While the impact of the El Niño–Southern Oscillation
(ENSO) on the stratospheric circulation has been long recognized, its
effects on stratospheric ozone have been less investigated. In particular,
the impact on ozone of different ENSO flavors, eastern Pacific (EP) El
Niño and central Pacific (CP) El Niño, and the driving
mechanisms for the ozone variations have not been investigated to date. This
study aims to explore these open questions by examining the anomalies in
advective transport, mixing and chemistry associated with different El
Niño flavors (EP and CP) and La Niña in the Northern Hemisphere in
boreal winter. For this purpose, we use four 60-year ensemble members of the
Whole Atmospheric Community Climate Model version 4. The results show a
significant ENSO signal on the total column ozone (TCO) during EP El Niño
and La Niña events. During EP El Niño events, TCO is significantly
reduced in the tropics and enhanced at middle and high latitudes in boreal
winter. The opposite response has been found during La Niña.
Interestingly, CP El Niño has no significant impact on extratropical TCO,
while its signal in the tropics is weaker than for EP El Niño events.
The analysis of mechanisms reveals that advection through changes in
tropical upwelling is the main driver for ozone variations in the lower
tropical stratosphere, with a contribution of chemical processes above 30 hPa. At middle and high latitudes, stratospheric ozone variations related to
ENSO result from combined changes in advection by residual circulation
downwelling and changes in horizontal mixing linked to Rossby wave breaking
and polar vortex anomalies. The impact of CP El Niño on the shallow
branch of the residual circulation is small, and no significant impact is
found on the deep branch.
Introduction
The El Niño–Southern Oscillation (ENSO) is one of the main sources of
interannual variability in the global climate. Although this phenomenon
takes place in the tropical Pacific Ocean, its impacts reach the
stratosphere (e.g., García-Herrera
et al., 2006; Manzini et al., 2006; Calvo et al., 2017; see Domeisen et al., 2019, for a review). During boreal winter, the El Niño (the warm ENSO
phase) signal can propagate poleward from the tropical Pacific by means of
atmospheric Rossby wave trains. In the Northern Hemisphere (NH), this is
related to a deeper Aleutian low and a strengthening of the Pacific–North
American (PNA) pattern. As a consequence, the propagation of Rossby waves
into the stratosphere is enhanced through the intensification of stationary
wave number 1 (Manzini et al., 2006).
Increased upward propagation of planetary waves during El Niño into the
stratosphere results in a weakened polar vortex and a strengthening of the
residual circulation of the Brewer–Dobson circulation (BDC), which leads to
tropical stratospheric cooling and stratospheric polar-cap warming (e.g., Calvo et al.,
2010; Mezzina et al., 2021). In contrast, during La Niña, a weakening of
the Aleutian low and destructive linear interference with the climatological
wave pattern occur, resulting in a stronger and colder NH polar vortex and a
weakening of the residual circulation (Iza et
al., 2016).
Although it has been widely known for many years that ENSO events are different
from each other in the location and intensity of sea surface temperatures
(SSTs), in recent years the importance of distinguishing between two flavors
of El Niño has arisen. These two types of El Niño correspond to the
events in the extrema of a wide range of longitudes where SST anomalies
peak during different El Niño events, as shown in Capotondi et al. (2015), and will be referred here as
eastern Pacific (EP) El Niño and central Pacific (CP) El Niño. While
the SST anomalies peak in the eastern equatorial Pacific for EP El Niño
(also referred as canonical El Niño), CP El Niño (also known as El
Niño Modoki or Dateline El Niño) is characterized by SST anomalies
that peak in the central equatorial Pacific (Larkin
and Harrison, 2005; Ashok et al., 2007; Kao and Yu, 2009). The differences
between these two types of events appear not only in the SSTs but also in
the thermocline depth, in the development and temporal evolution of the
event itself, and in their remote impacts not only in the troposphere but
also in the stratosphere (see Capotondi et al., 2020, and references therein).
The stratospheric signal of EP El Niño is very robust, and many studies
have considered it as the canonical response to the warm phase of ENSO. In
contrast, fewer studies have examined the NH stratospheric response to CP El
Niño, and their results were many times contradictory. On one hand, some
studies have found a similar response to CP El Niño than to EP El
Niño in the NH polar stratosphere, that is, a weaker and warmer polar
vortex (e.g., Hegyi et al., 2014, who used idealized WACCM4 – Whole Atmosphere Community
Climate Model – simulations, or Hurwitz et al. (2014), who studied
the seasonal-mean polar-cap geopotential anomaly at 50 hPa in a set of CMIP5 – Coupled Model Intercomparison Project – models). Other studies have also reported a weaker polar vortex during CP El
Niño, but the response was significantly weaker than for EP El Niño
events (Garfinkel et al., 2013; Weinberger et al., 2019). Finally, a
third group of papers have found a CP El Niño signal opposite to that of
EP El Niño, albeit of a smaller amplitude, in
reanalysis data (Xie et al., 2012), or not significant (Calvo et al., 2017) using a
set of high-top CMIP5 models. Several reasons have been proposed to explain
the contradictory results among these studies. Garfinkel et al. (2013) concluded that the
sign of NH stratospheric response to CP El Niño depends on the index
used to identify CP El Niño events (see Capotondi et
al., 2015, for a list of the main indices used in the literature), the
composite size and the month average analyzed. Note that, since the studies
cited above do not use the same methodology or the same indices to classify
ENSO events into EP or CP El Niño, it is not surprising that differences
appear between their results in response to CP El Niño. Calvo et al. (2017)
highlighted the importance of studying the seasonal evolution of the NH
stratospheric signals for understanding the different EP and CP El Niño
impacts. Other reasons may include interactions between El Niño and the
quasi-biennial oscillation
(QBO; Xie et al., 2012) and
overlapping with the signal from sudden stratospheric warmings (SSWs;
Iza and Calvo, 2015). Overall, further investigation
is still needed to better understand the differences between EP and CP El
Niño signals on the NH stratosphere.
Stratospheric ozone is an important component of the climate system and
plays a key role in the radiative budget and protecting the Earth from the
harmful solar ultraviolet (UV) radiation. In recent years several studies
have reported that polar stratospheric ozone changes and extremes can exert
significant influence on the NH surface climate (Calvo et
al., 2015; Ivy et al., 2017; Stone et al., 2019). Despite its importance,
few studies have addressed the impact of ENSO on stratospheric ozone in
depth. Most of them mainly focused on the anomalously low ozone values in
the tropical lower stratosphere during the ENSO warm phase, typically
associated with anomalously strong tropical upwelling (Pyle
et al., 2005; Marsh and Garcia, 2007; Randel et al., 2009; Calvo et al.,
2010; Oman et al., 2013). However, the impact of ENSO on ozone is not
restricted to the tropical stratosphere. Changes in the BDC due to anomalous
Rossby wave dissipation during ENSO events are linked to ozone anomalies in
NH mid-latitudes and the polar region opposite to those in the tropics (Cagnazzo
et al., 2009; Diallo et al., 2019; Lin and Qian, 2019).
Despite the ENSO signal on stratospheric ozone being clear, there are still
many open questions. First of all, the driving mechanisms for these ozone
anomalies remain unknown. Previous studies assumed that changes in the
residual circulation of the BDC drives the anomalous ozone concentrations
during ENSO events. However, global distribution of ozone is driven not only
by advection due to residual circulation but also by isentropic mixing
following Rossby wave dissipation, as well as by chemical production and
loss (Garcia
and Solomon, 1983; Plumb, 2002; Abalos et al., 2013). In fact, the
importance of mixing on stratospheric tracer transport, and in particular on
the distribution of ozone, has been increasingly recognized (Salby and
Callaghan, 2007; Garny et al., 2014; Dietmüller et al., 2017). Hence,
anomalous ENSO-related ozone concentrations are expected to be generated by
a balance between changes in advection by the residual circulation, changes
in mixing related to wave dissipation, and also changes in chemistry through
the ENSO modulation of stratospheric temperatures and concentration of other
chemical species. A second open question is whether different ENSO flavors
can affect ozone concentrations differently and whether the driving
mechanisms are the same or differ between EP and CP El Niño events.
Indeed, it is expected that if a different response appears during EP and CP
El Niño events in stratospheric temperature, polar vortex or planetary
wave activity, this has an impact on the ozone response and in particular
on advection, mixing and chemistry.
The present study constitutes the first comprehensive analysis of the NH
stratospheric ozone signal and driving mechanisms in response to different
El Niño flavors (EP and CP El Niño) and La Niña in boreal
winter. The analysis of simulations from the Whole Atmosphere Community
Climate Model (WACCM), a chemistry–climate model with a well-resolved
stratosphere, allows us to evaluate the separate contributions of the
advective BDC, the isentropic mixing and the chemical processes to ozone
variations during ENSO events. In the remainder of the paper, the
methodology, model simulations, reanalyses and observational dataset
analyzed are described in Sect. 2. Section 3 analyzes the seasonal-mean
impact of ENSO events on the NH stratosphere and the monthly evolution of
the total column ozone (TCO). The driving mechanisms of the anomalous ozone
concentration are examined in Sect. 4, while Sect. 5 summarizes the main
conclusions of this study.
Data and methods
We use monthly averaged fields from four ensemble members (60 years each, a
total of 240 years) of the Whole Atmosphere Community Climate Model
(WACCM4, Marsh
et al., 2013; Garcia et al., 2017). This WACCM version has a horizontal
resolution of 1.9∘ latitude by 2.5∘
longitude and 66 levels in the vertical with the top at about 140 km. These
simulations, which were carried out for the Chemistry–Climate Model
Initiative (CCMI, Eyring et
al., 2013), were performed with prescribed observed SSTs and external
forcings to match the observations for the period 1955–2014 (CCMI REF-C1
configuration). The QBO was nudged by relaxing the stratospheric tropical
zonal winds towards observations.
In order to eliminate the influence of the QBO, we performed a multiple
linear regression analysis on the simulated time series. Following
Wallace et al. (1993), we use two QBO indices
corresponding to the first two empirical orthogonal functions (EOFs) of the
zonal wind between 5∘ S and 5∘ N over the
layer 10–70 hPa. The results of the multiple regression fit are subtracted
from the original data; then we use the residual series, which contain the
ENSO signal, for our analysis.
ENSO events are identified directly from the observational record, since the
WACCM simulations analyzed here have been run with observed SSTs. EP El
Niño and CP El Niño events are selected as in
Iza and Calvo (2015). El Niño events are
defined using the standardized November–February (NDJF) SSTs anomalies in
the Niño3 (N3; 5∘ N–5∘ S,
150–90∘ W) and Niño4 (N4;
5∘ N–5∘ S, 160∘ E–150∘ W) regions. EP El Niño events are selected when
N3 exceeds 0.5 standard deviations (SD) and N3 minus N4 is larger than 0.1 SD. Analogously, CP El Niño events are selected when N4 exceeds 0.5 SD
and N4 minus N3 is larger than 0.1 SD. We have used N3 and N4 indices among
all the indices available in the literature to characterize EP and CP El
Niño events for easy comparison with previous recent studies. For La
Niña events, we follow the criteria of Iza et al. (2016) for “strong” La
Niña events. Using the standardized NDJF SSTs anomalies in the
Niño3.4 region (N3.4; 5∘ N–5∘ S,
170–120∘ W), strong La Niña events
are identified when N3.4 is less than -1 SD. We have used the N3.4 index
for identified La Niña events since different La Niña flavors have
not been established in the observational record. We use the threshold of -1 SD instead of -0.5 SD to select La Niña winters since Iza et al. (2016) demonstrated that,
using the threshold of -0.5 SD, the La Niña signal is masked by other
sources of variability like SSWs. Table 1 lists the selected ENSO events
used in this work.
Identified EP El Niño, CP El Niño and La Niña
events. Numbers in parentheses indicate the value of the El Niño index used for
selection in each case (N3 for EP, N4 for CP and N3.4 for La Niña).
The ENSO signal is analyzed by compositing monthly-mean anomalies for the
identified ENSO events (Table 1) in boreal extended winter (October to
March). For each ensemble member, anomalies are computed with respect to a
21-year running mean climatology of that member, which allows for removing
possible linear and non-linear trends. This is particularly important in the
case of ozone since ozone-depleting substance (ODS) concentrations are not
uniform throughout the 1955–2014 period. After that, we identified the ENSO
events in each simulation and finally composited all ENSO events in the four
simulations we are analyzing. The statistical significance of the ENSO
signal in the composites is assessed with a Monte Carlo test of 1000 trials
at the 95 % confidence level. To do so, we consider together the
anomalies of all ensemble members and randomly select as many years from the
total of 240 years (60 years for four simulations) as there are cases in the
composite of anomalies (which depends on each type of ENSO). We composite
this random selection and repeat the process 1000 times to create a
composite distribution. The anomaly is considered significant when it is
outside of the central 95 % of the random distribution.
For model validation and comparison purposes, ozone data from two reanalyses
and an observational dataset have been used. The same methodology applied to
WACCM has been followed here to remove the influence of the QBO and obtain
the ENSO signal. The Modern-Era Retrospective analysis for Research and
Applications, Version 2 (MERRA-2, Gelaro et al., 2017) provides data at
a horizontal resolution of 0.5∘ latitude by
0.625∘ longitude and 42 pressure levels with the top at 0.1 hPa. For our study, monthly-mean ozone data on pressure levels covering the
period January 1980–December 2016 have been used. MERRA-2 calculates ozone
concentrations as a fully prognostic variable, subject to assimilation; a
photochemistry scheme; and transport. It assimilates ozone satellite
observations from NOAA's SBUV (Solar Backscatter Ultraviolet Radiometer)
until 2004 and NASA's Aura OMI (Ozone Monitoring Instrument) and Aura MLS
(Microwave Limb Sounder) afterwards. MERRA-2 ozone concentrations generally
show better agreement with observations than other reanalyses, especially in
the middle stratosphere (Davis et
al., 2017).
The Japanese 55-year Reanalysis (JRA-55, Kobayashi et al., 2015) has also been
used. JRA-55 has a horizontal resolution of 2.5∘ latitude by
2.5∘ longitude and 37 pressure levels with the top at 1 hPa.
In JRA-55, ozone observations are not assimilated directly. Before 1979, a
monthly-mean climatology for the 1980–1984 period is used. From 1979
onwards, ozone fields are produced using an offline chemistry–climate model
(MRI-CCM1; Meteorological Research Institute) that assimilates TCO observations from NASA's TOMS (Total Ozone
Mapping Spectrometer) until 2004 and Aura OMI afterwards using a nudging
scheme (Shibata et al., 2005).
In this study, we use JRA-55 ozone for the period January 1980–December 2016.
The Stratospheric Water and Ozone Satellite Homogenized (SWOOSH) database is
a merged zonal-mean monthly-mean dataset which contains observations from the
SAGE II (v7.0; Stratospheric Aerosol and Gas Experiment), SAGE III (v4), HALOE (v19; Halogen Occultation Experiment), UARS MLS (v5; Upper Atmosphere Research Satellite) and EOS Aura MLS
(v4.2; Earth Observing System) instruments (Davis
et al., 2016). The SWOOSH dataset used in this study is version 2.6, with
a horizontal resolution of 2.5∘ latitude and 31 vertical
levels between 1 and 316 hPa covering the period January 1984–December 2016.
We use specifically the “combinedanomfillo3q” product.
Stratospheric impact of ENSO
Before investigating the ozone behavior, we evaluate the ENSO response in
temperature, zonal wind and residual circulation in WACCM4 against results
from previous literature. Figure 1a–c shows the latitude–pressure
November–February (NDJF) anomalies of the zonal-mean temperature and
zonal-mean zonal wind composited for EP El Niño, CP El Niño and La
Niña events (Figs. 1a, b and c, respectively). We have included November
in the extended winter season because we find significant ozone anomalies in
extratropical latitudes already in this month (Fig. S1 in the Supplement). In the tropics,
both EP El Niño and CP El Niño signals are characterized by a
significant warming in the troposphere and a cooling in the stratosphere,
peaking at about -1.4 K between 50 and 70 hPa in EP El Niño and at about
-1.2 K in CP El Niño. Along with these anomalies, a robust strengthening
of the subtropical jets appears in both EP El Niño and CP El Niño
events, stronger during EP El Niño (at about 3 m s-1 versus 2 m s-1 in the NH). The La Niña signal (Fig. 1c) is opposite to that of El
Niño, characterized by a significant cooling in the troposphere, warming
in the stratosphere and a weakening of the subtropical jets.
At mid-latitudes (∼30–60∘ N), EP El Niño and CP El Niño signals in the
lower stratosphere show larger differences than in the tropics. Significant
anomalies are only found during EP El Niño as an anomalous warming. During
La Niña events, the anomalies are opposite to those in EP El Niño,
with a significant cooling in the lower and middle stratosphere. At high
latitudes, the EP El Niño temperature response is characterized by warm
anomalies in the polar stratosphere, only significant in the lowermost
stratosphere, and a significant weakening of the polar vortex that extends
into the troposphere. In contrast, the temperature signal of CP El Niño
events is not significant in the polar stratosphere, with anomalies in the
polar vortex weaker than in the EP El Niño events. During La Niña
events, a robust cooling appears in the middle and upper polar stratosphere
accompanied by a strengthening of the polar vortex. The different location
of the significant zonal-mean polar temperature anomaly between EP El
Niño and La Niña is likely due to the occurrence of the SSWs. When
the temperature response is analyzed only for winters without SSWs, the
stratospheric warming associated with EP El Niño events also extends
into the middle and upper stratosphere (not shown). Overall, the ENSO
response shown here is in good agreement with previous knowledge from
radiosonde studies (Free and Seidel, 2009), reanalysis
data (García-Herrera
et al., 2006; Camp and Tung, 2007; Iza and Calvo, 2015; Iza et al., 2016)
and model simulations (Randel
et al., 2009; Calvo et al., 2010, 2017; Diallo et al., 2019).
In addition to changes in temperature and zonal wind, ENSO also has an impact
on the residual circulation (Fig. 1d–f). During EP El Niño, a
significant strengthening of the shallow and deep branches of the residual
circulation occurs (Fig. 1d) in agreement with results from previous studies
which analyzed the canonical response to ENSO (e.g., García-Herrera
et al., 2006; Calvo et al., 2010). This is consistent with the ENSO signal
in temperature as anomalously cold regions coincide with positive w*
anomalies and vice versa. In contrast, during CP El Niño, only a slight
acceleration occurs in the shallow branch, and no significant changes are
simulated in the deep branch (Fig. 1e), consistent with the lack of a
significant CP El Niño signal in polar stratospheric temperature shown
above.
Latitude–pressure cross sections of the composite of anomalies in the NDJF zonal-mean (a–c) temperature (T, colors) and zonal wind (U, black contours), (d–f) vertical component of the residual circulation w*, and (g–i) the ozone mixing
ratio for (from left to right) EP El Niño, CP El Niño and
La Niña events. Contours in upper panels are drawn every 0.6 m s-1 for
zonal wind and 0.15 K for temperature. Solid (dashed) contours denote
positive (negative) anomalies. The NDJF mean tropopause is indicated by the
thick grey line. Color shading (upper panels) denotes statistically
significant anomalies at the 95 % confidence level for temperature and
black dots (middle and bottom panels); the same is also done for w* and the ozone mixing
ratio. Thick black contours (upper panels) denote statistically significant
anomalies for zonal wind.
Regarding La Niña, the w* anomaly pattern mirrors that during EP El
Niño, with a deceleration of the residual circulation (Fig. 1f) leading
the tropical warming and the extratropical cooling. These results highlight
differences between EP and CP El Niño events on the residual circulation
and reveal that CP El Niño has no impact on the deep branch.
Next, we examine the ENSO anomalies on ozone, shown in Fig. 1g–i. They show
robust changes in the stratospheric ozone mixing ratio in response to ENSO. Both
the EP El Niño (Fig. 1g) and CP El Niño (Fig. 1h) events show a
significant reduction of ozone mixing ratios in the tropics in the lower and
middle stratosphere and an increase at mid-latitudes only in the lower
stratosphere, always stronger during EP El Niño events. At high
latitudes, a significant increase in ozone concentrations appears in the
lower stratosphere only during EP El Niño, in agreement with the lack of
a CP El Niño signal in zonal-mean temperature shown above. The anomalous
ozone pattern during La Niña events (Fig. 1i) is very similar to that of
EP El Niño but with an opposite sign. All these results for the lower
stratosphere are in line with previous studies using model simulations (Randel et al., 2009;
Calvo et al., 2010), observations (Lin and Qian, 2019) and
reanalyses (Diallo et al., 2019).
However, none of them distinguished between EP and CP El Niño, while
Fig. 1g–h clearly demonstrates that the anomalies are overall
larger for EP El Niño than CP El Niño, and in particular for the
polar region, CP El Niño events do not have a statistically significant
effect. Thus, our results highlight the need to distinguish between the two
types of El Niño to explore the impact of ENSO on the stratospheric
composition and specifically on stratospheric ozone concentrations.
Variations in the ozone mixing ratio can potentially affect TCO and therefore
the net UV levels reaching the surface. However, since anomalies in
ozone mixing ratios do not extend over the entire stratosphere and
anomalies of opposite sign appear at different stratospheric levels, it is
unclear from Fig. 1 whether ENSO actually affects TCO throughout the winter.
For this purpose, Fig. 2 shows the latitude–time October–March
evolution of WACCM4 TCO anomalies composited for ENSO events. For
comparison, two reanalyses (JRA-55 and MERRA-2, Fig. 2d–f and g–i,
respectively) and satellite observations (SWOOSH, Fig. 2j–l) are included.
Note that very few events are included in SWOOSH and reanalyses for EP El
Niño, and therefore the comparison in this case should be made with
caution.
In the tropical region (∼ 30∘ S–30∘ N), WACCM shows a significant reduction in TCO during
EP El Niño events and, to a lesser extent, during CP El Niño events,
while an increase in TCO appears during La Niña events. The comparison
of WACCM simulations with reanalyses and observations reveals particularly
good agreement for La Niña events, as the positive anomalies are
significant in both reanalyses and SWOOSH despite the small composite size
(five cases). For EP El Niño events significant negative anomalies in
the tropics are found from December to March in reanalyses, while SWOOSH
does not show any significant anomalies. Note that unfortunately the
composite with SWOOSH data includes only two EP El Niño events, so the
significance in this case needs to be taken with caution. Results for CP El
Niño events are less robust. While the model, reanalyses and observations
show negative anomalies in the tropics, weaker than those for their
corresponding EP El Niño composites, the seasonality and statistical
significance differs across datasets. In particular, only WACCM and MERRA-2
show significant anomalies.
At mid-latitudes (∼30–60∘ N), WACCM shows an
increase in TCO during EP EL Niño events from December to March, the
opposite during La Niña events. These results agree well with reanalyses
and observations in February and March. Interestingly, CP El Niño events
show no significant signal in this region in any of the datasets. As shown
above, the positive anomalies in the ozone mixing ratio (Fig. 1h) that appear in
CP El Niño events in the lower mid-latitude stratosphere are weaker than
in EP El Niño and are also accompanied by anomalies of an opposite sign in
the mid-stratosphere. This dipole structure at mid-latitudes leads to a lack
of significant signal in TCO for CP El Niño at mid-latitudes.
October–March composite evolution of total column ozone (TCO)
anomalies (DU, Dobson unit) as a function of latitude in (a–c) WACCM, (d–f) JRA-55, (g–i) MERRA-2 and (j–l) SWOOSH for (from left to right) EP El Niño, CP El
Niño and La Niña events. Numbers in parentheses indicate the number of
events in each composite. Black dots denote statistically significant
anomalies at the 95 % confidence level.
At high latitudes (∼60–90∘ N), WACCM shows
significant positive TCO anomalies in late winter during EP El Niño
events, while during La Niña events the TCO response is opposite of
that. This is in good agreement with SWOOSH and reanalyses,
although the anomalies do not reach significance in these datasets likely
due to the few cases composited and the large variability of the polar
stratosphere. Differences in early winter in EP El Niño between WACCM
and reanalyses could also come from variability of the polar stratosphere
related to SSWs. The larger occurrence of SSWs in November in WACCM during
EP El Niño favors positive anomalies appearing earlier in the model than
in reanalyses. Results for CP El Niño events are more uncertain in this
region. WACCM shows a reduction in TCO in late winter, which does not appear
in reanalyses or SWOOSH.
Therefore, the high-latitude TCO signal during CP El Niño events seems
to be weaker and more uncertain, and no general conclusions can be drawn in
this region, consistent with the lack of CP El Niño signal in the
seasonal-mean zonal-mean temperature, deep branch of the residual
circulation and ozone mixing ratio.
In summary, the analysis above shows that both EP El Niño and La
Niña have a robust signal on TCO. These results are in line with Cagnazzo et al. (2009),
who found an increase in the polar TCO and a reduction in tropical TCO
associated with satellite observations and a set of chemistry–climate models
but only for the canonical El Niño. Here we have shown that La Niña
also has an impact on TCO and also that the signal of CP El Niño appears
only in the tropics but not at high latitudes. Anomalies observed to be larger in
reanalyses than in WACCM are likely due to the lower number of events
composited in the former. In fact, when individual events are considered,
the magnitude of the anomalies is similar in WACCM, reanalyses and SWOOSH
(not shown). Therefore, the overall good agreement between WACCM and
reanalysis data allows us to use WACCM simulations to investigate the
mechanisms that are controlling the ozone changes during ENSO events in the
next section.
Driving mechanisms of ozone during ENSO
As discussed in the Introduction, the robust ENSO changes in stratospheric
ozone shown in the previous section can be caused by advection due to
residual circulation, isentropic mixing following planetary wave dissipation,
and/or local chemical production and loss. We use WACCM simulations to
evaluate the different terms of the TEM (transformed Eulerian mean) continuity equation for zonal-mean
ozone concentration (Eq. 1). This equation provides the local change in
ozone concentration as a result of transport and chemical processes
(Andrews et al., 1987).
χt‾=-v∗‾χy‾-w∗‾χz‾+ezH∇⋅M+P-L
In Eq. (), overbars denote zonal means and subindices indicate partial
derivatives. The term on the left-hand side represents the local tendency in
ozone concentration, where χ indicates the ozone mixing ratio. On the
right-hand side, the first and second terms represent the advection due to
residual circulation (v*,w*); P-L is the ozone tendency due to chemistry (chemical
production minus loss rate); and ezH∇⋅M denotes
the eddy transport term, whose horizontal and dominant component is related
to isentropic mixing, represented as the divergence of the eddy transport
vector M=(0,My,Mz), with components defined as in Andrews et al. (1987):
My=-e-zHv′χ′‾-v′T′S‾χz‾Mz=-e-zHw′χ′‾-v′T′S‾χy‾,
where primes indicate deviations from zonal means; T is the air temperature;
and S=N2⋅H/R with H=7 km, R=287 m2 s-2 K-1 and N2 as the Brunt–Väisälä frequency.
The analysis of the different terms of Eq. () has been carried out as
follows. First, ozone concentration anomalies are examined considering three different regions: tropics (20∘ S–20∘ N),
mid-latitudes of the NH (35∘ S–55∘ N) and
the Arctic region (70∘ S–90∘ N). Second, the
anomalies in the local tendency of ozone concentration (left term in Eq. 1)
are obtained, and finally the terms on the right-hand side of Eq. () are
analyzed to understand the driving mechanisms that give rise to the ozone
anomalies. Note that the residual term in Eq. () is smaller than 3 % in
the regions analyzed here, so it is small enough to consider that Eq. () closes the total ozone budget. This analysis has been carried out using
three of the four members of the WACCM4 ensemble since data for the eddy
transport term were not available in the fourth.
October–March composite evolution of anomalies in the ozone mixing ratio
(ppbv) as a function of pressure (a–c) in the tropics
(20∘ S–20∘ N), (d–f) at mid-latitudes
(35–55∘ N) and (g–i) in the Arctic (70–90∘ N) for (from left to right) EP El Niño, CP El Niño and La Niña
events. Black dots denote statistically significant anomalies at the 95 %
confidence level. The tropopause is indicated by the thick grey line.
Figure 3 displays the time–pressure evolution of anomalies in the ozone mixing ratio
averaged over each of the three regions defined above for the
three ENSO types. First, we analyze the anomalies in the tropics (Fig. 3a–c). As expected from Figs. 1 and 2, robust negative ozone anomalies
during EP El Niño and positive anomalies during La Niña events are
present throughout the entire winter in the lower and middle tropical
stratosphere (below 20 hPa). In CP El Niño events, anomalies are weaker
than in EP El Niño and confined below 50 hPa.
In order to understand the driving mechanisms of these tropical anomalies,
Fig. 4 shows the anomalies in the relevant terms of Eq. () for the
tropical region. The anomalies in the ozone tendency are small (Fig. 4a–c),
consistent with the near-constant tropical ozone concentration anomalies
throughout the winter in all three ENSO cases, as seen in Fig. 3a–c. It is
clear that the anomalies in the tropical ozone tendency during ENSO events
below 30 hPa come mainly from advection (Fig. 4d–f). This is consistent with
anomalous tropical upwelling present in Fig. 1d–f. Previous studies already
showed increased tropical upwelling associated with El Niño events (e.g., Calvo et
al., 2010; Diallo et al., 2019). Enhanced upwelling during El Niño leads
to ozone-poor air rises from the tropopause region, where the ozone
concentration is more than an order of magnitude lower, into the
stratosphere, generating negative anomalies therein. During La Niña
events the response is the opposite: there is a decrease in tropical
upwelling (Calvo et al., 2010), and less
ozone-poor air reaches the stratosphere, leading to positive anomalies in
the ozone mixing ratio.
Above 30 hPa, ozone changes due to advection are counteracted by changes due
to chemical processes (Fig. 4g–i). Hood
et al. (2010) indicated that enhanced tropical upwelling following El
Niño events leads to a reduction in odd nitrogen (NOx) in the middle
stratosphere. Such NOx decrease may lead to photochemical ozone increases by
modifying the NOx ozone loss catalytic cycle. Co-occurrence of anomalies in
the tendency due to advection and due to chemistry supports this hypothesis.
This mechanism may also be acting during La Niña events. The reduction
of tropical upwelling leads to a higher concentration
of NOx in the middle stratosphere and thus to a higher catalytic
destruction of ozone. The eddy transport term tends to counteract the
advection term below 30 hPa, consistent with the gradient-eroding effect of
mixing, but the magnitude is smaller (not shown). Regarding comparison
between EP and CP El Niño events, the different strength and timing in
the advection and chemistry anomalies are due to the differences in the
intensification of tropical upwelling shown in Fig. 1d and e and in the timing of
occurrence of this enhanced upwelling. The largest anomalies in the tropical
upwelling during EP El Niño occur in early winter, but during CP El
Niño events the response mainly occurs after December (not shown).
October–March composite evolution of the anomalies of
the most relevant terms in the zonal-mean ozone continuity equation (Eq. 1)
as a function of pressure, averaged over 20∘ S–20∘ N, for (from left to right) EP El Niño, CP El
Niño and La Niña events. (a–c) DO3dt is the local tendency in the ozone
mixing ratio. (d–f) ADV is variation due to the advection. (g–i) CHM
denotes the chemical balance. Black dots denote statistically significant
anomalies at the 95 % confidence level. The tropopause is indicated by
the thick grey line.
We next examine ozone anomalies at mid-latitudes (35–55∘ N,
Fig. 3d–f). We focus especially on the anomalies located below 30 hPa, since
these are the ones that have the largest impact on TCO. From December
onwards, significant positive ozone concentration anomalies appear in the
lower stratosphere associated with EP El Niño events, and negative
anomalies are associated with La Niña events. These anomalies in the ozone mixing ratio
produce the TCO anomalies seen in Fig. 2a and c. During CP El
Niño events, significant positive anomalies also appear in the lower
stratosphere, although these are weaker than during EP El Niño events. Moreover,
they are accompanied by strong negative anomalies above, between 15 and 30 hPa. This results in a lack of signal in TCO at mid-latitudes during CP El
Niño events as shown in Fig. 2b.
The evaluation of the anomalous patterns of the terms on the right-hand side
of Eq. () reveals that at mid-latitudes both advection due to the shallow
branch of the residual circulation (Fig. 5d–f) and mixing (Fig. 5g–i) are
key in generating the anomalies below 30 hPa, with both mechanisms leading
to ozone changes (Fig. 5a–c) of the same sign. During EP El Niño, ozone
accumulation occurs mainly in November and December (Fig. 5a) due to the
contribution of mixing in both months and contribution of advection in
December. During La Niña, negative ozone anomalies are generated from
November to February (Fig. 5c). In this case, the onset of the anomalies is
dominated by advection, while mixing contributes from January onwards.
As in Fig. 4 but averaged over 35–55∘ N and for
anomalies in DO3dt (a–c); ADV (d–f); and MIX (g–i), which represents changes
related to mixing.
In CP El Niño events, weaker positive ozone tendency anomalies appear in
January, mainly due to changes in mixing. The negligible role of advection
in the lower stratosphere during CP El Niño (Fig. 5e) contrasts with its
larger role during EP El Niño and La Niña. This key result is
consistent with the weak acceleration of the shallow branch during CP El
Niño winters than during EP El Niño in WACCM discussed in Sect. 3
(Fig. 1d–e). Chemical changes do not contribute significantly to the
ENSO-related ozone anomalies in the mid-latitudes below 30 hPa (not shown).
Latitude–pressure cross sections of the composite of anomalies in the November–March (NDJFM) zonal-mean (EP El Niño) and January–March (JFM) (CP El Niño and La Niña) (a–c) ozone
tendency related to mixing and (d–f) EPFD (colors) and zonal wind (black
contours) for (from left to right) EP El Niño, CP El Niño and La
Niña events. Contours in bottom panels are drawn every 0.5 m s-1 for
zonal winds. Solid (dashed) contours denote positive (negative) anomalies.
The NDJFM or JFM mean tropopause is indicated by the thick grey line. Color
shading (bottom panels) and black dots (upper panels) denote statistically
significant anomalies at the 95 % confidence level; thick contours denote
statistically significant anomalies for zonal wind.
Having established the key role of mixing processes as a main driver of
stratospheric ozone changes during ENSO events at mid-latitudes, we next
study the spatial pattern of these anomalies and the factors that favor
their occurrence. For this purpose, Fig. 6 shows the latitude–pressure
anomalies of the third term of Eq. (), associated with mixing (Fig. 6a–c),
and the Eliassen–Palm flux divergence (hereafter EPFD) and zonal-mean zonal
wind (Fig. 6d–f). Based on the timing of the largest mixing contribution
below 30 hPa at mid-latitudes (Fig. 5g–i), composites of EP El Niño
anomalies are computed for the November–March (NDJFM) average, while CP El Niño and La
Niña composites are computed for the January–March (JFM) mean. The Eliassen–Palm flux is
a measure of planetary wave propagation, while EPFD is a measure of its
dissipation (Andrews et al., 1987), with negative values
of the EPFD indicating wave breaking. Planetary wave breaking is closely
related to isentropic mixing, as it leads to
the development of tracer filaments which are ultimately diffused and mixed
with the environment. The intensity of the polar vortex, directly linked to
wave dissipation, constitutes a mixing barrier (Plumb,
2007) such that enhanced wave dissipation and mixing are related to a weak
polar vortex and vice versa.
In all three ENSO cases (EP and CP El Niño, and La Niña), an
anomalous dipole structure appears in the mixing term between mid-latitudes
and polar latitudes below 50 hPa (Fig. 6a–c), suggesting that changes in one
region are related to changes in the other. To understand these variations,
note that climatological ozone values below 30 hPa are higher at the pole
than at mid-latitudes in boreal winter (not shown). Therefore, the
climatological mixing effect tends to reduce this ozone concentration
gradient generating a net transport of ozone from polar latitudes to
mid-latitudes. Both EP and CP El Niño composites show positive anomalies
in the mixing term at mid-latitudes and negative anomalies in the polar
region, indicating an intensification of quasi-horizontal mixing. Hence, the
net effect of mixing during both types of El Niño events is to transport
more ozone from polar latitudes to mid-latitudes. These changes in mixing
are driven by anomalous Rossby wave breaking as shown by negative values of
the EPFD anomalies in the stratosphere in the region centered around
50–60∘ N, accompanied by a weaker polar vortex (Fig. 6d, e).
In contrast, during La Niña events, anomalies in the mixing term
indicate accumulation of ozone at the pole and reduction in ozone at
mid-latitudes, therefore implying a net reduction of mixing. Likewise,
during La Niña events, stratospheric wave breaking is reduced, resulting
in a stronger polar vortex (Fig. 6f).
In summary, it is clear that the enhanced wave breaking around the polar
vortex during EP El Niño and CP El Niño events causes an increase in
mixing through a weakened polar vortex. Opposite changes occur during La
Niña. The importance of the wave–mean flow interaction on ENSO signals
has been reported before using model simulations (e.g., Calvo et al.,
2008; Li and Lau, 2013) and reanalysis data (e.g., Iza et al., 2016), but until now it had not
been directly linked to mixing during ENSO events. Furthermore, our analysis
demonstrates the importance of considering mixing as a key factor in ozone
variations in the mid-latitude lower stratosphere during ENSO events, since
its contribution to these changes is comparable to the advection by the
shallow branch of the residual circulation, even more important during CP El Niño.
As in Fig. 5 but averaged over 70–90∘ N.
Finally, the dynamical mechanisms that control the changes in stratospheric
ozone during different ENSO phases are analyzed in the Arctic region
(70–90∘ N). Significant positive ozone anomalies appear in
the middle stratosphere in early winter during EP El Niño (Fig. 3g) and propagate downward during winter to the lower
stratosphere. Anomalies during La Niña events (Fig. 3i) are opposite to
those during EP El Niño. These anomalies are consistent with the ones in
TCO. During early winter, anomalies in the ozone mixing ratio in the lower
stratosphere are weak, and therefore their impact on the TCO is small. Anomalies in the ozone
mixing ratio in the middle stratosphere have a minor impact on the
TCO, and hence the TCO anomalies are generally small and not significant. In
late winter, ozone concentration anomalies are significant in the lower
stratosphere but are partially offset by anomalies of an opposite sign just
above, weakening the impact on polar TCO. The anomalies during CP El
Niño (Fig. 3h) are statistically insignificant in general, and no
conclusions are drawn for this case.
Figure 7 shows the different terms involved in the high-latitude ozone
anomalies. The main driver of the downward propagating anomalies in EP El
Niño and La Niña is advection by the deep branch of the residual
circulation (Fig. 7d–f). During EP El Niño events, the enhanced
advection (Fig. 7d) accumulates ozone in the lower polar stratosphere as a
result of the acceleration of the deep branch (Fig. 1d). However, in CP El
Niño events, the effect of the advection is smaller and not significant
(Fig. 7e), in agreement with the lack of significant CP El Niño impact
on the deep branch of the residual circulation (Fig. 1e).
During La Niña events the signal has an opposite sign, with a deceleration
of the deep branch and therefore weaker ozone advection to the polar lower
stratosphere. Note that, contrary to mid-latitudes, the effect of mixing
is the opposite to that of advection for all ENSO composites (Fig.7g–i). As
shown in Fig. 6, negative anomalies in the mixing term at polar latitudes,
as seen for EP and CP El Niño, imply that mixing between middle and
polar latitudes increases, with more ozone being transported to
mid-latitudes. In early winter, contributions of advection and mixing are
balanced, but in January and February, when anomalies in the deep branch of
the residual circulation increase, advection is the dominant mechanism in
the generation of anomalies. Chemical net production is not an important
factor in ozone anomalies at the pole since its action inside the polar
vortex starts in spring (from March onwards) under the presence of solar
radiation (not shown).
In summary, the analysis of the driving mechanisms of ozone variations
during ENSO events has revealed advection as the main driver due to changes
in the residual circulation. However, changes in advection alone cannot
explain the ozone anomalies, and changes in chemistry (in the tropics above
∼30 hPa) and mixing (at middle and high latitudes) must be
considered. Moreover, during CP El Niño advection in the extratropics is
weaker, and mixing is the dominant transport term in these regions.
January–March composites of anomalies in the ozone mixing ratio
at the 70 hPa level pressure for (a) EP El Niño, (b) CP El
Niño and (c) La Niña.
Summary and conclusions
In this study we analyzed NH ozone changes associated with ENSO phenomena in
boreal winter, distinguishing for the first time between different El
Niño flavors (EP and CP El Niño) and La Niña. We used WACCM4
simulations with prescribed observed SSTs and external forcings for the
period 1955–2014 and analyzed four ensemble members to increase statistical
significance of the results. We evaluated the different terms in the
continuity equation for zonal-mean ozone concentrations to examine the
driving mechanisms of ozone variations, separating contributions from the
advective BDC, isentropic mixing and chemical processes. Our results with
WACCM confirm the importance of separately studying EP and CP El Niño
events and highlight the key role of mixing for middle- and high-latitude
ozone variations during ENSO events. The main findings are summarized as follows:
Both EP and CP El Niño events show, in the tropics, a robust impact on
boreal winter temperature, zonal wind and the ozone mixing ratio of the same
sign, but anomalies are larger for EP El Niño events. In contrast, only
EP El Niño events show a significant impact in the Arctic region. In
addition, both shallow and deep branches of the residual circulation are
accelerated during EP El Niño (and decelerated during La Niña).
However, during CP El Niño the shallow branch acceleration is up to
3 times smaller than in EP El Niño, and there is no significant
impact on the deep branch.
EP El Niño and La Niña have a clear significant impact on TCO. EP El
Niño is characterized by a reduction in TCO in the tropics and an
increase in middle and polar latitudes from December to March, in agreement
with previous results by Cagnazzo et al. (2009)
based on the Niño3 index. The winter evolution of TCO anomalies during
La Niña mirrors those found during EP El Niño in both WACCM
simulations and reanalyses. In contrast, the impact of CP El Niño events
on TCO is small and not significant north of the tropics. The evaluation of
TCO-composited anomalies for the three ENSO types in WACCM against two
reanalyses and one merged satellite ozone product confirms that the model
captures the main features seen in the observational datasets.
Tropical stratospheric ozone variations are mainly driven by advection
through changes in tropical upwelling that modulate the rising of ozone-poor
air from the tropopause region. Our results show differences in the
upwelling response between the two types of El Niño, not only in the
strength but also in the timing. Changes in tropical upwelling also can lead
to changes in NOx concentration, modifying the NOx ozone loss catalytic
cycle, as proposed by Hood et al. (2010) and by Chipperfield et al. (1994) and Zhang et al. (2021) for QBO
ozone variations. Indeed, we find a different timing in chemical anomalies
in the tropical middle stratosphere (above 30 hPa), consistent with
different timing in upwelling, between the two types of El Niño.
At middle and high latitudes, mixing and advection are the main drivers of
ozone variations during ENSO events in boreal winter. Regarding advection,
EP El Niño events are associated with an acceleration of both shallow
and deep branches of the residual circulation, which leads to an
accumulation of ozone in the extratropics. In contrast, La Niña events
decelerate the residual circulation, and hence there is less ozone advective
transport to the extratropics. Ozone advection is weak in the extratropics
during CP El Niño events in agreement with the lack of an impact of CP El
Niño events on the deep branch of the residual circulation.
The present study shows that the contribution of mixing processes is not
negligible since its contribution to the generation of ozone anomalies at
middle and high latitudes has a magnitude similar to advection. Inspection
of anomalous wave dissipation patterns reveals that increased wave breaking
around the polar vortex during El Niño leads to a weakening of the
vortex and increased mixing across its climatological location. This leads
to a decrease in ozone at the pole and an increase in ozone at mid-latitudes
during boreal winter. The same, but opposite, mechanism is valid for La
Niña.
We acknowledge that other sources of variability can influence the
stratospheric response to ENSO and affect ozone concentrations. Most
importantly, SSWs are major disruption of the polar stratosphere, and
previous studies such as de
la Cámara et al. (2018) and Hong and
Reichler (2021) have shown that SSWs exert a strong effect on TCO, with
positive anomalies lasting more than 45 d after the SSW onset. In order
to assess if the ENSO signal is different in winters with and without SSW,
we have repeated our composite analyses isolating the ENSO signal from the
SSW signal. For this, we have selected the ENSO events for winters with at
least one SSW occurrence and computed the composited anomalies with respect
to a climatology based exclusively on winters with SSW occurrence.
Analogously, we selected the ENSO events for winters without SSWs and
computed the composited anomalies with respect to a climatology based on
winters without SSW. This methodology is applied to each type of ENSO. The
SSWs are obtained using the CP07 criterion (Charlton and
Polvani, 2007). The results obtained in both cases are similar to those
shown in the analysis performed including all ENSO events (not shown).
Therefore, we concluded that the ENSO signal in ozone is not significantly
affected by the occurrence of SSW in our analyses. Nevertheless, we note
that the relations between SSW and ENSO are complex and still under study
(e.g., Song and Son, 2018).
Another important source of variability in the stratosphere which could be
affecting our results is the QBO (e.g., Naoe et al., 2017; Zhang et al., 2021).
Indeed, Xie et al. (2020) showed
linear interactions between the QBO and EP El Niño signals, and its
interactions in the extratropics during El Niño events were evaluated in
Calvo et al. (2009). In our study,
we have eliminated its influence, performing a multiple linear regression
analysis. However, further investigation about the joint influence of
different flavors of ENSO and QBO on stratospheric ozone could be of
interest since previous studies (e.g., Xie et al., 2012)
have pointed out that there might be non-linear interactions between CP El
Niño and QBO on the stratosphere.
While our analysis is based on the zonal-mean ozone composites, studying the
zonally resolved anomalies is an interesting avenue of research, especially
in the context of stratosphere–troposphere exchange. In a recent study, Albers et al. (2022) show that
the zonally resolved pattern of ENSO ozone anomalies in the upper
troposphere and lower stratosphere is closely connected to the geopotential
height anomalies associated with the stationary Rossby wave train triggered
by deep convection (e.g., Trenberth et al., 1998). In order to complement our
zonal-mean analysis, Fig. 8 shows the zonally resolved ozone anomalies at
70 hPa, distinguishing for the first time between flavors of El Niño.
Our results are highly consistent with Albers et al. (2022); they confirm
the wave-like structure of the ozone anomalies and further reveal
substantially larger anomalies for EP El Niño than for CP El Niño,
consistent with our results. We note that the ozone zonal asymmetries
evident in Fig. 8 are included in the TEM analysis used here to investigate
zonal-mean ENSO composites, specifically in the horizontal component of the
eddy transport–mixing term in Eq. (), given that this term is dominated by
the meridional eddy ozone flux v′O3′‾.
Finally, it would be interesting to reproduce our analysis in other
chemistry–climate models with a well-resolved stratosphere and to extend our
study to the Southern Hemisphere.
Data availability
The output from the WACCM simulations is available at
https://www2.acom.ucar.edu/gcm/ccmi-output (last access: February 2020; NCAR, 2022) and upon request to the
corresponding author. The SWOOSH dataset is available at
https://www.esrl.noaa.gov/csd/groups/csd8/swoosh/ (last access: September 2020; CSL, 2022). Data from the JRA-55 and
MERRA-2 reanalyses are freely available at
10.5065/D60G3H5B (Japan Meteorological Agency/Japan, 2013) and at
10.5067/AP1B0BA5PD2K (Global Modeling and Assimilation Office, 2015), respectively.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-22-15729-2022-supplement.
Author contributions
SBB, NC and MA designed the study. SBB performed the data analysis and
wrote the article, with significant contributions from NC and MA regarding the
interpretation of the results and editing of the text.
Competing interests
The contact author has declared that none of the authors has any competing interests.
Disclaimer
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
We are thankful to John Albers and Peter Braesicke for their very
constructive comments. Samuel Benito-Barca acknowledges the FPU program from the Ministry of
Universities (grant no. FPU19/01481). Natalia Calvo was supported by the Spanish
Ministry of Science, Innovation and Universities through the JeDiS
project (no. RTI2018-096402-B-I00).
Financial support
This research has been supported by the FPU program from the Ministry of Universities (grant no. FPU19/01481) and by the Spanish Ministry of Science, Innovation and Universities through the JeDiS project (no. RTI2018-096402-B-I00).
Review statement
This paper was edited by Martin Dameris and reviewed by John Albers and one anonymous referee.
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