The lower stratosphere (10–25 km) is a key region in a changing climate. Transport, mixing and chemistry in this region regulate the amount of key greenhouse gases, such as water vapor and ozone, which radiatively impact temperatures both locally e.g., and globally e.g.,. Ozone is mainly produced in the stratosphere (10–50 km) and is directly regulated in the tropical lower stratosphere by the upwelling strength of the stratospheric circulation . Conversely, water vapor mainly originates from the troposphere and its stratospheric concentration is controlled by the tropical cold point tropopause temperatures and production from methane oxidation . The amount of stratospheric water vapor is thereby modulated by the coldest temperatures experienced by air parcels ascending through the tropical tropopause layer (TTL) e.g., between 14 and 19 km;. The dehydration in the air parcels crossing through the TTL plays an important role in the control of the lower stratospheric moisture. Stratospheric water vapor is the primary source of stratospheric hydrogen oxide radicals, which drive important gas-phase ozone loss cycles, and it also strongly influences heterogeneous chemistry on cold sulfate aerosol and the formation of polar stratospheric clouds, which promote chlorine activation and polar ozone loss e.g.,.

Water vapor and ozone abundances in the tropical lower stratosphere show multi-timescale variations ranging from daily to decadal e.g., dominated by temperature variations and the tropical upwelling strength, respectively e.g.,. These temperature fluctuations are driven by the varying strength of the stratospheric circulation. Beyond the annual cycle (tape recorder; ), one key driver of the interannual variability in water vapor is the interaction between the El Niño–Southern Oscillation (ENSO) and the Quasi-Biennial Oscillation (QBO) , which, in turn, modulates the stratospheric circulation.

The stratospheric mean meridional circulation is the Brewer–Dobson circulation (BD-circulation; e.g.,), defined as a slow circulation in which air parcels rising in the tropics drift poleward into the stratosphere and are transported downward in the high-latitude regions via its shallow and deep branches . Driven by wave breaking in the stratosphere , the BD-circulation varies on subseasonal to decadal timescales.

The QBO is a major mode of variability in the tropical upwelling of the BD-circulation . The QBO is composed of alternating westerly and easterly zonal wind shears, descending in the tropical stratosphere with a period of ∼28 months. Mostly driven by equatorially trapped waves , the QBO triggers a modulation of vertical and meridional transport in the stratosphere by affecting temperature and heating rates . The easterly shear is associated with enhanced tropical upwelling and anomalously cold tropopause temperatures. As the easterly shear reaches the tropopause, it therefore causes low anomalies of tropical lower stratospheric water vapor and ozone. Conversely, the westerly shear reduces the tropical upward motion, but also enhances the horizontal transport and mixing of stratospheric trace gases and aerosols poleward . The tropical upwelling is anticorrelated with the tropical temperature above the tropopause and its strength modulates stratospheric ozone by advecting tropospheric air generally poor in ozone into the stratosphere . The strength of the tropical upwelling also determines water vapor entry values by modulating TTL temperatures .

Another major mode of climate variability that affects the variability of the BD-circulation is the ENSO. ENSO is a coupled atmosphere–ocean phenomenon covering the equatorial Pacific Ocean with drastic changes in regional sea surface temperatures (SSTs), impacting surface weather and climate e.g.,. ENSO alternates between anomalously warm (El Niño) and cold (La Niña) conditions in the tropical Pacific Ocean at intervals of 2–8 years . In addition to warming the troposphere, El Niño events cool the tropical lower stratosphere and strengthen the tropical upwelling of the BD-circulation, decreasing ozone in the tropical lower stratosphere . From a zonal mean perspective, El Niño events induce tropospheric warming and stratospheric cooling with a node near the tropopause . Stratospheric water vapor, however, is predominantly controlled by cold point temperatures over the tropical western Pacific . El Niño events are associated with warmer cold point temperatures over this region, thereby causing increased lower stratospheric water vapor. In addition, based on chemistry climate simulations, these regional variations in temperatures and water vapor have been shown to exhibit a nonlinear response to ENSO in the Western Indo-Pacific . In contrast, La Niña events induce an opposite effect e.g.,.

Climate models predict that increasing greenhouse gas levels will speed up the mean tropical upwelling of the BD-circulation in the future . A previous study finds a long-term decrease in the QBO amplitude in the lowermost stratosphere associated with this strengthening tropical upwelling , consistent with projections of global climate models . Future projections of climate models also predict a shift of the basic state toward more frequent El Niño conditions in a warming climate . In this context, it is of particular importance to better understand the impact of the interplay between ENSO and QBO on changes in stratospheric water vapor and ozone , which directly impact the global radiative forcing of climate .

Recently, a previously unobserved timing of this interplay between ENSO and QBO occurred. During the boreal winter 2015–2016, a strong El Niño event (among the three strongest El Niño events on record; ) was aligned with a westerly QBO phase. This westerly QBO phase was abruptly disrupted well before completion by an easterly phase in January 2016 . The interplay of both circulation anomalies caused large changes in trace gas transport, the climate implications of which are currently a topic of debate. Based on modern reanalyses and satellite observations, including Aura Microwave Limb Sounder (MLS) water vapor mixing ratios, argued that the most recent El Niño event significantly moistened the lower stratosphere (±0.9 ppmv) during boreal winter 2015–2016 due to particularly warm tropopause temperature anomalies in the tropical western Pacific. Using a simple linear regression of MLS water vapor mixing ratios at 82 hPa with a QBO index at 70 hPa, concluded that the contribution of the QBO disruption was small (up to 0.1 ppmv) at 82 hPa, even though the study mainly focused on ENSO, particularly the role of tropical convective cloud ice in stratospheric hydration. In contrast, mainly focused on QBO disruption impact and attributed changes in the global stratospheric water vapor content from spring to autumn to the QBO disruption during the 2015–2016 winter. However, also acknowledged that the strong El Niño event could have strongly influenced their correlation (composite) analyses based on MLS satellite and radiosonde observations. Disentangling the effects of ENSO and QBO on this anomalous trace gas variability and identifying the dominant driver of recent lower stratospheric water vapor changes during 2015–2016 is a challenging task. A detailed explanation of the reasons for this lower stratospheric water vapor variability in 2015–2016 is still lacking.

Here, we quantify the impact of the interaction between the most recent El Niño event and the QBO disruption on lower stratospheric ozone and water vapor from spaceborne measurements during the 2015–2016 period. We describe the satellite observational data record and multiple regressions in Sect. . Section  describes the anomalous stratospheric circulation in boreal winter of 2015–2016 and Sect.  shows evidence for the impact of the El Niño event and QBO disruption on stratospheric ozone and water vapor. Finally, we discuss our results in the context of the puzzling water vapor response to the interaction of these two phenomena.

The data analyzed here are monthly mean ozone (O3) and water vapor (H2O) mixing ratios in the lower stratosphere from the Aura Microwave Limb Sounder satellite observations 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 and H2O . The version 4.2 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 data used here are not significantly different from the previous version MLS observations at pressures less than 100 hPa, but show less oscillatory behavior and fewer retrieval artifacts induced by cloud contamination in the tropical upper troposphere and lower stratosphere (UTLS). The vertical resolution, precision, systematic uncertainty and lowest recommended vertical range of the relevant v4.2 data are, respectively, 2.5–3 km, ±10–40 %, ±10–25 % and 316 hPa for H2O and 3–3.5 km, ±0.02–0.04 ppmv, ±0.02–0.05 ppmv + ±5–10 % and 261 hPa for O3 for individual profile measurements with a spatial representativeness of ∼200–300 km along the orbital-track line of sight . The regression results will not be affected by these intrinsic uncertainties since they apply to the H2O and O3 mixing ratios and not the anomalies. In addition, show that MLS zonal monthly mean H2O show very good to excellent agreement with the multi-instrument mean (MIM) in comparison between 13 instruments, throughout most of the atmosphere (including the UTLS) with mean deviations from the MIM between +2.5 % and +5 %, making these random errors irrelevant for the averaged monthly zonal mean H2O anomalies used in this study. Additional detailed information on the quality of O3 and H2O in the upper troposphere–stratosphere in previous versions can be found in dedicated validation papers .

As an illustration of the robustness of the regression results, MLS water vapor is compared in Sect.  to simulated H2O from the Chemical Lagrangian Model of the Stratosphere (CLaMS; ). Lagrangian transport in CLaMS is based on 3-D backward trajectories and a parameterization of small-scale mixing, which relates mixing to deformations in the large-scale flow. The model uses an isentropic vertical coordinate, with vertical transport driven by the total diabatic heating rate . The model simulations considered for this paper are driven by temperatures, horizontal winds and diabatic heating rates from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis . For the wind and temperature fields, CLaMS uses the native ERA-Interim vertical resolution, and therefore has higher vertical resolution than MLS. The mean vertical resolution of air parcels in CLaMS Lagrangian model is about 400 m near the tropopause. Stratospheric water vapor in CLaMS is calculated based on a simplified dehydration scheme, which is based on freezing at 100 % saturation and a parameterized ice particle fallout e.g.,, and additional chemical production in the middle stratosphere due to methane oxidation. For further details about the model set-up used here see . Based on modern reanalysis intercomparisons, show that the ERA-Interim temperatures compare favorably to other reanalyses throughout most of the atmosphere, including the TTL region. The assimilation of the Global Positioning System radio occultation data since December 2006 have reduced the ERA-Interim cold temperature bias compared with radiosondes in the tropopause layer and the lower stratosphere . ERA-Interim tropical tropopause temperatures have also been shown to compare very well against in situ observations over the eastern tropical Pacific . Based on a comparison of ERA-Interim tropopause temperature with in situ balloon observations, found fairly good agreement with a weak positive bias of 0.6 K and a standard deviation of 1.8 K in the TTL. show that even small temperature differences between reanalyses and observations can still induce differences in the associated H2O saturation mixing ratio using a trajectory model driven by ERA-Interim. However, the CLaMS dehydration scheme has been shown to provide lower stratospheric H2O anomalies in good agreement with current satellite observations, including the MLS product, giving good confidence in the CLaMS H2O reconstruction from the large-scale perspective e.g.,. In addition, biases, which do not have ENSO or QBO signals, affect the absolute H2O values but not the anomaly time series .

To disentangle the ENSO and QBO impact on these stratospheric trace gases from the other sources of natural variability, the 2005–2016 monthly zonal mean O3 and H2O mixing ratios from MLS observations are analyzed as a function of latitude (ϕ) and altitude (z) using a multiple regression model. This regression method is an established method and appropriate to disentangle the relative influences of the considered climate indices on stratospheric trace gas variability, as it includes time lag coefficients for both QBO and ENSO. For more details about the method and its further applications see . The regression method decomposes the temporal evolution of the monthly zonal mean trace gas mixing ratio, χ, in terms of a long-term linear trend, seasonal cycle, QBO, ENSO, aerosol optical depth (AOD; ) and a residual. The model yields for a given trace gas, χ (herein O3 and H2O) are χ(t,ϕ,z)=a(ϕ,z)⋅t+C(t,ϕ,z)+∑k=13bk(ϕ,z)⋅Pk(t-τk(ϕ,z))+ϵ(t,ϕ,z), where Pk represents the predictors or proxies. 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 AOD from satellite data . The coefficients are a linear trend a, the annual cycle C(t,ϕ,z), 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 ϵ(t,ϕ,z) in the least squares sense. Because of the presence of lags in the QBO, ENSO and AOD terms in Eq. (), 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 selected from a range of possible 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 .

Almost simultaneously with the exceptionally strong El Niño peaking in boreal winter of 2015–2016 , the fairly regular QBO cycle was disrupted by an unexpected shift from westerly (positive QBOi) to easterly (negative QBOi) winds. In January 2016, an easterly phase developed in the center of the westerly phase, breaking the regular cycle of easterly–westerly phase . The QBO disruption was attributed to planetary Rossby waves propagating from the Northern Hemisphere to the Southern Hemisphere in the winter stratosphere , potentially triggered by the strong El Niño event . Both the most recent El Niño event and the QBO disruption are expected to impact the tropical upwelling, via wave–mean-flow interaction and control of the cold point temperatures . Therefore, these two phenomena affect the transport and distribution of stratospheric trace gases most effectively when they peak in boreal winter 2015–2016 and mid-April, respectively .

Figure a, b show the interannual variability in the deseasonalized O3 (a) and H2O (b) in the tropical lower stratosphere as a percentage change relative to the monthly mean mixing ratio during the 2005–2016 period. Particularly, during the 2015–2016 period, the deseasonalized O3 shows negative anomalies in the lower stratosphere (380–550 K) as expected 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). In contrast, the H2O variability (tape recorder) is more challenging to interpret because of its regulation by the tropical cold point tropopause temperatures. The complexity in H2O variability lies in its dependency on ENSO, on the QBO phases , seasons (early or late in the winter) and location (central or eastern Pacific, where the ENSO maximum occurs; ). Therefore, to elucidate the ENSO and QBO impact on the stratospheric O3 and H2O anomalies, the multiple regression is performed both without and with explicitly including ENSO and QBO signals to isolate the impact of the ENSO and QBO on these trace gases, respectively. The difference between the residual (ϵ in Eq. ) with and without explicit inclusion of the ENSO and QBO signals gives the ENSO- and QBO-induced impact on stratospheric O3 and H2O anomalies. This approach of differencing the residuals is similar to direct calculations, projecting the regression fits onto the ENSO and QBO basis functions, i.e., the ENSO and QBO predictor time series (see supplement Figs. 2 and 4 in ). In addition, this differencing approach avoids the need to reconstruct the time series after the regression analysis.

Two previous studies (i.e., ) focussed on ENSO and QBO, respectively, and made contradictory statements on the H2O anomalies in 2015–2016. argued that the most recent El Niño event significantly moistened the lower stratosphere due to ice lofting, with the QBO having only a small contribution. In contrast, attributed the lower stratospheric H2O changes from spring to autumn to the 2015–2016 QBO disruption. Our analysis shows that the QBO disruption significantly decreased global lower stratospheric H2O from early spring to late autumn and reversed the lower stratosphere moistening triggered by the alignment of the warm ENSO event with westerly QBO in early boreal winter. These presented regression results are significant with respect to the measurement uncertainties.

An interesting open question concerns what would have happened to the lower stratospheric H2O anomalies if there had been no QBO disruption? The clearest picture emerges from the latitude–time series of H2O anomalies in Fig. , on which we concentrate our discussion in the following. Figure  shows the deseasonalized time series (a) together with the impact of the QBO (b) and ENSO (c) on H2O averaged in the lower stratosphere between 380 and 425 K. Remarkably, the variability in H2O anomalies shown in Fig. a is largely explained by the interplay between the ENSO- and QBO-induced variability. In early boreal winter 2015–2016, Fig. a shows that the lower stratosphere was strongly moistened by both the strong El Niño event (Fig. b) and the westerly QBO phase (Fig. c). Considered as one of the three strongest occurring since 1950 , the most recent El Niño event stands out in the decadal record of ENSO impact on H2O in the lower stratosphere (see black vertical dashed line in Fig. b), consistent with the findings of . The positive H2O anomalies induced by this most recent El Niño slowly propagate with time into the extratropical lower stratosphere of both hemispheres due to the shallow branch of BD-circulation and eddy mixing processes. During the boreal winter 2015–2016 (DJFM, December–March), the westerly QBO phase contribution to H2O anomalies adds to the El Niño-induced H2O variability, resulting in particularly large H2O anomalies, consistent with the findings of .

However, the QBO shift from westerly to easterly wind shear at 40 hPa (∼550 K) suddenly reverses the extreme lower stratospheric moistening by significantly decreasing H2O from boreal spring 2016 to boreal winter 2016–2017 (Fig. c). The QBO disruption contributes the most to the lower stratospheric water budget between 380 and 425 K, with strong negative H2O anomalies of about 20 % from boreal spring to boreal winter 2016–2017 compared to the El Niño, which only induces about 5–10 % increase on average in this layer during the same period. Therefore, if there had been no QBO disruption during the boreal winter of 2015–2016 with an ongoing westerly QBO phase, the H2O anomalies would have likely increased to more than 25 %, leading to changes larger than previously observed in the lower stratospheric water budget.

The control of the interannual variability in lower stratospheric H2O anomalies critically depends on the alignment of the ENSO events and QBO phases. Alignment of a westerly QBO phase with El Niño leads to strongly positive H2O anomalies as illustrated for the boreal winters of 2006–2007 and 2015–2016. Alignment of an easterly QBO phase with La Niña induces strongly negative H2O anomalies, for example, as seen during the boreal winter of 2005–2006 and 2007–2008. This result is consistent with previous studies based on observations and climate models . According to the findings of , the greatest dehydration of air entering the stratosphere from the troposphere occurs during the winter under La Niña and easterly QBO phase. suggested that a large decline in H2O anomalies can be found after strong El Niño/La Niña events combined with a transition from the westerly QBO phase during La Niña to the easterly QBO phase. In conclusion, the alignment of the westerly QBO phases with El Niño events (e.g., 2006–2007, early 2015–2016) and easterly QBO with La Niña events (e.g., 2005–2006, 2007–2008) are the key factors in creating extreme lower stratospheric water vapor anomalies via a control of cold point tropopause temperatures. Consistent with this picture, the variance in the deseasonalized H2O time series is largely captured by this interplay of the ENSO events and QBO phases as shown in Fig. . The variance in the QBO- and ENSO-induced changes in H2O anomalies shows that the QBO contributes the largest part to the H2O variability (Fig. ).

In addition, when the ENSO signal is weak or moderate (e.g., 2012–2015, early winter 2016–2017), the lower stratospheric H2O anomalies are dominated by the QBO phases. This QBO control of the lower stratospheric H2O budget is also illustrated during the boreal winter of 2010–2011. Despite the ongoing La Niña event, which dehydrated the lower stratosphere, the impact of the westerly QBO phase on H2O anomalies dominated, leading to positive anomalies approaching 25 %. According to , the westerly wind shear persisted slightly longer than usual during the 2008–2013 period (QBOi in Fig. c). Therefore, this persistence of the westerly QBO can explain the large H2O anomalies during this period. Note that the 2011 winter had an extreme anomalously strong vortex, i.e., strongly reduced BD-circulation, which also might have contributed to these large positive anomalies . An additional example of this QBO control on the lower stratospheric H2O anomalies is the drop in H2O during the 2012–2013 boreal winter . These extremely negative H2O anomalies are associated with the rapid cooling of the tropical cold point tropopause temperatures induced by easterly wind shear and a major sudden stratospheric warming . This cooling of the tropical cold point tropopause temperatures is induced by a downward shift of the zero wind line (∼30 hPa) during easterly wind shear, inducing more subtropical wave dissipation at low latitudes, therefore efficiently speeding up the shallow branch of the BD-circulation . Therefore, based on these recent findings , we can explain the sudden drop in the lower stratospheric moistening from boreal spring 2016 to boreal winter 2016–2017 despite the strong El Niño as a consequence of the rapid cooling of the tropical cold point tropopause temperatures induced by the QBO disruption (easterly; ) and the major stratospheric final warming in 2016 , which strengthened the shallow branch of the BD-circulation.

In order to gain confidence in the robustness of the above discussed results and to illustrate the ability of the CLaMS model to capture the unusual timing of QBO shift and El Niño in 2015–2016, we have also estimated the impact of their interplay on lower stratospheric H2O anomalies from the CLaMS simulations using the same regression method. Consistently, the CLaMS H2O anomalies show characteristics in good agreement with the zonally averaged H2O anomalies from MLS (Fig. a). CLaMS simulations and MLS observations agree remarkably well throughout the entire record and especially the El Niño and QBO signals in 2015–2016 (Fig. b, c). In particular, also in the model the El Niño signal is much weaker than the impact of the QBO disruption on lower stratospheric H2O. The influence of the QBO disruption turns out to be 4 times stronger than the El Niño impact in 2015–2016. Consequently, the reanalysis meteorology (here ERA-Interim) in combination with a sophisticated chemistry transport model (here CLaMS) realistically represents the effects of the interplay of QBO and ENSO on lower stratospheric H2O.

Current climate models predict a shift of the basic state toward more frequent El Niño conditions as well as a weakening QBO amplitude in the lower stratosphere for the future climate due to anthropogenic climate change . Hence, the interplay of ENSO events and QBO phases affecting the lower stratospheric water vapor and ozone is likely to change, causing changes in radiative forcing of surface climate. An improved understanding of the interplay between ENSO events and QBO phases will help to reduce related uncertainties in climate projections as well as in past and future lower stratospheric H2O trends . In addition, subtle differences in the alignment of ENSO and QBO could contribute to the large spread in basic state cold point tropopause temperature between different climate models and induced ozone radiative feedback .

Based on an established multiple regression method applied to Aura MLS observations and CLaMS model simulations, we found that both the most recent El Niño and the QBO disruption in 2015–2016 induced substantial changes in the lower stratospheric O3 and H2O. The El Niño-induced substantial positive anomalies of up to 10 % in H2O and negative anomalies of about 15 % in O3. Our results also demonstrate that if there had been no QBO disruption, the lower stratosphere would likely have been substantially moistened by the alignment of the El Niño with the westerly QBO, with deseasonalized anomalies exceeding 25 %.

In boreal winter of 2015–2016 (September 2015–March 2016), the alignment of the strong El Niño with the westerly QBO strongly moistened the lower stratosphere (positive anomalies of more than 20 %). However, the sudden shift in the QBO from westerly to easterly wind shear reversed the moistening of the lower stratosphere between 380 and 450 K, leading to large negative H2O anomalies of as much as 20 % by autumn 2016 (4 times bigger than the El Niño influence in early 2016). The QBO also led to positive H2O anomalies over 460–600 K from April to December 2016. The El Niño-induced H2O anomalies are opposite to the easterly QBO-induced H2O changes. This opposite response arises because the QBO affects the atmosphere in a zonally symmetric manner, whereas ENSO predominantly creates zonally asymmetric signatures (source region of the dehydration ), and therefore the two mechanisms give rise to different patterns of variability in the tropical cold point tropopause temperatures. Interestingly, although this QBO shift reversed the moistening of the lower stratosphere, the O3 mixing ratios continued to decrease in the tropics, indicating an additional acceleration of the BD-circulation.

The control of stratospheric H2O anomalies strongly depends on the interaction of ENSO events and QBO phases. The alignment of the westerly QBO phase with El Niño and the easterly QBO phase with La Niña are the key factors regulating the stratospheric water budget. The interaction of El Niño and the westerly QBO phase leads to large positive lower stratospheric H2O anomalies, while the interplay between La Niña and easterly QBO phase leads to negative anomalies. During weak and moderate ENSO events, the H2O anomalies are controlled by the QBO phase. The effects of QBO and ENSO on lower stratospheric H2O in the MLS observations are consistent with CLaMS model results.

Our results suggest that the interplay of ENSO events and QBO phases will be crucial for the control of the lower stratospheric water vapor and ozone budget under changing future climate, when increasing El Niño-like conditions and a decreasing lower stratospheric QBO amplitude are expected. The interplay will change, with ENSO likely controlling the lower stratospheric trace gas variability more strongly in the future. It is clear that ENSO impacts both tropopause height and tropopause temperature. Future analysis is needed using sensitivity runs from global circulation models and coupled chemistry-climate models to diagnose and separate the impact of future changes in tropopause height and tropopause temperature on stratospheric water.