EXTRATROPICAL–TROPICALINTERACTION MODEL
INTERCOMPARISON PROJECT(ETIN-MIP)
Protocol and Initial Results

Sarah M. K ang, Matt Hawcroft, Baoqiang Xiang, Yen-Ting Hwang, Gabriel Cazes,
Francis Codron, Traute Crueger, Clara Deser, Øivind Hodnebrog, Hanjun Kim, Jiyeong Kim,
Yu Kosaka, Teresa Losada, Carlos R. Mechoso, Gunnar Myhre, Øyvind Seland, Bjorn Stevens,
Masahiro Watanabe, and Sungduk Yu

ETIN-MIP is a community-wide effort to improve dynamical understanding of the linkages
between tropical precipitation and radiative biases in various regions, with implications foranthropogenic climate change and geoengineering.

T

he intertropical convergence zone (ITCZ) is anarrow equatorial band of intense rainfall that receives one-third of the global precipitation. Evena minor shift in the ITCZ position is of great societal
relevance not only because billions of people dependon this water source for their freshwater and foodproduction but also because the latent heat released
by condensation of water vapor in the atmosphereassociated with tropical precipitation drives profoundglobal impacts via poleward propagating Rossby
waves (Hoskins and Karoly 1981). Moreover, a displacement in the ITCZ position exerts a considerable
influence on the extratropics through changes in thefrequency of tropical cyclones (Dunstone et al. 2013;
Merlis et al. 2013), the poleward edge of the Hadleycirculation (Kang and Lu 2012; Chemke and Polvani2019), and the midlatitude jet position (Ceppi et al.
2013; Cvijanovic et al. 2013). It is for these reasons thatthe question of what controls the position, strength,
AMERICAN METEOROLOGICAL SOCIETY

and variability of the tropical rainbelts has emerged
as one of the central questions of climate science(Bony et al. 2015).
Despite the crucial importance of correctly simulating the distribution of tropical precipitation, generations of global climate models (GCMs) have had
difficulty simulating the observed pattern of tropicalprecipitation, with a too-pronounced “double ITCZ”(Mechoso et al. 1995; Zhang et al. 2015) being a robust bias. Great effort has been made to correct thisbias because it substantially influences the reliabilityof future climate projections (Zhou and Xie 2015).
This bias manifests in both hemispherically symmetric and antisymmetric components (Adam et al.
2016): the symmetric component is characterized by
deficient precipitation in the equatorial region andexcessive precipitation in the off-equatorial region;
the antisymmetric component is characterized byan overestimation of precipitation in the southern
DECEMBER 2019

| 2589tropics relative to the northern tropics manifested ina too zonally oriented and eastward extended South
Pacific convergence zone (SPCZ). In this study, we
will refer to the hemispherically antisymmetric component as the double ITCZ bias. In general, the double
ITCZ bias has been attributed to local origins suchas poor representation of tropical ocean–atmosphere
feedbacks (Lin 2007), stratocumulus clouds (Ma et al.
1996) and associated bias in tropical radiative fluxes
from atmospheric models (Xiang et al. 2017), unrealistic representation of convective entrainment rate
(Hirota et al. 2011), biased sea surface temperature(SST) thresholds leading to the erroneous onset ofdeep convection (Bellucci et al. 2010), and unrealistic
winds in the eastern Pacific and coastal areas (DeSzoeke and Xie 2008; Zheng et al. 2011). In a recent
paper, Song and Zhang (2018) report on a major reduction of the double ITCZ bias in their model witha revised parameterization of deep convection.
On the other hand, extratropical energy biases
have also been proposed as a possible cause of the
double ITCZ bias. In particular, the warm bias in
the Southern Hemisphere extratropics, observedin many GCMs associated with cloud biases over
the Southern Ocean, is suggested to contribute to
the double ITCZ bias (Hwang and Frierson 2013; Li
and Xie 2014). In response to the hemispheric energy imbalance associated with a warmer Southern
Hemisphere, the Hadley circulation adjusts in a way
to transport energy northward via its upper branchwhile transporting moisture southward via its lower
branch (Kang et al. 2008), thereby potentially driving
the double ITCZ. This energetics framework, which
relates the ITCZ response to the energy transport by
the Hadley circulation, has been successfully invoked
AFFILIATIONS: K ang , H. K im , and J. K im —School of Urban andEnvironmental Engineering, Ulsan National Institute of Science andTechnology, Ulsan, South Korea; Hawcroft—University of Exeter,
Exeter, United Kingdom, and University of Southern Queensland,
Toowoomba, Queensland, Australia; Xiang —NOAA/GeophysicalFluid Dynamics Laboratory, Princeton, New Jersey, and University Corporation for Atmospheric Research, Boulder, Colorado;
Hwang —Department of Atmospheric Sciences, National Taiwan
University, Taipei, Taiwan; Cazes —School of Engineering, Universidad de la República, Montevideo, Uruguay; Codron —LOCEAN/
IPSL, Sorbonne Université, CNRS, IRD, MNHN, Paris, France;
Crueger and Stevens —Max Planck Institute for Meteorology,
Hamburg, Germany; Deser—Climate and Global Dynamics,
National Center for Atmospheric Research, Boulder, Colorado;
Hodnebrog and Myhre —Center for International Climate Research(CICERO), Oslo, Norway; Kosaka—Research Center for Advanced
Science and Technology, The University of Tokyo, Tokyo, Japan;

2590 |DECEMBER 2019in a number of studies to explain how the ITCZ
responds to extratropical thermal forcing in global
climate models that do not include ocean dynamics (e.g., Broccoli et al. 2006; Kang et al. 2009). Slabocean coupled GCM experiments even suggest theextratropics as the forcing location most effective at
shifting the ITCZ position (Seo et al. 2014), lending
credibility to the hypothesis that remote effects of theSouthern Ocean warm bias are major contributors to
the double ITCZ bias.
To investigate this hypothesis, several recent studies perturbed the Southern Hemisphere extratropics
in fully coupled atmosphere–ocean models. Kay et al.
(2016) enhance cloud brightness over the Southern
Ocean, which is shown to result in little shift in tropical precipitation, in contrast to the expectation basedon slab ocean model studies. Similarly, Hawcroft et al.
(2017) apply targeted albedo corrections in the Southern Ocean and the double ITCZ problem persists.
Mechoso et al. (2016) artificially reduce insolation
over the southern extratropics in two independent
models. The one that more realistically simulates
the sensitivity of stratocumulus to underlying SST
shows some improvement in the double ITCZ bias,
though only partially in the zonal mean. Xiang et al.
(2018) contrast the tropical precipitation response toincreased insolation over the southern extratropics
and the southern tropics, respectively. While thesouthern tropical forcing is certainly more effectiveat shifting the ITCZ, the extent of the ITCZ shift
in response to the southern extratropical forcing is
still more significant than in other aforementioned
studies. The same conclusion is drawn from the experiments where stratospheric aerosols that reflect
incoming radiation are imposed in defined latitude
Losada—Department of Earth Physics and Astrophysics, Facultyof Physics, Universidad Complutense de Madrid, Madrid, Spain;
Mechoso —Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, California; Seland —Norwegian Meteorological Institute, Oslo, Norway; Watanabe —Atmosphere and Ocean Research Institute, The University ofTokyo, Tokyo, Japan; Yu —Department of Geology and Geophysics,
Yale University, New Haven, Connecticut
CORRESPONDING AUTHOR: Sarah M. Kang, skang@unist.ac.kr
The abstract for this article can be found in this issue, following the tableof contents.
DOI:10.1175/BAMS-D-18-0301.1
A supplement to this article is available online (10.1175/BAMS-D-18-0301.2)
In final form 26 August 2019©2019 American Meteorological Society
For information regarding reuse of this content and general copyrightinformation, consult the AMS Copyright Policy.

bands (Hawcroft et al. 2018). In sum, the ITCZ shift
responses to extratropical energy perturbations
are only modest in dynamic ocean coupled GCMs,
though with substantial differences among models.
The damped ITCZ response in fully coupled simulations relative to slab ocean simulations is because
energy perturbations need not be balanced by theatmosphere alone but are also mediated by changes
in oceanic heat transport. The less the energy perturbations are balanced by changes in atmospheric heattransport, due to oceanic compensation, the smaller
the ITCZ shift response. Previous studies indicate awide range of the atmospheric fractional contribution to the total cross-equatorial energy transport
response to the Southern Hemisphere extratropicalcooling that spans between 20% (Kay et al. 2016)
and 62% (Hawcroft et al. 2018). Such differences
may stem from differences in experimental design,different model physics, or underlying biases in any
given model. To address this issue, Kang et al. (2018a)
suggest that multimodel comparisons should be constructed to cleanly examine the nature and the spreadof model response to prescribed energy perturbations
at different latitude bands.
This proposal has resulted in the Extratropical–
Tropical Interaction Model Intercomparison Project(ETIN-MIP). The Green’s function approach would
be ideal for thoroughly assessing the global impactof regional energy perturbations, and was adopted
in either an AMIP-type prescribed SST setting (Zhouet al. 2017) or a slab ocean setting (F. Liu et al. 2018)
where warming or cooling is added over a limited
domain throughout the entire globe. However, thisis prohibitive in practice for fully coupled models
due to the high computational cost. As an alternative
approach, ETIN-MIP proposes to selectively perturb
three target regions of persistent model biases in fully
coupled models. Previous studies have adopted asimilar approach, but used one fully coupled climate
model (e.g., Hawcroft et al. 2018; Xiang et al. 2018;
White et al. 2018). ETIN-MIP will cast light on which
regions are particularly important and sensitive toenergy perturbations/biases in the context of theirteleconnections and whether this sensitivity is robust
by investigating causes of intermodel diversity andthe specific processes that govern any spread in themodels’ response.
Numerical experiments defined by ETIN-MIP are
guided by four core science questions:• How sensitive is the partitioning of energy transport response between the atmosphere and ocean
to the region of forcing?
AMERICAN METEOROLOGICAL SOCIETY• Does the ocean heat transport response primarily
result from dynamic ocean circulation changes orocean temperature anomalies?
• Which part of the ocean circulation (i.e., Ekman
transport, subtropical gyres, deep overturning
circulation) is most effective at inducing crossequatorial energy transport?
• How much does the intermodel response spreadvary with forcing location and what are the implications for understanding (i) the causes of bias in
the climatology of those models and (ii) the likely
fidelity of their future projections, individuallyand collectively?
By answering these questions, ETIN-MIP aims
to provide an improved understanding of the link
between tropical precipitation and regional energy
anomalies that are both local and remote. Moreover,
ETIN-MIP will provide a platform to study thecauses of climatological biases in coupled models at aprocess level, and the plausibility of model responses
to external perturbations, thereby contributing to
improve our ability to make robust future projectionsof regional patterns of climate change.
EXPERIMENTAL DESIGN. The first tier ofETIN-MIP asks modeling groups to perform one
control and three perturbation experiments with
their state-of-the-art fully coupled models. The
control experiment (CNTL) is a fully spun-up preindustrial run where 150 simulated years of output isrequested to be provided from a start date chosen to
initialize subsequent perturbation experiments. The
three perturbation experiments are also integrated
for 150 years after an abrupt reduction of solar flux
over three different latitude bands: the southern extratropics between 45° and 65°S (SEXT), the southern
tropics between 5° and 25°S (STRO), and the northern
extratropics between 45° and 65°N (NEXT). The
geographical distribution of solar flux perturbations
in all experiments are shown in Fig. 1. The forcing
domains correspond to regions with the largest intermodel spread in cloud radiative effects (Boucher
et al. 2013; Hwang and Frierson 2013). The forcing
induced by the altered solar f lux is time varying
due to the seasonal and diurnal cycles of insolation.
The annual mean of net top-of-atmosphere (TOA)
radiative forcing integrated over the forcing domain
is constrained to produce a total energy perturbationof approximately 0.8 PW, equivalent to 1.6 W m–2 inthe global mean.
In a fully coupled system, the magnitude of theimposed forcing is difficult to estimate due to the
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Fig. 1. The geographical distribution of solar flux perturbation.

slowly evolving SST and the associated feedbacks(Myhre et al. 2013). Furthermore, Forster et al. (2016)
demonstrates that the effective radiative forcing diagnosed from fixed SST simulations is more accurate
than that based on the regression method (Gregory
et al. 2004). Therefore, we estimate the forcing
magnitude based on model experiments with fixed
SSTs using the GFDL Atmosphere Model, version 4(AM4) (Zhao et al. 2018). AM4 integrated with theobserved SST and sea ice concentration is perturbed
by reducing solar flux as in one of the perturbation
experiments. The difference of annual-mean TOA
net shortwave radiation over the forcing domain
between the control and perturbation experiments
is set to be approximately 0.8 PW in GFDL AM4.
Because of the intermodel differences in climatology of planetary albedo, the same perturbation insolar flux does not necessarily guarantee a forcingof same magnitude. Thus, we compute a weighting
factor for each model experiment so as to adjust theprescribed solar flux perturbation multiplied by one
minus the planetary albedo in CNTL of each model
to 0.8 PW (Table ES1 in the online supplemental material: https://doi.org/10.1175/BAMS-D-18-0301.2).
This weighting factor, which ranges between 0.80
and 1.13 depending on the forcing region and amodel, is applied to any diagnostics in postprocessing prior to taking the multimodel mean. Keeping
in mind that our original motivation is to address
the double ITCZ bias in the mean state, we analyze
the last 50-yr mean of 150-yr integrations of coupledmodel experiments because 1) the simulations reach2592 |DECEMBER 2019a new quasi-equilibrium state after ~40 years basedon the global imbalance of TOA radiation as well as
net surface fluxes (Fig. ES1) and 2) 50 years is a longenough period to remove any signatures of decadal
variability. Although the deep ocean would be far
from reaching an equilibrium (Fig. ES2), we notethat it is not critical for our purpose.
Additional tier 2 experiments are under development by a subset of models to further 1) examine
sensitivity to the type of forcing (surface vs TOA), 2)
enable direct comparison between fully coupled andslab ocean simulations, 3) examine linearity to forcing magnitude, 4) examine the asymmetric response
to cooling and heating cases, and 5) separate rapid
adjustments from feedback responses via fixed SST/
sea ice experiments. These additional experiments
will help to elaborate upon and evaluate the robustness of our findings. Any modeling groups interested
in participating in either tier 1 or 2 are welcome tocontact the corresponding author.
Given the focus of ETIN-MIP on energy budgets,the diagnostics required to compute meridional
eddy heat and momentum fluxes for atmosphere andocean are requested (see Table ES2 for descriptions).
For ocean meridional mass and heat transport diagnostics, all parameterized components and meridional diffusion need to be provided. The variables inTable ES2 need to be calculated at every time step
before performing any time averages. We request to
output those variables at model levels (before interpolating to standard pressure levels) to better close
the budget.

Table 1. Description of the nine ETIN-MIP models. The analysis of UCLA–MIT GCM is based on the
average of last 20 years of 60-yr integrations. The analysis of NorESM1-HAPPI for NEXT is based on the
average of last 30 years of 100-yr integration. The relatively insensitive climate response to time (Fig. ES1)
justifies the inclusion of those simulation results in our analysis.
Model

Atmosphereresolution

Max Planck Institute Earth System Model (MPI-ESM1.2-LR)

T63 (1.875° × 1.875°), MPIOM1.6.3 (1.5°),
47 levels
40 levels

Ocean resolution

Key reference
Mauritsen et al. (2019);
Müller et al. (2018)

Hadley Centre Global Environ1.875° × 1.25°,
ment Model, version 2, Earth
38 levels
System (HadGEM2-ES)

1° reducing to 1/3° at
equator, 40 levels

Martin et al. (2011);
Collins et al. (2011)

Norwegian Earth System Model, 0.94° × 1.25°,
version 1 (NorESM1-HAPPI)
26 levels~1° and a displacedpole grid

Mitchell et al. (2017)

IPSL CM5A2

96 × 95 points,
39 levels

2° reducing to 1/2° at
equator, 31 levels

Dufresne et al. (2013)

GFDL AM4-FLOR

1° × 1°, 32 levels

1° × 1°, 50 levels

Xiang et al. (2018)

GFDL CM2.1

2.5° × 2°, 24 levels

1° reducing to 1/3° at
equator, 50 levels

Delworth et al. (2006)

Community Earth System
Model (CESM 1.2.2)

1.9° × 2.5°, 30 levels

1° (lon) and 0.6° reducHurrell et al. (2013)
ing to 0.3° at equator(lat), 60 levels

Model for Interdisciplinary
Research on Climate (MIROC5.2)

T85, 40 levels

1° × 1°, 63 levels

UCLA–MIT GCM

2.5° × 2°, 29 levels

1° × 0.3° for 10°S–10°N
1° ×1° poleward
22°S/N, 46 levels

ETIN-MIP model output is provided in the standardized format taken from a subset of the CMIP5
output protocol. The time mean over the last 50 yearsof a subset of output can be obtained online (https://zenodo.org/record/3362615#.XU6585MzbOQ). A
complete set of output, which is provided as 1) decadalmeans of each month for the entire simulation period,and 2) monthly means for the first and last 20 yearsof the simulation period, will be made available to theresearch community upon request to the corresponding author. Nine models participating in ETIN-MIP
and their descriptions are in Table 1.
TOA E N E RGY PE RTU R BATIO N AN D
CLIMATE RESPONSE. An initial finding from
ETIN-MIP is that among the three forcing domains,
the southern tropics is most efficient at driving a
meridional shift and manipulating the equatorial
peak of tropical precipitation (Fig. 2, left). The two
extratropical forcing cases exhibit a clear meridional shift of tropical precipitation in the Atlantic
and Indian Ocean, while a common equatoriallyconcentrated drying response appears in the Pacific.
The off-equatorial response in the Pacific features a
meridional shift in NEXT while it is nearly symmetric
AMERICAN METEOROLOGICAL SOCIETY

NoteNEXT run for
only 100 years

Watanabe et al. (2014)

STRO notavailable

Cazes-Boezio et al.
(2008)

Run for only
60 yearsin SEXT. To quantify these effects, we use the tropical precipitation asymmetry index (PASY), introducedby Hwang and Frierson (2013), and the equatoriallysymmetric precipitation index (PSYM), introduced
by Adam et al. (2016): PASY, the difference in the
precipitation averaged between 0° and 20°N andthat between 0° and 20°S normalized by the mean
precipitation between 20°S and 20°N, measures themeridional shift; while PSYM, the average precipitation
over 2°S–2°N divided by that over 20°S–20°N minus
1 measures the relative magnitude of the equatorial
peak. Changes in PASY and PSYM as well as changes intotal precipitation between 20°S and 20°N are shownin Fig. 3. For reference, overlaid with CNTL as a graystar symbol is the observed value based on Global
Precipitation Climatology Project (GPCP) data averaged between 1980 and 1999. The results clearly showthat the imprint of TOA energy biases on tropicalprecipitation differs depending on the geographic
location of the bias.
Figure 4 shows the global surface temperature
response to the prescribed TOA cooling in the three
perturbation experiments. The local cooling responseover the forcing domain is most pronounced in NEXT(−4.00 K) while the forcing domains are cooled
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| 2593

Fig. 2. Geographical distributions of the multimodel and annual mean changes in (a)–(c) precipitation (mmday–1) and (d)–(f) relative SST (defined as the SST subtracted from the tropical mean SST between 20°S and
20°N, in K), and their zonal-mean profiles over 20°S and 20°N. In the zonal-mean plots, the individual models
are color coded as in Fig. 3 and the multimodel mean is shown in black. Note the differing scale in the zonalmean precipitation response.

significantly less in the other two experiments with
−1.92 in SEXT and −0.89 in STRO. Although STRO
exhibits only a weak interhemispheric contrast in thesurface temperature response (Fig. 4, left), it exhibits
the largest meridional gradient of SST anomalies
within 20°S and 20°N (Fig. 2, right). Consequently,
STRO induces the strongest cross-equatorial Hadleycirculation anomalies (Fig. 4, right) and the largest
meridional shift of tropical precipitation (Fig. 2, left).
Figure 5a shows that the interhemispheric difference oftropical SST response is positively correlated with PASY
response. When all model experiments are considered,

85% of the intermodel variance of PASY response is
explained by variations in the meridional gradient of
tropical SST anomalies. The variance of PASY response
is nearly as well correlated with the cross-equatorial
atmospheric energy transport anomalies (FATM0),even within each experiment (Fig. 5b). This suggeststhat the ITCZ shift, atmospheric energy transport
and tropical SST changes are strongly coupled witheach other. Given this, we proceed to explain theintermodel spread of PASY response by investigating
the cause of the intermodel spread of FATM0 throughexamining the atmospheric energy budget.

Fig. 3. The tropical precipitation asymmetry index PASY (the difference in the precipitation averaged between
0° and 20°N and that between 0° and 20°S normalized by the mean precipitation between 20°S and 20°N), theequatorial precipitation index PSYM (the average precipitation over 2°S–2°N divided by that over 20°S–20°N
minus 1), and the area-averaged precipitation between 20°S and 20°N divided by a factor of 20 (in mm day–1).
The gray star symbol overlaid with CNTL is the observed value based on Global Precipitation Climatology
Project (GPCP) data averaged between 1980 and 1999.

2594 |DECEMBER 2019

Fig. 4. Geographical distributions of (a)–(c) the multimodel and annual mean changes in global surface temperature (in K) and its zonal-mean profile, and (d)–(f) the multimodel, zonal and annual mean temperaturechanges (shading; in K) and anomalous meridional streamfunction (contours interval = 3 × 109 kg s –1). Solid(dashed) contour indicates a clockwise (counterclockwise) circulation. In the zonal-mean plots, the individualmodels are color coded as in Fig. 3 and the multimodel mean is shown in black.

Fig. 5. Scatterplot of the precipitation asymmetry index (PASY ) response (unitless) vs (a) the interhemisphericdifference of sea surface temperature response over 20°S–20°N (in K) and (b) the anomalous cross-equatorial
atmospheric energy transport FATM0 (in PW). The individual models are color coded as in Fig. 3.
AMERICAN METEOROLOGICAL SOCIETY

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| 2595TROPICAL PRECIPITATION RESPONSE
AND ATMOSPHERIC ENERGY BUDGET.
The extent to which the TOA energy perturbations
induce a meridional shift of tropical precipitationis controlled by processes that determine the atmospheric energy budget in an equilibrium state:
ETOA – EOCN = ∇ ⋅ FATM,(1)

processes associated with deep overturning circulation also play an important role in altering EOCN, but
the adjustment time scale varies considerably depending on the forcing region. For example, the Atlantic
meridional overturning circulation (AMOC) strength
adjusts after approximately 50 years in NEXT while itsteadily increases for the entire simulation period of
150 years in SEXT (Fig. ES2). In addition to versions ofoceanic circulations, the prescribed forcing may also
influence the ocean heat uptake response EOCN andthe associated SST pattern via anomalous advection
by the mean circulation, which is a process on decadal
time scales (Li et al. 2013; Wang et al. 2018). That is,during the last 50-yr period that we analyze here,
multiple ocean processes play a role in shaping EOCN.
Attribution of EOCN to different oceanic processes isa challenging topic to be further explored.
To obtain an equation for the cross-equatorial
atmospheric energy transport anomalies FATM0, whichis shown to be strongly correlated with the ITCZ shift(Fig. 5b), we reformulate Eq. (1) to depict the hemispheric asymmetry by spatially integrating over theSouthern Hemisphere with the global mean removed:

where all quantities indicate the climatological difference between the perturbed and CNTL experiments.
Note that the atmospheric energy storage can beneglected when diagnosing the quasi-equilibrated
annual-mean response. Here, ETOA is the anomalous
net downward radiation at TOA, EOCN is the anomalous net downward surface energy flux, and FATM
is the anomalous northward atmospheric energy
transport. Equation (1) states that net atmosphericcolumn energy input through the TOA and ocean
surface is balanced by a divergence of atmosphericenergy transport.
The anomalous net downward radiation at TOA,ETOA includes the prescribed forcing, which is the fraction of solar flux perturbation ∆S felt by the system,
ES ≡ (1 − α)∆S, where α is the climatological mean
〈ES 〉 = –〈ETOA–S 〉 + 〈EOCN 〉 + FATM0, (2)planetary albedo in CNTL. As mentioned earlier, themagnitude of prescribed forcing across models may where brackets denote the spatial integral of thediffer due to model differences in α; thus, the weight- anomaly from the global mean over the Southern
ing factor in Table ES1 is accounted for to adjust the Hemisphere. All variables have the units in watts.
forcing magnitude to 0.8 PW in all models. The dif- Equation (2) indicates that the hemispheric asymference between ETOA and the prescribed forcing is metry in prescribed forcing 〈ES 〉 is balanced by adjustreferred to as the TOA response (denoted as ETOA–S), ing the hemispheric asymmetry in TOA radiation
taking into account both rapid adjustments, which response 〈ETOA–S 〉 and ocean heat uptake response
modify the radiative budget indirectly through fast 〈EOCN 〉, and the cross-equatorial atmospheric energy
atmospheric and surface changes, and feedbacks, transport response FATM0 (Fig. 6a). We define thewhich operate through changes in climate variables fraction of prescribed forcing balanced by each comthat are mediated by surface temperature changes ponent as the TOA compensation, oceanic compensa(Sherwood et al. 2015). The anomalous net surface tion, and atmospheric compensation:energy flux EOCN represents heat uptake by the ocean,− ETOA −S
E
F, COCN ≡ OCN , and CATM ≡ ATM0 ,CTOA ≡
which involves both ocean heat storage and ocean
ES
ESESheat transport divergence (W. Liu et al.− E
2018). In a
EOCN
FATM0
TOA − S
, COCN ≡, and CATM ≡,≡slab ocean setting where SSTs Care
based
TOAcomputed
ES
ES
ESon the local surface energy budget while neglecting
ocean dynamics, the net surface energy flux response such that CTOA + COCN + CATM = 1.
EOCN is zero by construction. In a fully coupled setFigure 7 compares the fractional compensation by
ting, the net surface energy flux response EOCN can be each component in all model experiments. Consistentshaped by distinct oceanic processes that take place with the sensitivity of PASY response to the location
on different time scales. Within the first decade, Ek- of forcing domains, all models exhibit the largest
man transport arising from the coupling between the CATM in STRO associated with the smallest C OCN.
Hadley circulation and the oceanic subtropical cells This implies that radiation biases over the tropics
as well as gyre circulations formed by the surface are more effective in driving the spurious double
wind patterns are primarily responsible for ocean ITCZ problem in current climate models than extraheat uptake changes E OCN (Fig. ES3). Slow ocean tropical radiation biases (Hawcroft et al. 2018; Xiang
2596 |DECEMBER 2019

et al. 2017, 2018; Green et al.
2019). A relatively smaller
CATM for the extratropicalexperiments is associatedwith a larger COCN while thecontribution from radiative
adjustment (CTOA) is smalland highly uncertain interms of sign. Comparing
the two extratropical experiments, NEXT induces
a slightly larger CATM than
SEXT in the multimodel
mean, consistent with astronger cross-equatorial Hadley circulation inNEXT (Fig. 4, right). However, this sensitivity to theforced hemisphere is model
dependent, with three outof nine models exhibiting the opposite sensitivity with a larger C ATM in
SEXT. The causes of thesedifferences are a topic ofplanned future researchwithin ETIN-MIP.
Recent studies attribute the muted tropicalprecipitation responses toextratropical energy perturbations in fully coupledmodels to oceanic processes
Fig. 6. Schematic diagram of the energy fluxes and ITCZ shift. Minus sign in the(Deser et al. 2015; Kay et al.
colored arrows indicates that the given process compensates the prescribed
2016; Green and Marshallforcing (acting as a negative feedback) while plus sign indicates that the given2017). The oceanic compenprocess amplifies the prescribed forcing (acting as a positive feedback). Graybars in the colored arrows in (b) and (c) denote the model spread from ETINsation COCN is zero in a slab
MIP. (a) A solar flux reduction in the Southern Hemisphere (black open arrow)ocean setting by construcis balanced by the upward ocean heat uptake response EOCN (green arrow) andtion; hence, a larger fraction
a southward cross-equatorial atmospheric energy transport response FATM0of energy perturbations(red arrow) while the TOA radiation response ETOA may act as either dampmust be balanced by theener or amplifier of forcing (orange arrow). A southward FATM0 is associatedatmospheric energy transwith a northward ITCZ shift. (b) Energy flux and ITCZ response to a solar
port compared to the caseflux reduction in the southern tropics. The forcing is balanced more by FATM0,
leading to a large ITCZ shift. (c) Energy flux and ITCZ response to a solar flux
when coupled to a full ocean
reduction in the southern extratropics. The forcing is damped effectively bymodel. Some studies point
ocean heat uptake response over the Southern Ocean, accompanying a small
to the coupling between
FATM0 and a muted ITCZ shift.
the Hadley circulation andthe oceanic subtropical cells
for the reduced tropical precipitation responses (Green thereby damping the ITCZ response. If Ekman couand Marshall 2017; Schneider 2017; Kang et al. 2018a; pling is the primary factor in the oceanic damping
Green et al. 2019). Ekman coupling ensures that the effect, STRO is expected to exhibit the largest oceanic
Hadley circulation and the oceanic subtropical cells compensation COCN considering that the anomaloustransport the anomalous energy in the same direction, Hadley cell strength is by far strongest (Fig. 4, right), yet
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Fig. 7. The fractional compensation (in %) by the atmospheric energy transport (CATM), the ocean heat uptake(COCN), and the TOA radiation (CTOA) at the equator. The oceanic compensation accomplished within 30°S–30°N
is displayed in red bars. The individual models are color coded as in Fig. 3.

STRO exhibits the smallest COCN (Fig. 7). The Ekman
damping effect by the oceanic subtropical cells should
be included in the fraction of COCN resulting from theocean heat uptake response within the tropics. Redbars in Fig. 7 display the tropical component of COCN,
computed by taking into account EOCN between 30°S
and 30°N in isolation. The tropical COCN in STRO is
smaller than that in NEXT by 48% despite a significantly stronger anomalous Hadley circulation in STRO
(Fig. 4, right). In addition, STRO and SEXT exhibit acomparable tropical COCN despite a stark contrast in
the anomalous Hadley cell strength. The result not
only implicates other potentially important oceanic
damping pathways than the Ekman transport but
also suggests a limited ability of the ocean’s Ekman
transport to compensate the energy perturbations,potentially due to small gross stability in the shallow
ocean mixed layer (Kang et al. 2018b).
A question then arises as to which oceanic processes are responsible for modulating the oceaniccompensation. Figure 8 shows that E OCN in NEXT
primarily occurs in the subpolar North Atlantic
and along the western boundary currents while thatin SEXT primarily occurs in the Southern Ocean.
Indeed, the full C OCN in the extratropical experiments is dominated by the extratropical component(Fig. 7). In other words, it is the extratropical oceanic processes that boost the oceanic compensation
2598 |DECEMBER 2019

in the extratropical experiments, thereby shaping
the overall sensitivity of COCN to forcing region (Yuand Pritchard 2019). To examine the origin of EOCN,
Fig. 9 compares the anomalous ocean meridional
overturning circulation (MOC) streamfunction andthe mean ocean temperature in CNTL on the left
column with the anomalous ocean temperature andthe mean ocean MOC streamfunction in CNTL on
the right column. The left column allows an estimation of the ocean heat transport change resulting
from ocean circulation changes (i.e., the dynamicterm) while the right column allows an estimationof that resulting from ocean temperature changes(i.e., the thermodynamic term). In NEXT, the subpolar North Atlantic EOCN results from the dynamic
term associated with a strengthened AMOC (Fig. 9a)while the Southern Ocean EOCN in SEXT results fromthe thermodynamic term associated with the mean
upward motion at 50°–60°S (Fig. 9f) (Bryan et al.
1988; Armour et al. 2016; Frey et al. 2017; Xiang
et al. 2018). This local ocean heat uptake response
EOCN over the forced latitude band is larger in SEXT
than in NEXT for all models, by a factor of 1.64 in
the multimodel mean (Fig. 8, left). However, remoteoceanic processes outside of the forcing region as
well as its interaction with radiative feedbacks add
uncertainty to the sensitivity of COCN, with it being
larger in SEXT for only two thirds of the models andFig. 8. Geographical distribution of the multimodel and annual mean changes in (a)–(c) net downward surface
heat flux E OCN and (d)–(f) effective net TOA radiation ETOA–S and their zonal-mean profiles. Both E OCN and ETOA–S
are defined positive downward. In the zonal-mean plots, the individual models are color coded as in Fig. 3 andthe multimodel mean is shown in black.

a third exhibiting the opposite sensitivity (Fig. 7). In
STRO, an anomalously anticlockwise circulation in
the southern tropical upper ocean (Fig. 9b) gives rise
to a southward ocean heat transport, which is largely
cancelled by the thermodynamic term associated withthe subsurface warming driven by the anomalous
downwelling (Fig. 9e). As a result, the equatorial COCN
in STRO is small relative to the extratropical cases(Fig. 7) (Xiang et al. 2018; Hawcroft et al. 2018). The
ETIN-MIP output will allow a rigorous decomposition of the anomalous ocean heat transport into thethermodynamic and dynamic terms.
The TOA compensation CTOA is highly uncertain
for all experiments, resulting in a near-zero CTOA
in the multimodel mean with a large intermodel
spread (Fig. 7). A large diversity in CTOA originatesfrom multiple factors such as rapid adjustment andclimate feedbacks associated with clouds, water
vapor, surface albedo, and Planck response. For
the purpose of separating the contribution of rapid
AMERICAN METEOROLOGICAL SOCIETY

adjustment to the diversity of CTOA from contribution of climate feedbacks, we plan to perform fixed
SST/sea ice experiments for tier 2. Potential factors
responsible for the large intermodel spread of CTOA is
the uncertainty in sea ice and cloud responses. Since
the ice-albedo feedback and shortwave low-cloud
feedback become weak during the winter months,
we weight the monthly changes in sea ice and low
cloud cover by monthly insolation before taking theannual mean in Fig. 10. In NEXT, HadGEM2-ES
exhibits the largest increase in sea ice cover overthe northern high latitudes (Fig. 10a), which greatly
amplifies the forcing effect, so that the radiative
adjustment acts as a positive feedback rather thana compensating effect (i.e., C TOA < 0) (Fig. 7). In
the extratropical cases, the low cloud cover tends
to increase within and equatorward of the forced
latitude band (Figs. 10d,f), due to an increase inlower-tropospheric stability associated with a cooler
boundary layer (Wood and Bretherton 2006). In
DECEMBER 2019

| 2599

Fig. 9. (a)–(c) The multimodel and annual mean ocean temperature in CNTL (shading; in K) and ocean MOC
streamfunction changes (contour interval = 2 Sv) (1 Sv ≡ 106 m3 s−1). Solid (dashed) contour indicates a clockwise(counterclockwise) circulation. (d)–(f) The multimodel and annual mean ocean temperature changes (shading;in K) and the ocean MOC streamfunction in CNTL (contour interval = 5 Sv).

SEXT, NCAR CESM exhibits the largest low cloud
cover increase in the southern subtropics to midlatitudes, which enhances the reflected shortwave
radiation thereby amplifying the forcing effect,
while MPI-ESM1.2 exhibits the smallest changes
in low cloud cover. This is consistent with negative
CTOA in NCAR CESM and positive in MPI-ESM1.2(Fig. 7). HadGEM2-ES in SEXT exhibits a hemispherically symmetric response in both sea ice andlow cloud cover relative to other models (Figs. 10c,f),
so that the radiative compensation CTOA is nearlyzero (Fig. 7). An ETIN-MIP study under development will apply the approximate partial radiative
perturbation method (Taylor et al. 2007) and kernel
method (Pendergrass et al. 2018) to investigate thecause of intermodel diversity of TOA compensationand its dependence on forcing location.
2600 |DECEMBER 2019

BROADER IMPLICATIONS. A primary motivation for ETIN-MIP is to identify the remote energy
biases that are potentially important for causing
the double ITCZ bias. Understanding how regionalenergy perturbations affect the tropical precipitation
pattern is of fundamental importance for improving
not only the present-day double ITCZ bias in many
current climate models but also the accuracy of projections of future changes in tropical precipitation
due to the uneven regional distribution of warming(e.g., Arctic amplification; Serreze and Barry 2011;
Screen et al. 2018).
Applying a forcing over finite latitudinal bands ina coupled model framework, similar to the ETIN-MIP
experiment configuration, has proven to be useful for
determining the causes of climate change patterns(Stuecker et al. 2018). We envision ETIN-MIP can

Fig. 10. Zonal and annual mean changes in (a)–(c) sea ice fraction (in %) and (d)–(f) low cloud cover (in %), forthe selected models where the variables were made available. For both variables, the monthly changes areweighted by the monthly insolation before taking the annual mean. The individual models are color coded asin Fig. 3 and the multimodel mean is shown in black

be generalized to study other aspects of the climate
response beyond tropical precipitation. First, understanding how the spatial pattern of tropical Pacific
SST evolves within ETIN-MIP will provide insights
relevant for a current topic of controversy—whether
the equatorial Pacific under global warming would
warm more in the east than the west (i.e., El Niño–
like) or the reverse (e.g., Kohyama et al. 2017). Second,
we plan to investigate how regional energy perturbations/biases influence the major climate modes suchas El Niño–Southern Oscillation (e.g., Timmermann
et al. 2007), which will help understand their future
projections under radiative forcing with complex spatial patterns. Third, ETIN-MIP data are suitable for
exploring one of the intriguing unanswered questions
about Earth’s albedo: the hemispheric symmetry in
AMERICAN METEOROLOGICAL SOCIETY

planetary albedo despite a substantial hemisphericasymmetry in clear-sky albedo (Voigt et al. 2013).
Furthermore, ETIN-MIP experiments can be examined within the context of geoengineering where
injecting stratospheric sulfate aerosols is proposed asa potential means of deliberately offsetting the global
warming effect (Crutzen 2006; Jones et al. 2017). For
example, ETIN-MIP results may highlight regions
where geoengineering techniques may be applied
for specific climate change mitigation effects to be
maximized. Thus, the project encourages the wider
research community to use the ETIN-MIP dataset forevaluating and understanding the global manifestation of regional energy perturbations, which can beviewed as energetics biases, anthropogenic forcings,
or geoengineering applications.
DECEMBER 2019

| 2601

SUMMARY. In ETIN-MIP, nine climate modelinggroups have performed common numerical experiments aimed at enhancing our understanding of themechanisms for two-way extratropics–tropics interactions. The link between the extratropics and tropics
is of high societal concern given its role in controlling
regional patterns of climate change. Improving ourunderstanding of the mechanisms that enable theseconnections would significantly enhance our ability
to predict and prepare for future changes in regionalhydrology. The spirit of ETIN-MIP is strongly in linewith one of the four questions of the World Climate
Research Programme’s Grand Challenge on Clouds,
Circulation and Climate Sensitivity (Bony et al. 2015).
In keeping with the original motivation for ETINMIP, namely, to provide guidance on identifying theorigin of the double ITCZ bias, we have presented
initial results focused on tropical precipitation andenergetics. The results have practical implications for
GCM development strategy and suggest that fixing
tropical biases would be a more viable option for alleviating hemispherically antisymmetric components oftropical precipitation biases while fixing extratropicalbiases is more desirable for improving the hemispherically symmetric component of tropical precipitationbiases. It also implies that the ability of extratropicalbiases to manifest the hemispherically antisymmetriccomponent of the double ITCZ bias would depend on
the strength of stratocumulus–SST feedback in thesubtropics (Mechoso et al. 2016). For example, theeffect of extratropical biases diminishes away fromthe source region, but the rate of damping would be
weaker in models with a stronger coupling between
the subtropical stratocumulus and SST that acts as apositive feedback; hence, extratropical biases are able
to project onto the double ITCZ bias in some models.
The limited ability of extratropical biases to meridionally displace the tropical precipitation compared totropical biases is due to efficient heat uptake responseby extratropical oceanic processes (Figs. 6 and 7). It suggests constraining tropical response to regional energy
perturbations requires improved understanding of deep
ocean circulation response. This project will enhance
our understanding of the origin of longstanding double
ITCZ bias, which is an essential first step in informing
model developers. More generally, ETIN-MIP will advance our physical understanding of the atmosphericand oceanic circulation responses to regional energy
perturbations in a fully coupled framework, and provides a resource for the climate dynamics community tounderstand the plausibility of different model responses
to such regionally varying energy perturbations, including those expected from anthropogenic climate change.
2602 |DECEMBER 2019ACKNOWLEDGEMENTS. SMK, HK, and JK were
supported by National Research Foundation of Korea(2017K2A9A1A06056874). MH is currently supportedby the Queensland Government and Meat and Livestock
Australia Donor Co. (MDC) through the Northern Australia Climate Program (NACP). YTH was supported by
Ministry of Science and Technology in Taiwan (108-2636M-002-007 and 106-2923-M-002-007-MY2). ØH and GM
are supported by the project HYPRE (243942) fundedthrough the Research Council of Norway, and NorESM1HAPPI supercomputing resources have been provided by
NOTUR (nn9188k). TL was supported by the Spanish Project CGL2017-86415-R. ØS was supported by the Norwegian
Research Council, Project 261821 (HappiEVA). SY was supported by research grants from the NSF (AGS-1419518) andNASA (NNX17AH21G). CESM1.2 model simulations were
performed on Cheyenne (ark:/85065/d7wd3xhc) provided
by the NCAR’s CISL, sponsored by the NSF.

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