Declining anthropogenic aerosols amplify Northern Hemisphere Hadley circulation weakening in the 21st century

Domain: chemistry
Published: 2026-03-02
Editorial outcome: major_revision

Abstract
The Hadley circulation plays a key role in transporting atmospheric heat from the tropics to the
subtropics, shaping the climate in low latitudes. While its projected weakening has been largely
attributed to rising greenhouse gas concentrations, the long-term impact of future anthropogenic
aerosol concentrations remains underexplored. Here, we show that the projected changes in
anthropogenic aerosol concentrations can account for about one-third of the Northern Hemisphere
Hadley circulation weakening between 1980 and 2080, emerging as a major driver of tropical
circulation change throughout the 21st century. This impact is linked to altered diabatic heating
patterns in the northern tropics, driven by precipitation changes under reduced aerosol forcing.
These results highlight a critical trade-off of aerosol mitigation: while improving air quality, it may
amplify tropical atmospheric circulation changes driven by greenhouse gases.

Introduction
The Hadley Circulation (HC) consists of ascending motion in the deep tropics, poleward flow in
the upper troposphere, descending motion in the subtropics, and equatorward return flow near the
surface. This thermally direct overturning circulation strongly influences tropical hydroclimate
and maintains subtropical dry zones1–4. As global warming accelerates, climate model simulations
consistently project a weakening of the Northern Hemisphere (NH) HC from the past to the future
climate5–9. This weakening has primarily been attributed to changes in anthropogenic greenhouse
gases and aerosols6,10–17.

While the weakening of the HC by increasing greenhouse gases is well documented, the response
of the HC to changing aerosols is not well understood as it is sensitive to the analysis period and
models due to the complex spatiotemporal evolution of aerosol forcing10,15,18. Anthropogenic
aerosols increased globally until the 1980s, particularly after the end of World War II, but have
since followed divergent regional trajectories: declining in Europe and North America due to
effective mitigation efforts but continuing to increase in East and South Asia19–24 (Supplementary
Fig. 1). Past studies utilizing climate model simulations in different configurations have shown
that the overall cooling effect of increasing anthropogenic aerosols has likely strengthened the HC
in the NH, counteracting the weakening induced by greenhouse warming10,17,25. However, the
impacts of anthropogenic aerosols over the past few decades are uncertain, as aerosol
concentrations have declined in the Western Hemisphere but increased in the Eastern Hemisphere.
While these zonally asymmetric aerosol forcings may have competed with each other, recent
studies have suggested that changes in HC intensity are more sensitive to aerosol changes in the
Western Hemisphere, thereby driving a likely weakening of the HC since the 1980s16,21,23. Despite
these findings, the impact of time-varying aerosol forcings (Supplementary Fig. 1) on HC intensity
change is not well quantified. The relative importance of anthropogenic aerosols compared to
greenhouse gases and their underlying mechanism(s) also remains poorly understood.

In this work, we show the pivotal role of anthropogenic aerosol forcing in driving intensity changes
of the NH HC. By examining large ensembles of single-forcing climate model simulations, we
identify the mechanisms underlying aerosol-induced HC intensity changes and compare them with
those driven by greenhouse gases. As the impacts of aerosols on atmospheric circulation changes
are often obscure and model-dependent26–28, the robustness of the results is also tested by
employing a multi-model framework and an additional suite of the latest large-ensemble
simulations.

Results
Hadley circulation weakening due to anthropogenic forcings

The HC intensity changes, derived from the CESM1 large ensemble single-forcing experiment
(CESM1 LENS), are presented in Fig. 1. Under all-forcing scenario (ALL experiment; See
Methods), the NH HC intensity (Ψ ) shows robust weakening from 1920 to 2080 at a rate of -
max
0.62×109 kg s-1decade-1 (Table 1). This is consistent with a previous study6. The time of emergence
of NH HC intensity change, determined by the year when the forced response exceeds the range
of natural variability29–31, is estimated to be around 2020. The natural variability is defined as the
one-standard-deviation range of Ψ in the pre-industrial simulation (green lines in Fig. 1a).
max
The long-term change is less pronounced in the Southern Hemisphere (SH) HC intensity (Ψ ).
min
From 1920 through 2080, Ψ remains within the bounds of the internal variability (Fig. 1b). This
min
result reinforces the finding that the HC weakening is more pronounced in the NH than in the
SH6,12. This hemispheric asymmetry is consistent with prior studies and may be related to
differences in aerosol distributions and stratospheric ozone27,32.

The intensity of the NH HC (hereafter referred to as HC unless otherwise specified) exhibits a
distinct decadal variation (Fig. 1a). Specifically, the trend switches sign around 1980, transitioning
from a strengthening phase prior to the 1970s to a weakening phase thereafter (Table 1). The recent
weakening is consistent with observations5, although it is less clear in reanalyses33,34. As shown
below, this transition is likely associated with changes in aerosol emissions in the NH
(Supplementary Fig. 1; See also refs.16,23,35,36).

The contribution of increasing greenhouse gas concentrations to the HC intensity change is
quantified by taking a difference between ALL and fixed greenhouse gas concentrations (XGHG)
experiments, denoted as GHG experiment (red in Fig. 1c; See Methods). The HC intensity trend
in GHG experiment is statistically significant over the analysis period (1920–2080) but is smaller
than the trend in ALL experiment. Even during the period of 1980–2080 when greenhouse-gas-
induced HC weakening accelerates, the trend is only ~60% of that in ALL experiment (Table 1).
The time of emergence in GHG experiment is also delayed by about 20 years compared to that in
ALL experiment (compare crossing of green lines in Fig. 1c with Fig. 1a). This suggests that
increasing greenhouse gases do not fully explain the HC weakening in ALL experiment, indicating
a substantial influence of anthropogenic aerosols.

The contribution of anthropogenic aerosols is quantified by differencing ALL from fixed
anthropogenic aerosols (XAER) experiments, denoted as AER (blue in Fig. 1c; See Methods).
While the aerosol-induced HC intensity change lies within the natural variability for the entire
period (1920–2080), statistically significant trends are observed in two distinct sub-periods (Table
1): the earlier period (1920–1980) when anthropogenic aerosols increased globally
(Supplementary Fig. 1), and the subsequent period (1981–2080) of anthropogenic aerosols decline,
especially in the Western Hemisphere36. During 1920–1980, increasing aerosol concentrations
strengthened the HC intensity by 0.47×109 kg s-1decade-1, which exceeds the trend in the ALL
experiment. After 1980, declining aerosol concentrations weaken the HC by -0.35×109 kg s-1
decade-1, accounting for approximately 34% of the total HC weakening in the ALL experiment
over 1980–2080 (Table 1). Since the latter weakening effect after 1980 outweighs the former
strengthening effect before 1980, the net impact of anthropogenic aerosol forcing on HC intensity
over the entire analysis period is an overall weakening (Table 1). The results are robust to the
specific choice of transition year within the 1970–1980 period, as NH aerosol emissions were in a
transition phase during this decade (Supplementary Fig. 1).

It is important to note that aerosol effect is not always secondary. In certain periods, it acts as the
dominant driver of HC intensity changes. For instance, during the earlier phase of aerosol decline
(1980–2040), the aerosol-induced HC weakening (-0.56109 kg s-1 decade-1) is more pronounced
than the greenhouse-gas-induced weakening (-0.34109 kg s-1 decade-1). This underscores the
time-dependent nature of aerosol forcing and its critical role in shaping near-term tropical
circulation changes.

The combined effects of greenhouse gases and aerosols are further evaluated by comparing the
trend derived from the linear sum of the GHG and AER experiments (GHG + AER; purple in Fig.
1c) with that from the ALL experiment (black in Fig. 1a). The two time series are quantitatively
similar, showing close agreement across the three investigated periods (Table 1). This result
indicates that anthropogenic greenhouse gases and aerosols are the two primary factors governing
the HC intensity changes from 1920 to 2080, consistent with ref.36.

The above results, derived from a single model, are supported by multi-model analyses. The multi-
model mean from the models participating in the CMIP6 Detection and Attribution Model
Intercomparison Project (DAMIP; See Methods)37 shows qualitatively similar results, despite
different experiment design and aerosol forcing (Table 1; See also Supplementary Fig. 3). In all-
forcing experiments, HC intensity exhibits a slight strengthening during 1920–1980, followed by
a weakening during 1980–2080. Approximately 26% of HC weakening is attributed to aerosol
reductions: -1.13×109 kg s-1 decade-1 in all forcing experiments versus -0.29×109 kg s-1 decade-1
in aerosol-only experiments over 1980–2080.

The robustness of HC intensity changes is also tested by examining the latest CESM2 large
ensemble single-forcing experiment (CESM2 LENS; See Methods). This experiment differs from
CESM1 LENS in that greenhouse gas or aerosol forcings are prescribed with all other forcings
held fixed at the 1850’s levels. Despite this difference, as well as differences in aerosol emission
scenarios, ensemble size, and integration length, qualitatively similar results are obtained
(Supplementary Fig. 4). The anthropogenic aerosol-only experiment in CESM2 LENS shows a
statistically significant HC strengthening of 0.43109 kg s-1 decade-1 for 1920–1980, and a
subsequent weakening of -0.48109 kg s-1 decade-1 for 1980–2050. This result is consistent with
the findings from both CESM1 LENS and CMIP6 DAMIP results (Table 1).

Physical processes of Hadley circulation weakening

While both increasing greenhouse gas concentrations and decreasing aerosol concentrations
contribute to the HC weakening during 1980–2080, their underlying mechanisms may differ. The
latitudinal-pressure structure of mass streamfunction (Ψ) indeed shows distinctively different
responses of the HC to the two forcings (Supplementary Fig. 2). Greenhouse gas forcing leads to
HC weakening centered in the subtropics (10°-30°N; Supplementary Fig. 2e), whereas aerosol
forcing causes weakening primarily in the deep tropics within ~15° N (Supplementary Fig. 2f).

To investigate the physical processes associated with these changes, we employ the Kuo-Eliassen
(KE) equation (See Eq. 2 in Methods). This equation provides a diagnostic framework that relates
HC intensity changes to various physical processes in the atmosphere, such as the meridional
gradient of diabatic heating (𝑄̅ ), static stability (S2), eddy heat flux convergence (𝑣 ̅̅ ′ ̅ 𝑇 ̅̅ ′),
y
eddy momentum flux convergence (𝑢 ̅̅ ′ ̅ 𝑣 ̅̅ ′), and zonal drag (𝑋̅). Here, 𝑄̅ is dominated by latent heating
y
of tropical convection and precipitation33,34. Since precipitation is maximized near the Inter-
Tropical Convergence Zone (ITCZ), climatological 𝑄̅ is negative on the equatorward side of the
y
HC center. In a warming climate, negative 𝑄̅ is anticipated to intensify as precipitation is projected
y
to increase in the ITCZ and decrease in the subtropics38,39. On the other hand, S2, determined by
the vertical profile of temperature change, is expected to increase in a warming climate because
upper tropospheric warming is faster than lower tropospheric warming as the temperature profile
in the tropics closely follows the moist adiabatic lapse rate. Other terms are relatively minor6. Eddy
fluxes are affected by subtropical and mid-latitude weather systems, whereas 𝑋̅ is dependent on
surface friction.

The Ψ changes reconstructed from the KE equation (𝛿Ψ ), defined as the sum of all individual
𝐾𝐸
terms in Eq. (4), reproduce the key features of the actual Ψ changes (𝛿Ψ; Supplementary Fig. 5).
This agreement supports the validity of the KE-based diagnosis, despite the use of monthly-mean
data to compute eddy flux terms. However, it should be noted that the KE equation does not
represent a causal relationship. Moreover, individual terms in the right-hand side of Eq. (4) are not
independent. Despite these limitations, the similarity between 𝛿Ψ and 𝛿Ψ enables us to
𝐾𝐸
qualitatively evaluate the physical processes associated with the HC intensity changes.

For each experiment (ALL, GHG, and AER experiments), HC trends derived from the KE equation
(𝛿Ψ ) are computed for the period 1980–2080 relative to the 1941–1970 climatology (Fig.
𝑚𝑎𝑥,𝐾𝐸
2). In ALL experiment (Fig. 2a), HC weakening is primarily driven by changes in S2 (red bar), as
reported in previous studies6,11,40. The second largest term is 𝑄̅ (green), which partially offsets the
y
HC weakening driven by S2. The counteracting effects of S2 and 𝑄̅ are also evident in the GHG
y
experiment (Fig. 2b). As in the ALL experiment, the negative impacts of S2 and other terms
overcome the positive impact of 𝑄̅ , resulting in a net weakening of the HC. In AER experiment,
y
the change in S2 still acts to weaken the HC, although its effect is much weaker than in the GHG
experiment due to the smaller aerosol-induced tropical warming (Supplementary Fig. 6). More
importantly, unlike in the GHG experiment, the 𝑄̅ effect is negative in the AER experiment during
y
the aerosol-declining phase. This negative contribution from 𝑄̅ , combined with enhanced
y
stratification (S2), eddy influences (𝑣 ̅̅ ′ ̅ 𝑇 ̅̅ ′ and 𝑢 ̅̅ ′ ̅ 𝑣 ̅̅ ′), and zonal drag (𝑋̅), collectively accelerates the
weakening of the HC (Fig. 2c).

Changes in S2 within the tropics are primarily determined by the thermodynamic response of the
atmosphere to surface temperature changes. GHG-induced tropical warming is more pronounced
in the upper troposphere than in the lower troposphere (Fig. S6e)6. This top-heavy warming pattern
increases static stability and slows down the tropical overturning circulation6,11. A similar warming
pattern emerges during the AER-declining period (1980–2080), where the warming is also
amplified in the upper troposphere following the moist adiabat (Fig. S6f), albeit with a smaller
magnitude. Specifically, the S2-induced HC weakening per 1-K tropical surface warming in
response to aerosol reduction (-2.21010 kg s-1 decade-1 per 1-K) closely align with that induced
by GHG increase (-2.51010 kg s-1 decade-1 per 1-K). This highlights that the same thermodynamic
mechanism controls the HC weakening via S2 changes in both GHG and AER experiments.

The meridional gradient of diabatic heating, Q , is another key component that modulates the HC
y
intensity33. Latitudinal precipitation profiles, which determine Q , respond differently to
y
greenhouse gas and aerosol forcings (Fig. 3). In the GHG experiment, the maximum increase in
precipitation occurs near the ITCZ, strengthening Q . To achieve a balanced state, a thermally
y
direct circulation developes, reducing Q through adiabatic cooling in the deep tropics and
y
warming in the subtropics (Fig. 2b). In contrast, aerosol-induced precipitation change shows a
maximum at approximately 11°N (Fig. 3b). This reduces the Q around the HC center and leads
y
to HC weakening (Fig. 2c). Similar precipitation pattern changes, albeit weaker, are also observed
in the CMIP6 DAMIP models (Supplementary Fig. 7), consistent with previous studies41–43. The
precipitation peak at 11°N is associated with an anomalous cross-equatorial circulation
(Supplementary Fig. 2f), driven by hemispherically asymmetric warming arising from aerosol
forcing (Supplementary Fig. 6f)25,41,44,45.

Although smaller in magnitude, other terms also contribute to changes in HC intensity. Eddy
momentum fluxes and zonal drag both contribute to HC weakening (Fig. 2). Under global warming,
enhanced stratification stabilizes the subtropical atmosphere, leading to a weakening of eddy
activity and thus the HC7,46. The zonal drag, 𝑋̅ , also contributes to HC weakening by modifying
near-surface zonal winds and the associated vertical wind shear. For instance, the Pacific trade
winds have strengthened over the past two decades in response to declining aerosol reduction47,48.
This has likely led to an increase in surface friction, thereby weakening the HC.

Methods
Definition of Hadley circulation (HC) intensity

To define the HC intensity, we utilize mass streamfunction (Ψ), which is computed by vertically
integrating zonal-mean meridional wind from the top of the atmosphere to the 500-hPa level,
Ψ= 2𝜋𝑎 𝑐𝑜𝑠𝜙 ∫ 𝑝 𝑣̅ 𝑑𝑝, (1)
𝑔 0
where 𝜙 is the latitude, 𝑝 is the pressure, a=6,371 km is the Earth’s radius, g is the gravitational
acceleration, and 𝑣̅ is zonal-mean (denoted by an overbar) meridional wind. All analyses are
conducted on the annual-mean 𝑣̅ from each ensemble member. The HC intensity is defined as the
absolute value of 500-hPa mass stream function maximum (Ψ ) in the Northern Hemisphere
max
and the minimum (Ψ ) in the Southern Hemisphere, between the ascending and descending
min
branches in the tropics (red asterisks in Supplementary Fig. 2)27,53. The use of Ψ accounts for
min
the negative sign of Ψ in the Southern Hemisphere. The overall results are consistent when using
the average of Ψ between 400-hPa and 700-hPa levels.

Kuo-Eliassen equation

The HC intensity changes are quantitatively diagnosed by computing the Kuo-Eliassen (KE)
equation6,34. With quasi-geostrophic assumptions, the KE equation is written as below:
𝑓2 𝑔 𝜕2Ψ𝐾𝐸+𝑆2 𝑔 𝜕 1 𝜕Ψ𝐾𝐸
2𝜋𝑎𝑐𝑜𝑠𝜙 𝜕𝑥2 2𝜋𝑎𝑎𝜕𝜙𝑎𝑐𝑜𝑠𝜙 𝜕𝜙
𝑅 1𝜕𝑄̅ 𝜕 1 𝜕𝑣̅̅′̅̅𝑇̅̅′𝑐𝑜𝑠𝜙 1 𝜕𝑢̅̅̅′̅𝑣̅̅′𝑐𝑜𝑠2𝜙 𝜕𝑋̅
= ( − )+𝑓( − ), (2)
𝑝 𝑎𝜕𝜙 𝑎𝜕𝜙𝑎𝑐𝑜𝑠𝜙 𝜕𝜙 𝑎𝑐𝑜𝑠2𝜙 𝜕𝑝𝜕𝜙 𝜕𝑝
𝑆2 = −( 𝑅𝑑){( 𝜕𝑇̅ )−( 𝑅𝑑)( 𝑇̅ )}, and 𝑋̅ = 1 𝜕2𝑢̅̅̅′̅𝑣̅̅′𝑐𝑜𝑠2𝜙 −𝑓𝑣̅.
𝑝 𝜕𝑝 𝑐𝑝 𝑝 𝑎𝑐𝑜𝑠2𝜙 𝜕𝑝𝜕𝜙

Here, overbar and prime represent the zonal mean and deviation from it, respectively. 𝑓 is the
Coriolis parameter, R=287 J kg-1 K-1 the specific gas constant for dry air, c =1004 J kg-1 K-1 the
p
specific heat capacity, 𝑆2 the static stability, 𝑋̅ the zonal drag, 𝑄̅ the diabatic heating, 𝑣 ̅̅ ′ ̅ 𝑇 ̅̅ ′ the
eddy heat flux, and 𝑢′𝑣′ the eddy momentum flux. Other symbols follow the standard definitions
in the atmospheric sciences. Both eddy heat and momentum fluxes are computed using monthly
data, as CESM1 provides daily data only at three vertical levels. To distinguish the streamfunction
obtained in Eq. (2) from the streamfunction computed in Eq. (1), the solution of Eq. (2) is denoted
by Ψ .
𝐾𝐸

Equation (2) can be written in a simple form:
𝐿Ψ = 𝐷 = 𝐷 +𝐷 +𝐷 +𝐷 (3),
𝐾𝐸 𝑄 ℎ 𝑚 𝑋
𝑤ℎ𝑒𝑟𝑒 𝐿 = 𝑓2 𝑔 𝜕2 +𝑆2 𝑔 𝜕 1 𝜕 .
2𝜋𝑎𝑐𝑜𝑠𝜙𝜕𝑥2 2𝜋𝑎𝑎𝜕𝜙𝑎𝑐𝑜𝑠𝜙𝜕𝜙

where L is the linear differential operator. 𝐷 is the sum of all forcing terms on the right-hand side;
diabatic heating (𝐷 ), eddy heat flux (𝐷 ), eddy momentum flux (𝐷 ), and zonal drag terms (𝐷 ).
𝑄 ℎ 𝑚 𝑋
Ψ is then computed by applying an inverse operator (L-1) to the right-hand side terms of Eq. (3).
𝐾𝐸
The change in Ψ (i.e., 𝛿Ψ ) is computed from 1980 to 2080, by decomposing L, Ψ , and D
𝐾𝐸 𝐾𝐸 𝐾𝐸
into their values in the past period (1941–1970; denoted by past) and the deviation from the past,
as in the literature 6,34: L=L + 𝛿L(t), Ψ =Ψ + 𝛿Ψ (t), and D = D + 𝛿D(t).
past 𝐾𝐸 𝐾𝐸,𝑝𝑎𝑠𝑡 𝐾𝐸 past

𝛿Ψ ≈ 𝐿 −1(𝛿𝐷−𝛿𝐿Ψ )
𝐾𝐸 𝑝𝑎𝑠𝑡 𝐾𝐸,𝑝𝑎𝑠𝑡
= 𝐿 −1(𝛿𝐷 +𝛿𝐷 +𝛿𝐷 +𝛿𝐷 −𝛿𝐿Ψ )
past 𝑄 ℎ 𝑚 𝑋 𝐾𝐸,𝑝𝑎𝑠𝑡
= 𝛿Ψ +𝛿Ψ +𝛿Ψ +𝛿Ψ +𝛿Ψ . (4)
𝑄 ℎ 𝑚 𝑋 𝑆2

Here, the small non-linear term, 𝛿𝐿Ψ , is neglected. This equation is solved numerically for
𝐾𝐸,𝑝𝑎𝑠𝑡
each ensemble member using a Jacobi iteration method.

Physically, the first four terms on the right-hand side of Eq. (4) represent the contributions of
diabatic heating (𝛿Ψ ), eddy heat flux (𝛿Ψ ), eddy momentum flux (𝛿Ψ ), and zonal drag
𝑄 ℎ 𝑚
changes (𝛿Ψ ) to stream function change since 1980 (𝛿Ψ ) under fixed static stability. The last
𝑋 𝐾𝐸
term, 𝛿Ψ , represents the change in stream function due to static stability change when the
𝑆2
preceding four terms are constant in time.

While ref.54 provides critical insights into the application of the KE equation, particularly regarding
its limitations in predicting steady-state responses to perturbations, our analysis employs the KE
framework as a diagnostic tool to quantitatively understand the contributing factors to long-term
trends of Ψ changes from 1921–2080 relative to a 1941–1970 baseline, rather than inferring new
steady states. Additionally, the Ψ changes reconstructed from the KE equation (Ψ ), defined as
𝐾𝐸
the sum of all individual rightmost terms in Eq. (4), successfully capture key features of the
actual Ψ changes (Supplementary Fig. 5). This close agreement supports the validity of the KE-
based diagnosis for understanding the long-term trends.

CESM1 LENS

A set of CESM1 55 large ensemble (LENS) simulations with a 1° spatial resolution 36 is analyzed
in this study. These simulations consist of 1) a 40-member ensemble simulation with all forcings
(ALL), 2) a 20-member ensemble simulation with time-fixed aerosol concentrations (XAER), and
3) a 20-member ensemble simulation with time-fixed greenhouse gas concentrations (XGHG).
Each ensemble member in XGHG and XAER experiments is initialized in the same manner in
ALL experiment. ALL experiment is forced by historical forcings for the period 1920–2005 and
by the CMIP5 RCP8.5 scenario for the period 2006–210053. Both XGHG and XAER experiments
use the same forcing protocol, except that either greenhouse gas or aerosol concentrations are held
fixed at the 1920’s condition. The temporal evolution of global-mean surface air temperature from
1920 to 2080 is illustrated in Supplementary Fig. 8. ALL experiment shows a steady warming
trend from the past to the future, being the warming intensity sensitive to the period. The warming
before the year 1980 is much weaker than the one afterward, with a large variability. The warming
trend in ALL experiment (-0.62 K decade-1) is well captured by the linear sum of the GHG and
AER experiments (GHG+AER; -0.62 K decade-1), supporting the use of these experiments to
attribute forced responses. They are compared to an 1800-year pre-industrial control simulation
(piControl), which is used to estimate the internal climate variability.

The impacts of greenhouse gases and aerosols forcings on the past and future changes in the HC
intensity are quantified by computing the ensemble-mean differences between the two experiments,
i.e., ALL-XAER (referred to as AER experiment) and ALL-XGHG (referred to as GHG
experiment). AER experiment isolates the effect of aerosol forcing, while the GHG experiment
isolates that of greenhouse gas forcing. Although 40 members are available for ALL experiment,
only the first 20 members are analyzed to make a fair comparison to XGHG and XAER experiment.
The results from all 40 ensemble members in ALL experiment are quantitatively the same as those
from the first 20 members (Compare Fig. 1a to Supplementary Fig. 9)

CESM2 LENS

A set of CESM2 LENS simulations56 is also examined. They differ from CESM1 LENS
simulations not only in model but also in experiment design. While CESM1 LENS uses an all-
but-one framework (i.e., XGHG and XAER), CESM2 LENS uses a forcing-only framework.
CESM2 single-forcing LENS simulations consist of 20 ensemble members of anthropogenic
aerosol-only (AAER) experiments, and 15 ensemble members of greenhouse gas-only (GHG)
experiments. To maintain consistency, the first 15 ensembles from both experiments are analyzed.
Each experiment spans from 1920 to 2050, which is shorter than the period covered by CESM1
LENS, based on historical (1920–2014) and SSP3-7.0 (2015–2050) scenarios.

Although CESM2 LENS is the latest single-forcing large ensemble experiments, this study
primarily analyses CESM1-LENS. This is because it has a longer temporal coverage (extending
to 2080) and larger ensemble size (20 members), both of which are essential for robustly detecting
long-term forced responses and identifying the underlying physical mechanisms.

CMIP6 DAMIP

In addition to CESM1 LENS, we use model output from the Detection and Attribution Model
Intercomparison Project (DAMIP)37 of CMIP657. DAMIP provides single-forcing simulations that
isolate the effects of individual forcing agents, including anthropogenic aerosols and greenhouse
gases, in both historical and future climates. This dataset allows us to assess whether the HC
response to aerosol forcings is consistent across a broader set of models. Specifically, four models
which provide both the historical aerosol-only (hist-aer) and GHG-only (hist-GHG) simulations
for 1850–2020, as well as their respective future scenarios (ssp245-aer and ssp245-GHG) for
2021–2100, are used. They are CanESM5, GISS-E2-1-G, MIROC6, and NorESM2-LM. Historical
simulation for 1850–2014 and SSP2-4.5 scenario simulation for 2015–2100 are also examined to
provide a more comprehensive comparison with CESM1 LENS. For consistency, only the first
ensemble member from each model (r1i1p1f2 for GISS-E2-1-G and r1i1p1f1 for the others) is
used for the common period 1920–2080 for a direct comparison among the simulations. Although
one ensemble member from each model is utilized to avoid overpresentation of models with larger
ensembles, the results do not change significantly when all available ensemble members are used.

It is important to note that the aerosol scenarios differ between the model experiments. DAMIP
follows the SSP2-4.5 aerosol pathway, while XAER experiment in CESM1 LENS and aerosol-
only experiment in CESM2 LENS are based on the RCP8.5 and SSP3-7.0 aerosol scenarios,
respectively. As such, comparisons between CESM1 LENS, CESM2 LENS, and DAMIP should
be interpreted qualitatively.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "I have completed my review of “Anthropogenic Aerosol Decline Substantially Amplifies Northern Hadley Circulation Weakening in the 21st century” by S.-Y. Kim et. al., submitted 2025 to Nature Communications.\nIn the study, the authors first quantify the change in the strength of the northern- and southern-hemisphere Hadley Circulation (HC) under historic and projected aerosol, greenhouse gas, and all-forcing scenarios in the CESM1 large ensemble. The authors find that the northern HC weakens under the all-forcing scenario from 1920-2080, while the change in the southern HC is indistinguishable from natural variability. They attribute this decline in the northern hemisphere HC to a combination of GHG and anthropogenic forcings through use of the CESM1 single-forcing large ensemble simulations. Further analysis of the CMIP6 Detection and Attribution Model Intercomparison Project (DAMIP) shows qualitatively similar results, but of a smaller magnitude.\nThe authors then utilize a Kuo-Eliassen decomposition to separate changes in the overturning streamfunction into contributions from diabatic heating, eddy heat flux, eddy momentum flux, zonal friction terms, and changes in static stability. This decomposition method was then applied to the various CESM1 Large Ensemble simulations. Differences in the components between the ALL, GHG, and AER configurations were then compared.\nI found the analysis contained within the study to be sound and that the topic potentially falls within the scope of Nature Communications. However this manuscript does not clearly articulate the key result(s) of the study, and how they are significant to the field. Therefore I recommend a major revision before this manuscript is accepted for publication. I have included additional comments below that I hope the authors will use to strengthen the manuscript.\n----------------\nGeneral Comments\n----------------\nAs written, the primary conclusion seems to be that past and future changes in aerosol forcing lead to a change in the strength of the northern hemisphere Hadley circulation. This is not a particularly novel result, and has been explicitly discussed (or implied, through discussion of e.g., atmospheric heat transport or ITCZ shifts) in various studies including:\n* Ming, Y., and V. Ramaswamy, 2011: A model investigation of aerosol-induced changes in tropical circulation. J. Climate, 24, 5125–5133, https://doi.org/10.1175/2011JCLI4108.1.\n* Hwang, Y.-T., D. M. W. Frierson, and S. M. Kang, 2013: Anthropogenic sulfate aerosol and the southward shift of tropical precipitation in the late 20th century. Geophys. Res. Lett., 40, 2845–2850, https://doi.org/10.1002/grl.50502.\n* Kang, S. M., 2020: Extratropical influence on the tropical rainfall distribution. Curr. Climate Change Rep., 6, 24–36, https://doi.org/10.1007/s40641-020-00154-y.\n* Needham et. al., 2024: Aerosol-Induced Changes in Atmospheric and Oceanic Heat Transports in the CESM2 Large Ensemble. J. Climate, 37, 6395-6412, https://doi.org/10.1175/JCLI-D-23-0455.1\nIn other words, I am not surprised to see a significant trend in the NH HC under the ALL-xAER scenario. Instead, I am much more interested in why this would be the case.\nI believe that the authors’ use of the Kuo-Eliassen equation is useful perspective from which to address this question. I would encourage the authors to consider how they could rework their discussion (i.e., of Fig. 2) to relate changes in these KE terms to real, physical phenomena in the atmosphere and oceans. Some of this has already been included (e.g., the diabatic heating term and precipitation). However, as I read the manuscript (particularly lines 118 – 173) I found myself constantly stopping and trying to reason through why a change in aerosol forcing would lead to a particular response to one of the KE terms.\n-----------------\nSpecific Comments\n-----------------\nLine 39 “rose steadily”: may want to specify the initial time bounds. For example, “rose rapidly from the end of WWII until the 1970s”\nLine 42: I found “unmask” to be a strange word choice. May be better served to rewrite this sentence to clarify that aerosol radiative forcing previously opposed/balanced GHG radiative forcing, but now aerosol forcing has diminished.\nLines 44-47: Should probably bring in some of the observational evidence of the tropical precipitation shift. For example, Hwang et al., 2013 \"Anthropogenic sulfate aerosol and the southward shift of tropical precipitation in the late 20th century\" and subsequent literature\nLine 57-58: Any particular reason for the choice of the CESM1-LENS simulations when the CESM2-LENS simulations are available? For example, a preference for the all-but-one over the only-one experimental setup? Should probably at least comment on why you are using the older simulations.\nLine 64: “ALL” has not been defined at this point in the text. Reference the methods?\nLines 67-68: Specifically on the “reversing an earlier strengthening” comment. This relates my general comment on how previous work has linked aerosol forcing to the 1970s era peak. The Needham et al. (2024) study referenced above explicitly discussed this in the context of a change in the streamfunction for CESM2-LENS simulations.\nLine 74: Should briefly note the sign change as the reason to use PSImin vs PSImax in the SH\nLine 109: “models show qualitatively similar results” is models the right word here, or should it instead be something like (e.g.,) “multi-model mean from multiple models under the same forcing scenario.”\nLine 125: First instance of “KE,” should use the full name and maybe reference the methods section.\nLines 127-128: This is an opportunity to expand a bit on my general comment above. I would suggest briefly linking the diabatic heating term to precipitation which is discussed a bit later in the manuscript. This allows the reader to understand the physical interpretation of the mathematical quantity called “diabatic heating.” Many readers will be able to make the connection themselves. But explicilty linking the physical to the mathematical within the text helps guide the reader to consider the relationship between the hadley circulation and (in this case) precipitation. Similar comments could be made for the other terms. This then helps the reader interpret Fig 2 as physical quantities instead of simply as bars on a plot.\nLines 147-148: Similarly, a brief note about the relationship between S^2 and -dT/dp as seen in the methods section makes it clear to the reader why you are referencing Fig S4e.\nLines 157-159: The comment about the Northern Pacific may be unclear to some readers so consider supporting this statement with a citation\nLine 169: Maybe clarify that “reduced Q” is relative to the All / GHG simulations\nLines 169-171: In Fig. S5 the “peak\" in precipitation ~10N is pretty weak for the DAMIP simulations. But I see that the STD range narrows. Consider reevaluating this claim that the patterns are consistent to more precisely align with Fig S5.\nLines 177-178: This again relates to my general comment above. The NHC weakening has also been explained in the context of changes in anthropogenic aerosols in those previous studies I mentioned, and references therein.", "reviewer_2": "The authors explore the potential influence of anthropogenic aerosol (AA) forcing on the Northern Hemisphere (NH) hadley cell weakening from 1970 to 2080 based on single forcing simulations from various climate models. Their analyses reveal that about 40% of the NH Hadley cell weakening is attributed to the decline in AA. Based on the KE equation decomposition, they further demonstrate that the weakening is linked to diabatic heating patterns asymmetrically placed in the two hemispheres.\nThe analyses based on KE equation is interesting, but I have a fundamental concern about this manuscript, where the authors seem to oversimplify the aerosol emission to be simply “decline” since 1970, which is a bit outdated compared to relevant studies published in recent years. It is true that the global-mean aerosol concentration has been continuously decreasing since the 1970s. However, the declines only occur in Europe and North America, while emissions in other regions, especially East and South Asia, kept increasing, which seems to be less discussed in the introduction. Actually, many of the cited studies discussing global-mean aerosol forcings were published about ten years ago, so some of the discussions on hemispheric aerosol imbalance seem to be outdated.\nMany studies have emphasized the complex co-impacts of regional aerosol forcings due to the strong spatial heterogeneity (e.g., [1-8]), in that different regional aerosol forcings could have distinct teleconnections to the large-scale circulations. For example, the Hadley cell discussed in this manuscript is sensitive to the latitudinal locations of forcings, and the aerosol forcings in Asia and Europe since the 1970s are located at distinct zonal and meridional locations, which should have very different dynamical impacts on the Northern Hemisphere Hadley cell ([3]).\nMoreover, since the authors also include the future projections up to 2080, it is worth noting that the emissions between East Asia and South Asia started to show different trends since the recent decade as well, which further increases the complexity (e.g., Ref.[9-11]). So recently many efforts have been made to diagnose the impacts of more aerosol forcings (e.g., RAMIP; [8-9]), and the RCP emission scenario seems to be outdated to diagnose the future impacts of aerosols.\nTherefore, I am concerned that the authors’ attribution to “decline of aerosol forcing” oversimplified the dynamical mechanisms behind the large-scale circulation responses. Although the energy analyses are interesting, I am concerned this study might not be novel and robust enough to extend the current understanding of anthropogenic aerosols, to be honest….\nMinor comments:\nLine 37: The impact of aerosol on the Northern hemisphere HC was discussed in some studies (e.g., Ref[3, 5]).\nLine 39 and many other places: The statement is misleading. “declined due to growing aerosol mitigation efforts” only occurred in North America and Europe as mentioned above. This should be clarified and emphasized here and there.\nLine 106: Some recent studies have conducted inter-model comparisons of aerosol forcings (e.g., [10]), which are worth referring to.\nLine 283: I think that CESM2 single forcing is still worth diagnosing in the authors’ setup. The aerosol emissions beyond 2050 are fairly small, so it does not matter that much if we stop at 2050. Also, CESM2 is more sensitive to aerosol forcings, which is debated to be unrealistic in some studies though. The differences between CESM1 and CESM as well as the caveat of CESM2 aerosol modules are worth discussing.\nLine 291: I am not quite sure if I understand the authors’ argument correctly, but the claim of “one-to-one comparison between the experiments” are incorrect for me. Although the single forcing simulations are branched from the ALL experiment, they are different “worlds” when forcings are changed since the internal variability changes after the first few decades. So it is impossible to do a “one-to-one” comparison between ensemble members.\nLine 292: Intuitively, all ensemble members are used when calculating forced responses to smooth out the impacts of internal variability as much as possible. It could be better if the authors could compare the results of ALL between using all members and using the first 20 members.\nLine 317: Same as the previous comment. Intuitively, all ensemble members should be used to calculate the ensemble mean, in my opinion.", "reviewer_3": "This study showed that the declining trend of anthropogenic aerosols can accelerate greenhouse gas induced weakening of Northern Hadley circulation based on model experiments. This study also discussed the main drivers of weakening of HC caused by aerosol forcing and GHG forcing from KE equations. This is an interesting topic, and I enjoyed reading the manuscript. However, I have few concerns need to be addressed before it can be published.\n1) As the authors stated the role of aerosols (or aerosol trend) on HC is relatively less studied compared to the extensively studied role of GHG. However, I found the studies reviewed and cited in this study doesn’t represent the current status of the studies on the role of aerosols. Followings are few examples highly relevant to this study. This is my main concern.\nHess, O., & Chemke, R. (2024). Anthropogenic forcings reverse a simulated multi-century naturally-forced Northern Hemisphere Hadley cell intensification. Nature Communications, 15(1), 1–8. https://doi.org/10.1038/s41467-024-48316-y\nKalik, V., Krishnan, R., Ayantika, D. C., Swapna, P., Manmeet, S., Sandeep, N., et al. (2024). Understanding the response of tropical overturning circulations to greenhouse gas and aerosol forcing. Environmental Research: Climate, 3(4). https://doi.org/10.1088/2752-5295/ad6f3c\nLionello, P., D’Agostino, R., Ferreira, D., Nguyen, H., & Singh, M. S. (2024). The Hadley circulation in a changing climate. Annals of the New York Academy of Sciences, 1534(1), 69–93. https://doi.org/10.1111/nyas.15114\nSun, B., Zheng, Y., Li, W., Zhou, S., Cai, J., Li, H., et al. (2025). Attribution of the Increased Intensity of Upper-Level Hadley Circulation Under Climate Change. Geophysical Research Letters, 52(14). https://doi.org/10.1029/2025GL115984\nYing, T., Li, J., Fu, Q., Liu, G., Zhang, L., Xia, Y., & Hu, Y. (2024). Fractional change of scattering and absorbing aerosols contributes to Northern Hemisphere Hadley circulation expansion. Science Advances , 10(46), 1–12. https://doi.org/10.1126/sciadv.adq9716\nZheng, Y., Sun, B., Li, W., Zhou, S., Cai, J., Li, H., & He, S. (2025). Attribution of regional Hadley circulation intensity changes in the Northern Hemisphere. Atmospheric and Oceanic Science Letters, 18(6), 100613. https://doi.org/10.1016/j.aosl.2025.100613\n2) L94, 96, etc. “the decline in aerosol concentrations” in 1970-2080 was presented as a key driver of the HC change, so adding a supplementary figure to show the timeseries of anthropogenic aerosols would help readers understand the finding. Aerosol concentration has been increased between 1920 and 1970 and the rate of change in this period is expected to be larger than the rate of change(decline) in 1970-2080. However, HC response to the change of aerosol concentration seems larger in 1970-2080. Also, HC response to AER is within natural variability for the entire study period (Fig. 1c). Interestingly, between 1970 and 2040, the changes (rate of change) due to GHG and AER are almost identical. Do these indicate GHG is a key driver, and the role of AER is just weakening the impact of GHG?\n3) During early period, 1920-1970, Fig. 1 shows AER enhance HC while GHG weaken HC slightly. Any thought on this? Can findings from Fig. 2 & Fig. 3 be inversely applied to this period (1920-1970)?\n4) Definition of the intensity of HC. Intensity of the HC was defined as maximum mass streamfunction at 500hPa. This point measure doesn’t seem to capture the changes of HC (for example, Fig. 1b vs Fig. S1c&f). Fig. 2 would be greatly affected by the selection of the point measure. Does the location of the maximum mass streamfunction stay same (in latitude) in different simulations (ALL vs XAER vs XGHG)?\n5) L163, S5f --> S4f"}, "author_response": "We thank the reviewer for the thoughtful and constructive comments. Following the\nreviewer’s suggestions, we revised the manuscript in a major way. In the revised\nmanuscript, we strengthened the process-level interpretation of the Kuo-Eliassen (KE)\ndiagnostics and highlighted the key findings. The text about Fig. 2 is also fully rewritten\nto explain KE terms and their impacts more physically. A point-by-point response to\neach comment is provided below, with our replies distinguished in colored and indented\ntext.\nBefore addressing the reviewer’s comment, we would like to highlight a major change\nto the analysis period. Based on aerosol optical depth (AOD) and global-mean surface\nair temperature time series, the analysis period is now divided into 1920-1980 and\n1980-2080, instead of 1920-1970 and 1971-2080. The overall results (Table R1) are\nsimilar to those presented in the original manuscript, but can be directly compared\nwith previous studies that divided the analysis period across the year 1980 (Kang et\nal., 2021; Dias et al., 2021; Shao et al., 2024). Note that Table R1 is identical to Table\n1 in the original manuscript and is shown here for easy comparison.\n\n[... omitted for brevity, contains Table R1 and detailed responses to Reviewers 1, 2, and 3 ...]"}, {"round": 2, "reviewer_comments": {"reviewer_1": "I commend the authors for their revisions to the manuscript, which I find is significantly improved over the original. In particular I think that the process-level interpretation of the key terms of the KE equation added significant value and will help a typical reader to translate the bar charts in Fig 2 into a physical understanding of the processes at hand. I also appreciate the clarifications regarding the choice of CESM1 LENS vs. CESM2 LENS.\nThe authors have responded satisfactorily to all of the comments I provided on the original manuscript. I can now recommend this manuscript for publication with only a few minor revisions based on the additional comments that I have included below.\n-----------------\nSpecific Comments\n-----------------\nLine 38-39: “A series of climate model simulations…” This phrasing is a bit ambiguous. I originally read this as a specific ensemble configuration (e.g., CESM1) but based on references 10, 17, and 25, I believe the authors simply meant that past studies relying on climate simulations have shown this effect. Perhaps this could be rephrased as “Past studies utilizing climate model simulations in different configurations have shown…” or similar\nLines 51-52: “…by examining large-ensemble single-forcing climate model simulations” it may be more precise to word this like “…by examining large ensembles of single-forcing climate model simulations” to clarify that more than one ensemble is used. Alternatively, consider explicitly listing out LENS1-SF, LENS2-SF, and DAMIP so that the abbreviations can then be used in the subsequent text, as the authors see fit.\nLine 85: Consider replacing “compare Fig. 1c with Fig. 1a” with “compare crossing of green lines in Fig. 1c with Fig. 1a” to make this more clear\nLine 155: Consider replacing “well capture” with “nearly but not exactly capture” or similar, which leads into the use of monthly-mean data for the eddy flux terms.", "reviewer_3": "I appreciate the authors for their efforts and time to address my comments on the earlier version of the manuscript. I am mostly satisfied with their response and revision. I have few additional comments.\n1. “contribution of aerosol forcing” or “in AER experiments”: These are used frequently throughout the manuscript. It gives the impression that the authors are describing the aerosol impact while the authors discuss the trend due to the reduction of aerosols. I suggest to make statement more clear. In fact, Fig. R2 shows aerosol effect as it shows trend during the period of increasing AOD. Fig. R2 and corresponding plots for ALL & GHG would be informative, so I suggest to include those plots as supplementary material.\n2. Fig. S1 suggests NH-SH difference of AOD is larger in 1920-1980 and smaller in after 1980. Accordingly, Fig. S2c & f show ITCZ shift southward(northward) before (after) 1980. On the other hand, Fig. S2 b & e indicate the expansion of NH HC. Potential expansion of HC is considered in the KE analysis (L137-139)? During 1920-1979, how the HC strengthen when ITCZ shift southward in AER?\n3. Table 1 shows 1920-1980 vs 1980-2080 while the discussion in L74-77 was based on before/after 1970.\n4. Fig. S1. Is this anomaly? If so, what is removed? How much is 0.0002 in the percentage values from the mean?\n5. L92, “Western Hemisphere” : Fig. S1 shows Northern Hemisphere.\n6. Fig. S6c, any thought on how aerosol caused instability in the tropics, 20S-20N?\n7. L181, “through the same thermodynamic processes”, Trend is shown, but it is not clear how aerosol or GHG play role in the thermodynamic processes (Fig. S6 c&f vs b&e).\n8. L189, “This”   location, but Qy is a gradient"}, "author_response": "We sincerely thank the reviewer for the constructive feedback throughout the revision process. We are pleased that the process-level interpretations of the Kuo-Eliassen equation and the clarification on the model selection helped improve the clarity and impact of our manuscript.\nWe have carefully addressed the remaining minor points as detailed below. Our responses are provided in blue-colored text and indented, and the corresponding changes are reflected in the revised manuscript.\n\n[... omitted for brevity, contains detailed responses to Reviewers 1 and 3 ...]"}]

Decision letter