Net influence of an internally-generated QBO on modelled stratospheric climate and chemistry

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Introduction
The quasi-biennial oscillation (QBO) is the leading mode of variability in the tropical lower and middle stratosphere (Baldwin et al., 2001).The QBO is characterized by a downward-propagating pattern of alternating easterly and westerly zonal winds in the equatorial region, with a period of approximately 28 months, and is driven by both gravity and planetary-scale waves (Reed et al., 1961).The zonal wind QBO induces changes in the tropical stratospheric circulation, affecting the concentrations of ozone and other trace constituents (Gray et al., 1989;Butchart et al., 2003;Tian et al., 2006).Introduction

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Full The phase of the QBO contributes to interannual variability in the polar stratosphere.Holton and Tan (1980) and Lu et al. (2008) showed that the phase of the QBO modulates the strength of the Arctic vortex in mid-winter; the vortex is weakest during the easterly phase of the QBO.QBO phase-related differences in the strength of the polar vortices modulate polar ozone loss (Lait, 1989;Randel and Cobb, 1994).Analogously to the Arctic response, the Antarctic vortex is generally weaker during the easterly phase of the QBO (Baldwin and Dunkerton, 1998).Also, the phase of the QBO modulates the polar stratospheric response to El Niño and La Niña events (Garfinkel and Hartmann, 2007;Hurwitz et al., 2011a).However, as the QBO signal is intrinsic to the observational record, the time-averaged impact of the easterly and westerly phases of the QBO on mean zonal wind, temperature and trace constituents is difficult to evaluate using atmospheric data.
A chemistry-climate model (CCM) is an ideal tool for understanding the net impact of the QBO.Punge and Giorgetta (2008) quantified the net effect of the QBO on the late 20th century stratospheric climate by comparing two CCM simulations: one without a QBO signal, and the other with zonal winds between 90 hPa and 10 hPa nudged to profiles taken at Singapore.The authors found that inclusion of this QBO signal impacted stratospheric zonal winds, temperature and ozone, mainly in the deep tropics.The vertical pattern of changes in tropical upwelling was consistent with changes in the distribution of trace species.However, the value of the conclusions reached by Punge and Giorgetta (2008) may be limited because the authors tested a "nudged" i.e., prescribed QBO.Nudging to observed zonal winds does not allow the tropical and mid-latitude stratosphere to internally adjust to changes in e.g., the QBO phase, nor does it allow for full interaction between stratospheric ozone and climate.
The Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM), Version 2 can be run with or without an internally-generated QBO.In the formulation of the GEOSCCM evaluated by SPARC CCMVal (2010), both tropical lower stratospheric variability and the QBO amplitude were negligible, typical of CCMs that lack a nudged or internal QBO signal.In contrast, a more recent model formulation (introduced by Introduction

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Full   et al., 2011b) can internally-generate a QBO with a realistic periodicity and amplitude, depending on the latitudinal structure of the non-orographic gravity wave drag (GWD).Comparing two simulations using this formulation of the GEOSCCM, one with a QBO and another without, this paper quantifies the net effect of the modelled QBO on stratospheric climate and variability.Section 2 provides a brief description of the GEOSCCM, as well as the two above-mentioned simulations.The net effects of the modelled QBO on the mean and variance of stratospheric zonal winds, temperature, mean age, ozone and methane are shown in Sect.3. Section 4 provides a summary and brief discussion.

Model and simulations
This paper considers the net impact of the QBO in Version 2 of the GEOSCCM.
The GEOSCCM couples the GEOS-5 general circulation model (Molod et al., 2012) with a comprehensive stratospheric chemistry module (Pawson et al., 2008).The GEOSCCM performed well in the SPARC CCMVal (2010) detailed evaluation of stratospheric processes.The present formulation of the GEOSCCM is the same as in Hurwitz et al. (2011b).In this formulation, the model has 2 • latitude × 2.5 • longitude horizontal resolution and 72 vertical layers, with a model top at 0.01 hPa.Predicted distributions of water vapour, ozone, primary greenhouse gases (CO 2 , CH 4 , and N 2 O), CFC-11, CFC-12 and HCFC-22 feed back to the radiative calculations.
In the GEOSCCM, tropical stratospheric zonal wind variability depends on the details of the non-orographic GWD scheme.As non-orographic gravity waves often accompany precipitation (e.g., convective and frontal systems; see Richter et al., 2010), the latitudinal structure of the gravity wave spectrum is designed to mimic the structure of the climatological mean precipitation field (solid black line in Fig. 5 of Molod et al., 2012).A 700 km wavelength is used for the tropical non-orographic waves to prevent an excessive downward propagation of the semi-annual oscillation into the lower stratosphere, and thus contamination of the QBO signal.With a tropical peak in Introduction

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Full non-orographic gravity wave stress, the present model formulation generates a QBO signal in equatorial zonal winds (see Sect. 3.1).Prior to this model formulation, the GEOSCCM did not generate a QBO i.e., zonal winds in the equatorial lower stratosphere were generally easterly (see Fig. 1c and SPARC CCMVal, 2010).Two GEOSCCM simulations are used to assess the net stratospheric impacts of the QBO.The two simulations are identical, except for the magnitude of the nonorographic GWD stress applied in the deep tropics.The first simulation (hereafter "Q") has a strong, quasi-realistic peak in tropical GWD, which as described above, generates a QBO signal.The second simulation (hereafter "N") has weak tropical GWD stress (dashed black line in Fig. 5 of Molod et al., 2012), and thus does not have a QBO.Both simulations are 50 yr "time-slice" simulations with fixed climate forcings and annually repeating sea surface temperature (SST) and sea ice climatologies.Surface mixing ratios of the primary greenhouse gases and ozone-depleting substances are specified from 2005 concentrations.The SST and sea ice climatologies are composites of 10 ENSO neutral years that span the satellite era (as in Hurwitz et al., 2011b).HadISST1 SSTs and sea ice concentrations at 1 • × 1 • resolution (Rayner et al., 2003) are used to prepare the composites.Variability related to the solar cycle and volcanic eruptions is not considered.
Modelled temperature and zonal wind fields are compared with the Modern Era Retrospective-Analysis for Research and Applications (MERRA).MERRA is a meteorological reanalysis, based on an extensive set of satellite observations and on the Goddard Earth Observing System Data Analysis System, Version 5 (GEOS-5), from 1979 through the present (Rienecker et al., 2011).The MERRA reanalysis has vertical coverage up to 0.1 hPa, and for this study, is interpolated to 1.25 Additionally, simulated stratospheric mean age-of-air, ozone, nitrous oxide and methane are compared with observational datasets.Simulated mean age-of-air is compared with profiles derived from CO 2 and SF 6 observations (Andrews et al., 2001;En-Introduction Conclusions References Tables Figures

Equatorial zonal winds
The QBO in zonal winds is well simulated in Q.The left-hand panels of Fig. 1 show 10 yr timeseries of equatorial winds in the MERRA reanalysis (1990-1999;Fig. 1a), Q (Fig. 1c) and N (Fig. 1e).The right-hand panels of Fig. 1 show the frequency spectra for equatorial winds for 1979-2012 in MERRA (Fig. 1b) and for the entire Q and N simulations (Fig. 1d, f).The simulated QBO signal has realistic amplitude and periodicity (compare Fig. 1a and c).In Q, the simulated peak frequency is 27 months at 30 hPa (Fig. 1d), with a secondary peak at 25 months, compared with 28 months in the MERRA reanalysis (Fig. 1b).In the upper and middle stratosphere, the annual (12 month) and semi-annual (6 month) frequencies are well simulated.Note that the simulated QBO signal is weaker than observed below 50 hPa (Hurwitz et al., 2011b).Equatorial zonal winds are easterly throughout the N simulation, without a QBO signal (Fig. 1e).That is, lower stratospheric zonal wind variability is negligible.However, the annual and semi-annual frequencies are simulated in the middle and upper stratosphere (Fig. 1f).Introduction

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Full show the 50 yr annual mean zonal wind, temperature, age-of-air, residual vertical and meridional velocities, methane, nitrous oxide and ozone fields in the Q simulation (lefthand panels), differences between Q and N (i.e., the net mean impact of the QBO) (middle panels), and QBO-related changes in stratospheric variability (right-hand panels).Annual and zonal mean zonal winds in the Q simulation are easterly in the tropical stratosphere and westerly in the extra-tropics (Fig. 2a), in good agreement with observations (black contours).In N, tropical stratospheric easterlies are on average stronger than in the MERRA reanalysis (not shown); thus, inclusion of the QBO represents both a relative zonal wind increase in the tropics (10-20 m s −1 ) and an improvement in the simulated mean comparison with MERRA (Fig. 2b).As expected, zonal wind variability increases by 3-5 times in Q, as compared with N, throughout the tropical stratosphere (Fig. 2c).
A modest cold bias around 60 • S may reflect the overly strong polar jet and delayed breakup of the Antarctic vortex in austral spring (Hurwitz et al., 2010).Inclusion of the QBO contributes to this bias: the QBO warms the tropical stratosphere and Arctic lower stratosphere by ∼ 1 K, but cools the Antarctic stratosphere by ∼ 1 K (Fig. 2e).QBO-related increases in temperature variability maximize in the middle stratosphere, in the deep tropics, with an additional lobe of increased variability around 30 • S (Fig. 2f).
Inclusion of the QBO acts to slow the stratospheric circulation.Age-of-air is an indicator of the strength and structure of the meridional overturning (i.e., Brewer-Dobson) circulation (SPARC CCMVal, 2010).In the GEOSCCM, mean age is an inert tracer that measures the time since a parcel of air has left the troposphere.Because most air enters the stratosphere in the tropics, mean age values are lowest in the tropical lower stratosphere and highest in the high latitude upper and middle stratosphere (Fig. 3a).Q-N differences in annual mean age are generally positive throughout the stratosphere Introduction

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Full i.e., the QBO slows the overturning circulation (Fig. 3b).The largest increases in mean age (∼ 0.3 yr) are seen in the tropical stratosphere around 10 hPa. Figure 5 shows observed and simulated mean age-of-air profiles in the deep tropics.While the mean age in N falls within the observational error, the older tropical mean age in the Q simulation is in better agreement with CO 2 and SF 6 observations.QBO-related changes in mean age variability, similarly to temperature variability, peak in the Southern Hemisphere tropical middle stratosphere (Fig. 3c).Decreased mean age in the lower stratosphere is consistent with slowing of the overturning circulation: less older air is advected downward into the mid-latitudes.QBO-related changes in the residual circulation are consistent with the changes in mean age-of-air.In the upper stratosphere and polar regions, the net impact of the QBO is dominated by the slowing of the meridional circulation.At and above 10 hPa, Q-N differences in w * (residual vertical velocity) oppose the w * climatology: negative differences in the tropics (weakened upwelling), and positive differences in the extratropics (weakened downwelling; compare Fig. 3d and e).Weakened tropical upwelling enhances tropical water vapour concentrations in the tropical stratosphere (not shown).In Fig. 3g-i, positive v * (residual meridional velocity) values indicate poleward motion in both hemispheres.Negative differences in v * , e.g.around 3 hPa in the tropics and in the uppermost polar stratosphere reflect weakened poleward transport (Fig. 3b).In the lower and middle stratosphere, the net impact of the QBO is to enhance poleward transport.That is, positive v * between 10 and 70 hPa, in the tropics and midlatitudes, is consistent with enhanced mixing in this region.Note that the v * differences are largest in the Southern Hemisphere and coincident with the peak change in v Introduction

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Full inverted as compared with mean age: the highest concentrations are found in the tropical lower stratosphere, while the lowest values are found in the polar upper stratosphere.The structure of the simulated tropical and subtropical methane distribution matches the scaled UARS HALOE climatology, but with a high bias (Fig. 4a).This bias results from the stronger than observed transport in the GEOSCCM (SPARC CCMVal, 2010).Inclusion of the QBO decreases tropical and upper stratospheric methane mixing ratios, reflecting slowing of the stratospheric circulation (Fig. 4b).Given the negative latitudinal gradient in methane concentrations (Fig. 4a), increased lower stratospheric methane suggests enhanced meridional mixing, i.e. weakening of the subtropical transport barrier (Fig. 4b); this effect is further discussed below.Inclusion of the QBO generally increases methane variability, with the largest increases in the tropics and sub-tropical Southern Hemisphere (Fig. 4c).QBO-related changes in N 2 O provide further evidence for enhanced sub-tropical mixing.Similarly to methane, the highest N 2 O concentrations are found in the tropical lower stratosphere, while the lowest values are found in the upper stratosphere (Fig. 4d).The simulated N 2 O distribution matches the MLS climatology, but with a high bias in the tropical lower stratosphere, similar to the methane bias.Inclusion of the QBO weakens the meridional gradient of N 2 O: decreasing equatorial N 2 O (exceeding 30 ppbv) and increasing N 2 O at sub-tropical latitudes (up to 10 ppbv) (Fig. 4e). Figure 6 shows the annual cycle of Q-N differences in the sub-tropical N 2 O gradient.
Mean N 2 O differences between 10 and 40 • s latitude serve as a proxy for the strength of the sub-tropical gradient i.e., the strength of the sub-tropical mixing barrier.Negative differences indicate a weakening of the sub-tropical N 2 O gradient, due to enhanced mixing (Douglass et al., 1999).The largest changes in sub-tropical N 2 O are centred around 10 hPa (consistent with the increases in sub-tropical v * and methane), in winter months.The QBO has a larger impact on sub-tropical N 2 O in the SH (Fig. 6a) than in the NH (Fig. 6b), consistent with the relatively larger enhancements in variability in the SH (Figs. 2-4, right-hand panels).Introduction

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Full The net impact of the QBO on ozone reflects warming of the tropical stratosphere, enhanced sub-tropical mixing and slowing of the stratospheric overturning circulation.The annual mean ozone mixing ratio maximizes at approximately 10 ppmv in the deep tropics, at 10 hPa, and decreases with latitude (Fig. 4g).Simulated ozone is generally in agreement with the MLS ozone climatology.Thus, inclusion of the QBO improves model performance; the peak in ozone mixing ratio around 10 hPa is ∼ 0.8 ppmv too high in the N simulation.Relative warming of the tropical middle stratosphere in Q contributes to the negative ozone differences in the deep tropics (Figs.2e and 4h).However, at the equator at 10 hPa, the ratio between temperature and ozone differences (i.e., ∆T/∆ O 3 = 0.72 K/0.8 ppmv = 0.9) does not agree with the ratio of ∼ 6.7 as determined by Oman et al. (2010).This result suggests that other mechanisms contribute to the change in tropical ozone.Decreased tropical ozone at 10 hPa is consistent with both (1) strengthening of vertical upwelling below 10 hPa (Fig. 3e) and ( 2) enhanced mixing with mid-latitude air with relatively lower ozone concentrations (Figs.4g and 6).

High latitude impact of the QBO in winter
In certain months, in the Q simulation, equatorial zonal winds at 30 hPa are positively correlated with zonal winds in the polar stratosphere (not shown).That is, the GEOSCCM reproduces the Holton-Tan (1980) relation between the phase of the QBO and polar vortex strength: the polar vortices are relatively stronger during the westerly phase of the QBO.In the GEOSCCM, equatorial zonal wind correlations with zonal winds at 60 • S are strong in e.g., September (Fig. 7), and at 60 • N in January (Fig. 8).
The net impact of the QBO on zonal winds and temperature (i.e., Q-N) mimics the differences between the westerly and easterly phases of the QBO (i.e., in the Q simulation), at Southern Hemisphere high latitudes in September.Inclusion of the QBO strengthens the Antarctic jet (around 60 • S) by 5-10 m s −1 (Fig. 7a).An equal strengthening is seen in Fig. 7b, which shows the zonal wind differences between the five Septembers in Q with the highest (i.e., QBO-W) equatorial zonal wind values at 30 hPa and the five Septembers in Q with the lowest (i.e., QBO-E) equatorial zonal wind val-13504 Introduction

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Full ues at 30 hPa.Note that the QBO-W-QBO-E differences are generally not statistically significant in the extra-tropics, due to the small size of the QBO-W and QBO-E composites.
Extra-tropical stratospheric temperatures decrease in September, consistent with the stronger zonal winds (i.e., by the thermal wind relation).Temperature differences are negative poleward of 45 • S, both for Q-N and QBO-W-QBO-E, with peak differences of 5 K in the Antarctic (Fig. 7c, d).Tropical and mid-latitude Q-N differences reflect changes in stratospheric circulation and mixing (see Sect. 3.2).
Equivalent zonal wind and temperature differences are seen in the Northern Hemisphere extra-tropics in January.Q-N differences reflect a relative shift toward the westerly phase of the QBO: a relative strengthening of the Arctic stratospheric jet (Fig. 8a,  b) and cooling throughout the extra-tropical stratosphere (Fig. 8c, d).In this case, zonal wind and temperature differences are larger in response to QBO phase as compared with the net impact of the QBO.Negative ozone differences in the Arctic lower stratosphere (Fig. 8e, f), though weak, hint at enhanced chemical ozone depletion, due to the cooler and more isolated polar air mass in January.The small size of the QBO-W and QBO-E composites likely weakens the statistical significance of the ozone differences.

Discussion
A model's representation of the QBO makes a significant difference to the mean stratospheric climate and variability.As expected, the addition of a QBO significantly enhances tropical variability.Extra-tropical zonal wind and temperature variability in winter is also enhanced.While the QBO is by definition an oscillating phenomenon, the multi-decadal mean of the modelled QBO modifies the average climate.In particular: 1. Adding an internal QBO signal affects the mean stratospheric climate.
In the GEOSCCM, inclusion of a QBO signal slows the meridional overturning circulation, leading to older mean age-of-air throughout the stratosphere and af-Introduction

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Full fecting the distribution of trace species such as ozone, methane and nitrous oxide.
The sub-tropical mixing barrier is weakened, enhancing methane and nitrous oxide in the extra-tropical lower stratosphere, and contributing the reduced peak ozone mixing ratio at 10 hPa.The polar vortices are strengthened, particularly in winter.The net dynamical and transport impacts of the QBO generally improve model performance.
2. The net impact of the QBO depends on both the baseline zonal wind field and the relative change in tropical zonal winds.
In the GEOSCCM, the baseline tropical zonal winds are easterly.In the simulation with a QBO signal, there is a relative increase in zonal winds in the tropical lower and middle stratosphere.Extra-tropical differences between the simulations with and without a QBO thus reflect a bias toward the westerly phase of the QBO: a relative cooling and strengthening of the polar vortices, and a weak reduction in Arctic lower stratospheric ozone.The annual mean impact of the QBO on the polar stratosphere is larger in the GEOSCCM (up to 12 m s −1 , in both hemispheres) than in the MAECHAM4-CHEM CCM (no significant zonal wind differences) (Punge and Giorgetta, 2008), likely reflecting larger tropical zonal wind differences between the QBO and "no QBO" GEOSCCM simulations and/or increased statistical robustness due to the greater length of the GEOSCCM simulations.
The QBO has a robust, net impact on the mean stratospheric climate and trace gas distributions.In the case of the GEOSCCM, inclusion of the QBO yields better agreement between the simulated fields and climatological averages derived from a meteorological reanalysis and satellite datasets of ozone, methane and nitrous oxide.While it is difficult to internally generate a QBO signal in a global climate model, a model with the ability to simulate a QBO presents significant advantages in predicting the future evolution of the stratosphere: climate change is likely to modify the GWD which will remotely modify stratospheric climate and variability.Introduction

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Full Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | gel et al., 2009).These observations were taken between 1986 and 2005.Simulated ozone (O 3 ) and nitrous oxide (N 2 O) are compared with the 2004-2012 climatology of the Aura Microwave Limb Sounder (MLS) version 3.3 O 3 and N 2 O products (Froide- Discussion Paper | Discussion Paper | Discussion Paper | 3.2 Annual mean impact of the QBO Inclusion of the QBO impacts stratospheric mean climate and variability.Figures 2-4 Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Fig. 8 .
Fig. 8. January (a, b) zonal wind [m s −1 ], (c, d) temperature [K] and (e, f) ozone [ppmv] differences in the Northern Hemisphere.(a, c, e) Q-N mean differences; (b, d, f) QBO-westerly -QBO-easterly differences in the Q simulation.White contours indicate zero difference.Black Xs indicate differences significant at the 95 % level in a two-tailed t test.