Open Access
Atmospheric Chemistry and Physics
Atmos. Chem. Phys., 14, 913–937, 2014 www.atmos-chem-phys.net/14/913/2014/ doi:10.5194/acp-14-913-2014 © Author(s) 2014. CC Attribution 3.0 License.
A global climatology of stratosphere–troposphere exchange using the ERA-Interim data set from 1979 to 2011 A global climatology B. Škerlak, M. Sprenger, and H. Wernliof stratosphere-troposphere exchange using the ERA-Interim data 1979 to 2011 ETH Zurich, IAC, Universitätstrasse 16, 8092set Zürich,from Switzerland ˇ B. Skerlak, M. Sprenger, and H. Wernli Correspondence to: B. Škerlak (
[email protected]) ETH Zurich, IAC, Universit¨ atstrasse 16, 8092, Z¨ urich, Switzerland Received: 15 March 2013 – Published in Atmos. Chem. Phys. Discuss.: 2 May 2013
ˇ – Accepted: Revised: 21 September 11 December 2013 – Published: 27 January 2014 Correspondence to: 2013 B. Skerlak (
[email protected]) We discuss the sensitivity of our results on the choice of Abstract. In this study we use the ERA-Interim reanalysis data set from the European Centre for Medium-Range the control surface representing the tropopause, the horizonWeather Forecasts (ECMWF) and a refined version of tal and vertical resolution of the trajectory starting grid, and the minimum residence time τ used to filter out transient STE a previously developed Lagrangian methodology to compile trajectories. a global 33 yr climatology of stratosphere–troposphere exchange (STE) from 1979 to 2011. Fluxes of mass and ozone are calculated across the tropopause, pressure surfaces in the troposphere, and the top of the planetary boundary layer 1 Introduction (PBL). This climatology provides a state-of-the-art quantification of the geographical distribution of STE and the preStratosphere–troposphere exchange (STE) has important imferred transport pathways, as well as insight into the temporal pacts on atmospheric chemistry: it changes the oxidative caevolution of STE during the last 33 yr. pacity of the troposphere (e.g. Kentarchos and Roelofs, 2003) We confirm the distinct zonal and seasonal asymmetry and potentially also affects the climate system because ozone found in previous studies using comparable methods. The and water vapour are potent greenhouse gases (e.g. Gauss subset of “deep STE”, where stratospheric air reaches the et al., 2003; Forster et al., 2007). PBL within 4 days or vice versa, shows especially strong geAlthough it has been known for roughly 50 yr that stratoographical and seasonal variations. The global hotspots for spheric ozone can be brought into the troposphere during deep STE are found along the west coast of North America STE events (Junge, 1962; Danielsen, 1968) and add to local and over the Tibetan Plateau, especially in boreal winter and photochemical production, the relative importance of these spring. An analysis of the time series reveals significant possources is not yet entirely certain. Modelling studies (e.g. itive trends of the net downward mass flux and of deep STE Roelofs and Lelieveld, 1997) indicate that the stratospheric in both directions, which are particularly large over North contribution to ozone in the troposphere could be as large America. as that from net photochemical production, which was also The downward ozone flux across the tropopause is domconfirmed in a more recent multi-model ensemble simulainated by the seasonal cycle of ozone concentrations at the tion (Stevenson et al., 2006). This contribution, albeit only tropopause and peaks in summer, when the mass flux is known with rather large uncertainty (Wild, 2007), is likely to nearly at its minimum. For the subset of deep STE events, increase over the next decades (Zeng and Pyle, 2003; Collins the situation is reversed and the downward ozone flux into the et al., 2003; Hegglin and Shepherd, 2009), which further emPBL is dominated by the mass flux and peaks in early spring. M STT TSTofO3 phasizes theO3 importance STE for tropospheric chemistry. Thus surface ozone concentration along theSTT west M coast TST of While ozone in the upper troposphere is mainly releTP −0.76 −0.87 −0.77 −0.85 North America and around the Tibetan Plateau are likely to as a greenhouse gas and oxidizer, deep STE down 400intrusions. hPa −0.58 −0.78 vant −0.56 −0.75 be influenced by deep stratospheric to the surface can also contribute to enhanced ozone lev500 hPa −0.50 −0.68 −0.48 −0.64 els at the ground and affect plant and human physiology
Supplementary material
600 hPa −0.48 −0.61 −0.45 −0.58 700 hPa −0.48 −0.59 −0.44 −0.57 Published by Copernicus Publications on behalf of the European Geosciences Union. 800 hPa −0.49 −0.59 −0.45 −0.57 PBL −0.50 −0.60 −0.46 −0.58
Table 1: Parameters κ from the power-law fit (c · τ κ with some constant c) to globally integrated fluxes of mass and ozone. 1
Figure S 1: Trends of deep STT mass flux into the PBL (top) and deep TST mass flux out of the PBL (bottom) from 1979 to 2011. Linear regression is applied to monthly averages at every grid point and regions where the trends are significant on a 1 % level are dashed. The trends in western and central North America are approximately 0.13 kg km−2 s−1 month−1 and 0.16 kg km−2 s−1 month−1 for deep STT and deep TST, respectively. The trend in deep STT over the Tibetan Plateau is approximately −0.19 kg km−2 s−1 month−1 but is only significant at a small number of grid points and does thus not appear as dashed region.
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0.6
1 0.8 ● ●
●
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max control = 20.56 max highres = 21.18 max 3.5 pvu = 2.28
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0.4
0.4
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F
M
0.2 A
M
J
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J
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S
a O
N
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D
0.8
J
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S
O
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M
A
M
J
J
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O
N
D
e
NH ● ●
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J
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max control = 118.08 max highres = 118.08 max 3.5 pvu = 162.38
F
M
A
M
J
J
d
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S
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Deep STT SH J
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O
N
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100 120 140 160
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max control = 0.32 max highres = 0.34 max 3.5 pvu = 0.06
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0.2
Deep STT NH
b F
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0.6
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Deep STT SH
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c max control = 0.8 max highres = 0.8 max 3.5 pvu = 0.29
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1
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0.4
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0.4
0.2 ●
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control highres 3.5 pvu
0
Ozone flux [ Tg month−1 ]
max control = 34.77 max highres = 33.88 max 3.5 pvu = 6.51
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J
Ozone at TP [ ppbv ]
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0.6
1 0.8
Deep STT NH
0
Mass flux [ 108 kg s−1 ]
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max control = 85.39 max highres = 85.39 max 3.5 pvu = 126.01 S
O
N
D
J
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F
M
A
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M
J
Month
Figure S 2: Seasonal cycles of hemispherically integrated deep STT fluxes of mass (top) and ozone (middle) in the NH (left) and the SH (right) for the year 2010. The three different data sets (“control”, “highres” and “3.5 pvu”) are described in Sect. 5 of the manuscript. The seasonal cycles are scaled to their maximum values shown within the individual figures, facilitating the comparison of amplitude and shape of the cycles. The bottom row shows the seasonal cycles of ozone mixing ratios at the corresponding control surfaces.
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J
a
F M A M J
J
A S O N D
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max control = 486.16 max highres = 478.34 max 3.5 pvu = 325.99
J
A S O N D J
F M A M J
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control = 21.14 max highres = 20.58 max 3.5 pvu = 6.8
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max control = 13.04 max highres = 12.49 max 3.5 pvu = 3.61
0.2 0
c
Deep TST NH J
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0.4
0.4 0.2
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F M A M J
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J
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0.6
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0.8
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b
1
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1
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0.8
max control = 466.06 max highres = 465.51 max 3.5 pvu = 301.83
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0.7 0.6
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control highres 3.5 pvu
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TST SH
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1
1 0.9
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0
Mass flux scaled to maximum [ 108 kg s−1 ]
TST NH
A S O N D
d
Deep TST SH J
A S O N D J
F M A M J
Month
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max control = 7.54 max highres = 7.05 max 3.5 pvu = 4.27
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0.5
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1
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max control = 6.75 max highres = 7.68 max 3.5 pvu = 4.95
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0.5
1
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0 J
A S O N D
F M A M J
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max control = 1.6 max highres = 1.59 max 3.5 pvu = 2.18 ●
0
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J
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c
−1
NET O3 NH
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−0.5
−0.5
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F M A M J
F M A M J
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J
A S O N D J ●
max control = 2.52 max highres = 3.14 ● max 3.5 pvu = 3.17
b
NET M SH
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J
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−1
a
0.5
−0.5
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NET M NH
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−1
control highres 3.5 pvu
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Net ozone flux [ Tg month−1 ] Net mass flux [ 109 kg s−1 ]
Figure S 3: Seasonal cycles of hemispherically integrated TST mass fluxes for all exchanges (top) and deep exchanges only (bottom) in the NH (left) and the SH (right) for the year 2010. The three different data sets (“control”, “highres” and “3.5 pvu”) are described in Sect. 5 of the manuscript. The seasonal cycles are scaled to their maximum values shown within the individual figures, facilitating the comparison of amplitude and shape of the cycles.
●
NET O3 SH J
A S O N D J
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d
F M A M J
Month
Figure S 4: Seasonal cycles of hemispherically integrated net (STT-TST) fluxes of mass (top) and ozone (bottom) for the year 2010. The three different data sets (“control”, “highres” and “3.5 pvu”) are described in Sect. 5 of the manuscript. The seasonal cycles are scaled to their maximum values shown within the individual figures, facilitating the comparison of amplitude and shape of the cycles.
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Figure S 5: Scaled STT mass flux for 2010 in the “control” setup as described in Sect. 5 of the manuscript.
Figure S 6: Scaled STT mass flux for 2010 in the “3.5 pvu” setup as described in Sect. 5 of the manuscript.
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Figure S 7: Scaled TST mass flux for 2010 in the “control” setup as described in Sect. 5 of the manuscript.
Figure S 8: Scaled TST mass flux for 2010 in the “3.5 pvu” setup as described in Sect. 5 of the manuscript.
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80 60
Latitude 0 20
40
control highres 3.5 pvu
max control = 94.11 max highres = 94.63
−90
−60
−30
max 3.5 pvu = 59.89
−0.8
−0.6
−0.4
−0.2 0 0.2 0.4 Mass flux [ 105 kg s−1 km−1 ]
0.6
0.8
1
0 2 4 6 J
A S O N D
J
A S O N D J
b F M A M J
2 −1 0
1
2 1 −1 0
NET O3 NH J
F M A M J
J
c
−3
−3
NET M SH
3
F M A M J
3
J
Ozone flux [ Tg month−1 ]
a
NET M NH
−8
−4
0 2 4 6 −4 −8
Mass flux [ 109 kg s−1 ]
Figure S 9: Zonally integrated STT, TST and net(STT-TST) mass fluxes for the three data sets “control”, “highres” and “3.5 pvu” as described in Sect. 5 of the manuscript. All curves are scaled to the maximum STT mass flux.
A S O N D
NET O3 SH J
A S O N D J
d F M A M J
Month
Figure S 10: Seasonal cycles of the net(STT-TST) fluxes of mass (top) and ozone (bottom) in the NH (left) and SH (right) averaged from 1979 to 2011. The shaded areas show 5 % and 95 % (light) as well as 25 % and 75 % (dark) quantiles of the monthly values. The white lines show the mean values of the 33 yr. The horizontal dashed lines are shown for visual guidance.
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