math, models, and climate change · the “ozone hole,” was first observed in the early 1980s....
TRANSCRIPT
Math, Models, and Climate Change How shaving cream moved a jet stream, and how mathematics can help us better understand why
Edwin P. GerberCenter for Atmosphere and Ocean ScienceCourant Institute of Mathematical SciencesNew York University
9 October 2013 - Wichita State University
Support for this research was provided by the U.S. National Science Foundation.
Anthropogenic Climate Change
Global Warming Ozone Holevs.
chlorofluorcarbons(CFCs such as freon)
greenhouse gasesCO2, CH4, N2O
Global Warming Ozone Hole
[IPCC 2013 Assessment Report]
vs.
Anthropogenic Climate Change
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Do Not Cite, Quote or Distribute& 0A23,& B@*$%&7$C/=D&2E3&
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Figure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
Global Warming Ozone Hole
[IPCC 2013 Assessment Report]
vs.
Anthropogenic Climate Change
!"#$%&'($)*&+,&-.#/&01234& 56$7*/(&0& 8955&:;8&!")*6&<==/==>/#*&?/7@(*&
Do Not Cite, Quote or Distribute& 0A23,& B@*$%&7$C/=D&2E3&
&
Figure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
The severe depletion of Antarctic ozone, known asthe “ozone hole,” was first observed in the early 1980s.The depletion is attributable to chemical destruction byreactive halogen gases, which increased in the strato-sphere in the latter half of the 20th century (see Q16).Conditions in the Antarctic winter stratosphere are highlysuitable for ozone depletion because of (1) the longperiods of extremely low temperatures, which promotepolar stratospheric cloud (PSC) formation; (2) the abun-dance of reactive halogen gases, which chemically destroyozone; and (3) the isolation of stratospheric air during thewinter, which allows time for chemical destruction tooccur (see Q10). The severity of Antarctic ozone deple-tion can be seen using satellite observations of total ozone,ozone altitude profiles, and long-term average values ofpolar total ozone.
Antarctic ozone hole. The most widely used imagesof Antarctic ozone depletion are those from space-basedmeasurements of total ozone. Satellite images madeduring Antarctic winter and spring show a large regioncentered near the South Pole in which total ozone is highlydepleted (see Figure Q11-1). This region has come to becalled the “ozone hole” because of the near-circular con-tours of low ozone values in the images. The area of theozone hole is defined here as the area contained withinthe 220-Dobson unit (DU) contour in total ozone maps(light blue color in Figure Q11-1). The maximum areahas reached 25 million square kilometers (about 10 mil-lion square miles) in recent years, which is nearly twicethe area of the Antarctic continent (see Figure Q11-2).Minimum values of total ozone inside the ozone hole aver-aged in late September have reached below 100 DU,which is well below normal springtime values of about200 DU (see Figure Q11-2).
Altitude profiles of Antarctic ozone. Ozone withinthe “ozone hole” is also measured using balloonborneinstruments (see Q5). Balloon measurements showchanges within the ozone layer, the vertical region thatcontains the highest ozone abundances in the stratosphere.At geographic locations where the lowest total ozone
values occur in ozone hole images, balloon measurementsshow that the chemical destruction of ozone is completeover a vertical region of several kilometers. Balloon
TWENTY QUESTIONS: 2006 UPDATE
Q.22
III. STRATOSPHERIC OZONE DEPLETION
Q11: How severe is the depletion of the Antarctic ozone layer?
100 300 400 500Total OzTT one (Dobson units)
4 October 2001
200
Antarctic Ozone Hole
Figure Q11-1. Antarctic “ozone hole.” Total ozonevalues are shown for high southern latitudes as meas-ured by a satellite instrument. The dark blue and purpleregions over the Antarctic continent show the severeozone depletion or “ozone hole” now found during everyspring. Minimum values of total ozone inside the ozonehole are close to 100 Dobson units (DU) compared withnormal springtime values of about 200 DU (see Q4). Inlate spring or early summer (November-December) theozone hole disappears in satellite images as ozone-depleted air is displaced and mixed with ozone-rich airtransported poleward from outside the ozone hole.
Severe depletion of the Antarctic ozone layer was first observed in the early 1980s. Antarctic ozone depletionis seasonal, occurring primarily in late winter and early spring (August-November). Peak depletion occurs inearly October when ozone is often completely destroyed over a range of altitudes, reducing overhead totalozone by as much as two-thirds at some locations. This severe depletion creates the “ozone hole” in imagesof Antarctic total ozone made from space. In most years the maximum area of the ozone hole far exceeds thesize of the Antarctic continent.
Antarctic Ozone Hole
[WMO 2006 Ozone Assessment]
How does anthropogenic forcing affect the atmospheric circulation?
[Image from wikipedia]
But first, what drives the atmospheric circulation?
r=6371 km
troposphere ~ 10 km
But first, what drives the atmospheric circulation?
(not drawn to scale)
But first, what drives the atmospheric circulation?Short answer: differential heating!
solar radiation: heat from below,
and more at the equator
But first, what drives the atmospheric circulation?Short answer: differential heating!
atmosphere transportsenergy (heat and moisture)upwards and polewards
Early ideas: George C. Hadley (1735)
a cell that transportsheat in the meridional
direction
↺
Early ideas: George C. Hadley (1735)
as low level winds approach equator,
they will turn westwardto conserve momentum:
the trade winds
What about the upper level winds?
(no one really worried aboutupper level winds until the
20th century)
.
What about the upper level winds?
x
xx.
osurface windskept in check
by friction
x but upper levelwinds are generate
strong eastward (westerly) jets,
generating strongvertical shear
o.
.
An unstable situation...
⚡Hadley’s singlecell is unstable
(baroclinic instability)
[Charney, 1947; Eady 1949]
Flow is fundamentally not zonally symmetric
⚡Hadley’s singlecell is unstable
(baroclinic instability)
Generates Rossby waves, whose
restoring force is the differential rotation of
the planet.[Rossby et al. 1939]
Meridional structure of the atmospheric circulation
Hadley Cell
Ferrel Cell
Polar Cell
Instability breaks upthe meridional circulation
into three cells
⚡
Hadley Cell
Ferrel Cell
Polar Cell
William Ferrel (1817-1891)
Instability breaks upthe meridional circulation
into three cells
⚡
Meridional structure of the atmospheric circulation
The “eddies,” or deviations from the zonal mean play a critical role in the circulation
Hadley Cell
Ferrel Cell
Polar Cell
⚡
Rossby waves andeddies transport heat and momentum - necessary
to explain the zonal mean.
[Lorenz, 1967]
The circulation in all its glory ...
The brightness (equivalent blackbody) temperature
The circulation in all its glory ...
The brightness (equivalent blackbody) temperature
Latitude
80S 60S 40S 20S EQ 20N 40N 60N 80N
20
50
200
500
8501000 20
15105
0510152025303540455055
ERA40 DJF zonal mean zonal wind [u]
20 km
pres
sure
(hP
a)
10 km
0 km
=120 mph
The jet streams in austral summer (Dec.-Feb.)
m/s
The jet streams in austral summer (Dec.-Feb.)Recent trends
2000–2079 in the CCMVal!2 REF!B2 and AR4 A1B sce-nario integrations. An exception is section 3.1, where trendsare calculated for the period 1979–1999 to be comparedwith reanalysis data, and for the period 2001–2050 to becompared with the previous CCMVal activity (CCMVal!1).Past climate changes are analyzed for a relatively longperiod of 40 years, mainly because O3 depletion beganbefore 1979; observations have shown that O3 concentrationstarted to decrease in the late 1960s, although early trendsare quite weak [e.g., Solomon, 1999, Figure 1]. The longerperiod also allows us to obtain better statistics and compareour results with previous studies. The analysis length forfuture climate change is twice as long as that for past climatechange because O3 recovery is predicted to be slower thanits depletion in the past. The CCMVal!2 models predict thattotal column O3 over the Antarctic will likely reach its 1980value around 2060 [Austin et al., 2010]. Although the
analysis period is somewhat subjective, results are onlyweakly sensitive to the choice of time period. It is found thattrends over 2000–2049 are quantitatively similar to thoseover 2000–2079, although the intermodel standard deviationis somewhat larger.[13] Stratospheric O3 has strong seasonality and its long!
term trend is largest in the late spring. Its impact on the tro-pospheric circulation, however, is delayed by a few monthsand reaches a maximum in the summer, December–February(DJF) [Gillett and Thompson, 2003; Shindell and Schmidt,2004; Perlwitz et al., 2008; Son et al., 2008]. Hence, mostanalyses in this study are carried out for the SH summer.
3. Results
[14] We first evaluate the CCMVal!2 models by com-paring the spatial and temporal structure of the zonal mean
Figure 1. The long!term mean (thick orange) and linear trend (thin black contour) of DJF [u] over1979–1999: (a) CCMVal!2 REF!B1 multimodel mean, (b) ERA40, and (c) NCEP!NCAR reanalysisdata. (d) Future trends over 2000–2079 as simulated by the CCMVal!2 REF!B2 models. Contour intervalsof climatological wind and trend are 10 m s!1 starting from 10 m s!1 and 0.4 m s!1/decade, respectively. InFigures 1a and 1d, multimodel mean values exceeding 1 standard deviation are shaded. In Figures 1b and1c, trends which are statistically significant at the 95% confidence level are shaded. Zero contours are omit-ted in all plots.
SON ET AL.: OZONE AND SOUTHERN HEMISPHERE CLIMATE D00M07D00M07
4 of 18
[Son et al. 2010]
20 km
pres
sure
(hP
a)
10 km
0 km
DJF Trends in zonal mean zonal wind
late 20th century
[Son et al. 2008;Gerber et al. 2011]
reanalysis
DJF Trends in zonal mean zonal wind
reanalysis
late 20th century
models w/GHGs models w/ GHGs+O3
[Son et al. 2008;Gerber et al. 2011]
DJF Trends in zonal mean zonal wind
reanalysis
late 20th century
models w/GHGs models w/ GHGs+O3
[Son et al. 2008;Gerber et al. 2011]
DJF Trends in zonal mean zonal wind
late 20th century
predictions 2000-2079
?
[Son et al. 2008;Gerber et al. 2011]
reanalysis models w/GHGs models w/ GHGs+O3
Questions
• What are the relative roles of greenhouse gases and ozone in forcing Southern Hemisphere circulation changes?
• What causes uncertainty in the circulation response? (That is, why is there such variance in model projections?)
• How can we reduce the uncertainty in the circulation response?
• Coupled Models (CMIP3,5 Coupled Model Intercomparison Project, phases 3,5)
• simulate the atmosphere, ocean, and land surface (a “coupled” simulation between the key components of the climate system)
• our best tool for quantitative prediction of climate change
• Chemistry Climate Models (CCMs)
• simulate interactive ozone chemistry in the stratosphere: can predict ozone hole and its recovery
• generally specify the surface ocean temperatures (not a coupled simulation)
• Idealized Atmospheric Models
• primitive equation dynamics on the sphere (guts of an atmospheric model)
• simplified climate physics (no radiation, clouds, moisture)
Century II Performing Arts Center
(cast, in order of decreasing CPU time)
Temperature Signature of Anthropogenic Forcing
hPa (a)
Temperature change, 1960 1999
Mod
els
with
fixe
d oz
one 200
400
600
800
1000
(b)
Temperature change, 2000 2079
hPa
latitude
(c)
Mod
els
with
var
ying
ozo
ne
60S 30S 0 30N 60N
200
400
600
800
1000
latitude
°C
(d)
60S 30S 0 30N 60N
10 8 6 4 2 0 2 4 6 8
hPa (a)
Temperature change, 1960 1999
Mod
els
with
fixe
d oz
one 200
400
600
800
1000
(b)
Temperature change, 2000 2079
hPa
latitude
(c)M
odel
s w
ith v
aryi
ng o
zone
60S 30S 0 30N 60N
200
400
600
800
1000
latitude
°C
(d)
60S 30S 0 30N 60N
10 8 6 4 2 0 2 4 6 8
hPa (a)
Temperature change, 1960 1999
Mod
els
with
fixe
d oz
one 200
400
600
800
1000
(b)
Temperature change, 2000 2079
hPa
latitude
(c)
Mod
els
with
var
ying
ozo
ne
60S 30S 0 30N 60N
200
400
600
800
1000
latitude
°C
(d)
60S 30S 0 30N 60N
10 8 6 4 2 0 2 4 6 8
Temperature Signature of Anthropogenic Forcing
hPa (a)
Temperature change, 1960 1999
Mod
els
with
fixe
d oz
one 200
400
600
800
1000
(b)
Temperature change, 2000 2079
hPa
latitude
(c)
Mod
els
with
var
ying
ozo
ne
60S 30S 0 30N 60N
200
400
600
800
1000
latitude
°C
(d)
60S 30S 0 30N 60N
10 8 6 4 2 0 2 4 6 8
Temperature Signature of Anthropogenic Forcing
Circulation responds to changes in temperature gradients
Butler et al. 2010
FIG. 2. The zonal-mean response to tropical tropospheric heating. Bold black lines in all plots represent the control run tropopauseheight. (left) The thermal forcing (K day21). (middle) The total eddy heat flux response (shading) (K m s21) and the temperature re-sponse (contours) (K). (right) The total eddy momentum flux response (shading) (m2 s22) and the zonal-mean zonal wind response(contours) (m s21). (a) Results for tropical upper-tropospheric heating; (b) results for shallow tropical upper-tropospheric heating;(c) results for narrow tropical upper-tropospheric heating; (d) results for tropical heating centered at 500 hPa. Note the forcings are shownpole–pole but the responses are shown for only one hemisphere. The thermal forcings are detailed in Table 1.
1 JULY 2010 BUTLER ET AL . 3481
GHG-likewarming
Butler et al. 2010
FIG. 2. The zonal-mean response to tropical tropospheric heating. Bold black lines in all plots represent the control run tropopauseheight. (left) The thermal forcing (K day21). (middle) The total eddy heat flux response (shading) (K m s21) and the temperature re-sponse (contours) (K). (right) The total eddy momentum flux response (shading) (m2 s22) and the zonal-mean zonal wind response(contours) (m s21). (a) Results for tropical upper-tropospheric heating; (b) results for shallow tropical upper-tropospheric heating;(c) results for narrow tropical upper-tropospheric heating; (d) results for tropical heating centered at 500 hPa. Note the forcings are shownpole–pole but the responses are shown for only one hemisphere. The thermal forcings are detailed in Table 1.
1 JULY 2010 BUTLER ET AL . 3481
FIG. 2. The zonal-mean response to tropical tropospheric heating. Bold black lines in all plots represent the control run tropopauseheight. (left) The thermal forcing (K day21). (middle) The total eddy heat flux response (shading) (K m s21) and the temperature re-sponse (contours) (K). (right) The total eddy momentum flux response (shading) (m2 s22) and the zonal-mean zonal wind response(contours) (m s21). (a) Results for tropical upper-tropospheric heating; (b) results for shallow tropical upper-tropospheric heating;(c) results for narrow tropical upper-tropospheric heating; (d) results for tropical heating centered at 500 hPa. Note the forcings are shownpole–pole but the responses are shown for only one hemisphere. The thermal forcings are detailed in Table 1.
1 JULY 2010 BUTLER ET AL . 3481
GHG-likewarming
The circulation response to thermal forcing in an idealized, dry atmospheric model
the cooling while continuing to allow the upper bound ofthe cooling to extend through the top of the stratosphere.When the center of the heating is lifted by 25 hPa (Fig.5b), the amplitude of the response is damped by ;50%,but the structure of the response is unchanged and thekey features remain significant: the heat fluxes are stillanomalously positive in the polar stratosphere, the upper-tropospheric momentum fluxes are still anomalouslypoleward across 508 latitude, and the surface zonal flow isstill anomalously easterly along ;408 and westerly along;608 latitude (see also Table 4). However, when thecenter of the heating is lifted by 50 hPa (Fig. 5c), thebarotropic component of the tropospheric responselargely vanishes.The sensitivity of the tropospheric response to polar
stratospheric cooling is investigated further in Fig. 6. We
again examine the effect of lifting the cooling, but in thiscase the depth of the cooling is only;100 hPa. Figure 6ashows results for shallow cooling centered at 200 hPa.The structure of the response is largely unchanged fromthat shown in the top of Fig. 5, albeit the amplitude ofthe response is weaker. Note that in the case of shallowcooling the increased heat fluxes in the polar strato-sphere are confined to the levels where cooling is oc-curring (Fig. 6a, middle panel). Figures 6b,c show resultsfor the same shallow cooling, but in these cases thecooling has been lifted by 25 hPa (Fig. 6b) and 50 hPa(Fig. 6c). Lifting the cooling has little effect on the changesin polar stratospheric temperatures (middle column), but ithas a dramatic effect on the changes in the troposphericcirculation (right column). When the cooling is liftedby 25 to 175 hPa (Fig. 6b), the tropospheric response
FIG. 5. As in Fig. 2, but for (left) the responses to the polar stratospheric thermal forcings. The forcings are documented in Table 1 and arecentered at (a) 100, (b) 75, and 50 hPa (c). (right) Note the shading scaling is about half that for Fig. 2.
3484 JOURNAL OF CL IMATE VOLUME 23
The circulation response to thermal forcing in an idealized, dry atmospheric model
Butler et al. 2010
FIG. 2. The zonal-mean response to tropical tropospheric heating. Bold black lines in all plots represent the control run tropopauseheight. (left) The thermal forcing (K day21). (middle) The total eddy heat flux response (shading) (K m s21) and the temperature re-sponse (contours) (K). (right) The total eddy momentum flux response (shading) (m2 s22) and the zonal-mean zonal wind response(contours) (m s21). (a) Results for tropical upper-tropospheric heating; (b) results for shallow tropical upper-tropospheric heating;(c) results for narrow tropical upper-tropospheric heating; (d) results for tropical heating centered at 500 hPa. Note the forcings are shownpole–pole but the responses are shown for only one hemisphere. The thermal forcings are detailed in Table 1.
1 JULY 2010 BUTLER ET AL . 3481
the cooling while continuing to allow the upper bound ofthe cooling to extend through the top of the stratosphere.When the center of the heating is lifted by 25 hPa (Fig.5b), the amplitude of the response is damped by ;50%,but the structure of the response is unchanged and thekey features remain significant: the heat fluxes are stillanomalously positive in the polar stratosphere, the upper-tropospheric momentum fluxes are still anomalouslypoleward across 508 latitude, and the surface zonal flow isstill anomalously easterly along ;408 and westerly along;608 latitude (see also Table 4). However, when thecenter of the heating is lifted by 50 hPa (Fig. 5c), thebarotropic component of the tropospheric responselargely vanishes.The sensitivity of the tropospheric response to polar
stratospheric cooling is investigated further in Fig. 6. We
again examine the effect of lifting the cooling, but in thiscase the depth of the cooling is only;100 hPa. Figure 6ashows results for shallow cooling centered at 200 hPa.The structure of the response is largely unchanged fromthat shown in the top of Fig. 5, albeit the amplitude ofthe response is weaker. Note that in the case of shallowcooling the increased heat fluxes in the polar strato-sphere are confined to the levels where cooling is oc-curring (Fig. 6a, middle panel). Figures 6b,c show resultsfor the same shallow cooling, but in these cases thecooling has been lifted by 25 hPa (Fig. 6b) and 50 hPa(Fig. 6c). Lifting the cooling has little effect on the changesin polar stratospheric temperatures (middle column), but ithas a dramatic effect on the changes in the troposphericcirculation (right column). When the cooling is liftedby 25 to 175 hPa (Fig. 6b), the tropospheric response
FIG. 5. As in Fig. 2, but for (left) the responses to the polar stratospheric thermal forcings. The forcings are documented in Table 1 and arecentered at (a) 100, (b) 75, and 50 hPa (c). (right) Note the shading scaling is about half that for Fig. 2.
3484 JOURNAL OF CL IMATE VOLUME 23
FIG. 2. The zonal-mean response to tropical tropospheric heating. Bold black lines in all plots represent the control run tropopauseheight. (left) The thermal forcing (K day21). (middle) The total eddy heat flux response (shading) (K m s21) and the temperature re-sponse (contours) (K). (right) The total eddy momentum flux response (shading) (m2 s22) and the zonal-mean zonal wind response(contours) (m s21). (a) Results for tropical upper-tropospheric heating; (b) results for shallow tropical upper-tropospheric heating;(c) results for narrow tropical upper-tropospheric heating; (d) results for tropical heating centered at 500 hPa. Note the forcings are shownpole–pole but the responses are shown for only one hemisphere. The thermal forcings are detailed in Table 1.
1 JULY 2010 BUTLER ET AL . 3481
GHG-likewarming
ozone-likecooling
Which forcing has dominated to date?
A Simple Model of the Jet Response
jet shift = ozone pull + GHG push
model simulations give us the forcings and response
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Quantifying the temperature forcing
hPa (a)
Temperature change, 1960 1999
Mod
els
with
fixe
d oz
one 200
400
600
800
1000
(b)
Temperature change, 2000 2079
hPa
latitude
(c)
Mod
els
with
var
ying
ozo
ne
60S 30S 0 30N 60N
200
400
600
800
1000
latitude
°C
(d)
60S 30S 0 30N 60N
10 8 6 4 2 0 2 4 6 8
ΔTO3
ΔTGHG
A Simple Model of the Jet Response
jet shift = ozone pull + GHG push
model simulations give us the forcings and response
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
2000–2079 in the CCMVal!2 REF!B2 and AR4 A1B sce-nario integrations. An exception is section 3.1, where trendsare calculated for the period 1979–1999 to be comparedwith reanalysis data, and for the period 2001–2050 to becompared with the previous CCMVal activity (CCMVal!1).Past climate changes are analyzed for a relatively longperiod of 40 years, mainly because O3 depletion beganbefore 1979; observations have shown that O3 concentrationstarted to decrease in the late 1960s, although early trendsare quite weak [e.g., Solomon, 1999, Figure 1]. The longerperiod also allows us to obtain better statistics and compareour results with previous studies. The analysis length forfuture climate change is twice as long as that for past climatechange because O3 recovery is predicted to be slower thanits depletion in the past. The CCMVal!2 models predict thattotal column O3 over the Antarctic will likely reach its 1980value around 2060 [Austin et al., 2010]. Although the
analysis period is somewhat subjective, results are onlyweakly sensitive to the choice of time period. It is found thattrends over 2000–2049 are quantitatively similar to thoseover 2000–2079, although the intermodel standard deviationis somewhat larger.[13] Stratospheric O3 has strong seasonality and its long!
term trend is largest in the late spring. Its impact on the tro-pospheric circulation, however, is delayed by a few monthsand reaches a maximum in the summer, December–February(DJF) [Gillett and Thompson, 2003; Shindell and Schmidt,2004; Perlwitz et al., 2008; Son et al., 2008]. Hence, mostanalyses in this study are carried out for the SH summer.
3. Results
[14] We first evaluate the CCMVal!2 models by com-paring the spatial and temporal structure of the zonal mean
Figure 1. The long!term mean (thick orange) and linear trend (thin black contour) of DJF [u] over1979–1999: (a) CCMVal!2 REF!B1 multimodel mean, (b) ERA40, and (c) NCEP!NCAR reanalysisdata. (d) Future trends over 2000–2079 as simulated by the CCMVal!2 REF!B2 models. Contour intervalsof climatological wind and trend are 10 m s!1 starting from 10 m s!1 and 0.4 m s!1/decade, respectively. InFigures 1a and 1d, multimodel mean values exceeding 1 standard deviation are shaded. In Figures 1b and1c, trends which are statistically significant at the 95% confidence level are shaded. Zero contours are omit-ted in all plots.
SON ET AL.: OZONE AND SOUTHERN HEMISPHERE CLIMATE D00M07D00M07
4 of 18
A Simple Model of the Jet Response
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
two unknowns
jet shift = ozone pull + GHG push
A Simple Model of the Jet Response
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
two equations1960-1999 trends 2000-2079 trends
[Perlwitz et al. 2008]
specified at the lower boundary of the model. Aspects ofstratospheric ozone-temperature coupling and the climatol-ogy of the SH polar vortex have been evaluated by Stolarskiet al. [2006], Eyring et al. [2006] and Pawson et al. [2008].The model captures the main aspects of the global couplingbetween ozone and temperature. As with other CCMs, theAntarctic vortex breaks down too late in the season. Otherweaknesses of the GEOS CCM are too much year-to-yearvariability in the vortex structure, a high initial bias in totalozone and a warm bias in lower stratospheric temperaturewhen there is no chlorine-induced ozone loss, which meanthat Antarctic ozone loss and ozone-induced cooling areoverestimated [Pawson et al., 2008].[6] We analyze two simulations of the recent past (P-1
and P-2) and three C21 simulations (C21-HSST, C21-CSSTand C21Cl1960). The atmospheric and lower boundaryforcings of these transient simulations are summarized inTable 1. Simulations P-1 and P-2, starting from differentinitial conditions, are forced with observed changes in SSTand sea ice (HadISST [Rayner et al., 2003]), GHG concen-trations and halogens. GHG concentrations in the C21 runsfollow IPCC scenario A1b (medium, SRESA1B). In C21-HSST and C21-CSST, the halogens are prescribed accord-ing to the Ab scenario [World Meteorological Organization/United Nations Environment Programme, 2003], while inC21Cl1960, chlorine is fixed at 1960 values. SST and seaice distribution for the C21 simulations are taken fromsingle AR4 SRESA1b simulations with the coupledocean-atmosphere models HadGEM1 (C21-HSST) andCCSM3.0 (C21-CSST, C21Cl1960). Run C21-HSST wasincluded in the multi-model analysis of Eyring et al. [2007].
3. Results From GEOS CCM
[7] Figure 1 shows the time series of 70-hPa minimumzonal mean ozone mixing ratio (OMR-min) reached be-tween 90!S and 60!S on any day in October. Around year1960, OMR-min is about 2.7 ppmv. Stratospheric halogenincreases cause the strong decline of OMR-min to less than0.1 ppmv. Although 1980 is commonly used as a baselineagainst which ozone depletion and recovery are evaluated,some Antarctic ozone is lost as halogen emissions increasein the 1970s. In the GEOS simulations, about 10% of thetotal Antarctic ozone is lost between 1970 and 1980[Pawson et al., 2008, Figure 14]. As the stratospherichalogen loading decreases through the C21, the Antarcticozone hole recovers. By the end of the C21, OMR-minreaches 1970 values. In C21Cl1960, OMR-min variesaround 2.8 ppmv.[8] Figure 2 compares SH climate change for 1969 to
1999 (period I) and 2006 to 2094 (period II). The change foreach period is defined as the difference between 11-year
means centered on 1999 and 1969 (Period I) and 2094 and2006 (period II). Monthly changes in polar cap (90!S to64!S) ozone and temperature, and in mid-latitude (70!S to50!S) zonal-mean zonal wind are investigated. In addition,three-month overlapping changes in the SAM index basedon the surface pressure difference between 65!S and 40!S[Gong and Wang, 1999] are shown.[9] Figures 2a, 2c, 2e, and 2g (Figures 2b, 2d, 2f, and 2h)
show the results for period I (II) based on the ensemblemean of simulations P-1 and P-2 (C21-HSST and C21-CSST). The results discussed are very similar for the twoindividual simulations. They are significant on the monthlytime scale in the stratosphere (99% level) and on theseasonal time scale in the troposphere (95% level).[10] Between 1969 and 1999 in P-1 and P-2, ozone loss
over the polar cap migrates down from near 10 hPa inAugust to near 200 hPa in November, with largest lossbetween 50 and 70 hPa during October (Figure 2a). (Tro-pospheric ozone in GEOS CCM is represented by relaxationto climatology, so no trends are expected.) Polar ozone lossforces lower stratospheric cooling in the polar cap(Figure 2c), most pronounced at 100 hPa in December.[11] The polar cooling increases the meridional tempera-
ture gradient and causes westerly zonal wind anomalies inthe stratosphere (Figure 2e). Changes in tropospheric west-erlies maximize during December and January, lagging thestratospheric zonal wind changes by one month. The SAM
Table 1. Time Period, SST Data Set, Scenarios for Halogens and GHGs for GEOS CCM Experiments
Experiment Time Period SST Halogens Greenhouse Gases
P-1 1950–2004 Had1SST Observed ObservedP-2 1951–2004 Had1SST Observed ObservedC21-HSST 1996–2099 HadGEM1 WMO Baseline scenario Ab IPCC/GHG scenario A1b (medium)C21-CSST 2000–2099 CCSM3.0 WMO Baseline scenario Ab IPCC/GHG scenario A1b (medium)C21Cl1960 2001–2099 CCSM3.0 Chlorine fixed at 1960 values IPCC/GHG scenario A1b (medium),
with chlorine fixed at 1960 values
Figure 1. Time series of 70-hPa minimum zonal meanozone mixing ratio [ppmv] over SH polar cap area (between90!S and 60!S) during October (using daily model output).
L08714 PERLWITZ ET AL.: OZONE HOLE RECOVERY AND CLIMATE CHANGE L08714
2 of 5
jet shift = ozone pull + GHG push
Regression Coefficients: Estimate of Sensitivity
CCMVal2 Models
1 2 3 4 5 6 7 8 9 10
0.4
0.2
0
0.2
0.4
0.6
model
regr
essio
n co
effic
ient
s (d
eg./
K)
strat. polar cap temp. (O3)tropical temp. (GHG)
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Regression Coefficients: Estimate of Sensitivity
CCMVal2 Models
1 2 3 4 5 6 7 8 9 10
0.4
0.2
0
0.2
0.4
0.6
model
regr
essio
n co
effic
ient
s (d
eg./
K)
strat. polar cap temp. (O3)tropical temp. (GHG)
mea
n
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
1 2 3 4 5 6 7 8 9 10
0.4
0.2
0
0.2
0.4
0.6
model
regr
essio
n co
effic
ient
s (d
eg./
K)
strat. polar cap temp. (O3)tropical temp. (GHG)
Regression Coefficients: Estimate of Sensitivity
CCMVal2 Models CMIP3 Models
1 2 3 4 5 6 7 8 9 10
0.4
0.2
0
0.2
0.4
0.6
model
regr
essio
n co
effic
ient
s (d
eg./
K)
strat. polar cap temp. (O3)tropical temp. (GHG)
mea
n
mea
n
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
1 2 3 4 5 6 7 8 9 101
0.8
0.6
0.4
0.2
0
model
trend
s (d
eg./d
ecad
e)
total
Attribution of 20 Century Climate Trends
CCMVal2 Models CMIP3 Models
mea
n1 2 3 4 5 6 7 8 9 101
0.8
0.6
0.4
0.2
0
model
trend
s (d
eg./d
ecad
e)
total
mea
n
1 2 3 4 5 6 7 8 9 101
0.8
0.6
0.4
0.2
0
model
trend
s (d
eg./d
ecad
e)
O3totalGHG
Attribution of 20 Century Climate Trends
CCMVal2 Models CMIP3 Models
1 2 3 4 5 6 7 8 9 101
0.8
0.6
0.4
0.2
0
model
trend
s (d
eg./d
ecad
e)
O3totalGHG
mea
n
mea
n
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Summary of Model Trends
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
c) jet shift, 1960 99
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
e) jet shift, 2000 79
3
2
1
0
1C
CM
Val2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)b) T trends, 1960 99
3
2
1
0
1
CC
MVa
l2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)
d) T trends, 2000 79
0.6
0.4
0.2
0
0.2
0.4
CM
IP3
CC
MVa
l2
CM
IP5
r 03
andr GHG
(°/K
)
a) regression coef.
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Summary of Model Trends
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
c) jet shift, 1960 99
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
e) jet shift, 2000 79
3
2
1
0
1C
CM
Val2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)b) T trends, 1960 99
3
2
1
0
1
CC
MVa
l2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)
d) T trends, 2000 79
0.6
0.4
0.2
0
0.2
0.4
CM
IP3
CC
MVa
l2
CM
IP5
r 03
andr GHG
(°/K
)
a) regression coef.
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Summary of Model Trends
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
c) jet shift, 1960 99
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
e) jet shift, 2000 79
3
2
1
0
1C
CM
Val2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)b) T trends, 1960 99
3
2
1
0
1
CC
MVa
l2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)
d) T trends, 2000 79
0.6
0.4
0.2
0
0.2
0.4
CM
IP3
CC
MVa
l2
CM
IP5
r 03
andr GHG
(°/K
)
a) regression coef.
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Summary of Model Trends
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
c) jet shift, 1960 99
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
e) jet shift, 2000 79
3
2
1
0
1C
CM
Val2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)b) T trends, 1960 99
3
2
1
0
1
CC
MVa
l2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)
d) T trends, 2000 79
0.6
0.4
0.2
0
0.2
0.4
CM
IP3
CC
MVa
l2
CM
IP5
r 03
andr GHG
(°/K
)
a) regression coef.
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Shaving cream moved the jet stream!
Summary of Model Trends
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
c) jet shift, 1960 99
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
e) jet shift, 2000 79
3
2
1
0
1C
CM
Val2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)b) T trends, 1960 99
3
2
1
0
1
CC
MVa
l2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)
d) T trends, 2000 79
0.6
0.4
0.2
0
0.2
0.4
CM
IP3
CC
MVa
l2
CM
IP5
r 03
andr GHG
(°/K
)
a) regression coef.
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Summary of Model Trends
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
c) jet shift, 1960 99
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
e) jet shift, 2000 79
3
2
1
0
1C
CM
Val2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)b) T trends, 1960 99
3
2
1
0
1
CC
MVa
l2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)
d) T trends, 2000 79
0.6
0.4
0.2
0
0.2
0.4
CM
IP3
CC
MVa
l2
CM
IP5
r 03
andr GHG
(°/K
)
a) regression coef.
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
But what about the black bars?
But what about the black bars?A Tale of Two Models (London and Paris)
Jet shifts equatorward
2010 2020 2030 2040 2050 2060 2070 2080
3
2
1
0
1
2
3
year
Ula
t (° la
titud
e)
GFDL CM3IPSL CM5A MR
Jet shifts poleward
Changes in Jet PositionPrinceton
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
c) jet shift, 1960 99
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
e) jet shift, 2000 79
3
2
1
0
1C
CM
Val2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)b) T trends, 1960 99
3
2
1
0
1
CC
MVa
l2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)
d) T trends, 2000 79
0.6
0.4
0.2
0
0.2
0.4
CM
IP3
CC
MVa
l2
CM
IP5
r 03
andr GHG
(°/K
)
a) regression coef.
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Two Sources of Model Spread:Differences in the thermal response to GHG, O3
Returning to our case study...
2010 2020 2030 2040 2050 2060 2070 2080
3
2
1
0
1
2
3
year
Ula
t (° la
titud
e)
GFDL CM3IPSL CM5A MR
change in jet position
RCP4.5 Changes in Jet Position
Returning to our case study...
2010 2020 2030 2040 2050 2060 2070 2080
3
2
1
0
1
2
3
year
Ula
t (° la
titud
e)
GFDL CM3IPSL CM5A MR
change in jet position
2010 2020 2030 2040 2050 2060 2070 20802
0
2
4
6
8
10
12
year
TG
HG
(K)
GFDL CM3IPSL CM5A MR
change in tropical temperature
RCP4.5 Changes in Jet Position
Returning to our case study...
2010 2020 2030 2040 2050 2060 2070 2080
3
2
1
0
1
2
3
year
Ula
t (° la
titud
e)
GFDL CM3IPSL CM5A MR
change in jet position
2010 2020 2030 2040 2050 2060 2070 20802
0
2
4
6
8
10
12
year
TG
HG
(K)
GFDL CM3IPSL CM5A MR
2010 2020 2030 2040 2050 2060 2070 20802
0
2
4
6
8
10
12
year
T03
(K)
GFDL CM3IPSL CM5A MR
change in tropical temperature
RCP4.5 Changes in Jet Position
change in polar temperature
Uncertainty in global warming a poor predictor...
0.2 0.4 0.6 0.8−0.4
−0.3
−0.2
−0.1
0
0.1
0.2
0.3a) ! Ulat vs. ! Ttrop
! Ttropical (K/decade)
! U
lat (°
/dec
ade)
CCMVal2, R=−0.18CMIP3, R=−0.52CMIP5, R=−0.24
−0.5 0 0.5 1 1.5
b) ! Ulat vs. ! Tpolar
! Tpolar (K/decade)
CCMVal2, R=0.62CMIP3, R=0.81CMIP5, R=0.73
Fig. 9. The relationship between the 21st century shift in the austral jet stream !Ulat and(a) tropical upper tropospheric temperatures !Ttrop or (b) polar stratospheric temperatures!Tpolar. Circles, squares, and triangles refer to CCMVal2, CMIP3, and CMIP5 models,respectively. The shading of each symbol reflects the temperature trends of the other com-ponent: !Tpolar in (a) and !Ttrop in (b), with redder shades reflecting a warmer signal, andbluer symbols a colder signal. For example, in (a) there is a shift from blue to red as onegoes from bottom to top: for a given change in tropical temperatures, the jet shifts moreequatorward the more the polar stratosphere warms.
49
Uncertainty in global warming a poor predictor...rather, key is what is happening over the pole!
0.2 0.4 0.6 0.8−0.4
−0.3
−0.2
−0.1
0
0.1
0.2
0.3a) ! Ulat vs. ! Ttrop
! Ttropical (K/decade)
! U
lat (°
/dec
ade)
CCMVal2, R=−0.18CMIP3, R=−0.52CMIP5, R=−0.24
−0.5 0 0.5 1 1.5
b) ! Ulat vs. ! Tpolar
! Tpolar (K/decade)
CCMVal2, R=0.62CMIP3, R=0.81CMIP5, R=0.73
Fig. 9. The relationship between the 21st century shift in the austral jet stream !Ulat and(a) tropical upper tropospheric temperatures !Ttrop or (b) polar stratospheric temperatures!Tpolar. Circles, squares, and triangles refer to CCMVal2, CMIP3, and CMIP5 models,respectively. The shading of each symbol reflects the temperature trends of the other com-ponent: !Tpolar in (a) and !Ttrop in (b), with redder shades reflecting a warmer signal, andbluer symbols a colder signal. For example, in (a) there is a shift from blue to red as onegoes from bottom to top: for a given change in tropical temperatures, the jet shifts moreequatorward the more the polar stratosphere warms.
49
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
c) jet shift, 1960 99
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
e) jet shift, 2000 79
3
2
1
0
1C
CM
Val2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)b) T trends, 1960 99
3
2
1
0
1
CC
MVa
l2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)
d) T trends, 2000 79
0.6
0.4
0.2
0
0.2
0.4
CM
IP3
CC
MVa
l2
CM
IP5
r 03
andr GHG
(°/K
)
a) regression coef.
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Two Sources of Model Spread:Differences in the circulation response to temperature
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
c) jet shift, 1960 99
1
0.8
0.6
0.4
0.2
0
0.2
CC
MVa
l2
CM
IP3
CM
IP5
Ulat
(°/d
ecad
e)
e) jet shift, 2000 79
3
2
1
0
1C
CM
Val2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)b) T trends, 1960 99
3
2
1
0
1
CC
MVa
l2
CM
IP3
CM
IP5
T 03
and
T GHG
(K/d
ecad
e)
d) T trends, 2000 79
0.6
0.4
0.2
0
0.2
0.4
CM
IP3
CC
MVa
l2
CM
IP5
r 03
andr GHG
(°/K
)
a) regression coef.
∆Ulat = rO3 · ∆T03 + rGHG · ∆TGHG
Two Sources of Model Spread:Differences in the circulation response to temperature
Uncertain Forcing vs. Uncertain Dynamics
• Variability in modeled circulation response due to
• differences in thermal forcing by ozone and GHGs
• differences in “circulation sensitivity”
Jet position in historical simulation (degrees)
21 C
entu
ry J
et S
hift
(deg
rees
)
[ Kidston and Gerber 2010]
Connection between 21st Century Jet Shift and20th Century Climatology
equatorward bias
[ Kidston and Gerber 2010]
Connection between 21st Century Jet Shift and20th Century Climatology
position of jet in reanalyses
21 C
entu
ry J
et S
hift
(deg
rees
)
Jet position in historical simulation (degrees)
position of jet in reanalyses
equatorward bias
larger jet shift
[ Kidston and Gerber 2010]
Connection between 21st Century Jet Shift and20th Century Climatology
21 C
entu
ry J
et S
hift
(deg
rees
)
Jet position in historical simulation (degrees)
Connection between the Climatological Jet Position and Time Scales of Internal Variability
Ann
ular
Mo
de
Tim
e S
cale
(day
s)
equatorward bias
long
er ti
me
scal
es
[ Kidston and Gerber 2010]Jet position in historical simulation (degrees)
What does this annular mode time scale represent?
latitude80 60 40 20
J
F
M
A
M
J
J
A
S
O
N
D
J
latitude
80 60 40 20
70 30 10 10 30 70
a) model w/ short time scales b) model w/ long time scales
500 hPa geopotential height anomalies in two models
[ Gerber et al. 2010]
January
time
Connection between the Climatological Jet Position and Time Scales of Internal Variability
Ann
ular
Mo
de
Tim
e S
cale
(day
s)
equatorward bias
long
er ti
me
scal
es
[ Kidston and Gerber 2010]Jet position in historical simulation (degrees)
Internal Variability - Jet Shift Connection
Annular Mode Time Scale (days)
larger jet shift
longer time scale
[ Kidston and Gerber 2010]
21 C
entu
ry J
et S
hift
(deg
rees
)
Similar Connections in CCMVal2 Models (20th Century)
equa
torw
ard
bias
[44] The geometry of the sphere and the equator!to!poletemperature difference establish a high!latitude limit to theextent of the extratropical jet. If the jet changes its locationin response to external forcing, the poleward displacement(and intensification) may preferentially occur when the cli-matological jet is located in the latitudes lower than thishigh!latitude limit. In models where the climatological jet islocated in high latitudes, it is likely difficult to move the jetfarther poleward. In contrast, in models where the climato-logical jet exhibits an equatorward bias, there is much moreroom for the jet to move poleward. This simple, likelyoversimplified, argument amounts to a geometric constraint.[45] The dynamic constraint is linked to a connection
between internal variability and background flow. A seriesof idealized modeling studies by Gerber and Vallis [2007],Son et al. [2008] and Simpson et al. [2010] have shown thatthe e!folding time scale of zonal mean flow variability orannular mode (hereafter simply “the time scale”) is highlysensitive to the background flow. They found that it isshorter in integrations where the climatological eddy!drivenjet is located in higher latitudes. Figure 10b shows therelationship between the time scale and the location of cli-matological jet for the CCMVal!2 models. Here, the timescale is estimated by e!folding time scale of the SAM index,derived from the Empirical Orthogonal Function (EOF)analyses of daily zonal mean geopotential height. Thise!folding time scale is first calculated at each model leveland then integrated from the surface to 250 hPa. (See Gerberet al. [2010] for further details.) It is found that the timescale is highly correlated with the location of climatologicaljet, decreasing as the jet is located in higher latitudes. This isconsistent with idealized model experiments. A similarrelationship is also found in the AR4 model integrations[Kidston and Gerber, 2010].
[46] The fluctuation!dissipation theorem links the inter-nal variability of a system to its response to externalforcing [e.g., Leith, 1975]. Proper application of fluctua-tion!dissipation theory requires knowledge of the correla-tion structure between all modes of the system, or at least asubset sufficient to represent the dynamics [e.g., Majdaet al., 2010], but such an analysis is beyond the scope ofthis study. As discussed by Leith [1975], however, a simplerrelationship may apply if the annular mode is sufficientlyuncorrelated with other modes in the system. In this case onemight expect that for models with more persistent internalvariability (e.g., longer time scale), the jet should respondmore to external forcing, as found by Gerber et al. [2008]and Ring and Plumb [2008] in idealized model integra-tions. This is to a large degree in agreement with thefindings of Figure 10.[47] Why is the e!folding time scale shorter as the jet is
located in higher latitudes? It may arise from meridionalpropagation of baroclinic eddies [Son et al., 2007; Simpsonet al., 2010]. The summer hemisphere jet is essentiallydriven by eddies and generally forms at the region ofmaximum baroclinicity as discussed in section 3.3 (see alsoFigure 9a). Given that baroclinicity in the subtropics is fixedby the Hadley circulation, the extratropical jet at higherlatitudes implies a broader baroclinic zone where baroclinicwaves can propagate. This may allow eddies to propagatelatitudinally more effectively, weakening the stability of theeddy fluxes which maintain the zonal mean flow anoma-lies. The result would be a less stationary zonal mean flowanomaly in time, leading to shorter time scale. The oppo-site would be the case for the jet located in lower latitudes.Eddy activity would be confined to a more limited latitudeband, and would increase the chances that eddy fluxescontinuously occur at similar latitudes, making zonal mean
Figure 10. The relationship between the climatological jet location in the CCMVal!2 REF!B1 scenarioand (a) the tropospheric jet response to ozone depletion and (b) time scale of the SAM index in the SHsummer as simulated by the CCMVal!2 REF!B1 models. In Figure 10a the tropospheric [u]max trend isnormalized by the hO3i50 trend. Only 15 models are used here excluding two outliers which show tooweak hO3i50 trend or negative [u]max trend (see Figures 7 and 8). In Figure 10b, only 11 models areused, as others have not archived sufficiently daily data. Time scale based on the NCEP!NCAR reanalysis[Baldwin et al., 2003] is indicated with error bar in Figure 10b.
SON ET AL.: OZONE AND SOUTHERN HEMISPHERE CLIMATE D00M07D00M07
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larger jet shiftlonger time scale
long
er ti
me
scal
e
[ Son et al. 2010]
What connects variability and change?
Springs: An (imperfect) analogy
Hooke’s LawF = −kx
Springs: An (imperfect) analogy
Hooke’s Law
{x F=kx
pull spring down
it pullsback!
F = −kx
Springs: An (imperfect) analogy
F = ma
Hooke’s Law
Newton’s Second Law
F = −kx
Springs: An (imperfect) analogy
− k
mx =
d2x
dt2
−α2x =d2x
dt2
F = ma
Hooke’s Law
−kx = md2x
dt2
let α =�
k
m
Newton’s Second Law
F = −kx
F = −kx
Springs: An (imperfect) analogy
− k
mx =
d2x
dt2
−α2x =d2x
dt2
F = ma
Hooke’s Law
−kx = md2x
dt2
d2x
dt2= −α2x(t)
So, period of oscillation is 2π
α=
2π√
m√k
Look for solution of form:
then:
Newton’s Second Law
x(t) = A cos(αt) + B sin(αt)
Springs: An (imperfect) analogy
{x
pull spring down
Fspring = Fexternal
The response to “external” forcing: in equilibrium,
Period of oscillation is 2π
α=
2π√
m√k
Fexternal
Fspring=kx
it pullsback
Springs: An (imperfect) analogy
{x Fspring=kx
pull spring down
it pullsback
Fspring = Fexternal
−kx = Fexternal
The response to “external” forcing: in equilibrium,
Period of oscillation is 2π
α=
2π√
m√k
Fexternalx = −Fexternal
k
L is related to the timecorrelation structure of x, properties of the natural
variability.
Fluctuation-Dissipation Theory (in brief!)
= −Lx + N(x)
= −Lx + W
∂x∂t
= B(x)
Fluctuation-Dissipation Theory (in brief!)
= −Lx + N(x)
= −Lx + W
+f
+f
+f
external perturbation
∂x∂t
= B(x) L is related to the timecorrelation structure of x, properties of the natural
variability.
∂x∂t
= B(x)
Fluctuation-Dissipation Theory (in brief!)
= −Lx + N(x)
= −Lx + W
+f
∂x∂t
= −Lx + W + f
0 = −Lx + 0 + f
x = L−1f
+f
+f
external perturbation
L is related to the timecorrelation structure of x, properties of the natural
variability.
Fluctuation-Dissipation Theory (in brief!)
= −Lx + N(x)
= −Lx + W
+f
∂x∂t
= −Lx + W + f
0 = −Lx + 0 + f
x = L−1f
In most simple case,
L−1 =� ∞
0ρ(τ)dτ
ρ(τ) = x(t)x(t + τ)
+f
+f
∂x∂t
= B(x) L is related to the timecorrelation structure of x, properties of the natural
variability.
Does it work?
latitude
pres
sure
(hPa
)
5
30
−5
0
−80 −60 −40 −20
100
200
300
400
500
600
700
800
900
zonal mean zonal wind, u
Idealized Atmospheric Model Experiments
latitude
pres
sure
(hPa
)
−80 −60 −40 −20
100
200
300
400
500
600
700
800
900 −5
−3
−1
1
3
5
u and the annular mode
Idealized Atmospheric Model Experiments
Apply torque that projects on internal variability
latitude
pres
sure
(hPa
)
−80 −60 −40 −20
100
200
300
400
500
600
700
800
900 −5
−3
−1
1
3
5
[Ring and Plumb, 2008]
u and the annular mode
System responds modally: strong projection on to internal variability
latitude
pressure
01530456075
200
400
600
800
torque
shading: annular mode positive and negative
contours: response ofmodel to the torque,uforced - ucontrol(negative dashed)
[after Ring and Plumb 2008]
Model with greater persistence more sensitive to external forcing
−0.1 −0.05 0 0.05 0.1 0.15−5
0
5
projection of forcing
proj
ectio
n of
resp
onse
m=17
m=89
NH, L20NH, L40SH, L20SH, L40
[Gerber, Voronin, and Polvani 2008]
τ = 33 days
τ = 96 days
Conclusions
• In austral summer, the Southern Hemisphere jet stream is pushed poleward by greenhouse gas induced tropical warming and pulled poleward by ozone induce cooling of the polar stratosphere. To date, ozone loss has been the most important driver.
• Uncertainty in climate forecasts stems from differences in the thermal response to anthropogenic forcing (primarily differences in ozone) and the circulation sensitivity to temperature changes.
• A model’s ability to simulate today’s climate and variability is an important measure for determining if its climate change projections are trustworthy.