ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-19-425-2019Structural changes in the shallow and transition branch of the Brewer–Dobson circulation induced by El NiñoShallow and transition branch of the BDC responses to El NiñoDialloMohamadoum.diallo@fz-juelich.dehttps://orcid.org/0000-0003-0225-8120KonopkaPaulSanteeMichelle L.MüllerRolfhttps://orcid.org/0000-0002-5024-9977TaoMengchuhttps://orcid.org/0000-0002-1071-5953WalkerKaley A.https://orcid.org/0000-0003-3420-9454LegrasBernardhttps://orcid.org/0000-0002-3756-7794RieseMartinhttps://orcid.org/0000-0001-6398-6493ErnManfredhttps://orcid.org/0000-0002-8565-2125PloegerFelixInstitute of Energy and Climate Research, Stratosphere (IEK–7), Forschungszentrum Jülich, 52425 Jülich, GermanyLaboratoire de Météorologie Dynamique, UMR8539, IPSL, UPMC/ENS/CNRS/Ecole Polytechnique, Paris, FranceJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USADepartment of Physics, University of Toronto, Toronto, Ontario, CanadaInstitute for Atmospheric and Environmental Research, University of Wuppertal, Wuppertal, GermanyMohamadou Diallo (m.diallo@fz-juelich.de)11January201919142544610July20186August201820November201819December2018This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/This article is available from https://acp.copernicus.org/articles/19/425/2019/acp-19-425-2019.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/19/425/2019/acp-19-425-2019.pdf
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.
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
e.g..
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 e.g. BDC;, 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 e.g..
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
e.g.. 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
e.g.. 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 e.g.. 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. .
Section shows the ENSO impact on simulated and observed
ozone mixing ratios in the lower stratosphere. Section 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. ).
Data and methodologyDescription 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 1∘×1∘ 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.
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 .
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
(w∗‾), 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 e.g..
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) τ=t-ti′, the age spectrum
is constructed from these N pulse tracers at each sample field time t and
sample region r as G(r,t|Ω,t-τi)=χi(r,t). 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 w∗‾, calculated from the transformed Eulerian
mean (TEM) circulation standard formula in geometric coordinates
e.g. Eq. 3.5, and the diabatic heating rate
from both reanalyses.
In contrast to the integrated residual circulation transit time along the
trajectory of an air parcel, w∗‾ is a local 2-D quantity.
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, w∗‾, RCTT, Ψ, age spectrum,
air mass fraction, temperature, zonal mean wind, Eliassen–Palm flux, and its
divergence),
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 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(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 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 .
Time 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.
ENSO impact on lower stratospheric O3
Figure a 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. .
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. a, 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 e.g., by the climate change impact
e.g., and
by the emissions of ozone depletion substances e.g..
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. ) 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 b 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. )
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.
Latitude–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 a–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. )
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. a, 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. ) . 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.
Zonal 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 a–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. a–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. .
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. a) 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 O3e.g..
Thus, tropical upper tropospheric O3 mixing ratios may be enhanced not
only because of increased convective transport, but also increased fire
emissions
this was especially true in 2015,. 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.
Zonal mean distribution of the ENSO impact on mean age (a, b), residual
vertical velocity (w∗‾) (c, d) and diabatic heating rate (Θ˙) (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
w∗‾ and Θ˙ 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,
w∗‾ and Θ˙ are overplotted as dashed grey lines.
Structural changes in the lower stratospheric BDC
In this section, various diagnostics of the BDC strength (e.g. AoA,
w∗‾, 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. ).
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 a–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. ).
Figure c, d depict the ENSO-induced variability in the w∗‾,
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
w∗‾ and in the diabatic heating rate (Θ˙)
(Fig. c–f).
During El Niño, the increase in the ascending branch of the BDC
(positive tropical w∗‾ and
Θ˙) 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. ), contrasting with model projections
of shorter stratospheric residence time due to enhanced downwelling in a
warming climate e.g..
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 w∗‾ and Θ˙ agree well in the two
reanalyses in terms of morphology, though not in magnitude (see Fig. c–f).
The w∗‾ and Θ˙ 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
w∗‾ anomalies in the tropics than JRA-55, consistent with
the differences between the two reanalyses in O3 anomalies (Fig. ).
Zonal 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 e.g., 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. a–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. ).
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. a, 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. c, 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. c, d). ENSO-induced
variability in the deep branch is less evident in the reanalyses (not shown).
Lag 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 a–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. e, f) as well as with the differences in the lag
correlation.
ENSO 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. ) 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. a 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. ).
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. a, 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. ). 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. c, 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. and ). 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. 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.
Zonal 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. a, b) and the old air mass
fraction with a transit
time longer than 24 months (Fig. c, 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. c, 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.
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.
Zonal 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. ).
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 e.g..
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. a, 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. b, 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. agree with prior model and observational studies
e.g.
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. c, 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. c,
f).
Hence, the wave drag changes shown in Fig. c, 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
.
Zonal 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 a–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. a) 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. b),
consistent with results from the WACCM model see Fig. 3
of.
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. c 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. b).
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. –).
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 θ˙
anomalies (Figs. , and ).
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 .
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, w∗‾, 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.
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, w∗‾, RCTT and age spectrum data set can be requested from the corresponding author Felix Ploeger (f.ploeger@fz-juelich.de).
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.
The authors declare that they have no conflict of
interest.
This article is part of the special issue “The SPARC Reanalysis
Intercomparison Project (S-RIP) (ACP/ESSD inter-journal SI)”. It is not
associated with a conference.
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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