ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-16-10083-2016Changes in the width of the tropical belt due to simple radiative forcing changes in the GeoMIP simulationsDavisNicholas A.nadavis@atmos.colostate.eduhttps://orcid.org/0000-0002-5691-2020SeidelDian J.BirnerThomashttps://orcid.org/0000-0002-2966-3428DavisSean M.https://orcid.org/0000-0001-9276-6158TilmesSimoneDepartment of Atmospheric Science, Colorado State University, Fort Collins, CO, USANOAA Air Resources Laboratory, College Park, MD, USANOAA Earth System Research Laboratory, Boulder, CO, USANational Center for Atmospheric Research, Boulder, CO, USAretiredNicholas A. Davis (nadavis@atmos.colostate.edu)11August20161615100831009520April201611May201616July201619July2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/16/10083/2016/acp-16-10083-2016.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/16/10083/2016/acp-16-10083-2016.pdf
Model simulations of future climates predict a poleward expansion of
subtropical arid climates at the edges of Earth's tropical belt, which would
have significant environmental and societal impacts. This expansion may be
related to the poleward shift of the Hadley cell edges, where subsidence
stabilizes the atmosphere and suppresses precipitation. Understanding the
primary drivers of tropical expansion is hampered by the myriad forcing
agents in most model projections of future climate. While many previous
studies have examined the response of idealized models to simplified climate
forcings and the response of comprehensive climate models to more complex
climate forcings, few have examined how comprehensive climate models respond
to simplified climate forcings. To shed light on robust processes associated
with tropical expansion, here we examine how the tropical belt width, as
measured by the Hadley cell edges, responds to simplified forcings in the
Geoengineering Model Intercomparison Project (GeoMIP). The tropical belt
expands in response to a quadrupling of atmospheric carbon dioxide
concentrations and contracts in response to a reduction in the solar
constant, with a range of a factor of 3 in the response among nine
models. Models with more surface warming and an overall stronger temperature
response to quadrupled carbon dioxide exhibit greater tropical expansion, a
robust result in spite of inter-model differences in the mean Hadley cell
width, parameterizations, and numerical schemes. Under a scenario where the
solar constant is reduced to offset an instantaneous quadrupling of carbon
dioxide, the Hadley cells remain at their preindustrial width, despite the
residual stratospheric cooling associated with elevated carbon dioxide
levels. Quadrupled carbon dioxide produces greater tropical belt expansion in
the Southern Hemisphere than in the Northern Hemisphere. This expansion is
strongest in austral summer and autumn. Ozone depletion has been argued to
cause this pattern of changes in observations and model experiments, but the
results here indicate that seasonally and hemispherically asymmetric
tropical expansion can be a basic response of the general circulation to
climate forcings.
Introduction
Earth's tropical belt can be defined by the band of rainy
equatorial regions bordered by the arid subtropics to the north and the
south. The Hadley cells, two thermally direct tropospheric circulations with
rising motion near the Equator, significantly influence the surface climate
of the tropical belt. Converging easterly near-surface trade winds transport
moisture into the Intertropical Convergence Zone, a meandering front of
convection that brings rain to the equatorial latitudes and heats tropical
air through the condensation of water vapor. This heated air rises through
the troposphere and diverges poleward into the upper troposphere of both
hemispheres, eventually subsiding in the subtropics, where it dries and
stabilizes the atmosphere against convection. Because of the strong
latitudinal gradients in temperature and precipitation at the edges of the
tropical belt, any shift in its edges could drive major changes in surface
climate .
There is mounting evidence that such changes are already taking place. Soil
moisture , precipitation , and sea surface salinity trends
over the past several decades consistently indicate an intensification and
poleward shift of the hydrological cycle. The intensification is widely
considered to be driven primarily by increasing water vapor concentrations in
a warming atmosphere . A concurrent weakening of the Hadley
circulation is predicted in models, reflecting the reduction in upward mass
flux in a warmer climate . The circulation
changes that drive poleward shifts in the hydrological cycle are not as well
understood. Further subtropical drying and a poleward expansion of arid lands
are projected to continue .
Evidence of tropical expansion has been reported based on satellite
observations of outgoing longwave radiation and total column ozone . Observational
estimates of the tropical belt width based on dynamical fields, such as the
subtropical ridges in sea level pressure, also indicate tropical expansion,
although the trends are weaker than those based on outgoing longwave
radiation and precipitation metrics .
Other metrics for the tropical belt edge latitudes, such as the latitudes of
the jet streams and the latitudes of the
subtropical tropopause breaks , indicate historical tropical expansion,
as well. An expansion of the Hadley cells has been detected in reanalyses
.
Tropical expansion estimates based on reanalyses, however, may suffer from
spurious trends and discontinuities in basic meteorological fields
. The rate of Hadley cell expansion and even the
mean strength of the Hadley cells vary among the reanalyses
, which could indicate that the meridional winds are not well
constrained. There is also significant uncertainty in the observed rate of
tropical expansion because it is highly variable for different metrics and
data products .
Attributing surface impacts to tropical expansion and attributing tropical
expansion itself to particular climate forcings is difficult given the number
of external forcings changing over the historical period, as well as the
impact of natural climate variability on the trends. Factors such as the
Pacific Decadal Oscillation, the El Niño–Southern Oscillation
, and the Southern Annular Mode influence the tropical belt
width and may explain non-negligible fractions of its historical trend
.
Climate model simulations offer an avenue for assessing the response of the
Hadley cells and tropical belt to different climate forcings and forcing
evolutions, and long integrations minimize the impact of interannual
variability . Both and
found that significant tropical expansion occurs only when greenhouse gas
concentrations increase in historical climate simulations. Increasing
greenhouse gas concentrations in future climate simulations similarly cause
the tropical belt to expand relative to its preindustrial control width
, with the amount of expansion scaling with the
concentration of greenhouse gases . However, have
shown that the Hadley cell width is generally sensitive to changes in both
mean sea surface temperatures and meridional temperature gradients. Any
climate forcing that modifies mean temperatures or their gradients could thus
drive variations in the tropical belt width. Stratospheric ozone depletion
and its resulting polar stratospheric cooling have been argued to be a
potentially dominant driver of Southern Hemisphere tropical expansion
, and ozone recovery over the coming decades may
oppose any future greenhouse-gas-driven expansion . Black carbon, tropospheric ozone , and
aerosols may have also played a role in historical
tropical expansion, especially in the Northern Hemisphere. While examining
the response of climate models to realistic sets of past and future forcings
is appealing, it is not ideal for identifying how the tropical belt responds
to particular forcings. Many climate forcing agents are simultaneously
changing in these simulations, and separating their effects is often
intractable.
Idealized modeling, which involves changing a single climate forcing or model
parameter, complements those more realistic simulations. The models are often
simplified versions of fully coupled climate models that may solve only the
equations of motion and thermodynamics without explicitly resolving radiation
and convection. and found that stratospheric cooling in
such an idealized model produced a poleward shift of the midlatitude jet. It
also produced a poleward shift in the pattern of surface easterlies and
westerlies which indicates an expansion of the tropical belt. While
found that cooling the stratosphere and raising the height of
the tropopause were sufficient to produce a poleward shift of the tropospheric
jets, found that stratospheric cooling without perturbing the
tropopause height was sufficient to drive an expansion of the Hadley cells.
Similar to , found that idealized increases in
stratospheric water vapor drove enhanced stratospheric cooling and a poleward
shift of the tropospheric jets. Warming in the troposphere alone can also
drive an expansion of the Hadley cells . Thus,
stratospheric cooling and tropospheric warming can both drive poleward shifts
in the circulation.
However, idealized models do not explicitly model clouds or cloud-related
feedbacks. Convection is a fundamental aspect of the Hadley cells
, and cloud radiative effects can impact modeled
circulation changes . Some studies have
begun to bridge this gap by examining the response of comprehensive models to
idealized and more realistic greenhouse gas forcings. While
found evidence that Southern Hemisphere Hadley cell expansion scales with
climate sensitivity, found little relationship between the
transient climate response and Hadley cell expansion. Studies have also found
evidence of a seasonality and a lack of seasonality
in Southern Hemisphere expansion. The scaling and
seasonality seem to emerge if there is a steady greenhouse gas forcing (e.g.,
as in , and ). Work is still needed to
understand this response and how it may scale with other changes in the
climate system.
In this study, we will examine the equilibrium response of the tropical belt
to highly idealized forcings in the Geoengineering Model Intercomparison
Project (GeoMIP) . GeoMIP, a companion project to the Coupled
Model Intercomparison Project Phase 5 (CMIP5) , is designed to
improve the understanding of the response of the Earth system to
idealizations of different proposed climate geoengineering activities.
Geoengineering impacts aside, the GeoMIP experiments offer a unique
opportunity to study the response of fully coupled climate models to very
simple climate forcings, which may shed light on the processes responsible
for observed past and possible future tropical width changes.
Data and methods
The model name, modeling group or agency, the 4×CO2
experiment top-of-atmosphere radiative forcing relative to piControl, and the
G1 experiment residual top-of-atmosphere radiative forcing relative to the
piControl experiment for each of the nine models examined. All radiative
forcings are from and are in W m-2. Information on the
radiative forcings in the CSIRO-Mk3L-1-2 model is unavailable.
ModelGroup4×CO2 radiativeG1 radiativeforcing (W m-2)forcing (W m-2)CanESM2Canadian Centre for Climate Modelling and Analysis8.00.0CCSM4National Center for Atmospheric Research6.2-0.5CSIRO-Mk3L-1-2Commonwealth Scientific and Industrial Research OrganisationNANAGISS-E2-RGoddard Institute for Space Studies7.81.4HadGEM2-ESMet Office Hadley Centre for Climate Science and Services6.40.4IPSL-CM5A-MRInstitut Pierre Simon Laplace Climate Modelling Centre6.20.2MIROC-ESMUniversity of Tokyo, National Institute for Environmental Studies,8.70.0and Japan Agency for Marine-Earth Science and TechnologyMPI-ESM-LRMax-Planck-Intitut für Meteorologie8.60.2NorESM1-MNorwegian Climate Center6.80.4
NA = not available
While numerous climate forcings can impact the width of the tropical belt, we
focus on variations in carbon dioxide and insolation simulated in GeoMIP. Our
analysis is based on monthly-mean output from nine climate models (Table 1)
that performed three sets of experiments: the GeoMIP Geoengineering 1 (G1)
experiment , the preindustrial control (piControl), and the
abruptly quadrupled carbon dioxide (4×CO2) experiments in CMIP5
. The piControl experiment fixes all climate forcings at
preindustrial levels to provide an estimate of the unperturbed climate system
and will be the control experiment in this study. The 4×CO2
experiment applies an instantaneous quadrupling of piControl carbon dioxide
concentrations, while the G1 experiment balances this abrupt quadrupling with
a decrease in the solar constant such that the global-mean top-of-atmosphere
radiative forcing is zero . This crudely models the effect of
a global climate intervention scheme based on albedo modification
but more generally tests the impact of a decrease in insolation
on the climate system, with some relevance for paleoclimate research. We only
use the G1 experiment from GeoMIP because of its simple forcing scheme that
is applied uniformly in all models.
For the G1 experiment, not all models achieved a perfect cancellation of the
top-of-atmosphere radiative forcings. Table 1 lists the top-of-atmosphere
radiative forcing in the 4×CO2 experiment and the residual
top-of-atmosphere radiative forcing in the G1 experiment after the solar
constant reduction for each model (e.g., ).
Because the 4×CO2 and G1 experiments involve an abrupt forcing at
the start of the simulation, we discard the first 5 years of each experiment,
a conservative choice as the circulation metrics adjust to the abrupt forcing
within 2 years. The piControl simulations from each model range from 500 to
3000 model years, the 4×CO2 simulations range from 140 to 150 model
years, and the G1 simulations range from 50 to 100 model years. For each
experiment, we use the same number of model years from each model simulation
based on the shortest simulation; e.g., for the piControl experiment we use
the first 500 years from all of the model simulations.
All calculations and analyses use monthly-mean model output. For testing the
significance of changes in the tropical belt edge latitudes and width we use
two-sided Student's t tests for the difference of means with unequal
variances and sample sizes. The tests thus take into account the different
lengths and internal variability of each experiment. We use the effective
degrees of freedom, which are calculated using the lag-1 autocorrelation of
the monthly-mean anomalies . This yields approximately
400∘ of freedom for the G1 simulations and 4000∘ of freedom
for the piControl simulations, with some inter-model variability. Differences
are deemed statistically significant for p≤0.05 (the 95 % confidence
level).
Tropical belt edge metric
We define the tropical belt edge latitudes as the latitudes where the
vertically averaged mean meridional streamfunction is zero, poleward of its
tropical maximum (minimum) in the Northern (Southern) Hemisphere
. The tropical belt width is defined as the difference, in
degrees latitude, between the Northern and Southern Hemisphere edge
latitudes. The mean meridional streamfunction is the vertical integral of the
zonal-mean meridional mass flux between a given level and the top of the
atmosphere, and it is the primary field used to study variations in the Hadley
cells' width and intensity. It is expressed mathematically as
Ψ(p,ϕ)=2πacos(ϕ)g∫p0[v]dp,
where Ψ is the mean meridional streamfunction at the pressure p and
latitude ϕ, [v] is the zonal-mean meridional wind,
a=6.371×106 m is the mean radius of the Earth, and
g=9.81 ms-2 is the acceleration due to gravity. While the Hadley cell
edge latitudes are often calculated as the latitudes where the 500 hPa
streamfunction is zero, the choice of a single, arbitrary pressure level
subjects the metric to spurious trends due to mean-state changes, such as a
deepening of the troposphere, and to inter-model differences in the
circulation . Instead we
vertically average the streamfunction in pressure before calculating the edge
latitudes. The interpretation of this vertical average of the streamfunction
is simple: it measures the average meridional overturning circulation
strength at a given latitude, and the latitude where it is zero indicates the
separation of the Hadley and Ferrel cells.
We note that this metric and our analyses focus on the zonal mean. However,
historical tropical expansion exhibits significant zonal asymmetries
, and some zonally asymmetric dynamics contribute to
the longitudinal structure of the meridional overturning circulation
.
Tropical belt edge locations
The piControl experiment climatology of the tropical belt edge
latitudes for each of the nine models. The middle bar of each box represents
the median, and the left and right bars of each box represent the lower and
upper quartiles, respectively, of the tropical belt edge latitudes. Whiskers
indicate the maximum and minimum tropical belt edge latitude for the
piControl experiment.
Before analyzing the 4×CO2 and G1 experiments, we will first
examine the climatology of the tropical belt edge latitudes in the piControl
experiment (Fig. 1). The median tropical belt edge latitudes in each
hemisphere are comparable among the models. In general, models with more
equatorward edge latitudes in one hemisphere have more equatorward edge
latitudes in the other hemisphere (R2=0.7). There is greater interannual
variability in the Northern Hemisphere edge latitude, which is borne out in
reanalyses and observations . Some models, including the
IPSL-CM5A-LR and GISS-E2-R models, have little interannual variability in
their Northern Hemisphere edge latitudes.
Temperature response
We will first characterize the temperature changes in each model between the
4×CO2 and piControl and between the G1 and piControl experiments.
The motivation to examine the basic zonal-mean temperature response in all
nine models is threefold: (1) temperature changes are associated with changes
in the tropical belt width (e.g., ), (2) the zonal-mean
temperature response may provide information about a model's sensitivity to
different forcings, and (3) examining only the multi-model mean may obscure
important information about the robustness of the response and its
inter-model variations.
The difference in the zonal-mean temperature between the
4×CO2 and piControl experiments for each of the nine models. The
4×CO2 experiment temperature minus the piControl experiment
temperature is shown in shading (Kelvin), while the piControl experiment
temperature is shown by the black contours (Kelvin). Stippling indicates
differences not significant at the 95 % confidence level. The change in
global-mean surface temperature (Kelvin) between the 4×CO2 and
piControl experiments is shown in the upper right of each panel.
Quadrupled carbon dioxide concentrations drive the expected surface and
tropospheric warming and stratospheric cooling (Fig. 2). The
tropical upper-tropospheric warming is due to moist adiabatic adjustment
communicating the surface warming to upper levels .
Enhanced Arctic warming, or “Arctic amplification”, is partly due to
decreases in surface albedo brought on by reductions in snow cover and sea
ice and enhanced downwelling longwave radiation through the
so-called “ice-insulation” feedback . The stratospheric cooling
is partly driven by enhanced infrared cooling to space due to increased
carbon dioxide concentrations. Other processes such as changes in the
strength of the Brewer–Dobson circulation may contribute to the latitudinal
structure of the cooling. While all models capture this canonical greenhouse
gas response in zonal-mean temperature, the temperature changes vary by
nearly a factor of 3. The IPSL-CM5A-LR has the strongest response with
13 K upper-tropospheric and Arctic warming, while the CCSM4 model has the
weakest response with 5 K upper-tropospheric and 8 K Arctic warming. The
IPSL-CM5A-LR model also has the strongest surface temperature increase in the
abrupt 4×CO2 experiment at 6.1 K, while the CCSM4 model has the
second-weakest response at 3.5 K.
The difference in the zonal-mean temperature between the G1 and
piControl experiments for each of the nine models. The G1 experiment
temperature minus the piControl experiment temperature is shown in shading
(Kelvin), while the piControl experiment temperature is shown by the black
contours (Kelvin). Stippling indicates differences not significant at the
95 % confidence level. The change in global-mean surface temperature
(Kelvin) between the G1 and piControl experiments is shown in the upper right
of each panel.
The G1 experiment's solar constant reduction generally balances most of the
warming from quadrupled carbon dioxide (Fig. 3). Because Fig. 3 shows the
difference in temperature between the G1 and piControl experiments, it can be
interpreted as the temperature response to 4×CO2 that is
not counteracted by the solar constant reduction in the G1
experiment. In the G1 experiment, the stratosphere is cooler than it is in
the piControl experiment in all models. This is likely because of the
reduction in absorbed solar radiation by ozone and infrared radiation
emission by the (still enhanced) carbon dioxide concentrations. However, the
troposphere is marginally cooler in some models (CCSM4, GISS-E2-R, and
MIROC-ESM) and marginally warmer in others (CanESM2, HadGEM2-ES, and
MPI-ESM-LR). Unlike the robust temperature response in the 4×CO2
experiment, there is no robust residual warming or cooling in the troposphere
in G1 compared to piControl. Contrary to expectations, the model with the
strongest residual radiative forcing in the G1 experiment, GISS-E2-R, does
not have a warmer troposphere, while one of the models with a radiative
forcing of zero, CanESM2, has a significantly warmer troposphere. In the
coming sections, we will explore how the tropical belt responds to these
simple forcings and whether any processes could explain such changes.
Tropical belt width response
The change in the Hadley cell edge latitudes and width between the
4×CO2 and piControl experiments and between the G1 and piControl
experiments, for the Northern Hemisphere and Southern Hemisphere edge
latitudes and for the total change in Hadley cell width. Positive
values indicate poleward expansion or an increase in width. Models with edge
latitude or width changes significant at the 95 % confidence level are
shown in black. The mean change in the tropical belt width or edge latitude
and its 95 % confidence interval in degrees latitude is shown at the bottom
of each plot.
Quadrupled carbon dioxide drives a statistically significant expansion of the
tropical belt as measured by the Hadley cell edge latitudes in both the
Southern and Northern Hemisphere (Fig. 4). There is a large spread in the
magnitude of tropical expansion, though, with values ranging from 1∘
of total (width) expansion in the CSIRO-Mk3L-1-2 model to nearly 7∘
of total expansion in the IPSL-CM5A-LR model (the model with the strongest
temperature response to quadrupled carbon dioxide). The nearly factor-of-7
difference in the circulation response is far larger than the factor-of-2–3 temperature response difference.
The seasonal change in the Hadley cell edge latitudes and width
between the 4×CO2 and piControl experiments and between the G1 and
piControl experiments, for the Northern Hemisphere and Southern Hemisphere
edge latitudes. Positive values indicate poleward expansion. Models with edge
latitude changes significant at the 95 % confidence level are shown in
black. Values are shown for December through February (DJF), March through
May (MAM), June through August (JJA), and September through November (SON).
The mean change in the tropical belt width or edge latitude and its 95 %
confidence interval in degrees latitude is shown at the bottom of each plot.
More surprising is that the Southern Hemisphere expansion is on average twice
the Northern Hemisphere expansion (Fig. 4). Southern Hemisphere stratospheric
ozone depletion has been argued to be a dominant driver of the more rapid
observed expansion of the Southern Hemisphere Hadley cell . However, the results here indicate that, even with a
hemispherically symmetric climate forcing which does not include ozone
changes, the tropical belt responds asymmetrically with greater expansion in
the Southern Hemisphere. Furthermore, the expansion is strongest in the
Southern Hemisphere in austral summer and autumn (Fig. 5), consistent with
. These are the seasons when the stratospheric cooling due to
ozone depletion is expected to have its greatest impact on Southern
Hemisphere expansion trends as ozone is depleted throughout austral spring.
The solar constant reduction in the G1 experiment counteracts most of the
CO2-driven expansion in the 4×CO2 experiment, despite the
residual stratospheric cooling. This suggests that stratospheric cooling on
the order of 1–6 K with the maximum cooling over the poles (Fig. 3) is not
sufficient to appreciably widen the tropical belt. However, the altitude of
the cooling may be an important factor in determining whether the tropical
belt responds or not. For example, in idealized dry simulations
found that extratropical stratospheric cooling must extend
down to the tropopause to drive a strong circulation response. In the G1
experiment, the cooling is well above the typical height of the extratropical
tropopause (Fig. 3), which is generally located at approximately
250–300 hPa. This may be why there is no robust tropical expansion in the
G1 experiment. Processes in fully coupled models that are not represented in
idealized dry simulations, including cloud and radiation feedbacks, could act
to further damp the response of the tropical belt to stratospheric cooling.
For most models the differences between their G1 and piControl experiment
edge latitudes and width are small, often less than ±0.5∘
latitude (with an average difference of zero). Just as there is no robust
tropospheric temperature difference between the G1 and piControl experiments,
there is no robust residual tropical expansion or contraction. Changes in the
tropical belt width are not statistically significantly correlated with the
residual radiative forcings in the G1 experiment.
In the Northern Hemisphere (Fig. 5), tropical expansion in response to
increased carbon dioxide concentrations is approximately constant from
December–January–February (DJF) through June–July–August (JJA). It is
twice as large in September–October–November (SON). The enhanced expansion
in boreal autumn is consistent with realistic and more
idealized CMIP5 forcing simulations and with historical
reanalyses . While proposed that the observed
tropical expansion in Northern Hemisphere summer and autumn was driven by the
combined effects of black carbon and tropospheric ozone, it appears that
increased carbon dioxide concentrations alone could also drive some of this
enhanced expansion. As a caveat, however, the seasonality of Northern
Hemisphere tropical expansion is not particularly robust as the tropical belt
contracts in some models and seasons in response to quadrupled carbon dioxide
concentrations. This may arise from the opposing effects of the direct
radiative forcing and changes in sea surface temperatures on land–sea
temperature contrasts . The resulting circulation response
appears to be senstitive to which of the two dominates.
The difference in zonal-mean temperature between the 4×CO2
and piControl experiments in the four models with the greatest tropical
expansion (upper left) and in the four models with the least tropical
expansion (upper right). The 4×CO2 experiment minus the piControl
experiment temperatures are shown in shading (Kelvin), while the piControl
experiment temperatures are shown by the black contours (Kelvin). The
difference in the 4×CO2 experiment minus the piControl experiment
temperatures between the models with the greatest and least tropical
expansion is shown on the bottom, with shading indicating the difference
(Kelvin) and black contours indicating the mean piControl experiment
temperature (Kelvin) for all models. Stippling indicates changes not
significant at the 95 % confidence level.
To explore whether the large range in the responses and the asymmetric
response in the two hemispheres are associated with any particular zonal-mean
temperature structures, we composite the difference in temperature between
the 4×CO2 and piControl experiments in the four models with the
greatest and in the four models with the least total tropical expansion
(Fig. 6). Both groups show the same general pattern of tropospheric warming
and stratospheric cooling. In fact, the difference in the temperature
response to quadrupled carbon dioxide between the models with the greatest
and the least tropical expansion itself resembles the temperature response to
quadrupled carbon dioxide. An exception can be found in the upper
stratosphere, where the cooling is similar between the two subsets of models.
There is not a substantial difference between the separate composites on
Northern and Southern Hemisphere expansion, but both show a slightly weaker
stratospheric cooling signal (not shown). Overall there are no unique
relationships in the strength of the tropical upper-tropospheric
amplification, the Arctic amplification, the surface warming, or the
stratospheric cooling. Rather, these temperature responses all consistently
scale among the models with greater tropical expansion.
The change in the Hadley cell edge latitude versus the change in
subtropical static stability in the Northern Hemisphere and in the Southern
Hemisphere. For both hemispheres, positive changes in the Hadley cell edge
latitude indicate poleward expansion. Shown are values for the
4×CO2 experiment minus the piControl experiment (black) and for the
G1 experiment minus the piControl experiment (gray). The percent of the
inter-model variation in the change in the Hadley cell edge latitude
explained by the change in subtropical static stability between each
experiment is indicated in each plot.
Inter-model differences in the tropical width response and associated thermodynamic changes
Subtropical static stability increases due to tropical upper-tropospheric
amplification may be important for driving tropical expansion (Fig. 6).
derived a scaling theory for the Hadley cell width based on the
critical shear for baroclinic instability in the Phillips two-layer model
. If one assumes that the poleward flow in the Hadley cells
conserves angular momentum, and that the flow terminates at the latitude of
the onset of baroclinic instability, then the edge latitude of the Hadley
cell is only a function of the tropopause height and the gross static
stability (the difference between the potential temperature of the tropopause
and the surface). Increases in static stability or tropopause height would
both act to further stabilize the flow against baroclinic instability and
allow the Hadley cell to expand poleward. found changes in
static stability to be strongly correlated with changes in the Hadley cell
edge latitude, and a cursory scale analysis shows that the scaling theory is
dominated by the static stability term for typical variations in static
stability and tropopause height . For these reasons we will
focus exclusively on changes in subtropical static stability.
The scaling theory has been used to study tropical expansion in
models ranging from dry dynamical cores to fully coupled climate models
, although modified scaling theories that relax
the angular momentum conservation constraint , as well as
theories based on other criteria , may
be more realistic. Similar to , we evaluate the gross static
stability, hereafter “subtropical static stability”, at the tropical belt
edge latitude. We define the subtropical static stability as the difference
in potential temperature between 100 hPa (approximately the tropical
tropopause) and 1000 hPa (approximately the surface) averaged over
5∘ of latitude equatorward of the tropical belt edge latitude for
each month in each hemisphere.
In both hemispheres, tropical expansion between the 4×CO2 and
piControl experiments is associated with an increase in subtropical static
stability, with the increase in stability explaining 29–55 % of the
inter-model variation in tropical expansion (Fig. 7). This relationship also
holds for the tropical expansion and contraction between the G1 and piControl
experiments, where changes in static stability explain 42–46 % of the
total inter-model variation in the tropical belt edge latitudes. These
results are noteworthy for two reasons. Firstly, the relationships remain
linear for small and large changes in subtropical static stability and the
Hadley cell edge latitude. Secondly, despite differences in the models' mean
edge latitudes and their parameterizations of convection and other processes,
and despite a dearth of physical inter-model relationships
, this particular relationship is robust across models and
scenarios.
As in Fig. 7 but for the change in the Hadley cell edge latitude
versus the change in global-mean surface temperature in the Northern
Hemisphere and in the Southern Hemisphere.
Tropical upper-tropospheric temperatures tend to warm more than surface
temperatures due to moist adiabatic adjustment .
Because the moist adiabatic lapse rate scales with surface temperature, any
change in static stability in the tropics and subtropics reflects changes in
surface temperature. Accordingly, tropical expansion in both hemispheres also
scales with increases in global-mean surface temperature (Fig. 8), explaining
47–49 % of the inter-model variation in tropical expansion between the
4×CO2 and piControl experiments. Despite being the residual rather
than the forced response, increases in global-mean surface temperature also
explain 74 % of the inter-model variation in tropical expansion in the
Southern Hemisphere in the G1 experiment, though less so in the Northern
Hemisphere. Compared to the Southern Hemisphere, Northern Hemisphere tropical
expansion seems to scale nonlinearly for large increases in global-mean
surface temperature.
The seasonality of these correlations (not shown) generally reflects the
seasonality of the response (Fig. 5). For example, tropical expansion in the
Northern and Southern Hemispheres is most highly correlated with the change
in global-mean surface temperature in SON (R2=0.31) and MAM (R2=0.43),
respectively. In the other seasons, no significant correlation is found
between the change in global-mean surface temperature and tropical expansion
in the Northern Hemisphere.
The change in the total Hadley cell width versus the change in
global-mean surface temperature and the change in subtropical static
stability. Positive changes in the Hadley cell width indicate tropical
expansion. Shown are values for the 4×CO2 experiment minus the
piControl experiment (black) and for the G1 experiment minus the piControl
experiment (gray). The percent of the inter-model variation in the change in
the Hadley cell edge latitude explained by the change in global-mean surface
temperature and the change in subtropical static stability between each
experiment is indicated in each plot.
Tropical expansion as measured by the total change in tropical belt width
disproportionately increases as the global-mean surface temperature increases
(Fig. 9). This reflects the nonlinearity seen in the expansion of the
Northern Hemisphere tropical belt edge latitudes. The change in the tropical
belt width is better correlated with the change in global-mean surface
temperature than with the change in subtropical static stability, explaining
54–79 % of the total inter-model variation in the change in the tropical
belt width.
We also examined Arctic warming and tropical upper-tropospheric warming
separately, as the two may have different impacts on tropical expansion
and/or may explain some additional inter-model variation in the tropical belt
response. However, both of these indices are correlated with the total change
in global-mean surface temperature (Fig. 10), even seasonally (not shown).
Tropical upper-tropospheric temperature changes are well-correlated with the
change in global-mean surface temperature across the models for both the
difference between the 4×CO2 and piControl experiments and the
difference between the G1 and piControl experiments. For the Arctic warming,
the correlations do not depend upon whether one defines Arctic amplification
as the total temperature change at the surface in the Arctic (as is done
here) or as the difference between the total temperature change at the
surface in the Arctic minus the change in global-mean surface temperature; if
one is correlated with global-mean surface temperature, the other will be as
well.
Conclusions
We have examined the equilibrium response of the tropical belt to simple
radiative forcings in the GeoMIP experiments. Quadrupled concentrations of
carbon dioxide in the 4×CO2 experiment produce the canonical
temperature response and drive significant tropical expansion in all models.
The insolation reduction in the G1 experiment generally counteracts the
carbon-dioxide-induced tropospheric warming but leaves the stratosphere
colder than it was in the piControl experiment. The lack of any significant
change in the tropical belt width between the G1 and piControl experiments
indicates that broad stratospheric cooling alone may not drive tropical
expansion, at least when the cooling does not extend down to the tropopause.
The change in tropical upper-tropospheric temperature versus the
change in global-mean surface temperature (left), and the change in Arctic
surface temperature versus the change in global-mean surface temperature
(right), between the 4×CO2 and piControl experiments (black) and
between the G1 and piControl experiments (gray). Tropical upper-tropospheric
temperature is defined as the mean temperature between 200 and 300 hPa and
between 10∘ S and 10∘ N. Arctic temperature is defined as
the mean surface temperature between 75 and 90∘ N.
The expansion in response to quadrupled carbon dioxide concentrations is
greater in the Southern Hemisphere and peaks in austral summer and autumn,
consistent with recent findings by , who also analyzed the
4×CO2 experiment. Both responses have previously been identified as
signatures of Antarctic ozone depletion on observed Southern Hemisphere
tropical expansion. They also appear to reflect the basic response of the
circulation to simple hemispherically symmetric, non-ozone climate forcings.
This does not imply that ozone depletion and other climate forcings have not
contributed to observed tropical expansion. Rather, it may be that ozone
depletion and increased greenhouse gas concentrations have together enhanced
the expansion in the Southern Hemisphere and in summer and autumn. The
Southern Hemisphere Hadley cell may exist in a different dynamical regime
than the Northern Hemisphere cell due to the Southern
Hemisphere cell's strong coupling to the eddy-driven jet . This jet has a more robust poleward shift in response to
greenhouse gas increases than its Northern Hemisphere counterparts
, which may enhance Southern Hemisphere tropical expansion.
Further, the Hadley cells are more susceptible to the influence of
extratropical Rossby waves in summer , which may contribute to the
seasonality of the expansion in both hemispheres.
Models with a stronger temperature response to increased carbon dioxide
(which includes stronger surface, upper-tropospheric, and Arctic warming and
stronger stratospheric cooling) have greater tropical expansion. While
tropical expansion scales with increases in both subtropical static stability
and global-mean surface temperature, these indices effectively measure the
same thermodynamic response because of moist adiabatic adjustment. Increases
in global-mean surface temperature can explain up to 79 % of the total
inter-model variation in tropical expansion, noteworthy because it occurs
within the inter-model space of fully coupled climate models. Different mean
states , the representation of parameterized processes
, the strength of cloud feedbacks ,
and model design choices such as horizontal resolution can all influence the circulation and its response. Tropical belt
width changes are thus part and parcel of global climate change. They are
strongly correlated with changes in other key climate features and are not a
separate phenomenon. Tropical expansion could be considered as robust a
response of the climate system to increasing greenhouse gas concentrations as
an acceleration of the hydrological cycle.
How the temperature or static stability changes could actually drive tropical
expansion is an open question. While the dynamical response is relatively
fast, occurring within the first several years of the abrupt 4×CO2
experiment, the increase in global-mean surface temperature takes much
longer. Rather than being indicative of a mechanism for expansion, it is more
accurate to conclude that dynamical sensitivity as measured by the Hadley
cells scales with climate sensitivity, at least in response to changes in
carbon dioxide concentrations and insolation.
While it is consistent with the modeled tropical expansion, the scaling
theory used here includes some unrealistic assumptions. Angular momentum is
not perfectly conserved in the poleward flow of the Hadley cell due to eddy
momentum fluxes , and the boundary between the Hadley and
Ferrel cells is shaped by these eddy fluxes . While the scaling theory can be adjusted to take into account the
degree to which eddy fluxes draw the circulation away from angular momentum
conservation , some bootstrap or input of the properties of the
eddies is still needed to form a complete theoretical scaling for the Hadley
cell width . Further, localized and even
non-localized cooling in the subtropical lower stratosphere
can drive variations in the Hadley cell width, potentially independent of
changes to tropospheric static stability. This must be accounted for by any
theory for the width of the Hadley cells and their response to radiative
forcings.
Additionally, baroclinic instability is generally a feature of the
eddy-driven jets, which can be well separated from the subtropical jets at
the edges of the Hadley cells. Despite the inter-model correlation between
tropical expansion and increases in static stability, increases in static
stability may not be the only process associated with tropical expansion.
Instead, changes to the eddy phase speeds that lead to poleward shifts in the
latitudes of wave breaking may be responsible for poleward
shifts of the Hadley cell edges . Both occur simultaneously with
increasing greenhouse gas concentrations and global-mean surface
temperatures. It is therefore impossible to exclude other factors and
conclude that the static stability increases alone drive tropical expansion.
Both Arctic warming and tropical upper-tropospheric warming scale with
increases in global-mean surface temperature. Separating these influences on
the tropical belt and any other feature of the climate system is not feasible
in the experiments examined here and may not be possible in projections of
future climate. Despite the significant variation in the magnitude of the
model response to simple forcings, we find a robust physical scaling
throughout the climate system, between the tropics and the poles and between
the thermodynamics and the circulation.
Data availability
Access to CMIP5 model output requires registration with the Earth System Grid Federation. Further information can be found at http://cmip-pcmdi.llnl.gov/cmip5/.
CMIP5 is registered with the Registry of Research Data Repositories,
10.17616/R3X64R.
Acknowledgements
Two anonymous reviewers are thanked for their constructive comments. We thank
all participants of the Geoengineering Model Intercomparison Project and
their model development teams, the CLIVAR/WCRP Working Group on Coupled
Modeling for endorsing GeoMIP, and the scientists managing the Earth System
Grid Federation data nodes who have assisted with making GeoMIP output available. We
also thank Ben Kravitz for supplying some model output. We acknowledge the
World Climate Research Programme's Working Group on Coupled Modeling, which
is responsible for CMIP, and we thank the climate modeling groups for
producing and making available their model output. Nicholas Davis was supported
by a National Science Foundation Graduate Research Fellowship. The National
Center for Atmospheric Research is supported by the National Science
Foundation.Edited by: H. Wang
Reviewed by: two anonymous referees
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