LETTER
doi:10.1038/nature11097
Recent Northern Hemisphere tropical expansion
primarily driven by black carbon and
tropospheric ozone
Robert J. Allen1, Steven C. Sherwood2, Joel R. Norris3 & Charles S. Zender4
Observational analyses have shown the width of the tropical belt
southeast Asia, while decreasing over much of Europe (Fig. 1). Despite
increasing in recent decades as the world has warmed1. This expan-
the geographically heterogeneous evolution, black carbon has
sion is important because it is associated with shifts in large-scale
atmospheric circulation2-4 and major climate zones5,6. Although
a
recent studies have attributed tropical expansion in the Southern
Hemisphere to ozone depletion7-10, the drivers of Northern
Hemisphere expansion are not well known and the expansion
has not so far been reproduced by climate models11. Here we use a
climate model with detailed aerosol physics to show that increases in
heterogeneous warming agents--including black carbon aerosols
and tropospheric ozone--are noticeably better than greenhouse
gases at driving expansion, and can account for the observed
summertime maximum in tropical expansion. Mechanistically,
atmospheric heating from black carbon and tropospheric ozone
has occurred at the mid-latitudes, generating a poleward shift of
the tropospheric jet12, thereby relocating the main division between
tropical and temperate air masses. Although we still underestimate
tropical expansion, the true aerosol forcing is poorly known and
could also be underestimated. Thus, although the insensitivity of
models needs further investigation, black carbon and tropospheric
ozone, both of which are strongly influenced by human activities,
are the most likely causes of observed Northern Hemisphere
-4
-3
-2
-1
-0.25
0
0.25
1
2
3
4
tropical expansion.
Black carbon (ng per kg per year)
Recent observational analyses show that the tropics have widened
by 2u-5u latitude since 1979 (ref. 1). This evidence is based on several
metrics, including a poleward shift of the Hadley cell2, subtropical dry
b
zones5, and extratropical storm tracks6. A more recent estimate of the
tropospheric jet shift4, based on satellite-derived temperatures, suggests
a smaller rate of expansion of 1.6u.
Tropical expansion occurs in model simulations forced by increas-
ing greenhouse gases, thus suggesting a likely cause1,13,14. Model-
predicted expansion rates, however, are significantly less than those
observed11. This discrepancy may be related to the relatively short
observational record, the large natural variability of some expansion
metrics, or model deficiencies.
Several recent studies have focused on tropical expansion in the
Southern Hemisphere, and the important contribution of stratospheric
ozone depletion7-10. Less has been said about the causes of Northern
Hemisphere expansion. Recent equilibrium simulations with atmo-
spheric general circulation models have shown that direct heating of
the troposphere, such as that caused by absorbing aerosols or
tropospheric ozone, can drive expansion15. Although indirect aerosol
effects may also be important and could yield the opposite response16,
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
they may be significantly overestimated in current general circulation
Ozone (p.p.b.v. per year)
models17 and in any case they mainly cool the surface rather than the
Figure 1 | 1970-2009 annual mean tropospheric trends. a, Black carbon;
atmosphere.
b, Ozone. p.p.b.v., parts per billion by volume. Black carbon concentration
Owing to increased combustion of fossil fuels and biofuels, black
trends include hydrophobic and hydrophilic black carbon and are based on
carbon aerosols have increased substantially over much of the
CAM simulations using CMIP5 black carbon emissions. Ozone trends come
Northern Hemisphere during the last few decades, particularly over
directly from the CMIP5 forcing data set.
1Department of Earth Sciences, University of California, Riverside 92521, USA. 2Climate Change Research Centre and ARC Centre of Excellence for Climate Systems Science, University of New South Wales,
Sydney 2052, Australia. 3Scripps Institution of Oceanography, University of California, San Diego 92093, California, USA. 4Earth System Science, University of California, Irvine 92697, California, USA.
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LETTER RESEARCH
increased monotonically since 1970 on average in the low and mid-
a
1.0
latitudes, including the band 30u-50u N (Supplementary Figs 1-2),
where recent studies show that heating can displace the tropical edge12.
The same is true of tropospheric ozone, another indirect byproduct of
combustion. Here, we investigate the transient effects of these atmo-
0.5
spheric warming agents on Northern Hemisphere tropical width.
We quantify tropical width using a variety of metrics5,11: (1) the
latitude of the tropospheric zonal wind maxima (JET); (2) the latitude
where the Mean Meridional Circulation (MMC) at 500 hPa becomes
zero on the poleward side of the subtropical maximum; (3) the latitude
0.0
where precipitation minus evaporation (P 2 E) becomes zero on the
poleward side of the subtropical minimum; (4) the latitude of the
subtropical precipitation minimum (PMIN); and (5) the latitude of
the subtropical cloud cover minimum over oceans (CMIN). To obtain
-0.5
an overall measure of tropical expansion, we also average the trends of
all five metrics into a combined metric called `ALL'. Expansion figures
quoted in the text will be based on ALL unless otherwise specified.
Figure 2 compares the annual-mean poleward displacement of each
-1.0
metric, with 2s uncertainty, between observations and a much-studied
JET
P - E
MMC
PMIN
CMIN
ALL
set of twentieth-century (Coupled Model Intercomparison Project
Metrics
version 3, CMIP3) climate simulations (Supplementary Table 1) for
ees per decade)
the period 1979-99, for which both observations and simulations are
b
1.0
available. All observed metrics show poleward displacement of the

(degr
Northern Hemisphere tropical boundary by 0.2u-0.75u per decade.


Although the JET and PMIN displacements are not significant at the
95% confidence level, the others are, and the combined metric ALL
0.5
shows significant poleward displacement of 0.33u 6 0.12u per decade.
As shown previously11, the CMIP3 models underestimate Northern
Hemisphere expansion. However, we note that this failure is more
evident in models that lack time-varying black carbon or ozone,
wherein four of the five metrics actually move in the wrong direction.
0.0
In models that do include one or both forcings, poleward displacement
is robust across most indicators. In those with both forcings, ALL
shows 0.14 6 0.06u per decade--about half what is observed and sig-
BC + O3
nificantly more than in models not including black carbon and ozone
-0.5
non-BC/O
forcing (non-BC/O
3
3).
O
Expansion rates vary by season (Fig. 2, bottom). In the Northern
3
Observations
Hemisphere, observed expansion is strongest in June-August (JJA)
and September-November (SON) at 0.53u per decade and 0.58u per
-1.0
decade, respectively. Non-BC/O
MAM
JJA
SON
DJF
Annual
3 CMIP3 models significantly under-
estimate expansion in these seasons. Models that include ozone,
Months
however, and those also including black carbon, simulate more expan-
sion in JJA and SON. The impact of both forcings (BC 1 O
Figure 2 | Observed and modelled 1979-1999 Northern Hemisphere
3), that is, the
difference relative to non-BC/O
tropical expansion based on five metrics. a, Annual mean poleward
3, is greatest in JJA (0.24u per decade)
followed by SON (0.20u per decade) and March-May (MAM) (0.15u per
displacement of each metric, as well as the combined ALL metric. b, Poleward
decade), with the smallest difference in December-February (DJF)
displacement by season, based on ALL. CMIP3 models are grouped into nine
that included time-varying black carbon and ozone (red); three that included
(0.07u per decade). Such a seasonal cycle is similar to that of the observed
time-varying ozone only (green); and six that included neither time-varying
trend, although expansion overall is still too small even in the BC 1 O3
black carbon nor ozone (blue). Boxes show the mean response within each
models. The impact of these forcings becomes more statistically signifi-
group (centre line) and its 2s uncertainty. Observations are in black. In the case
cant in the models when examining a longer time period, 1970-1999
of one observational data set, trend uncertainty (whiskers) is estimated as the
(Supplementary Fig. 3).
95% confidence level according to a standard t-test.
The preceding results are based on a relatively short time period, are
probably affected by differences between the models that used different
These CAM simulations confirm the important role of time-varying
forcings, and were based on relatively crude aerosol treatments. We
black carbon and ozone in driving simulated expansion. In the non-BC/
therefore conduct a suite of longer (1970-2009) simulations with a
O3 run, annual-mean expansion dropped to 0.04 6 0.03u per decade, or
single climate model, the Community Atmosphere Model version 3
about one-third of that with all forcings. Little if any of this is due to
(CAM3)18 of the National Center for Atmospheric Research (NCAR),
stratospheric ozone, given that almost the same result (0.06 6 0.04u per
equipped with new aerosol physics. We isolate the impact of a given
decade) is obtained in the non-BC/tO3 run, where tO3 is tropospheric
forcing agent by comparing model runs with and without that agent.
ozone. Although the latter result is not quite significantly different from
The annual-mean observed displacement over 1979-2009,
the all-forcings response over 1979-2009, it is significantly different
0.38 6 0.11u per decade, is about 15% stronger than for the shorter
over the longer time period, and is robust across metrics (Supplemen-
period and has approximately the same seasonal cycle (Fig. 3). The
tary Fig. 4). Moreover, as seen in the CMIP3 simulations, BC 1 tO3
CAM 1979-2009, CAM 1970-2009, and CMIP3 BC 1 O3 1979-1999
produces a much more realistic warm-season trend maximum; the JJA
runs all produce similar counterpart expansions of about 0.14u per
and MAM trend increases are statistically significant .
decade, with similar seasonal cycles. Therefore none of the important
Black carbon and tropospheric ozone are negligible drivers of
results are sensitive to the observing period.
Southern Hemisphere expansion (Supplementary Fig. 5). Instead we
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RESEARCH LETTER
a
1.0
1979-2009). The combined impact of black and organic carbon (which
are generally emitted together) also falls in this range, showing that
little of the expansion from black carbon is offset by organic carbon,
which is non-absorbing. These results are again qualitatively robust
across individual metrics, although less statistically significant
0.5
(Supplementary Fig. 7). Each of the heterogeneous warming agents
produces a more realistic seasonal trend cycle than do greenhouse
gases. Decreases in scattering aerosols (due to declining mid-latitude
sulphate) have not significantly contributed to Northern Hemisphere
0.0
tropical expansion except during JJA, the time of maximum solar
insolation.
We relate tropical expansion to a temperature index that compares
All forcings
mid-latitude tropospheric warming to that at other latitudes12.
-0.5
ALL without BC + O3
Warming of mid-latitudes relative to others displaces the maximum
ALL without BC + tO
meridional
climatological
temperature
gradient
poleward.
3
Observations
Geostrophic adjustment to this perturbed temperature gradient also
implies a poleward shift of the tropospheric jet12.
We consider a quantity called the `expansion index': 2|DT30{60{
-1.0
MAM
JJA
SON
DJF
Annual
DT0{30zDT60{90, where DT is the log-pressure (850-300 hPa)
ees per decade)
area-weighted temperature response in low (0u-30u), mid- (30u-60u),
b
1.0
and high (60u-90u) latitudes12. As the expansion index becomes more

(degr
positive, mid-latitude warming amplification dominates, and we expect


more tropical expansion. Similarly, as the expansion index becomes less
positive, mid-latitude cooling amplification dominates, and we expect
0.5
less tropical expansion.
The above relationship helps to explain why black carbon and
tropospheric ozone drive Northern Hemisphere tropical expansion
(Supplementary Information and Supplementary Figs 8-14). Both
agents heat primarily within the 30u-55u N latitude range. Although
0.0
dynamical responses can cause the geographical patterns of applied
heating and resulting warming to be quite different, in the zonal mean,
tO3
mid-latitude heat input does appear to produce warming at roughly
BC
the heated latitudes12, consistent with our results. Experiments with an
-0.5
BC + tO3
alternative general circulation model, the Geophysical Fluid Dynamics
Greenhouse gases
Laboratory (GFDL) atmospheric model AM2.1 (ref. 19 and Sup-
Sulphate
plementary Information), increase our confidence that this response
Organic carbon
to mid-latitude heating, and black carbon and tropospheric ozone in
-1.0
particular, is robust across different climate models, as well as different
MAM
JJA
SON
DJF
Annual
aerosol and ozone forcings.
Months
This relationship also explains the seasonal cycle of the response,
because both black carbon and tropospheric ozone warm primarily by
Figure 3 | Northern Hemisphere seasonal tropical expansion based on the
absorbing solar radiation, which is far more abundant during summer.
combined ALL metric. a, CAM simulations for all forcings (red), all forcings
except black carbon and ozone (blue); and all forcings except black carbon and
In our CAM simulations, atmospheric solar absorption by black
tropospheric ozone (green). The first box in each like-coloured pair represents
carbon in the Northern Hemisphere mid-latitudes increases by more
1970-2009; the second box in each like-coloured pair represents 1979-2009.
than a factor of three from DJF to JJA, 0.76 W m22 versus 2.63 W m22.
Observations (black) for 1979-2009 are also included. b, CAM individual
This results in about 0.05 K per decade more tropospheric warming in
forcing experiments for 1970-2009 showing the difference between the all
the Northern Hemisphere mid-latitudes during JJA compared to DJF.
forcings experiment and all forcings without tropospheric ozone (red), black
A similar variation results from tropospheric ozone (Supplementary
carbon (blue), black carbon and tropospheric ozone (green), greenhouse gases
Fig. 15).
(purple), sulphate (light blue) and organic carbon (grey). Boxes show the mean
Figure 4 quantifies the relationship between annual mean Northern
response (centre line) and its 2s uncertainty.
Hemisphere tropical expansion and expansion index for 1970-2009.
find, as have previous studies7-10, that stratospheric ozone depletion is
Climate forcing agents that yield a positive expansion index also yield a
the main driver there, particularly during the peak DJF expansion
positive (poleward) displacement for most metrics, and vice versa. The
season.
corresponding correlation coefficient, over all experiments and
We explored the role of various forcings more thoroughly by con-
metrics is 0.66, significant at the 99% confidence level. Correlations
ducting additional ten-ensemble member simulations with CAM,
for the individual metrics are 0.86 for JET; 0.62 for P 2 E; 0.89 for
individually omitting each of black carbon, tropospheric ozone,
MMC; 0.68 for PMIN; and 0.16 for CMIN.
greenhouse gases, and the scattering aerosols--sulphate and organic
Our analysis strongly suggests that recent Northern Hemisphere
carbon (Fig. 3b). In most seasons, greenhouse gases and heterogeneous
tropical expansion is driven mainly by black carbon and tropospheric
warming agents (that is, black carbon and tropospheric ozone) push
ozone, with greenhouse gases playing a smaller part. Compared to
the Northern Hemisphere tropical boundary poleward. Over the year,
observations, the magnitude of the simulated change is underestimated.
greenhouse gases yield about 0.05u per decade, which is only significant
This could be related to the aforementioned caveats with the observa-
for the longest time period, 1970-2009. Either tropospheric ozone,
tions, model deficiencies, or deficient black carbon aerosol forcing. The
black carbon or their combination (BC 1 tO3) each cause roughly
average top-of-the-atmosphere black carbon radiative forcing is
twice this much expansion, ranging from 0.07u to 0.12u per decade,
0.35 W m22 for CMIP3 models20, 0.43 W m22 in our CAM simula-
which is significant for both time periods (Supplementary Fig. 6 shows
tions, and was reported as 0.25 W m22 in a third suite of relatively
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LETTER RESEARCH
0.3
one observational data set, trend uncertainty was estimated as the 95% confidence
level according to a standard t-test30.
Full Methods and any associated references are available in the online version of
0.2
the paper at www.nature.com/nature.
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regression yielded similar results. When multiple realizations (or observational
Supplementary Information is linked to the online version of the paper at
data sets for a given metric) were available, trend uncertainty was estimated from
www.nature.com/nature.
s
the multiple realizations, as twice the standard error, 2|
ffiffi
p ffi , where s is the
n
Acknowledgements This study was funded by R.J.A.'s University of California at
standard deviation of the trends and n is the number of trends. In the case of
Riverside initial complement. We acknowledge the individual modelling groups, the
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RESEARCH LETTER
Program for Climate Model Diagnosis and Intercomparison and the Working Group on
and assisted in experimental design. C.S.Z. assisted with CAM experiments, including
Coupled Modeling of the World Climate Research Programme (WCRP) for their part in
the SNICAR model.
making available the WCRP CMIP3 multimodel data set. Support of this data set is
provided by the Office of Science, US Department of Energy.
Author Information Reprints and permissions information is available at
www.nature.com/reprints. The authors declare no competing financial interests.
Author Contributions R.J.A. conceived the project, designed the study, carried out all
Readers are welcome to comment on the online version of this article at
data analysis and wrote the manuscript. S.C.S. advised on methods and interpretation,
www.nature.com/nature. Correspondence and requests for materials should be
and assisted in the writing of the manuscript. J.N. provided homogenized cloud data
addressed to R.J.A. (rjallen@ucr.edu).
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LETTER RESEARCH
METHODS
Displacements for all metrics are estimated by first smoothing the zonal
monthly mean of the appropriate field(s) and interpolating to 0.5u resolution using
Our black carbon radiative forcing is computed interactively at each time step as
cubic splines. Smoothing was performed by taking a running mean over about 10u
the difference in fluxes with all species present and all species except black carbon.
of latitude. However, nearly identical results are obtained without interpolating.
Thus, our 0.43 W m22 top-of-the-atmosphere radiative forcing is a measure of the
instantaneous forcing, which for aerosols is a close approximation of the (adjusted)
For trend uncertainty calculations (in the case of one observational metric), the
radiative forcing used by CMIP3 models. CAM alterations, including the SNICAR
influence of serial correlation is accounted for by using the effective sample size,
model and modification of black carbon optical properties to account for enhanced
n1{r1 1z

r1{1, where n is the number of years and r1 is the lag-1 autocorrela-
solar absorption by coated hydrophilic particles, are described elsewhere27,28.
tion coefficient30.
Observational data comes from several sources, including the Global
When multiple realizations (or observational data sets for a given metric) are
Precipitation Climatology Project version 2.2 (GPCP)31 the Integrated Global
available, trend uncertainty is estimated as twice the standard error. These 2s
Radiosonde Archive (IGRA)32 and five reanalyses33-37 for MMC calculations.
ranges are approximate, given that we have a ten-member ensemble and cannot
Cloud cover observations, which span July 1983 to June 2008 only, come from
confirm that the trends are Gaussian-distributed. However, ten ensemble
two recently homogenized satellite data sets38 based on the International Satellite
members is relatively large for such a study and is the largest we could manage
Cloud Climatology Project (ISCCP)39,40 and the Advanced Very High Resolution
given the high computational costs of running nine forcing scenarios.
Radiometer (AVHRR) Pathfinder Atmospheres Extended (PATMOS-x)41,42. Our
31. Adler, R. et al. The version-2 Global Precipitation Climatology Project (GPCP)
P 2 E estimate is based on precipitation from GPCP and evaporation from the
monthly precipitation analysis (1979-present). J. Hydrometeorol. 4, 1147-1167
Woods Hole Oceanographic Institution (WHOI) Objectively Analyzed air-sea
(2003).
Flux (OAFlux) project43. Because the WHOI OAFlux data are over ocean only,
32. Durre, I., Vose, R. S. & Wuertz, D. M. Overview of the Integrated Global Radiosonde
our P 2 E estimate is for the global oceans.
Archive. J. Clim. 19, 53-68 (2006).
For the IGRA jet analysis, monthly mean zonal wind data are used at stations
33. Kalnay, E. et al. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc.
with 75% valid years, where a valid year has four valid seasons and a valid season
77, 437-471 (1996).
has two of three valid months. This is required at all tropospheric pressure levels
34. Kanamitsu, M. et al. NCEP-DOE AMIP-II Reanalysis (R-2). Bull. Am. Meteorol. Soc.
83, 1631-1643 (2002).
(850 hPa, 700 hPa, 500 hPa, 400 hPa, 300 hPa). To minimize trend errors, we also
35. Uppala, S. et al. The ERA-40 re-analysis. Q. J. R. Meteorol. Soc. 131, 2961-3012
required a station to possess eight valid years in the first and last decade. Data from
(2005).
both 00Z and 12Z are used. This resulted in 273 12Z and 300 00Z IGRA stations for
36. Rienecker, M. M. et al. MERRA: NASA's Modern-Era Retrospective Analysis for
1979-1999 and 247 12Z and 281 00Z stations for 1979-2009, most of which are in
Research and Applications. J. Clim. 24, 3624-3648 (2011).
the Northern Hemisphere. Data are gridded to 5u 3 10u resolution by assigning
37. Saha, S. et al. The NCEP Climate Forecast System Reanalysis. Bull. Am. Meteorol.
each station's monthly zonal wind to the nearest grid point without interpolation.
Soc. 91, 1015-1057 (2010).
When more than one station matched the same grid point, that grid point's value is
38. Clement, A., Burgman, R. & Norris, J. R. Observational and model evidence for
positive low-level cloud feedback. Science 325, 460-464 (2009).
estimated as the average of the available station values. Sub-sampling the CMIP3
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models at the IGRA station locations yielded similar results, but sub-sampling
72, 2-20 (1991).
decreases the ensemble mean jet displacement from 0.11 6 0.10u per decade to
40. Rossow, W. B. & Schiffer, R. A. Advances in understanding clouds from ISCCP. Bull.
0.03 6 0.16u per decade.
Am. Meteorol. Soc. 80, 2261-2287 (1999).
Our jet-based measure of tropical width is based on locating the `sides' of the jet
41. Jacobowitz, H. et al. The Advanced Very High Resolution Radiometer Pathfinder
using the 75th percentile of monthly mean zonal wind for each tropospheric (850-
Atmosphere (PATMOS) climate data set: a resource for climate research. Bull. Am.
Meteorol. Soc. 84, 785-793 (2003).
300 hPa) pressure level12. The 75th percentile is estimated by sorting the monthly
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mean zonal wind--for each hemisphere and tropospheric pressure level--from
and VIRS: algorithm description, validation, and comparisons. J. Appl. Meteorol.
low to high and taking the 0:75| Nz

1 value, where N is the number of zonal
44, 804-826 (2005).
wind values (that is, latitudes). Taking the midpoint and averaging over pressure
43. Yu, L. & Weller, R. A. Objectively analyzed air-sea heat fluxes for the global ice-free
levels yields a time series of monthly jet locations for each hemisphere.
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(c)2012 Macmillan Publishers Limited. All rights reserved

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Document Outline

• Title
• Authors
• Abstract
• Methods Summary
• References
• Methods
• Methods References
• Figure 1 1970-2009 annual mean tropospheric trends.
• Figure 2 Observed and modelled 1979-1999 Northern Hemisphere tropical expansion based on five metrics.
• Figure 3 Northern Hemisphere seasonal tropical expansion based on the combined ALL metric.
• Figure 4 Northern Hemisphere 1970-2009 annual mean tropical expansion for each metric versus the expansion index for CAM simulations.

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