calculated by projecting the regression fits onto the ENSO basis functions for the 2005–2016 period. Note that there is a factor of 2 difference in the colour scales in (a), (b), and (c), reflecting the difference in the magnitude of the O3 changes between CLaMS and MLS. Black dashed horizontal line indicates the climatological tropopause from ERA-I (a, b) and JRA-55 c). Zonal mean wind component u (m s−1), averaged over the 2005–2016 period, from ERA-I is overplotted as solid white (westerly) and dashed grey (easterly) lines.

Figure 3a–c depict the zonal mean impact of ENSO on O3 variability for CLaMS simulations driven by ERA-I (a) and JRA-55 (b) together with MLS (c) calculated as the projection of the regression fits onto the ENSO basis functions for the 2005–2016 period, i.e. the amplitude variation. There is good agreement between CLaMS and MLS regarding the pattern of O3 variations related to El Niño-like conditions, with the negative O3 anomalies in the JRA-55 simulations much more confined to the tropics. In the tropical UTLS, the negative O3 anomalies during El Niño are due to the enhanced tropical upwelling, transporting upward fresh air poor in O3 from the troposphere. The negative O3 anomalies from simulations driven by ERA-I are stronger than those from MLS and JRA-55, corroborating the too strong upwelling in ERA-I . In the extratropical UTLS (30–70), CLaMS simulations driven by both reanalyses together with MLS observations show a related positive O3 anomaly due to enhanced downwelling and consistent with recent studies . In addition, the positive O3 anomalies induced by the ENSO signal in the extratropics indicate hemispheric asymmetry in both simulations and observations, with a generally weaker response in the Southern Hemisphere than in the Northern Hemisphere (Fig. 3a–c). This hemispheric asymmetry results from a weak quasi-horizontal mixing between tropics and extratropics induced by the asymmetry in the wave breaking response to El Niño-like conditions, which will be discussed further in Sect. 5. The negative O3 anomalies seen in the Southern Hemisphere polar region reflect the large variability at high latitudes in Antarctic ozone due to chemical O3 loss . Note that the absence of O3 anomalies above 500 K in CLaMS (Fig. 3a) results from the upper boundary condition, which is imposed above this level based on mean climatological fields and thus precludes representation of variability.

Despite generally good agreement between simulations and observations, the signal in the MLS data is weaker in both the tropics and the extratropics, particularly in the Southern Hemisphere. The stratospheric entry value of fire emission markers is strongly enhanced under El Niño conditions . Increased upper tropospheric O3 mixing ratios have also been linked to increased O3 precursor emissions from biomass burning. The dynamical changes, severe drought, and ensuing large-scale forest fires in Indonesia and Malaysia induced by strong El Niño events have been conclusively associated with substantial anomalies in UTLS CO and O3 (Chandra et al.2007, 2009; Field et al.2016; Livesey et al.2013; Logan et al.2008; Nassar et al.2009; Thompson et al.2001). Thus, tropical upper tropospheric O3 mixing ratios may be enhanced not only because of increased convective transport, but also increased fire emissions (Field et al.2016). Hence, the tropical UTLS O3 mixing ratios will reflect the net change from competing effects that CLaMS simulations cannot capture because of the use of zero O3 as a lower boundary condition, as mentioned earlier. In some cases these local/regional effects may have been large enough to impact the tropical mean O3 mixing ratios. In the CLaMS model this chemical relationship between CO and O3 is missing, which might explain the discrepancies with MLS observations.

Figure 4Zonal mean distribution of the ENSO impact on mean age (a, b), residual vertical velocity ($\stackrel{\mathrm{‾}}{{w}^{\ast }}$) (c, d) and diabatic heating rate ($\stackrel{\mathrm{˙}}{\mathrm{\Theta }}$(e, f) from CLaMS simulations driven by ERA-I and JRA-55. The mean age anomalies are in percent change relative to the zonal monthly mean climatology. The units of $\stackrel{\mathrm{‾}}{{w}^{\ast }}$ and $\stackrel{\mathrm{˙}}{\mathrm{\Theta }}$ are in m s−1 and K day−1. The amplitude of the O3 variations (term b2×SD(MEI)) attributed to ENSO is calculated by projecting the regression fits onto the ENSO basis functions for the 1979–2013 period. Black dashed horizontal line indicates the climatological tropopause from ERA-I and JRA-55 reanalyses. Zonal mean climatologies of the mean age, $\stackrel{\mathrm{‾}}{{w}^{\ast }}$ and $\stackrel{\mathrm{˙}}{\mathrm{\Theta }}$ are overplotted as dashed grey lines.

4 Structural changes in the lower stratospheric BDC

In this section, various diagnostics of the BDC strength (e.g. AoA, $\stackrel{\mathrm{‾}}{{w}^{\ast }}$, Ψ, RCTT, age spectrum) from simulations with CLaMS, driven by ERA-I and JRA-55 reanalyses, are analysed for ENSO-related variability and consistency with the O3-based results (see Sect. 3). In contrast to the complex chemistry in trace gases, the AoA is particularly useful as a diagnostic for investigating variability in stratospheric transport and mixing, as it is not influenced by chemistry.

Figure 4a–b show the amplitude variation of the ENSO impact on AoA for the 1979–2013 period. The vertical structure of AoA anomalies depicts a pattern of changes similar to the ENSO imprint on O3 mixing ratios. Negative AoA anomalies (young AoA) emerge throughout the tropics in both ERA-I and JRA-55 reanalyses and propagate upwards into the stratosphere during El Niño-like conditions. Positive AoA anomalies (old AoA) arise in the extratropics with a strong effect in the Northern Hemisphere during El Niño, leading to hemispheric asymmetry consistent with the O3 anomalies. The picture of AoA anomalies agrees well with O3 anomalies from CLaMS simulations and MLS observations, albeit with a smoother pattern of changes for MLS O3 anomalies in the Southern Hemisphere lower stratosphere (Fig. 3).

Figure 4c, d depict the ENSO-induced variability in the $\stackrel{\mathrm{‾}}{{w}^{\ast }}$, indicating a clear increase in the tropical upwelling during El Niño-like conditions, consistent with recent findings . The vertical structure of AoA and O3 changes in the UTLS, i.e. negative anomalies in the tropics and positive anomalies in the extratropics during El Niño-like conditions, is mainly explained by the ENSO-induced anomalies in $\stackrel{\mathrm{‾}}{{w}^{\ast }}$ and in the diabatic heating rate ($\stackrel{\mathrm{˙}}{\mathrm{\Theta }}$) (Fig. 4c–f). During El Niño, the increase in the ascending branch of the BDC (positive tropical $\stackrel{\mathrm{‾}}{{w}^{\ast }}$ and $\stackrel{\mathrm{˙}}{\mathrm{\Theta }}$) anomalies enhances upward transport of young tropospheric air poor in O3 into the tropical stratosphere. The enhanced downwelling in the mid and high latitudes transports more old stratospheric air rich in O3 downwards into the polar regions (see Fig. 3), contrasting with model projections of shorter stratospheric residence time due to enhanced downwelling in a warming climate (Butchart2014; Hardiman et al.2014; Lin and Fu2013; McLandress and Shepherd2009). The main difference in the response of the AoA to El Niño compared to its global warming response lies in the difference in the transition branch response and the difference in timescale of the El Niño perturbations compared to those induced by a globally warming climate, which is of the order of years. In a warming climate, climate models predict a globally decreasing AoA due to faster upwelling and downwelling of all branches (transition, shallow, and deep) over a timescale of decades, leading to a shorter stratospheric residence time of air parcels tropically ascending. In contrast, during El Niño, the shallow and transition branches evolve in different regimes, i.e. a weakening transition branch, a strengthening shallow branch, and an unclear response for the deep branch. El Niño strengthening the downwelling of the shallow branch has a typical timescale of a few months and maximizes in winter, transporting much older air downward to the lower extratropical stratosphere and hence increasing AoA. The El Niño effect is analogous to the effect of seasonality, where stronger winter downwelling is also related to increasing AoA in the extratropical lower stratosphere. Consequently, during El Niño the enhanced tropical upwelling depletes O3 in the tropical lower stratosphere, while the strengthened downwelling of the shallow branch enhances O3 in the mid and high latitudes. Opposite changes occur during La Niña (not shown). The ENSO-induced variations in $\stackrel{\mathrm{‾}}{{w}^{\ast }}$ and $\stackrel{\mathrm{˙}}{\mathrm{\Theta }}$ agree well in the two reanalyses in terms of morphology, though not in magnitude (see Fig. 4c–f). The $\stackrel{\mathrm{‾}}{{w}^{\ast }}$ and $\stackrel{\mathrm{˙}}{\mathrm{\Theta }}$ changes related to El Niño for JRA-55 are more confined in the tropics and exhibit stronger downwelling in the Northern Hemisphere than those from ERA-I. The latter also exhibits stronger $\stackrel{\mathrm{‾}}{{w}^{\ast }}$ anomalies in the tropics than JRA-55, consistent with the differences between the two reanalyses in O3 anomalies (Fig. 3).

Figure 5Zonal mean distribution of the ENSO impact on residual circulation transit time (RCTT) (a, b) and the residual circulation mass stream function (ψ) (c, d) from CLaMS simulations driven by ERA-I (a, c) and JRA-55 (b, d). RCTT is shown in percent change relative to the monthly zonal mean climatology. The amplitude of the RCTT and ψ variations (term b2×SD(MEI)) attributed to the ENSO events is calculated by projecting the regression fits onto the ENSO basis functions for the 1979–2013 period. Black dashed horizontal line indicates the climatological tropopause from ERA-I and JRA-55 reanalyses. Zonal mean climatologies of the RCTT and ψ are overplotted as dashed grey lines.

However, as the AoA is affected by both residual circulation and mixing processes (Garny et al.2014; Ploeger et al.2015a, b), there could be an ambiguous relation between AoA changes and upwelling or downwelling. Therefore, we also analyse the ENSO-induced RCTT and ψ anomalies (Fig. 5a–d). The ENSO impact on the vertical structure of the BDC becomes evident from the mass stream function and the RCTT, i.e. the timescale of transport by the pure residual circulation (Fig. 5). In the tropics, El Niño causes decreasing RCTT throughout most parts of the stratosphere (below 550 K) related to the strengthening tropical residual circulation cell associated with the shallow branch of the BDC . The strengthening tropical residual circulation in Fig. 5a, b is consistent with positive (negative) stream function changes in the Northern Hemisphere (Southern Hemisphere), indicating a strengthening residual mean mass circulation in the tropics (Fig. 5c, d). In the extratropical lower stratosphere at altitudes below 450 K, the RCTT increases during El Niño, consistent with a weakening extratropical residual circulation cell related to the transition branch of the BDC . These changes in extratropical RCTT also corroborate a weakening of residual circulation cells in the extratropics of both hemispheres during El Niño. The pattern of changes in the residual circulation (transit time and stream function) depicts a weakening transition branch during El Niño, while the shallow branch is strengthening in both reanalyses. However, differences occur between the two reanalyses concerning the strength of the shallow branch. The strengthening of the shallow branch in response to El Niño does not extend as far poleward in JRA-55 as it does in ERA-I, reflecting the difference in the strength of the tropical upwelling response in the two reanalyses (Fig. 4c, d). ENSO-induced variability in the deep branch is less evident in the reanalyses (not shown).

Figure 6Lag correlation of the ENSO impact on RCTT versus the MEI from CLaMS simulations driven by ERA-I (a, c) and JRA-55 (b, d). Transition branch (a, b) and shallow branch (c, d) changes are shown in percent change relative to the monthly zonal mean climatology. The RCTT variations attributed to the ENSO events using the regression analysis are averaged between 20 and 70 and between 370 and 420 K for the transition branch and between 10 and 70 and between 420 and 500 K for the shallow branch during the 1979–2013 period.

Next we quantify the changes in the strength of the transition and shallow branches. Figure 6a–d show the lag correlation of the ENSO-induced changes in the transition and shallow circulation branches inferred from the RCTT anomalies versus the MEI. A lag correlation is calculated for each given latitude and altitude grid point in these two regions: 20–60 and 370–420 K for the transition branch and 10–60 and 420–500 K for the shallow branch. Note that positive lag correlations imply weaker circulation, and negative ones imply stronger circulation. The estimated changes in the transition and shallow branches are as large as ±8 % over the 1979–2013 period, except the strong Niño in 1997, where the changes in the shallow branch from ERA-I reach 10 %. These changes are robust as, shown by the lag correlation estimated from the transition branch versus MEI, which reaches 73 % for ERA-I and 75 % for JRA-55. For the shallow branch, the lag correlation is 73 % for ERA-I and 53 % for JRA-55. The vertical structure of changes in the BDC during El Niño with a strengthening ascending branch and a weakening circulation in the mid-latitude lower stratosphere is also consistent with the strengthening shallow circulation branch and a weakening transition branch. The vertical structure of the BDC branches agrees between the two reanalyses, although the changes in JRA-55 are more confined in latitude and altitude than changes in ERA-I, consistent with the variations in diabatic heating rates related to ENSO in the two reanalyses (Fig. 4e, f) as well as with the differences in the lag correlation.

Figure 7ENSO impact on the monthly mean age spectrum from CLaMS simulations driven by ERA-I and JRA-55 reanalyses for the 1979–2013 period: (a, b) tropics at 400 K and (c, d) mid latitudes at 350 K. The El Niño and La Niña composites shown are derived from the multiple regression fit as the difference between the residual (ϵ in Eg. 1) without and with explicit inclusion of the ENSO signal. Note that the x axes for the tropic and mid-latitude panels are not the same. The ERA-I and JRA-55 mid-latitude panels use different y-axis ranges. The x-axis ranges of the tropical panels stop at 30 months, while the x-axis ranges of the mid-latitude panels stop at 90 months.

The most complete transit time diagnostic is the age spectrum, which includes the full transit time information related to all circulation pathways and mixing processes, thereby giving clearer insight into the reanalysis differences. From Fig. 7a to d, it can be concluded that the ENSO-induced variations in the age spectrum appear to be mainly caused by changes in the residual circulation and mass stream function (Fig. 5). The El Niño and La Niña impacts on the fraction of young air masses in the tropics and extratropics are consistent with the structural changes in the residual circulation induced by ENSO. Both reanalyses show an increase in the fraction of young air masses with age shorter than about 6 months during El Niño and a significant decrease during La Niña in the tropical lower stratosphere (here 10 S–10 N at 400 K) (Fig. 7a, b). Note that JRA-55 depicts a smaller El Niño impact on the youngest air mass fraction than ERA-I, consistent with the reanalysis differences in the RCTTs (Fig. 5). The age spectrum tail, which is most sensitive to changes in mixing with very old air from the extratropics, is unchanged in both reanalyses after 25 months. Hence, the ENSO-induced changes in the tropical age spectrum mainly reflect the strengthening upwelling branch of the residual circulation in the tropics during El Niño, in agreement with the discussion by . In the lower stratosphere at mid latitudes (here 40–55 N at 350 K), the age spectrum shows a decrease in the fraction of young air and a slight change in the spectrum tail after 40 months during El Niño, indicating a long-lasting ENSO signal in the Northern Hemisphere and mixing effects (Fig. 7c, d). The amplitude of decreasing young air mass fraction during El Niño is larger in JRA-55 than in ERA-I, corroborating the observed differences in the AoA and RCTTs (Figs. 4 and 5). These changes in the age spectrum are consistent with the weakening transition branch of the residual circulation in the lowermost stratosphere at mid latitudes (see Fig. 5 and related discussion). Hence, the ENSO-induced changes in the lower stratospheric age spectra are consistent with the structural changes in the residual circulation, with El Niño causing an upward shift of the poleward outflow from the shallow branch of the BDC and a weakening of the transition branch below. La Niña causes the opposite changes.

Figure 8Zonal mean distribution of the ENSO impact on monthly mean young and old air mass fraction from CLaMS simulations driven by (a, c) ERA-I and (b, d) JRA-55 reanalyses. The amplitude of the air mass fraction variations (term b2×SD(MEI)) attributed to ENSO is calculated by projecting the regression fits onto the ENSO basis functions for the 1979–2013 period. ENSO amplitude variation of the young air mass fraction with a transit time τ shorter than 6 months is shown in (a) and (b) panels. ENSO amplitude variation of the old air mass fraction with a transit time τ longer than 24 months is shown in (c) and (d) panels. Grey contours are the climatology. Black dashed horizontal line indicates the climatological tropopause from ERA-I and JRA-55 reanalyses.

A very clear picture of the structural circulation changes induced by ENSO emerges from the separation of the young air mass fraction with a transit time shorter than 6 months (Fig. 8a, b) and the old air mass fraction with a transit time longer than 24 months (Fig. 8c, d), calculated from the age spectrum. During El Niño, the young air mass fraction with a transit time shorter than 6 months increases throughout the tropical lower stratosphere and extends poleward in the layer between about 400 and 500 K. These changes in young air mass fraction are consistent with a strengthened shallow branch. In contrast, below about 400 K, the poleward transport of young tropical air weakens, and a negative young air anomaly even occurs during El Niño, consistent with the weakening transition branch and isolated mid-latitudinal regions. Hence, El Niño clearly strengthens the shallow branch of the BDC (420–500 K) and weakens the transition branch in both reanalyses, with a hemispheric asymmetry. The ENSO-induced variations in the air mass fraction with a transit time longer than 24 months consistently show a significant decrease in the tropics and a significant increase in the extratropics in both reanalyses during El Niño (Fig. 8c, d). Differences between ERA-I and JRA-55 reanalyses are larger in the old air mass fractions, especially in the extratropics above 400 K, where JRA-55 exhibits larger positive anomalies in older air mass fractions than ERA-I. The signal of the old air mass fraction with a transit time longer than 24 months from JRA-55 spreads throughout the lower stratosphere except in the tropics. Despite the differences in the distribution of the old air mass fraction between ERA-I and JRA-55 reanalyses, the decrease in old air in the tropics and the increase in old air in the extratropics is consistent between the two reanalyses. Note that the ENSO-induced changes are less evident above about 600 K (not shown), indicating that the ENSO impact on the BDC is largely confined to the region below and hence to the transition and shallow branches.

5 Discussion

In a recent study, showed from an idealized model that zonally symmetric SST perturbations drive the deep branch of the stratospheric BDC, whereas zonally localized SST perturbations drive the shallow circulation branch. Here, we find no clear evidence of an El Niño effect on the deep branch of the BDC above about 600 K. Nevertheless, our results are consistent with the findings of , who suggested that a zonally symmetric anomalous SST pattern like during El Niño strengthens the shallow branch of the BDC and suppresses the isentropic mixing induced by a stronger subtropical jet. Furthermore, we found evidence that El Niño alters the two sub-branches of the BDC, i.e. strengthens the shallow branch between about 420 and 500 K and weakens the transition branch between about 370 and 420 K. The strengthening of the deep branch related to El Niño is less evident in the reanalyses examined here.

Figure 9Zonal mean distribution of the ENSO impact on monthly mean temperature (K), zonal wind (m s−1), and EP flux and its divergence (m s−2) derived from (a–c) ERA-I and (d–f) JRA-55 reanalyses. The amplitude of the temperature, zonal wind, and EP-flux variations (term b2×SD(MEI)) attributed to the ENSO events is calculated by projecting the regression fits onto the ENSO basis functions for the 1979–2013 period. Black dashed horizontal line indicates the climatological tropopause from ERA-I and JRA-55 reanalyses. Zonal mean climatologies are overplotted as dashed grey lines. The thick black line in Fig. 8c, f indicates the zero line zonal mean wind. The arrows indicate the EP-flux vectors.

Insight into the underlying dynamical mechanism causing the changes in the transition and shallow branches of the BDC is derived from the temperature, zonal mean wind, Eliassen–Palm flux (EP flux), and EP-flux divergence variations related to ENSO (Fig. 9). Generally both reanalyses agree well in ENSO-induced variations in temperature, zonal mean wind, and EP-flux divergence anomalies. In the tropics (30 S–30 N), El Niño clearly warms the upper troposphere and cools the lower stratosphere in both reanalyses, consistent with previous studies (Calvo et al.2010; Randel et al.2009; Simpson et al.2011). Large tropical temperature changes remain confined below about 500 K. In the extratropics, El Niño generally warms the whole lower stratosphere, except below about 400 K near the subtropical jets, where negative temperature anomalies occur (Fig. 9a, d). The cooling of the tropical stratosphere and warming of the extratropical lower stratosphere are consistent with the increased tropical upwelling and extratropical downwelling during El Niño. In addition, the negative temperature anomalies in the mid latitudes are consistent with a weakening transition branch. The strong differences in the temperature changes between the upper tropical troposphere and the mid latitudes (i.e. a strong tropical–mid-latitudinal temperature gradient) cause a strengthening of the subtropical and polar zonal jets on their equatorward flanks, resulting in an equatorward and upward shift of the subtropical jet (∼10 and ∼10K) (Fig. 9b, e), consistent with the results of . According to , this equatorward shift of the mid-latitude jet related to El Niño results in an enhanced source of waves with higher phase speeds in the mid latitudes and changed propagation characteristics into the stratosphere. Recently, also attributed the ENSO-related jet variability to wave breaking frequency rather than to the typical ENSO teleconnection patterns. The temperature and zonal mean wind variations induced by El Niño shown in Fig. 9 agree with prior model and observational studies (Abalos et al.2017; Lu et al.2008; Simpson et al.2011; Zhou et al.2018) and with the idealized model results from . This ENSO-induced variability in temperatures and zonal wind can be understood as a direct response to the zonal extent of the SST perturbations.

The changes in EP-flux divergence related to El Niño show positive anomalies at lower levels close to the tropopause and negative anomalies in the mid-latitude lower stratosphere above about 420 K (Fig. 9c, f). The positive anomalies suggest decreased wave breaking at lower levels in the lower stratosphere during El Niño , consistent with the weakening of the transition branch. In contrast, the negative anomalies above indicate that more waves break at higher levels in the extratropical lower stratosphere, depositing their momentum flux in these regions and therefore accelerating the shallow branch (Fig. 9c, f). Hence, the wave drag changes shown in Fig. 9c, f are qualitatively consistent with a weakening of the transition branch of the BDC and a strengthening of the shallow branch during El Niño. These wave drag changes are also consistent with the findings of , who concluded that the magnitudes of the stratospheric zonal mean responses are larger in the case of extreme El Niño events, as the strong upward propagation of planetary-scale waves induces a weaker Northern Hemisphere polar vortex by breaking at high latitudes.

Gravity waves have been shown to play an important role in driving ENSO-related variations in the lower stratospheric circulation, particularly in the subtropics . According to , zonal gravity wave momentum fluxes at the tropopause were 11 % smaller during El Niño than during La Niña because of a shift in the precipitation to the central Pacific, where upper tropospheric zonal winds are less favourable for vertical wave propagation. According to , zonal mean variation of wave forcings in the stratosphere results from the phase of the QBO and the changes in wave sources, i.e. the vertical shear of zonal mean winds associated with the Walker circulation. Hence, close agreement between the ENSO variations in the wave drag and the residual circulation variations is not necessarily expected, due to the strong effect of gravity waves.

To quantify the contribution of wave drag to the changes in the transition and shallow branches of the BDC induced by El Niño, the zonal mean wave drag of the explicitly resolved waves (both global-scale and gravity waves) is calculated from the divergence of the EP flux using ERA-I. The estimate for the planetary wave drag is then obtained by integrating the EP-flux divergence over zonal wave numbers 1–20. According to , the missing wave drag in ERA-I can be assumed to be the part of the contribution of gravity wave drag in the zonal mean momentum budget that is not explicitly resolved by the model grid, and its relative variations should still contain valuable information. The total gravity wave drag is estimated as the sum of the missing drag and the model-resolved waves integrated over zonal wave numbers 21–180. Fore more details about the calculations and inter-comparisons of the ERA-I wave drag with those derived from satellite observations, see .

Figure 10Zonal mean distribution of the ENSO impact on monthly mean net resolved wave drag (a), planetary wave drag (PW) (d), and gravity wave drag (c) derived from ERA-I reanalysis. The amplitude variations (term b2×SD(MEI)) attributed to the ENSO events is calculated by projecting the regression fits onto the ENSO basis functions for the 1979–2013 period. Black dashed horizontal line indicates the climatological tropopause from ERA-I. Zonal mean climatologies are overplotted as dashed grey lines. The thick grey line indicates the zero line zonal mean wind.

Figure 10a–c show the zonal mean distribution of the ENSO impact on monthly mean net wave forcings (PWD + GWD  du dt) (a), planetary wave drag (PWD) (b), and gravity wave drag (GWD) (c). The net wave forcings (Fig. 10a) explain the changes in the branches and the hemispheric asymmetry to a remarkable degree. Clearly, the weakening of the transition branch is due to an upward shift in the wave dissipation height up to 425 K, while the strengthening of the shallow branch results from wave breaking above 425 K. The hemispheric asymmetry is a consequence of the asymmetry in both wave distributions (global-scale and gravity), with a larger contribution in the Northern Hemisphere than the Southern Hemisphere. Most of the ENSO-induced variations in wave forcing are contained in the zonal wavenumbers up to 20 (global-scale waves) and are focused around the tropopause. In the Northern Hemisphere, there is a positive pattern of planetary wave changes above the tropopause and a negative pattern below the tropopause over a wide latitude range in the extratropics (Fig. 10b), consistent with results from the WACCM model (Calvo et al.2010). This pattern of changes indicates an altitude shift in the dissipation height of the global-scale waves. In the Southern Hemisphere, the pattern of planetary wave changes is somewhat different and indicates a general shift towards positive values. For the gravity wave response to El Niño, Fig. 10c shows a positive response in the subtropics around 380 K, i.e. a reduction in wave drag, which is however weaker than the planetary wave response. Interestingly, there is a negative response at higher altitudes in the Northern Hemisphere subtropics between 425 and 550 K, i.e. an increase in wave drag, that is even stronger than the response for the zonal wavenumbers up to 20 (Fig. 10b). In summary, the altitude shift in the dissipation height of the large-scale and gravity waves clearly causes the slowdown of the transition branch, while the gravity wave breaking in the tropics–subtropics combined with planetary wave breaking at high latitudes drive the acceleration of the shallow branch. Gravity wave breaking in the subtropics close to the edge of the upwelling region contributes the most to the strengthening of the tropical upwelling. Driven by the wave breaking, the mixing efficiency between tropics and extratropics will be different in the Northern Hemisphere and Southern Hemisphere, leading to the observed hemispheric asymmetry. In addition to the lack of tropospheric O3 chemistry and the O3 lower boundary condition set to zero in CLaMS, uncertainties in the upwelling strength also contribute to the factor of 2 difference observed in the O3 anomalies (Figs. 13).

Future projections of climate models predict a shift of the ENSO basic state toward more frequent El Niño conditions in a warming climate due to an increase in anthropogenic greenhouse gases . As changes in UTLS trace gases, including O3 and H2O , directly impact the global radiative forcing of climate , it is crucial to understand such future changes in trace gases induced by a shift of the ENSO basic state toward more frequent El Niño-like conditions. Despite the uncertainty in the magnitude of the future El Niño events, we speculate that the projected change in the El Niño occurrence frequency will cause structural changes similar to the current O3, RCTT and $\stackrel{\mathrm{˙}}{\mathit{\theta }}$ anomalies (Figs. 3, 4 and 5). In a future climate characterized by a shift of the basic state toward more frequent El Niño conditions, the negative O3 anomalies in the tropics and positive O3 anomalies in the mid latitudes will strengthen (by at least 15 %), enhancing stratosphere-to-troposphere of ozone mass flux and stronger ozone radiative feedback .

6 Summary and conclusions

Based on an established multiple regression method applied to MLS observations and CLaMS simulations driven by ERA-I and JRA-55 reanalyses, we found that ENSO induces structural changes in the BDC in the lower stratosphere. These structural changes in the BDC lead to substantial changes in the tropical and mid-latitudinal lower stratospheric O3 anomalies of about 15 % for MLS observations with a hemispheric asymmetry (i.e. stronger O3 changes in the Northern Hemisphere than in the Southern Hemisphere). This circulation asymmetry results from the asymmetry in the wave breaking response to ENSO.

The regression analysis of different metrics of the circulation strength related to ENSO, including mean AoA, $\stackrel{\mathrm{‾}}{{w}^{\ast }}$, RCTT, ψ, and age spectra, shows structural changes in the lower stratospheric BDC branches, consistent with observed O3 anomalies. The ENSO influence on the BDC turns out to be mainly evident for the transition and shallow circulation branches . During El Niño, the transition branch (370–420 K) weakens, while the shallow branch (420–500 K) strengthens. These structural changes in the transition and shallow branches are as large as ±8 % and are tightly linked to the dynamical response of the atmosphere to ENSO. During El Niño, the strengthened tropical–mid-latitudinal temperature gradient induces a strengthening of the subtropical zonal jets on their equatorward flanks, resulting in an equatorward and upward shift of the subtropical jet. This equatorward shift of the mid-latitude jet induced by El Niño results in enhanced wave propagation towards the extratropical lower stratosphere and breaking therein, consistent with the structural changes in the BDC. The decomposition of the wave drag into planetary and gravity wave drags led to a quantification of the contributions of these two groups to the weakening transition and strengthening shallow branches. The upward shift in the dissipation height of the large-scale and gravity waves drives the slowdown of the transition branch, while enhanced gravity wave breaking in the tropics–subtropics (above about 425 K) mainly drives the acceleration of the shallow branch combined with a contribution from planetary wave breaking at high latitudes. The contribution of gravity waves mainly predominates in the strengthening of the shallow branch. During La Niña, opposite change occurs (not shown).

These structural circulation changes related to ENSO affect the distributions of radiatively active trace gases in the UTLS, including O3, which, in turn, crucially impact the global radiation budget . Hence, the ENSO influence on the structure of the BDC in the UTLS opens a pathway for a stratospheric impact on future climate. It is thus necessary, that climate models represent these processes well to achieve reliable climate projections. Our results suggest that in the context of a changing future climate, where increasing El Niño-like conditions and decreasing lower stratospheric QBO amplitude are expected, the ENSO effect will be increasingly important for controlling the distributions of radiatively active greenhouse gases in the UTLS.

Data availability
Data availability.

The Aura Microwave Limb Sounder product (http://disc.sci.gsfc.nasa.gov/Aura/data-holdings/MLS/index.shtml, last access: 20 November 2018, Livesey et al., 2017; Santee et al., 2017) and ERA-Interim reanalysis data (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-interim, last access: 20 November 2018, Dee et al., 2011) are available. The O3, AoA, $\stackrel{\mathrm{‾}}{{w}^{\ast }}$, RCTT and age spectrum data set can be requested from the corresponding author Felix Ploeger (f.ploeger@fz-juelich.de).

Author contributions
Author contributions.

All co-authors made substantial contributions to the analysis, interpretation of the data as well as contributing to provide the analysed data and drafting the article.

Competing interests
Competing interests.

The authors declare that they have no conflict of interest.

Special issue statement
Special issue statement.

Acknowledgements
Acknowledgements.

We particularly thank the NASA Jet Propulsion Laboratory, the European Centre for Medium-Range Weather Forecasts and the Japan Meteorological Agency for providing Aura Microwave Limb Sounder product (https://mls.jpl.nasa.gov/, last access: 9 January 2019), the ERA-Interim and JRA-55 reanalyses data. Work at the Jet Propulsion Laboratory, California Institute of Technology, was done under contract with the National Aeronautics and Space Administration. This work was funded by the Helmholtz Association under grant number VH-NG-1128 (Helmholtz-Hochschul-Nachwuchsforschergruppe), enabling a research stay at the Institute of Energy and Climate Research, Stratosphere (IEK-7), Forschungszentrum in Jülich during which this work was carried out.

The article processing charges for this open-access
publication were covered by a Research
Centre of the Helmholtz Association.

Edited by: Gabriele Stiller
Reviewed by: two anonymous referees

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