Changes in various branches of the Brewer-Dobson circulation from

Changes in various branches of the Brewer–Dobson circulationfrom an ensemble of chemistry climate models

P. Lin,1 and Q. Fu1,2

Received 7 September 2012; revised 20 November 2012; accepted 26 November 2012; published 16 January 2013.

[1] We analyzed the changes of simulated Brewer–Dobson circulation (BDC) for 1960–2099from 12 chemistry climate models participating the Chemistry-Climate Model Validationactivity phase 2 (CCMVal-2). We decomposed the BDC into transition, shallow, and deepbranches with vertical extent of 100–70, 70–30, and above 30 hPa, respectively. Modelsconsistently simulate the acceleration in all three BDC branches over 140 years, but theacceleration rate of the deep branches is much smaller. The acceleration rate of the transitionand shallow branches in general shows weak seasonal or hemispheric dependence andincreases with time, consistent with the continuous and homogeneous increase of greenhousegas concentrations. The trend magnitudes of shallow and transition branches differ frommodel to model, which are found to be associated with the simulated changes in subtropicaljets and tropical upper tropospheric temperature. The acceleration of the deep branch is also aresponse to the increase of greenhouse gas concentrations but is modulated by the changes inozone concentrations. The effect of ozone changes is particularly prominent in the southerndeep branch during austral summer: almost all models simulated strong significantacceleration during the ozone depletion era, weak deceleration during the ozone recovery era,and near-zero trends during the stable ozone era. However, the ozone effect is less evident inother seasons and in other branches.

Citation: Lin, P. and Q. Fu (2013), Changes in various branches of the Brewer–Dobson circulation from an ensemble ofchemistry climate models, J. Geophys. Res. Atmos., 118, 73–84, doi:10.1029/2012JD018813.

1. Introduction

[2] The Brewer–Dobson circulation (BDC) is the slowoverturning circulation of the stratosphere with an ascendingbranch in the tropics and descending branches in the extra-tropical region of each hemisphere (e.g., [Holton et al.,1995]). The strength and width of the BDC vary withseason, with the stronger cell occurring in the winter hemi-sphere and the upwelling regions shifting toward the sum-mer hemisphere [Rosenlof, 1995]. The BDC moves air intoand out of the stratosphere and thus sets the mean age orthe residence time of air in the stratosphere [Hall & Plumb,1994]. In particular, the BDC transports ozone and otherchemically/radiatively important trace gases from the tropicsto polar regions and thus influences the formation and therecovery of the ozone hole [e.g., Solomon, 1999; Austinand Wilson, 2006]. The BDC also affects the stratosphericconcentrations of trace gases that have tropospheric originsby setting the rate at which these species enter the strato-sphere in the tropics (e.g., [Randel et al., 2006]). Some of

these stratospheric species (such as ozone and water vapor)can contribute significantly to the radiation balance of thetroposphere and the surface (e.g., [Forster & Shine, 1997;Solomon et al., 2010]).[3] Because of its importance to both stratospheric and

tropospheric climate and stratospheric ozone chemistry,many efforts have been made to simulate the BDC, espe-cially its change under anthropogenic forcing. A strongerBDC in the future as greenhouse gas (GHG) concentrationsrise is consistently predicted bymany general circulation mod-els (GCMs) (e.g., [Rind et al., 1990; Butchart et al., 2006]),simple GCMs with idealized physics (e.g., [Eichelberger &Hartmann, 2005]), and by many recent coupled chemistry cli-mate models (CCMs) (e.g., [Butchart et al., 2010; SPARCCCMVal, 2010]). Several studies also find BDC changes inresponse to changes in ozone concentrations (e.g., [Li et al.,2008; Oman et al., 2009;McLandress et al., 2010]). Detailedmechanisms of how these forcings drive the BDC changes arenot fully understood yet and vary among models [SPARCCCMVal, 2010].[4] The relative importance of these two anthropogenic

forcings have been discussed in many previous studies (e.g.,[Shindell & Schmidt, 2004; Oman et al., 2009; Morgensternet al., 2010a; Polvani et al., 2011; McLandress et al., 2010;McLandress et al., 2011]). Oman et al., [2009] suggestedozone depletion is the dominant forcing for the stratosphericBDC changes over the past few decades in their simulations,but ozone and GHG forcings are more comparable in simula-tions done by McLandress et al. [2010]. Several individual

1Department of Atmospheric Sciences, University of Washington, Seattle,WA, USA.

2College of Atmospheric Sciences, Lanzhou University, Lanzhou, China.

Corresponding author: P. Lin, Department of Atmospheric Sciences,University of Washington, 408 ATG Bldg., 4000 15th Ave NE, Seattle,WA 98195, USA. ([email protected])

©2012. American Geophysical Union. All Rights Reserved.2169-897X/13/2012JD018813

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JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES, VOL. 118, 73–84, doi:10.1029/2012JD018813, 2013

model studies suggest that the lower part of the BDC wouldaccelerate more in the future (e.g., [Garcia & Randel, 2008;Garny et al., 2011]).[5] In this paper, we analyzed the simulated BDC from 12

recent CCMs from past to future with changes in both GHGsand ozone concentrations. Most previous studies havefocused on changes in the overall strength of the BDC (e.g.,[Butchart et al., 2006; SPARC CCMVal, 2010]). Here weinvestigated the detailed spatial and temporal structures ofchanges in the BDC from these simulations. In particular,we divided the BDC into different branches based on itsvertical extent and hemispheric location and examined theirchanges in the periods of 1961–2000, 2011–2050, and2058–2098. We found that the different BDC branches aredistinct in their temporal evolution from past to future, andthe distinction is consistent among different models. We showthat these spatial and temporal structures of the BDC canserve as the “fingerprints” of the forcings and thus are helpfulto distinguish and understand the agents driving these changes.In the following, section 2 describes the data and methodsused in this analysis, section 3 presents the results, section4 discusses the mechanisms driving the BDC changes, andsection 5 gives the summary and conclusions.

2. Data and Methods

2.1. Model and Reanalysis Data

[6] We examined the model output from 12 CCMs partici-pating in the Chemistry Climate Model Validation activityphase 2 (CCMVal-2, [Eyring et al., 2005; SPARC CCMVal,2010]). These are the state-of-the-art CCMs that are employedto predict ozone recovery in the recent ozone assessment[WMO, 2011]. Detailed representations of stratospheric dynam-ical, radiative, and chemical processes are included in thesemodels but vary greatly from model to model.[7] We analyzed simulations from the REF-B2 scenario,

which is a transient run from past to future under anthropo-genic forcing. The GHG concentrations in this scenario aretaken from observations before 2000 and from A1B scenariodefined in IPCC [2000] afterward, and the ozone-depletingsubstances are adjusted from halogen emission scenario A1defined in WMO [2007] to include the phaseout of halogenemissions in the 21st century. Except for CMAM, none ofthese models were run with a coupled ocean; instead, theyprescribe sea surface temperature (SST) and sea ice concen-trations (SIC) from IPCC-AR4 20th century and A1B simu-lations. These models also produce simulations under theREF-B1 scenario, in which all forcings and SST/SIC aretaken from the observations. We found these REF-B1 simu-lations to be in general similar to their REF-B2 counterpartsin our analysis, which is also shown in previous studies[SPARC CCMVal, 2010]. More details of these models andscenarios can be found in the SPARC CCMVal [2010], thestudy by Morgenstern et al. [2010b], and references therein.[8] The REF-B2 simulations in most of these models

cover the period of 1960–2098 with two exceptions:UMUKCA-METO ends its REF-B2 simulation in 2084,and GEOSCCM REF-B2 simulation starts in 2000. ForGEOSCCM, we used results from the REF-B1 simulationsfor 1960–1999. No appreciable discontinuity can be foundin the combined time series. We calculated trends for three40-year periods: 1961–2000, 2011–2050, 2059–2098, which

roughly correspond to the ozone depletion, ozone recovery,and stable ozone periods, respectively. Five models havemultiple ensembles (Four models have three ensembles, andone has two ensembles). The ensemble mean for these modelsis used here. Using one ensemble of each model yields verysimilar results.[9] We used ERA–interim reanalysis data [Dee et al.,

2011] to check the simulated BDC climatology. Seviouret al. [2012] found that the BDC is well represented in thisreanalysis data.

2.2. Defining Different BDC Branches

[10] The Lagrangian-mean meridional mass transport bythe BDC can be approximated by the transformed Eulerianmean (TEM) stream function [Andrews et al., 1987]. Figure 1illustrates the annual mean TEM stream function from thesemodels, and the seasonal mean TEM stream functions areplotted in Figure 2. The strength of the BDC is estimated bymass flux across a boundary level calculated from the TEMvelocity. We set three boundary levels and define differentBDC branches by whether they can transport air parcels acrossa certain boundary level. Previous studies (e.g., [Butchartet al., 2006; Butchart et al., 2010; SPARC CCMVal, 2010])employed the upward mass fluxes across 70 hPa to representthe overall strength of the BDC. 70 hPa is the upper boundaryof the tropical tropopause layer [Fu et al., 2007] and roughlythe lower boundary of the “overworld” [Hoskins, 1991;Holton et al., 1995; Rosenlof et al., 1997]. Several studieshave also considered mass fluxes below 70 hPa (e.g.,[Garny et al., 2011]). We thus also examined the massfluxes across 100 hPa, which is roughly the level of themean tropical tropopause. The layer just above tropicaltropopause is referred to as the “tropically controlled transi-tion region” by Rosenlof et al. [1997]. The layer between100 and 70 hPa is the upper part of the transition layer be-tween the stratosphere and the troposphere referred to as the“tropical tropopause layer” [Fueglistaler et al., 2009]. Herewe refer to the branch that can extend beyond 70 hPa as the“stratospheric branch” and the branch that passes across100 hPa but not 70 hPa as the “transition branch.”[11] The stratospheric BDC branch is further divided into

deep and shallow branches with the boundary level of30 hPa. We chose 30 hPa to be the boundary so that the shal-low and the deep branches transport roughly equal amountsof mass. This definition is consistent with that of Birner andBönisch [2011], who defined the shallow and deep BDCbranches based on transit time along trajectories. Our results,however, are not qualitatively sensitive to the choice of theboundary levels. The definition of various BDC branchesis summarized in Figure 1.[12] We use the TEM vertical velocity w* archived in the

CCMVal-2 database and derive w* from the 6-hourly ERA-Interim reanalysis data. Vertical mass flux is then calculatedby horizontally integrating w* weighted by air density andcosine of latitude. We calculated the upward and downwardmass fluxes separately. The upward mass fluxes in thesesimulations are largely confined to the lower latitudes andare closely (but not exactly) balanced by the summationof the downward mass fluxes in each hemispheres. Thestrengths of the transition branch, shallow branch, and deepbranch are estimated by the difference between the upward(or downward) mass fluxes across 100 and 70 hPa, between

LIN AND FU: BREWER DOBSON CIRCULATION IN CCMVAL2

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70 and 30 hPa, and mass flux across 30 hPa, respectively.The northern and southern branches are separated by calcu-lating the downward mass fluxes in each hemisphere.

3. Results

[13] Based on the aforementioned definitions, we calcu-lated mass fluxes associated with various BDC branches

from each model. Table 1 lists the annual mean mass fluxestransported by each BDC branch from multimodelmean (MMM) and ERA interim reanalysis averaged over1980–2009. The reanalysis-derived mass fluxes across 70 hPaagree with previous estimation by Rosenlof [1995] based onstratospheric analysis datasets and radiative heating rate calcu-lation. All BDC branches from MMM agree well with thereanalysis, although the simulated mass fluxes are consistently

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Figure 2. Climatology of seasonal mean TEM stream function from the multimodel mean for 1980–2009in units of 108 kg/s.

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Figure 1. Climatology of annual mean TEM stream function from the multimodel mean for 1980–2009 inunits of 108 kg/s. Positive values for clockwise turning, and negative values for counterclockwise turning.Various branches of the Brewer–Dobson circulation defined in the text are represented by various colors.


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slightly smaller than reanalysis. The relative strength of eachbranch from the models matches that from the reanalysis verywell. Half of the mass ascending through 100 hPa is trans-ported poleward by the transition branches before reaching70 hPa. Then half of the mass ascending through 70 hPa istransported by the shallow branch, and the remaining half istransported by the deep branch. Northern branches are stron-ger than their counterparts in the Southern Hemisphere (SH).[14] Figure 3 compares annual and seasonal mean strength

of the BDC stratospheric branches in each model, MMM,and ERA interim reanalysis. Both shallow and deep branchesare stronger in winter and weaker in summer. The MMMclimatology matches the reanalysis very well in terms of themagnitude and the seasonality of each branch. Individualmodels all capture the correct seasonality. For most models,the simulated annual mean strength of the BDC stratosphericbranch is between 70% and 120% of the reanalysis. Largermodel spread is found in seasonal mean strength, but in gen-eral, the model simulations agree well with the reanalysis.[15] Figure 4 compares annual and seasonal mean strength

of the BDC transition branch in models and reanalysis.Again, the MMM climatology shows excellent agreementwith the reanalysis. The models show larger spread of thestrength in the transition branch than the stratosphericbranch, with a few cases where the simulated transitionbranch is less than 50% of the reanalysis. UMUKCA-METO

and UMUKCA-UCAM (which are based on the sameunderlying climate model) show very weak transition branchyear-around.[16] The temporal evolution of all BDC branches from

past to future is examined in the following sections.

3.1. Stratospheric branches

[17] Figure 5 shows the time series of annual mean massflux anomalies transported by stratospheric BDC and its deepand shallow components for each model. The MMM timeseries are also shown. The steady strengthening of the BDCover the period 1960–2099 is consistently seen in all models,which is also shown in previous studies [Butchart et al., 2006;SPARC CCMVal, 2010]. As shown in the figure, the strength-ening of the shallow branches is the main contributor to theoverall stratospheric BDC trends. The trends of the shallowbranch also dominate the intermodel spread of the BDCtrends. On the other hand, these models also consistently sim-ulate a strengthening in the deep branch, but the change ismuch smaller than the shallow branch.[18] We calculated the seasonal and annual mean trends of

stratospheric BDC branches for 1961–2000, 2011–2050,and 2059–2098. These trends are shown in Figure 6. Therelative trends with respect to the climatology of 1980–2008from the MMM are listed in Table 2. Significant strengthen-ing trends are seen in all seasons, in all three periods, and in

Table 1. Climatology of annual mean mass fluxes (109kg/s) transported by different branches of the Brewer–Dobson circulation for1980–2009 from ERA interim reanalyses (OBS) and multimodel mean (MMM)

Total (100 hPa- ) Transition (100–70 hPa) Stratospheric (70 hPa-) Shallow (70–30 hPa) Deep (30 hPa- )

T T N S T T N S T N S

OBS 12.77 6.19 3.20 2.99 6.59 3.31 1.86 1.44 3.28 1.73 1.54MMM 10.86 5.02 2.83 2.37 5.83 2.87 1.64 1.39 2.96 1.50 1.50

“T” stands for upwelling in the tropics, “N” for downwelling in the Northern Hemisphere, and “S” for downwelling in the Southern Hemisphere.

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Figure 3. Climatology of mass fluxes transported by four stratospheric branches of the Brewer–Dobsoncirculation from ERA interim reanalysis (OBS) and 12 CCM simulations for 1980–2009 for (a) annual mean,(b) December–January–February, (c)March–April–May, (d) June–July–August, and (d) September–October–November. The results from the multimodel mean (MMM) of the 12 CCMs are also shown.


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both shallow and deep branches for MMM. However, shal-low branches in general have stronger trends than theircounterparts in deep branches, and more of them from indi-vidual models pass the statistical significance test. The annualmean stratospheric BDC on average is strengthened by1.1� 108kgs� 1 or 1.8% per decade for the entire period(1960–2099), which is consistent with previous model assess-ments [Butchart et al., 2006; Butchart et al., 2010; SPARCCCMVal, 2010]. Shallow branch contributes 0.8� 108kgs� 1

per decade to the strengthening, and deep branch contributes0.3� 108kgs� 1 per decade. In the relative sense, shallowand deep branches accelerate by 2.7% and 1.0% per decade,respectively. Comparing the MMM trends in the three periods(Figure 6 and Table 2), larger trends in the BDC stratosphericbranch are found in the later period for annual mean and in

each season except for DJF. The acceleration rate of theMMM shallow branch increases with time in all seasons,which is consistent with the continuous increase of GHG con-centration. Two models (Niwa-SOCOL and SOCOL) showmuch stronger acceleration than others in shallow branch for2059–2098 in DJF and MAM. The MMM trends of the shal-low branch excluding these two outliers are still stronger inthe future than in the past (not shown). The MMM deepbranch, on the other hand, does not show stronger accelera-tion in the future than in the past. In DJF, the trends of thedeep branch are considerably weaker in the future than inthe past.[19] In the 1961–2000 period, both shallow and deep

branches show stronger trends in DJF than other seasons.The strengthening of the deep branch in DJF in the past isespecially prominent. As a result, the total stratosphericBDC trend in DJF is about twice as large as those in otherseasons, for both absolute and relative trends. The BDCtrends show less seasonal dependence in the future.[20] We further disaggregated the shallow and the deep

BDC into the northern and the southern branches, and theirtrends are shown in Figure 7. Table 2 summarizes the rela-tive trends in each of the BDC stratospheric branches fromthe MMM. Most deep branch trends are much smaller thantheir shallow branch counterparts. On average, both northernand southern shallow branches accelerate by � 0.4� 108

kgs� 1 or � 2.6% per decade for 1960–2099. For the deepbranch, the northern branch accelerates by 0.2� 108kgs� 1

or 1.3% per decade, and the southern branch accelerates by0.1� 108kgs� 1 or 0.8% per decade.[21] For both northern and southern shallow branches,

(Figures 7a and 7b), MMM trends are stronger in the futureexcept in DJF for the southern shallow branch. Larger spreadamong models and more nonsignificant trends are found inwinter and spring, which is consistent with larger interannualvariability in those seasons. The intermodel spread is espe-cially large for the northern shallow branch in DJF for2059–2098, where trends from two models (Niwa-SOCOLand SOCOL) are more than twice as large as the rest, and

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Figure 4. As in Figure 3, except for the transition branches of the Brewer–Dobson circulation.

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Figure 5. Annual mean mass fluxes anomalies with respectto 1980–2009 climatology for shallow (red lines), deep (bluelines), and stratospheric (black lines) branches of the Brewer–Dobson circulation. Thin lines are for each CCM, and thicklines are for the multimodel mean.


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one model (ULAQ) shows significant deceleration. Theshallow branch acceleration shows weak seasonal depen-dence, with slightly stronger acceleration in winter. How-ever, the strongest relative trends usually are not in winterbecause the climatological mass fluxes are much strongerin winter (see Table 2).[22] For the deep branch, the most drastic changes occur

in the southern branch in DJF (Figure 7d). All but one modelshow strong and significant strengthening in the past. Thesestrengthening trends on average are about 0.5� 108kgs� 1 or10% per decade, with one exceeding 25% per decade (permodel basis). However, none of the models produce signifi-cant acceleration trends in DJF in the future. Ten of the 12models predict deceleration in the southern deep branch for2011–2050, four of which are statistically significant. For2059–2098, all but one model predict nonsignificant trends.While the summer southern deep branch contributes little tothe overall BDC transport in the climatology, its shift intrend from the past to future is so large that the overall strato-spheric BDC trend in DJF is noticeably weaker in the future(Figure 6a). Beyond austral summer, the deep branch shows

larger spread of trends in winter and spring seasons, similarto those in the shallow branch.

3.2. Transition Branches

[23] Figure 8 shows the time series of annual mean massflux anomalies for the BDC transition branch. The strato-spheric branch is also plotted for comparison. As with thestratospheric branch, strengthening of the transition branchover the 140 years from 1960 to 2099 is consistently seenin every model. The acceleration rate of the transition branchis similar to those of the stratospheric branches during thefirst half of the 140 years, and surpasses the stratosphericbranches in the second half. One model (CMAM) showsvery strong acceleration of its transition branch from 2030,which brings its transition branch at the end of the 21stcentury to about twice the strength in 1960.[24] Overall, the models predict an acceleration rate of

1.5� 108kgs� 1 or 3.0% per decade for the transition branchfor 1960–2099, of which, 0.7� 108kgs� 1 per decade is contrib-uted by the Northern Hemisphere (NH), and 0.8� 108kgs� 1

per decade by the SH. The trends in the transition branch for

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Figure 6. Annual and seasonal mean trends in the mass fluxes transported by (a) total stratosphericBDC, (b) shallow branch, and (c) deep branch in units of 108kgs� 1 per decade. Trends are calculatedfor three periods: 1961–2000 (left), 2011–2050 (middle), and 2059–2098 (right). Trends from each modelare indicated by black circle when they are significantly different from zero at 95% confidence level andby red cross when they are not significant. Black diamond and error bar indicate multimodel mean trendsand their 95% confidence intervals. The uncertainty of the multimodel mean trends is estimated from themultimodel mean time series.


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1961–2000, 2011–2050, and 2059–2098 are shown inFigure 9.The corresponding MMM relative trends are listed in Table 3.The MMM trends of the transition branch all indicate signifi-cant acceleration except for the northern branch during2059–2098 in MAM. The acceleration rate of the transitionbranch roughly doubles that of the shallow branch. However,the spatial and temporal distribution of the acceleration ofthe transition branch is very similar to the shallow branch(Figures 7a and 7b vs. Figures 9b and 9c). As with the shallowbranch, stronger acceleration of the transition branch is gener-ally found in the future rather than in the past. The absoluteincrease of mass flux transported by the transition branch isfairly equal among the four seasons, with a slightly largerMMM value and larger model spread in winter. The modelspread is especially large for the northern branch in winterfor the last 40 years of the 21st century. The relative accelera-tion rate of the transition branch is strongest in boreal summerand austral spring.

4. Discussion

[25] The “fingerprints” of GHGs and ozone in driving theBDC changes can be seen in the spatial and temporal distri-butions of BDC trends. Generally speaking, the transition,shallow, and deep branches show continuous accelerationfrom past to future, which is consistent with the continuousincrease of GHGs concentrations. The GHGs “fingerprint”is especially apparent in the shallow and transition branches,since most of them show an increase of acceleration ratewith time with weak seasonal or hemispheric dependence.Changes in ozone concentrations, on the other hand, arenot homogeneous in space and time. They are stronger inthe SH and in the spring season and show opposite trendsin the past and in the future. The effect of this spatial andtemporal behavior would be embedded in the resulting

circulation changes. The ozone’s effect is most perceptiblein the southern deep branch during DJF, which shows strongacceleration as ozone sharply decreases, weak decelerationas ozone slowly recovers, and near-zero trends as ozone sta-bilizes. Hints of ozone’s effect are also seen in the southernshallow branch during DJF and in the northern deep branchduring MAM, which show reduction of trends in the future.This is consistent with previous studies [Li et al., 2008;Garcia and Randel, 2008; Oman et al., 2009] suggestingozone depletion leads to BDC acceleration and vice versa.Recently, McLandress et al. [2010] suggested ozone deple-tion may cause a BDC deceleration in SON (but accelerationin DJF), which may explain the insignificant trends of thesouthern shallow branch seen in almost all models in SON inthe past. However, the deceleration induced by ozone deple-tion in SON is not evident in the southern deep branch. Noozone “fingerprint” can be identified in the transition branch.[26] Ozone and GHGs impact the BDC through different

pathways. Many efforts have been made to understand thedetailed mechanisms driving the BDC changes (e.g., [Rindet al., 1990; Eichelberger & Hartmann, 2005; Li et al.,2008]). Several recent works [Garcia & Randel, 2008;Shepherd & McLandress, 2011] suggest that the increasein GHGs leads to stronger upper tropospheric warming,which strengthens the upper flanks of the subtropical jets,leading to an upward shift in the critical layer. As a result,more waves can penetrate the tropopause and dissipate inthe lower stratosphere. According to the “downward control”principle [Haynes et al., 1991], the vertical mass flux acrossa certain level is determined by wave dissipation above it.The BDC strengthening from this mechanism is thereforeexpected to be largely confined to the lower stratosphere sincethe anomalous wave dissipation is confined to the lowerstratosphere where the subtropical jets intensify. As shownin Figure 10, consistent strengthening and upward expansionof the subtropical jets are seen among different models in bothhemispheres in all three periods considered. This agrees withthe consistent strengthening of the BDC shallow and transi-tion branches in these models.[27] Furthermore, models that show stronger acceleration

in the BDC shallow and transition branches are also themodels with stronger acceleration of zonal wind in the sub-tropical lower stratosphere. Figure 11 shows the trend inthe combined BDC shallow and transition branch (i.e.,between 100 and 30 hPa) for 1960–2099 from each modelversus the zonal wind acceleration at the turnaround latitudeaveraged over 100–30 hPa. A high correlation is foundbetween the two with a correlation coefficient of 0.84.The two outliers (Niwa-SOCOL and SOCOL) showing thestrongest acceleration in the shallow branch in 2059–2098(Figure 6) also show stronger zonal wind acceleration inthe subtropical lower stratosphere than other models (notshown). The zonal wind acceleration in the subtropicallower stratosphere, in turn, is found to be highly correlatedwith the warming in the tropical upper troposphere as shownin Figure 12. This is because the strong warming in thetropical upper troposphere increases the meridional tempera-ture gradient at the subtropical upper troposphere and accel-erates the zonal wind above through thermal wind balance.As shown in the figure, all but one model lay closely alongthe linear fitting line. In the outlier model (ULAQ), thestrong warming in the upper troposphere is found over a

Table 2. Relative trends (% per decade) of the mass fluxes trans-ported by different stratospheric branches of the Brewer–Dobsoncirculation with respect to the 1980–2009 climatology from themultimodel mean

Annual DJF MAM JJA SON

Total stratospheric 1961–2000 1.5 2.3 1.3 1.3 1.02011–2050 1.9 1.9 2.2 2.2 1.52059–2098 2.5 2.4 3.1 2.4 2.3

Shallow 1961–2000 1.8 2.3 1.7 1.8 1.12011–2050 3.0 3.1 3.2 3.4 2.32059–2098 3.9 3.7 4.4 4.1 3.5

Deep 1961–2000 1.3 2.3 0.8 0.9 0.92011–2050 0.9 0.7 1.0 1.2 0.92059–2098 1.2 1.0 1.6 0.9 1.3

N Shallow 1961–2000 1.6 1.5 1.8 2.7 1.22011–2050 3.1 3.4 3.6 3.8 2.12059–2098 3.8 3.6 5.2 5.2 2.5

S Shallow 1961–2000 1.6 4.1 1.3 1.4 0.42011–2050 2.6 2.0 2.6 3.0 2.62059–2098 3.8 3.4 3.5 3.6 5.4

N Deep 1961–2000 1.0 1.1 1.6 –0.3 0.82011–2050 1.4 1.4 0.9 1.8 1.42059–2098 1.7 1.3 3.0 3.0 1.4

S Deep 1961–2000 1.6 10.3 0.5 2.0 1.12011–2050 0.6 –2.9 1.3 1.0 0.22059–2098 0.7 –0.4 0.9 0.6 1.0

Trends that are not significant at 95% confidence level are marked by under-line. Statistical significance is estimated from the multimodel mean time series.


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much wider region extending to � 50∘. Thus, the meridionaltemperature gradient and zonal wind in the subtropics do notincrease much despite the strong warming in this model.(ULAQ is an outlier in regard to several other stratosphericdynamical variables [Butchart et al., 2010].) Overall, the cor-relation between the tropical upper tropospheric warmingand the zonal wind acceleration is 0.81 (0.93 excludingULAQ).[28] Recent studies [Deckert & Dameris, 2008; Garny

et al., 2011] suggest that warmer tropical SST underincreasing GHGs can excite more waves and leads to stron-ger tropical upwelling. These convection-excited waves arelargely trapped in the tropical upper troposphere, so theresulting meridional circulation anomaly is expected to beshallow and narrow, with both ascending and descendinganomalies locating in the tropics [Garny et al., 2011]. Thus,

the net effect of these tropical waves is to redistribute the up-welling within the tropics, but it has little impact on the totalupwelling averaged over the tropics (see also the discussionin Shepherd & McLandress, [2011]). Since our analysis onlyconsidered the integrated mass fluxes over a wide region,much of this type of response would be masked.[29] Ozone depletion and recovery, on the other hand, would

directly affect the strength of the polar night jets, which furtheraffect the propagation of planetary waves in midlatitude/highlatitude. Because the dissipation of these large-scale waves orig-inating in midlatitudes/high latitudes usually occurs at higheraltitudes, it would be expected to affect the BDC deep branch.A moderately strong westerly is favorable for the verticalpropagation of the planetary waves and hence stronger BDC,while easterly and very strong westerly prohibit wave propaga-tion [Charney & Drazin, 1961]. The ozone-induced westerly

−0.5

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eep

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ANN DJF MAM JJA SON

−0.5

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S D

eep

(d)

Figure 7. As in Figure 6, except for (a) northern shallow branch, (b) southern shallow branch, (c) northerndeep branch, and (d) southern deep branch.


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anomalies are therefore efficient in enhancingwave propagationand enhancing BDC only when the background westerlies arerelatively weak. As shown in Figure 10, strong acceleration ofthe circumpolar westerlies is seen in the SH stratosphere duringthe ozone depletion era, which is largely confined in austral

spring and summer (not shown). However, the strong ozone ef-fect in southern deep branch is only found in DJF because thatis when the simulated background westerlies are weak.[30] In contrast, the simulated westerly polar night jets are

relatively strong in SON. Wave propagation is therefore notvery sensitive to stronger westerlies. If the background polarvortex is too strong, the westerly anomalies induced byozone depletion may lead to reduced wave propagation.Thus, a BDC deceleration is expected in this case as sug-gested by McLandress et al. [2010]. This ozone depletion–induced BDC deceleration in spring is hinted in the southernshallow branch in our analysis, where near-zero trends arethe result from a cancellation between GHG increases andozone depletion but is not seen in the deep branch.[31] In the NH, the polar night jets are weaker than those

in the SH, and the ozone effect would be expected to bestrong in boreal spring. The MMM NH polar jets in MAMaccelerate in the past and decelerate in the future (notshown). This is consistent with the reduction of accelerationrate in the northern deep branch from past to future in MAM.Overall speaking, the ozone effect is weaker in the NH thanin the SH.[32] While the results presented in this paper appear to be

robust among models, one needs to keep in mind that therecould be biases in the model simulations compared toreality. Several studies [Fu et al., 2010; Ueyama & Wallace,2010] inferred the BDC changes over the past few decadesfrom lower stratospheric temperature measurements and

1960 1980 2000 2020 2040 2060 2080 2100−2

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Year

Mas

s F

lux

Ano

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ies

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trans.

Figure 8. As in Figure 5, except for transition (green lines)and stratospheric (black lines) branches of the Brewer–Dobsoncirculation.

0

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8

Tra

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.

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Figure 9. As in Figure 6,except for (a) total transition branch, (b) northern transition branch, and(c) southern transition branch.


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found anticorrelation between temperature variations in thetropics and polar regions on interannual and decadal scales.Young et al. [2011] further showed that the anticorrelationexist throughout the stratosphere. These temperature signalssuggest that changes in the BDC deep branch may bethe main players. Observational analyses [Lin et al., 2009;Fu et al., 2010; Young et al., 2012] have also shown thatthe strongest BDC acceleration occurs in austral spring butchanges little in summer, which does not agree with themodel simulations analyzed here. This discrepancy in

Table 3. As in Table 2, except for the transition branches of theBrewer–Dobson circulation

Annual DJF MAM JJA SON

Total transition 1961–2000 1.6 1.3 1.5 2.1 1.82011–2050 3.3 3.4 2.6 3.9 3.52059–2098 3.9 3.4 2.3 5.1 5.4

N transition 1960–2000 1.5 1.1 1.3 3.0 1.32011–2050 2.6 3.0 1.5 4.3 2.22059–2098 2.8 2.2 0.3 6.0 4.0

S transition 1960–2000 1.7 1.4 1.5 1.6 2.42011–2050 3.6 3.6 3.0 3.4 5.02059–2098 4.6 5.5 3.5 4.1 6.7

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103

−0.9 −0.6 −0.3 0 0.3 0.6 0.9

Figure 10. Annual mean zonal wind trends (color contours)and climatology (black contours) for (a) 1961–2000, (b)2011–2050, and (c) 2059–2098 from multimodel mean.The trends are in units of ms� 1/decade with contour inter-val 0.15ms� 1/decade. The statistical significance of themultimodel mean trends against the intermodel spread isestimated by Student’s t test at 99% confidence level, andsignificant trends are indicated by filled contours. The zonalwind climatology are plotted with contour interval 10ms� 1.For clarity, only westerlies are plotted.

0.2 0.4 0.6 0.8

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U Trend (m s−1/decade)

Mas

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ade)

CAM3_5CCSRNIESCMAMGEOSCCMLMDZreproMRINiwa_SOCOLSOCOLULAQUMUKCA_METOUMUKCA_UCAMWACCM

Figure 11. Scatterplot of the trends in mass fluxes forthe combined BDC shallow and transition branch versus thezonal wind trends at the “turnaround” latitude averaged over100–30 hPa. The trends are calculated for 1960–2099. Theturnaround latitude is where w* change signs from positivein the tropics to negative in the extratropics. We defined theturnaround latitude in the w* climatology. It varies with modeland level but is usually around 30∘ in both hemispheresbetween 100 and 30 hPa.

0.3 0.4 0.5 0.6 0.70.2

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T Trends (K/decade)

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rend

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s−

1 /dec

ade)

CAM3_5CCSRNIESCMAMGEOSCCMLMDZreproMRINiwa_SOCOLSOCOLULAQUMUKCA_METOUMUKCA_UCAMWACCM

Figure 12. Scatter plot of the zonal wind trend at the turn-around latitude averaged over 100–30 hPa versus the tem-perature trend at 150 hPa averaged over 20∘S� 20∘N. Thetrends are calculated for 1960–2099. The turnaround lati-tude is defined in Figure 11.


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seasonality may relate to a well-known deficit of these mod-els: they tend to produce a too-strong and persistent polarvortex in the SH (e.g., [SPARC CCMVal, 2010; Butchartet al., 2011; Gerber et al., 2010]).[33] Recently, studies suggested the current general circu-

lation models overestimate the tropical upper troposphericwarming in response to GHGs increase [Fu et al., 2011;Po-Chedley & Fu, 2012]. If this were true, then the strength-ening in the BDC shallow and transition branches, whichdominates the overall simulated BDC strengthening, wouldalso be overestimated in the model simulations.

5. Summary and Conclusions

[34] In this paper, we analyzed the simulated BDC from 12CCMVal-2 CCMs from 1960 to the end of the 21st century.The BDC is divided into transition, stratospheric shallow,and deep branches based on its vertical extent and furtherinto northern and southern branches. For air mass ascendingthrough 100 hPa, about half the mass is transported pole-ward by the transition branch, and the shallow and deepbranches each transport one quarter. Overall strengtheningis seen in all three branches over the 140 years, but contribu-tion from the deep branch is much less than one quarter.Most BDC acceleration is found in shallow and transitionbranches, which distributes fairly evenly among the fourseasons and between the two hemispheres.[35] We compared the BDC trends in each branch over the

past few decades, during the early 21st century and near theend of the 21st century, and found continuous BDC acceler-ation except in the southern deep branch during australsummer. Models consistently simulated strong accelerationof the austral summer deep cell in the past, but decelerationduring the early 21st century, and near-zero trends near theend of the 21st century. Most of the models show strongeracceleration rate of the transition and shallow branches inthe future than in the past.[36] The spatial and temporal distribution of the BDC

trends shows the distinct fingerprints of ozone and GHGforcing. Ozone’s influence on the BDC is manifested in thesouthern deep branch during austral summer and is alsohinted in the northern and southern deep branches in springand the southern shallow branch in spring and summer.Beyond these specific branches in these specific seasons,the BDC changes are dominated by the GHGs-related con-tinuous acceleration.[37] While most of the results presented here are robust

across models, relatively large intermodel spread is seen inthe trends associated with the shallow and transitionbranches, especially in the NH and in winter. Part of theintermodel spread can be explained by the differences ofsimulated wind changes, which in turn are largely causedby warming in the tropical upper troposphere. Furthermore,some of the results that are robust across models mightnot necessarily agree with observations. Further research isrequired to reconcile the model-predicted BDC strengtheningwith observations.

[38] Acknowledgments. We thank Profs. J. M. Wallace and D. L.Hartmann for useful discussions. We acknowledge the modeling groupsfor making their simulations available for this analysis, the Chemistry-ClimateModel Validation (CCMVal) Activity for WCRP’s (World Climate ResearchProgramme) SPARC (Stratospheric Processes and their Role in Climate)

project for organizing and coordinating the model data analysis activity, andthe British Atmospheric Data Center (BADC) for collecting and archivingthe CCMVal model output. European Centre for Medium-Range WeatherForecasts (ECMWF) ERA-Interim data used in this study have been obtainedfrom the ECMWF data server. This work is supported by NASA grantsNNX09AH73G and NNX11AE544. It is also in part supported by theNational Basic Research Program of China (2010CB428604) and the NationalScience Foundation of China under grant 41275070.

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