The realization of the difficulty of limiting global-mean
temperatures to within 1.5 or 2.0 ∘C above
pre-industrial levels stipulated by the 21st Conference of Parties in
Paris has led to increased interest in solar radiation management (SRM)
techniques. Proposed SRM schemes aim to increase planetary albedo to reflect
more sunlight back to space and induce a cooling that acts to partially
offset global warming. Under the auspices of the Geoengineering Model
Intercomparison Project, we have performed model experiments whereby global
temperature under the high-forcing SSP5-8.5 scenario is reduced to follow
that of the medium-forcing SSP2-4.5 scenario. Two different mechanisms to
achieve this are employed: the first via a reduction in the solar constant
(experiment G6solar) and the second via modelling injections of sulfur
dioxide (experiment G6sulfur) which forms sulfate aerosol in the
stratosphere. Results from two state-of-the-art coupled Earth system models
(UKESM1 and CESM2-WACCM6) both show an impact on the North Atlantic
Oscillation (NAO) in G6sulfur but not in G6solar. Both models show a
persistent positive anomaly in the NAO during the Northern Hemisphere winter
season in G6sulfur, suggesting an increase in zonal flow and an increase in
North Atlantic storm track activity impacting the Eurasian continent and leading
to high-latitude warming over Europe and Asia. These results are broadly
consistent with previous findings which show similar impacts from
stratospheric volcanic aerosol on the NAO and emphasize that detailed
modelling of geoengineering processes is required if accurate impacts of SRM
effects are to be simulated. Differences remain between the two models in
predicting regional changes over the continental USA and Africa, suggesting
that more models need to perform such simulations before attempting to draw
any conclusions regarding potential continental-scale climate change under
SRM.
Introduction
Successive Intergovernmental Panel on Climate Change (IPCC) reports (e.g.
Forster et al., 2007; Myhre et al., 2013) have highlighted that anthropogenic
greenhouse gas emissions exert a strong positive radiative forcing, leading
to a warming of Earth's climate. However, the same IPCC reports also suggest
that aerosols of anthropogenic origin exert a significant (but poorly
quantified) negative radiative forcing, leading to a cooling effect on the
Earth's climate through aerosol–radiation and aerosol–cloud interactions.
Aerosols have therefore been at the forefront of discussions about
increasing planetary albedo by deliberate injection either into the
stratosphere (stratospheric aerosol intervention, SAI; Dickinson, 1996) or
into marine boundary layer clouds (marine cloud brightening, MCB; e.g. Latham,
1990). Such putative albedo-increasing interventions are referred to as
solar radiation management (SRM) geoengineering.
Initial simulations of the impacts of SAI and MCB were carried out by
individual groups using models of varying complexity for a range of
different scenarios, but the range of different scenarios applied to the
models meant that definitive reasons for differences in model responses were
difficult to establish (e.g. Rasch et al., 2008; Jones et al., 2010). The Geoengineering
Model Intercomparison Project (GeoMIP) framework was therefore established
with specific protocols for performing model simulations under a range of
defined scenarios (Kravitz et al., 2011). The scenarios considered by GeoMIP have
themselves evolved with the earliest idealized simulations being
supplemented by progressively more complex scenarios aiming to address more
specific policy-relevant questions. The earliest simulations involved
balancing an abrupt quadrupling of atmospheric carbon dioxide concentrations
by simply reducing the solar constant (GeoMIP experiment G1; Kravitz et al.,
2011). While such simulations are highly idealized, the simplicity of the
scenario means that many climate models could perform the simulations,
providing a robust multi-model assessment (Kravitz et al., 2013, 2020).
Policy-relevant questions regarding SRM can only be addressed by climate
model simulations that represent deployment strategies which use
technologies that are considered safe, cost-effective and have a reasonably
short development time (Royal Society, 2009). SAI has been suggested as one
such potentially plausible mechanism; its plausibility is enhanced by
observations of explosive or effusive volcanic eruptions which cause a
periodic negative radiative forcing and a cooling of the Earth's climate
(e.g. Robock, 2000; Haywood et al., 2013; Santer et al., 2014; Malavelle et al., 2017).
Observations of such natural analogues provide powerful constraints on the
ability of global climate models to represent complex aerosol–radiation and
aerosol–cloud processes, although the pulse-like nature of the emissions
from volcanic eruptions means that they are not perfect analogues for SRM
(Robock et al., 2013). Single model simulations which include treatments of
aerosol processes associated with SAI (e.g. Jones et al., 2017, 2018; Irvine et al., 2019)
have shown that policy-relevant climate metrics at global, continental and
regional scales such as sea-level rise, sea-ice extent, European heat waves,
Atlantic hurricane frequency and intensity, and North Atlantic storm track
displacement can be significantly ameliorated under SAI geoengineering
compared with baseline (non-geoengineered) scenarios. Additionally, SAI
strategies could potentially be tailored to provide spatial distributions of
stratospheric aerosol that mitigate some of the residual impacts of SAI such
as the overcooling of the tropics and undercooling of polar latitudes that
are evident under more generic SAI strategies (e.g. MacMartin et al., 2013; Tilmes
et al., 2018). However, studies suggest that SAI would by no means ameliorate all
effects of climate change (e.g. Simpson et al., 2019; Da-Allada et al., 2020; Robock,
2020).
The North Atlantic Oscillation (NAO) can be defined as a change in the
pressure difference between the Icelandic Low and the Azores High pressure
regions (e.g. Hurrell, 1995), and by convention, a positive NAO anomaly is
associated with an increase in the surface pressure gradient between these
regions. Both model simulations (e.g. Stenchikov et al., 2002) and observations
(e.g. Graf et al., 1994; Kodera, 1994; Lorenz and Hartmann, 2003) have shown that
one of the most significant atmospheric responses following explosive
volcanic eruptions is a strengthening of the polar vortex and an impact on
the Northern Hemisphere wintertime NAO, although in the case of the 1991
Pinatubo eruption the causal link has recently been questioned by Polvani
et al. (2019). Shindell et al. (2004) provide a concise summary of the mechanism by
which volcanic stratospheric aerosols are thought to influence the dynamical
response of the NAO, leading to wintertime warming over Eurasia and North
America (Robock and Mao, 1992). Essentially, (1) sunlight absorbed by
aerosols leads to heating of the lower stratosphere, which enhances the
meridional temperature gradient; (2) this leads to a strengthening of the westerly zonal winds near the tropopause; (3) planetary waves propagating upwards in the
troposphere are refracted away from the pole due to the change in wind
shear, further strengthening the westerlies; (4) the enhanced westerlies
propagate down to the surface via a positive feedback between the zonal wind
anomalies and tropospheric eddies; and (5) strengthened westerly flow near
the ground creates the surface pressure and temperature response patterns.
As SAI geoengineering could be considered equivalent to a continuous
volcanic eruption, it seems plausible that it too could generate similar
anomalies in the NAO and so surface temperature.
In addition to work on the dynamical features and NAO response to SAI via volcanic
eruptions, there has been much debate on the influence of the 11-year solar
cycle with stronger solar activity being associated with a positive phase of
the NAO and weaker solar activity being associated with a negative phase.
Early work (e.g. Kodera, 2002; Kodera and Kuroda, 2005; Matthes et al., 2006)
suggested that mechanisms influencing the NAO from solar variability
originated near the stratopause, propagated downward through the
stratosphere and influenced the troposphere via changes in meridional
propagation of planetary waves. More recent work has suggested that stronger
correlations exist between the solar cycle and the phase and strength of the
NAO if a lag is accounted for (Gray et al., 2013), owing to ocean–atmosphere
interactions that strengthen the response (Scaife et al., 2013). These lagged
responses to solar cycles have been replicated in some climate models
(e.g. Ineson et al., 2011), including a version of the model that was the forerunner
of the UKESM1 model that is used in our analysis (see Sect. 2).
Stratospheric aerosol and the 11-year solar cycle are not the only phenomena
to influence the NAO: Smith et al. (2016) indicate that Atlantic sea-surface
temperatures, the phase and strength of El Niño, the quasi-biennial
oscillation, Atlantic multi-decadal variability, and Pacific decadal
variability may all play a role. However, skilful predictions of the
wintertime NAO index using sophisticated seasonal prediction models that
account for these factors are now possible (Dunstone et al., 2016). Note that the
two driving mechanisms investigated in this study, i.e. SAI and a reduction in
solar constant, may induce opposing impacts on the NAO: SAI might strengthen
the NAO, while reducing the solar constant might weaken it.
The most recent GeoMIP Phase 6 scenarios (GeoMIP6; Kravitz et al., 2015) attempt
to provide more policy-relevant information on SRM geoengineering by
aligning with the Coupled Model Intercomparison Project Phase 6 (CMIP6;
Eyring et al., 2016). Two GeoMIP6 experiments will be considered here: G6solar
and G6sulfur. In both experiments the modelled global-mean temperature under
a high-forcing scenario is reduced to that in a medium-forcing scenario. The
mechanism for performing the temperature reduction is either an idealized
reduction of the solar constant (experiment G6solar) or a more realistic
injection of sulfur dioxide into the stratosphere (experiment G6sulfur)
where it forms sulfate aerosol that reflects sunlight back to space. We
examine results from two Earth system models which have performed both
experiments (UKESM1 and CESM2-WACCM6). The main objective is to determine
whether, under SRM strategies which are continuous rather than sporadic or
periodic in nature, the two models produce NAO responses that are consistent
with the expectations discussed above, i.e. that SAI induces a significant shift
to the positive phase of the NAO compared with reducing the solar constant.
Our analysis focuses on the broad-scale microphysical, chemical and
dynamical features in the Northern Hemisphere winter, i.e. aerosol spatial
distributions, impacts on ozone, stratospheric temperatures, stratospheric
and tropospheric zonal mean winds, and induced surface pressure patterns with
a focus on the NAO, before examining impacts on continental-scale
temperature and precipitation patterns. SAI is considered the most plausible
SRM method, owing to considerations of effectiveness, timeliness, cost and
safety (e.g. Royal Society, 2009). Our focus is therefore on the difference
between the responses to SRM via SAI and that via generic reductions in the
solar constant, noting that many previous assessments of the impacts of SRM
use a reduction of the solar constant as a proxy for SAI.
Section 2 provides a brief description of the UKESM1 and CESM2-WACCM6
models. Section 3 provides a description of the experimental design of the
G6solar and G6sulfur experiments. Results are presented in Sect. 4 before
discussions and conclusions are presented in Sect. 5.
Model description
Both UKESM1 and CESM2-WACCM6 are fully coupled Earth system models which
have contributed to CMIP6 and GeoMIP6. Both models (or their immediate
forebears) have undergone various degrees of validation relevant to SAI
using observations from explosive volcanic eruptions (e.g. Haywood et al., 2010;
Dhomse et al., 2014; Mills et al., 2016).
UKESM1 is described by Sellar et al. (2019). It comprises an atmosphere model
based on the Met Office Unified Model (UM; Walters et al., 2019; Mulcahy et al., 2018)
with a resolution of 1.25∘ latitude by 1.875∘ longitude
with 85 levels up to approximately 85 km, coupled to a 1∘
resolution ocean model with 75 levels (Storkey et al., 2018). It includes
components to model tropospheric and stratospheric chemistry (Archibald et al.,
2020) and aerosols (Mann et al., 2010), sea ice (Ridley et al., 2018), the land
surface and vegetation (Best et al., 2011), and ocean biogeochemistry (Yool et al.,
2013).
CESM2-WACCM6 is described by Danabasoglu et al. (2020) and Gettelman et al. (2019a).
The atmosphere model has a resolution of 0.95∘ in latitude by
1.25∘ in longitude with 70 levels from the surface to about 140
km. This is coupled to an ocean model component with a nominal 1∘
resolution and 60 vertical levels (Danabasoglu et al., 2012) and a sea-ice model
(Hunke et al., 2015). It includes a full stratospheric chemistry scheme that is
coupled to the atmospheric dynamics, aerosol and radiation schemes (Mills
et al., 2017), and a land model with interactive carbon and nitrogen cycles
(Danabasoglu et al., 2020).
G6solar and G6sulfur experimental design
As described in Kravitz et al. (2015), the goal of GeoMIP experiments G6solar and
G6sulfur is to modify simulations based on ScenarioMIP high-forcing scenario
SSP5-8.5 (O'Neill et al., 2016; experiment ssp585) so as to follow the evolution
of the medium-forcing scenario SSP2-4.5 (experiment ssp245). Kravitz et al. (2015) define the criterion for comparing the modified simulations with
their ssp245 target in terms of radiative forcing. This was subsequently
found to be impractical for some models, so for GeoMIP6 the criterion
applied was that for each decade from 2021 to 2100 the global decadal-mean
near-surface air temperature of G6solar or G6sulfur should be within 0.2 K
of the corresponding decade of each model's ssp245 simulation.
Experiment G6solar performs the required modification in an idealized manner
by gradually reducing the solar constant over the 21st century, whereas
G6sulfur achieves it by the arguably more technologically feasible method of
injecting gradually increasing amounts of SO2 into the lower
stratosphere. SO2 was injected continuously between 10∘ N–10∘ S along the Greenwich meridian at 18–20 km altitude in UKESM1
and on the Equator at the date line at ∼ 25 km altitude in
CESM2-WACCM6.
The results presented are ensemble means of three (UKESM1) or two
(CESM2-WACCM6) members. These are ultimately initial condition ensembles:
the G6solar and G6sulfur ensemble members are based on ensemble members of
each model's ssp585 experiment, which are themselves continuations of
corresponding CMIP6 historical simulations, which in turn are initialized
from different points in each model's pre-industrial control simulation.
We investigate the impact of SAI by examining differences between G6sulfur
and G6solar, generally over the final 20 years of the 21st century. We
are thereby comparing two experiments in which the temperature evolution is
nominally the same, but they achieve this by different methods. This should
highlight any impacts which are captured by a more detailed treatment of
modelling SAI geoengineering (G6sulfur) which are not seen when
geoengineering is treated in a more idealized fashion (G6solar).
Results
We first provide a brief analysis of the levels of success that G6sulfur and
G6solar have in reducing the temperature change to that of ssp245. As the
experimental design assures that the decadal-mean temperature in G6sulfur
and G6solar are within 0.2 K of the values for ssp245, we do not show the
temporal evolution of temperature, but there is some merit in examining the
inter-model and inter-forcing differences of the resulting spatial patterns
of temperature change to give context to the results that follow. When
analysing the results from the simulations, we generally focus on the
difference “G6sulfur minus G6solar” for several key variables that are
associated with our understanding of the influence of stratospheric aerosol
on the development of NAO anomalies.
Spatial distribution of 21st century temperature change
The spatial pattern of the global-mean temperature change is calculated as
the change from present day (PD; mean of 2011–2030) compared with the period
2081–2100 and is shown for experiments ssp245, G6solar and G6sulfur for
UKESM1 and CESM2-WACCM6 in Fig. 1. PD data are from years 2011–2014 of each
model's CMIP6 historical experiment combined with years 2015–2030 from the
corresponding ssp245 experiment.
Annual-mean temperature change (K) from present day (PD;
2011–2030 mean) to the end of the century (2081–2100 mean) in the various
experiments. Upper row (a, b, c) shows results from UKESM1 and lower row (d, e, f) for
CESM2-WACCM6. All results are ensemble means (three members for UKESM1, two
for CESM2-WACCM6).
It is obvious from Fig. 1 that the inter-model differences in temperature
response (i.e. the differences between the top and bottom rows) are much
greater than the inter-forcing differences in temperature response (i.e. the
differences between the columns in any one row). In UKESM1 the warming is
around 2.6 K compared with present day, while for CESM2-WACCM6 the warming
is more moderate at around 1.9 K. This result is interesting in itself
because the base models that are used in these simulations have been
diagnosed as having equilibrium climate sensitivities (i.e. for a doubling of
CO2) of 5.4 K (UKESM1; Andrews et al., 2019) and 5.3 K (CESM2; Gettelman et al.,
2019b); one might thus expect a similar transient climate response under the
SSP2-4.5 scenario.
Both models warm over land regions more than over ocean regions as
documented in successive IPCC reports (e.g. Forster et al., 2007; Myhre et al., 2013).
UKESM1 shows a strong polar amplification, particularly in the Northern
Hemisphere, while polar amplification is more muted in CESM2-WACCM6. This is
likely linked to differences in poleward atmospheric and oceanic heat
transport. Indeed, CESM2-WACCM6 suggests that areas of the North Atlantic
are subject to a cooling as the mean climate warms. This is presumably as a
result of a strong reduction of the Atlantic Meridional Overturning
Circulation, which has been documented to collapse in CESM2 from a
present-day level of ∼ 23 to ∼ 8 Sv (sverdrup) by 2100
under the SSP5-8.5 scenario (Muntjewerf et al., 2020; Tilmes et al., 2020). UKESM1
shows no such behaviour.
The similarity between the inter-forcing patterns of temperature responses
in ssp245, G6solar and G6sulfur for each model is quite striking. On the
basis of such an analysis, it would be tempting to conclude that G6solar,
which has the benefits of being relatively simple to implement in a great
number of climate models (e.g. Kravitz et al., 2013, 2020), might be a reasonable
analogue for the far more complex G6sulfur simulations. This conclusion will
be examined in the following sections.
SO2 injection rate and aerosol optical depth
In G6sulfur the mean SO2 injection rate during the final 2 decades
(2081–2100) is 19.0 Tg yr-1 for UKESM1 and 20.6 Tg yr-1 for
CESM2-WACCM6. Such injection rates are broadly similar to the amount
injected by the 1991 eruption of Mt Pinatubo (Guo et al., 2004), but unlike the
latter they continue year on year. Such large, persistent perturbations are
obviously different to the pulse-like injection and subsequent exponential
decay of explosive volcanic eruptions (e.g. Jones et al., 2016a), which suggests
that one cannot simply assume that the responses to such SAI would be
analogous to those from volcanic eruptions. The injection rates by the end
of the century have to be so large to counteract the warming due to the
increased concentration of atmospheric carbon dioxide which has accumulated
over the period 1850–2100. While such injection rates appear high, they are
typical in model geoengineering studies. A previous GeoMIP experiment known
as G3 (Kravitz et al., 2011) involved injecting increasing amounts of SO2 to
offset anthropogenic radiative forcing in the RCP4.5 scenario (Thomson et al.,
2011) over the period 2020–2070, and Niemeier et al. (2013) found that an
injection rate of around 12 Tg of SO2 yr-1 was needed in their
model by 2070. Niemeier and Timmreck (2015) suggested a massive 90 Tg of
SO2 yr-1 would be needed by 2100 to offset the temperature change
in the RCP8.5 scenario (Riahi et al., 2011) in a model that explicitly simulated
the evolution of aerosol microphysics to larger sizes via condensation and
coagulation as the injection rate increased. The increase in aerosol size
leads to a decreased cooling efficiency per unit mass with increasing
SO2, owing to decreased stratospheric lifetime (caused by higher aerosol
terminal velocities) and also less efficient cooling in the shortwave part
of the spectrum along with a stronger counterbalancing impact on terrestrial
radiation (Niemeier and Timmreck, 2015). Both UKESM1 and CESM2-WACCM6
include these microphysical mechanisms, so the injection rates used here are
by no means exceptional in SAI geoengineering studies.
The resulting anomalies in annual-mean aerosol optical depth (AOD,
determined at 550 nm) for 2081–2100 are 0.33 for UKESM1 and 0.28 for
CESM2-WACCM6; their geographic distributions are shown in Fig. 2.
The distribution of the 2081–2100 mean anomaly in annual
mean AOD at 550 nm (dimensionless) due to stratospheric
SO2 injection for UKESM1 (a), CESM2-WACCM6 (b) and zonal means for both models (c). The anomaly is
calculated from the difference between G6sulfur and G6solar.
By 2081–2100 the AOD needed to reduce the SSP5-8.5 temperature levels to
those of SSP2-4.5 is some 18 % greater for UKESM1 than for CESM2-WACCM6,
although the amount of cooling produced in the two models is very similar
(-2.47 K for UKESM1 and -2.33 K for CESM2-WACCM6). This can be attributed to
the different SO2 injection strategies and to different transport
strengths from the tropics to the poles in the Brewer–Dobson circulation of
the stratosphere. In UKESM1 there is considerably more geoengineered AOD in
the tropical reservoir (e.g. Grant et al., 1996) than in CESM2-WACCM6 where the
transport to higher latitudes is more efficient.
Stratospheric ozone
Stratospheric aerosol is widely acknowledged to reduce stratospheric ozone
through heterogeneous chemistry processes, particularly in polar regions
(e.g. Solomon, 1999; Tilmes et al., 2009), and has been studied in earlier GeoMIP
activities (e.g. Pitari et al., 2014). Both UKESM1 and CESM2-WACCM6 include detailed
stratospheric chemistry and are capable of modelling the impact of
stratospheric aerosol on stratospheric ozone (Morgenstern et al., 2009; Mills et al.,
2017). The impact of SAI on stratospheric ozone concentrations is shown in
Fig. 3.
The difference in 2081–2100 annual-mean ozone
concentrations (µgm-3) diagnosed from
{G6sulfur minus G6solar} for UKESM1 (a) and
CESM2-WACCM6 (b).
The SAI-induced changes in ozone concentration between G6solar and G6sulfur
are consistent with the distributions of aerosol in the two models. UKESM1,
with its higher concentration of aerosol in the tropical reservoir, shows a
greater tropical ozone change, with the maximum reduction centred around
20–30 hPa (∼ 24–27 km) for both models. These changes are
consistent with the findings of Tilmes et al. (2018) and are a combination of
chemical and transport changes. The reduction in ozone concentrations in the
tropics around 20–30 hPa is the result of an increase in vertical advection,
while the increase in ozone above this is a result of a decreased rate of
catalytic NOx ozone loss (see Tilmes et al., 2018, for more details).
Stratospheric temperature
Perturbations to stratospheric temperatures are a key mechanism implicated
in observed and modelled changes in the Northern Hemisphere wintertime NAO
subsequent to stratospheric aerosol injection from volcanoes (e.g. Stenchikov
et al., 2002; Lorenz and Hartmann, 2003; Shindell et al., 2004). The annual-mean and
the Northern Hemisphere wintertime (December–February) stratospheric
temperature perturbations are shown in Fig. 4.
The difference in zonal mean temperature (K) diagnosed
from {G6sulfur minus G6solar}; panels (a) and (c)
show results from UKESM1 and panels (b) and (d) from CESM2-WACCM6. Panels (a) and (b) show global annual-mean results from 2081–2100; panels (c) and (d) show
Northern Hemisphere winter (December–February) means over the same period.
For both models, the peak in the annual-mean temperature perturbation is in
the tropics, which is where the SO2 is injected and the resulting
stratospheric AOD is greatest (Fig. 2). Differences between the models'
aerosol and radiation schemes mean that CESM2-WACCM6 has slightly more
warming in the tropical stratosphere despite having somewhat lower AOD
compared with UKESM1. Although stratospheric sulfate is primarily a
scattering aerosol in the solar part of the spectrum, the small amount of
absorption of solar radiation by stratospheric aerosols in the
near-infrared, together with absorption of terrestrial longwave radiation,
causes the stratospheric heating (e.g. Stenchikov et al., 1998; Jones et al., 2016b).
Perturbations to stratospheric temperatures in the tropics due to less
ultraviolet absorption from the reduction of stratospheric ozone (Fig. 3)
play a more minor role. The right-hand panels of Fig. 4 show that the
impact of solar absorption in the stratosphere cannot be effective during
the polar night. This, along with a reduced flux of terrestrial radiation
due to low wintertime temperatures, means that stratospheric heating from
the aerosol is only present at latitudes south of the Arctic Circle
(Shindell et al., 2004). The cooling at high latitudes during Northern Hemisphere
winter is consistent with a strengthening of the polar vortex during this
period.
Wind speedStratospheric winds
The effect that the aerosol-induced stratospheric temperature perturbation
has on the zonal mean wind speed during Northern Hemisphere winter is shown
in Fig. 5.
The perturbation to mean December–February zonal wind
speed over 2081–2100 (m s-1) caused by SAI, diagnosed
from {G6sulfur minus G6solar}. Panels (a) and (b) show the change in Northern Hemisphere zonal wind, with positive values
indicating a westerly perturbation and negative values an easterly one. Panels (c) and (d) show the spatial distribution of this change at 10 hPa which is
the level of maximum perturbation. Panels (a) and (c) show results from
UKESM1, panels (b) and (d) those from CESM2-WACCM6.
As in Shindell et al. (2001, their Plate 5), the left-hand panels in Fig. 5 show
that in both UKESM1 and CESM2-WACCM6 a strong stratospheric zonal mean wind
anomaly develops at around 10 hPa at 60–70∘ N with an
increase of more than 12 m s-1 for UKESM1 and 9 m s-1 for
CESM2-WACCM6, thereby enhancing the strength of the polar vortex. The
maximum increase in the zonal wind at this level is centred over Alaska in
both models (right-hand panels in Fig. 5).
Tropospheric winds
Figure 5 shows the propagation of this enhanced westerly flow to lower levels
in the troposphere and to the surface, with both models suggesting an
increased westerly flow north of around 50∘ N. Figure 6 shows the
Northern Hemisphere wintertime zonal mean wind perturbation at 850 hPa
induced by SAI for both models.
The distribution of the 2081–2100 mean December–February
zonal wind speed perturbation due to SAI at 850 hPa (m s-1) for UKESM1 (a) and CESM2-WACCM6 (b).
Positive values represent a westerly perturbation and negative values an
easterly perturbation; white areas indicate regions where the surface
elevation is higher than the mean 850 hPa pressure level.
As with the stratospheric winds, both models show similar behaviour. Both
show enhanced 850 hPa winds particularly over the northern Atlantic between
the southern tip of Greenland and the UK. This increased westerly flow
penetrates into northern Eurasia, indicating that zonal flow is enhanced and
shows a strong similarity to the pattern of wind speed perturbation
identified in reanalysis data when the polar vortex is strong (e.g. Graf and
Walter, 2005).
Mean sea-level pressure and NAO index
As noted in Sect. 1, the NAO may be quantified in terms of the pressure
difference between Iceland and the Azores. Here we use December–February
mean sea-level pressure (MSLP) from the nearest model grid cell to
Stykkishólmur, Iceland (65∘05′ N, 22∘44′ W), and Ponta Delgada in the Azores (37∘44′ N, 25∘41′ W). We also construct
an NAO index by removing the long-term mean from the time series of each
location's MSLP, normalizing the resulting anomalies by their standard
deviation and then taking the difference between the normalized anomalies
(e.g. Hurrell, 1995; Rodwell et al., 1999). A positive NAO index indicates when the
pressure difference between the two stations is greater than normal, and a
negative phase indicates when the pressure difference is less than normal. The
perturbation to the mean Northern Hemisphere winter surface pressure
patterns from SAI is shown in Fig. 7.
The change induced by SAI in 2081–2100 mean
December–February MSLP (hPa) for UKESM1 (a) and CESM2-WACCM6 (b)
diagnosed from {G6sulfur minus G6solar}.
Both models show similar large-scale perturbations to MSLP with a vast swath
of high-pressure anomalies centred over the Atlantic Ocean at around
50∘ N and to the south of Alaska. The patterns of increased MSLP
are broadly similar over Eurasia but are subtly different over the
continental USA. A strong area of anomalous low pressure is evident towards
the pole in both models, and the strongest pressure gradient anomaly is over
the northern Atlantic. This area of strong baroclinicity is associated with
the strengthening zonal flow shown in Fig. 6. Over the period 2081–2100, SAI
causes the NAO index in UKESM1 to change from -0.36 in G6solar to +0.73 in
G6sulfur. This corresponds to the Azores to Iceland pressure difference
increasing from 16.4 hPa (G6solar) to 22.3 hPa (G6sulfur), indicating a
strengthening of the NAO of around +6 hPa, which is significant as the
standard error due to natural variability is around 1 hPa. In CESM2-WACCM6,
the NAO index increases from -0.34 (G6solar) to +0.77 (G6sulfur),
corresponding to a change in pressure difference of 21.3 to 25.9 hPa,
indicating a strengthening of around 4.5 hPa, which is again significant
compared with natural variability.
Before concluding that such impacts on the Northern Hemisphere wintertime
NAO are an important difference between end-of-century climates produced by
the two different forms of SRM geoengineering, we need to assess if there
are any systematic changes in the NAO over the course of the 21st
century in the absence of geoengineering. As noted by Deser et al. (2017), some
studies project a slight positive shift in the probability distribution of
the NAO phase by the end of the 21st century. As G6solar and G6sulfur
track the temperature evolution of the SSP2-4.5 scenario, we compare
2081–2100 means from each model's CMIP6 ssp245 simulation with present day
(PD, 2011–2030) means constructed from each model's CMIP6 historical and
ssp245 experiments. In UKESM1 the change in Azores-to-Iceland pressure
difference between PD and 2081–2100 in SSP2-4.5 is 17.6 to 17.7 hPa (NAO
index essentially unchanged at +0.19), and in CESM2-WACCM6 the
corresponding values are 21.3 to 19.8 hPa (NAO index change -0.26 to -0.63).
It is therefore clear that the impact of SAI geoengineering on the Northern
Hemisphere wintertime NAO dominates over any effects due to global warming
over this period.
Regional mid-latitude temperature
We have seen that both models simulate the impact of SAI by inducing a
positive phase of the NAO with both models showing similar patterns of
response in stratospheric heating, stratospheric and tropospheric winds, and
MSLP. We now briefly examine the impact of SAI on near-surface temperatures
by looking at the difference between G6sulfur and G6solar during the
Northern Hemisphere wintertime with a focus on the continental scale. To put
these changes in context, by experimental design the temperature changes in
all experiments compared with present day (PD) show the expected warming of
climate commensurate with the SSP2-4.5 scenario (annual-mean changes from PD
to 2081–2100 shown in Fig. 1). The purpose of examining regional changes in
temperature is to emphasize that despite the inter-model similarity of
response of many dynamical features associated with the NAO, there are
considerable inter-model differences in the resulting regional temperatures
in some areas.
Both models indicate that SAI induces broad-scale patterns of temperature
perturbation over Eurasia during Northern Hemisphere winter resembling those
associated with a positive phase of the NAO observed subsequent to large
tropical volcanic eruptions (Shindell et al., 2004), i.e. a warming to the north and
a cooling to the south of ∼ 50∘ N (Fig. 8).
Explosive volcanic eruptions provide a very useful, albeit imperfect,
analogue for stratospheric aerosol injection geoengineering (Robock et al.,
2013). The facts that similar temperature patterns are observed following
explosive volcanic eruptions and that the proposed mechanisms for impacting
the strength of the NAO are identical for volcanic and geoengineering cases
suggest that the inducing of positive phases of the NAO under SAI
geoengineering is a relatively robust conclusion.
The perturbation to 2081–2100 mean December–February
near-surface air temperature (K) induced by SAI diagnosed from
{G6sulfur minus G6solar} for UKESM1 (a) and CESM2-WACCM6 (b). The area plotted is chosen to
replicate that presented by Shindell et al. (2004, their Fig. 2).
While there are similarities in the broad-scale hemispheric pattern of
temperature perturbations, over continental North America the models suggest
rather different regional temperature responses. In UKESM1 the induced
positive phase of the NAO from SAI leads to a warming of the eastern side of
the continent as observed (Shindell et al., 2004) as well as over the
north-western Atlantic, while CESM2-WACCM6 suggests a general cooling across
the continent with only the warm anomaly over the North Atlantic being
evident. This cooling in CESM2-WACCM6 is consistent with the high-pressure
anomaly across the whole continent in this model (Fig. 7), which would
enhance advection of cold air from higher latitudes. In contrast, UKESM1 has
a low-pressure anomaly over much of continental North America, which would
have the opposite tendency. It is generally accepted that Northern
Hemisphere wintertime conditions over the eastern USA are anomalously warm
during the positive phase of the NAO (e.g.
http://climate.ncsu.edu/images/edu/NAO2.jpg, last access: 22 January 2021) which perhaps indicates that
UKESM1 may reproduce this phase of the NAO with greater fidelity. In
contrast, however, CESM2-WACCM6 seems to better represent the cooling
observed at high latitudes over North America following large volcanic
eruptions. Significant cooling is also observed over northern Africa following
such eruptions with cold anomalies extending to around 10∘ N
(Shindell et al., 2004). Both models show cool anomalies in this region but they
extend further south in UKESM1 compared with CESM2-WACCM6, suggesting a
somewhat weaker response to SAI in the latter model.
Regional mid-latitude precipitation
Over Europe, while the models exhibit some differences in the exact
demarcation between increased precipitation over northern Europe and
Scandinavia and decreased precipitation over southern Europe (Fig. 9), the
general patterns are clearly in line with observations during positive
phases of the NAO. For example, Fowler and Kilsby (2002) and Burt and Howden
(2013) investigated precipitation anomalies in northern areas of the UK and
concluded that precipitation and stream-flow is considerably enhanced during
positive phases of the NAO. On larger scales, López-Moreno et al. (2008) and
Casanueva et al. (2014) conclude that, during the positive phase of the NAO,
positive precipitation anomalies occur over northern Europe while negative
precipitation anomalies occur over southern Europe. Furthermore, the study
of Zanardo et al. (2019) indicates that the NAO clearly correlates with the
occurrence of catastrophic floods across Europe (and the associated economic
losses) and that over northern Europe the majority of historic winter floods
occurred during a positive NAO phase.
The perturbation to 2081–2100 mean December–February land
precipitation rate (mm d-1) induced by SAI
diagnosed from {G6sulfur minus G6solar} for
UKESM1 (a) and CESM2-WACCM6 (b).
Over North America, both models are consistent and indicate an increase in
wintertime precipitation, which is again consistent with observations of
wintertime precipitation anomalies during the positive phase of the NAO.
There are fewer quantitative studies of the impacts of the NAO over North
America as the social and economic costs are not so readily apparent as over
Europe. However, an analysis by Durkee et al. (2008) indicates positive anomalies
of rain over south-eastern states and positive anomalies of snowfall over
north-eastern states during positive phases of the NAO.
Contextualizing in terms of changes compared with present-day
precipitation
We have shown that the SAI-induced response of the NAO and the associated
impacts on precipitation are relatively well understood and reasonably
consistent between the two models. As in earlier modelling and observational
studies, the impact is particularly marked over Europe, with northern Europe
experiencing enhanced precipitation and southern Europe reduced
precipitation. We therefore focus our attention on the magnitude of the
SAI-induced feedbacks on precipitation from the positive NAO anomaly
compared with the temperature- and circulation-induced feedbacks on
precipitation from global warming over the European area. We do this by
comparing end-of-century (2081–2100) precipitation in UKESM1 and
CESM2-WACCM6 with that from the present day (PD, 2011–2030) for the ssp585,
ssp245, G6solar and G6sulfur simulations (Fig. 10 for UKESM1 and Fig. 11 for
CESM2-WACCM6).
Changes in mean December–February land precipitation rate
(mm d-1) between present day (PD, 2011–2030) and
2081–2100 in experiments ssp245, ssp585, G6solar and G6sulfur in UKESM1. PD
means are constructed in the same manner as in Fig. 1.
As expected, Fig. 10 shows that the precipitation changes in 2081–2100
compared with PD are significantly less in ssp245 than in ssp585. North of
50∘ N there are many areas in ssp585 that experience a change in
precipitation exceeding +0.5 mm d-1, while south of 45∘ N
areas tend to be drier than in PD; these patterns are consistent with the
patterns of precipitation and runoff changes in multi-model climate
change simulation assessments (Kirtman et al., 2013; Guerreiro et al., 2018). When
comparing the future precipitation response in G6sulfur to that in ssp245,
it is evident that the precipitation anomaly pattern from the NAO-induced
feedback (Fig. 9) acts to reinforce the temperature-induced precipitation
feedback. Compared with ssp245, the precipitation anomaly in G6sulfur is
more positive in northern Europe and more negative in southern Europe, with
a negative anomaly that encompasses the area all around the Black Sea. When
comparing the future precipitation response in G6sulfur with G6solar, it is
evident that while the precipitation increases north of around 50∘ N show some consistency between the two, there is no such agreement further
south. Over Iberia, Italy, the Balkans, Greece, Turkey, Ukraine and southern
Russia the precipitation anomalies show a wintertime precipitation decrease
in G6sulfur but an increase in G6solar. It is therefore evident that the
idealized approach of G6solar does not adequately represent the regional
impacts on precipitation over Europe.
Generally, the conclusions from UKESM1 presented in Fig. 10 are supported by
the results from CESM2-WACCM6 (Fig. 11). The strong signal of increased
precipitation in northern Europe evident in ssp585 is reduced in
ssp245, G6solar and G6sulfur. G6sulfur again shows a greater reduction in
precipitation south of about 45∘ N when compared with G6solar. The
implications of these findings are discussed in more detail in the following
section.
Same as Fig. 10 but for CESM2-WACCM6.
Discussion and Conclusions
Using data from two Earth system models, we have compared the final 20 years
from two numerical experiments which employ different representations of
geoengineering in a scenario where the amount of cooling generated is the
same. The G6solar experiment achieves the required cooling by the highly
idealized method of reducing the solar constant over the course of the
21st century, while the G6sulfur experiment achieves the same degree of
cooling by injecting increasing amounts of SO2 into the tropical lower
stratosphere (SAI geoengineering). Comparing the results from the two
experiments should help cast light on geoengineering impacts which only
become evident when the method of geoengineering is represented with some
fidelity.
Although both models' SAI simulations are successful in cooling from
SSP5-8.5 to SSP2-4.5 levels, the resulting perturbations to the AOD
distribution are by no means identical. Differences far larger than these
have been reported in earlier coordinated GeoMIP simulations. Pitari et al. (2014, their Fig. 3d) indicate that some models (e.g. GEOSCCM) perform
similarly to UKESM1 in maintaining a peak AOD of 3 times that at
mid-latitudes in the tropical reservoir, while other models (e.g. GISS-E2-R)
show almost the opposite behaviour with a peak AOD twice that in the
tropical reservoir at mid-latitudes. Pitari et al. (2014) caution that aspects of
the performance of these two models are hampered by the lack of explicit
treatment of heterogeneous chemistry (GISS-E2-R) and the lack of impact of
the stratospheric aerosol on photolysis rates (GEOSCCM); these caveats do
not apply to the UKESM1 and CESM2-WACCM6 models, which include these
processes.
The results from both models indicate that a key impact of tropical SAI
geoengineering is the generation of a persistent positive phase of the NAO
during Northern Hemisphere wintertime. The intensification of the
stratospheric jet produces an increase in surface zonal winds over the North
Atlantic, leading to a warming of the Eurasian continent northwards of about
50∘ N and the associated risks of flooding in northern European
regions (e.g. Scaife et al., 2008). The mechanism for generating these anomalies
appears to be the same as that observed following large explosive volcanic
eruptions in the tropics. This is consistent with the form of SAI simulated
in G6sulfur being essentially equivalent to a continuous, large volcanic
eruption in the tropics and indicates that the response to any putative,
continuous large-scale SO2 injection is likely to be the same as that
which has been suggested to follow large sporadic eruptions.
In terms of impacts, the end-of-century (2081–2100) European wintertime
precipitation anomalies in ssp585, ssp245, G6solar and G6sulfur provide an
example relating to a critical argument that has been circulating in the
geoengineering community for over a decade: that of winners and losers
(e.g. Irvine et al., 2010; Kravitz et al., 2014). While few would argue against the
benefits of ameliorating the changes in wintertime precipitation under
SSP5-8.5 by following the SSP2-4.5 scenario (Figs. 10 and 11), the situation
is different when examining the changes seen in G6sulfur. For example,
when taking the results from CESM2-WACCM6 at face value, one might argue that the
impacts of the wintertime drying of vast swathes of the European continent
surrounding the Mediterranean Sea (Fig. 11) might be more damaging in terms
of their impact on biodiversity, ecology and peoples' lives than the impact
of increased flood risk in northern Europe under even the extreme SSP5-8.5
scenario. Of course, here we are limited to analysing the results from just
two Earth system models which take no account of trying to tailor the
injection strategy to minimize residual climate impacts (e.g. MacMartin et al.,
2013), and studies have shown that SAI can ameliorate many regional impacts
of climate change (e.g. Jones et al., 2018). Nevertheless, the impact of the
SAI-induced effects on the NAO indicate the need for detailed modelling of
geoengineering processes when considering the potential regional impacts of
such actions. Studies which have investigated the issue of geoengineering
winners and losers have generally studied results from idealized solar
reduction approaches to geoengineering and therefore may have missed some of
the effects shown here. The differences in regional response over the
continental USA and Africa (e.g. Fig. 8) demonstrate that inter-model
uncertainty remains and indicate that more models need to perform these
simulations before any conclusions regarding potential continental-scale
climate change under SRM are drawn.
In addition to the potential climate impacts from SAI shown here, such
intervention would produce many other benefits and risks (e.g. Robock, 2020).
Some of these additional risks are related not only to the physical climate
system but also deal with governance, unknowns, ethics and aesthetics.
Furthermore, the technology to inject sulfur into the stratosphere does not
currently exist. Before any decision by society to start climate
intervention, much more work is needed to quantify all these potential
benefits and risks. In the meantime, even if some climate intervention is
used for a time, there remains a great deal of work on mitigation and
adaptation to address the threat of global warming.
Code availability
Due to intellectual property rights restrictions, we cannot provide either
the source code or documentation papers for the Met Office Unified Model.
The UM is available for use under licence – for further information on how
to apply for a licence, see
http://www.metoffice.gov.uk/research/modelling-systems/unified-model (last
access: 23 July 2020). Previous and current Community Earth System Model (CESM) versions are freely
available at http://www.cesm.ucar.edu/models/cesm2 (last access: 23 July
2020).
Data availability
The simulation data used in this study are archived on the Earth System
Grid Federation (ESGF) (https://esgf-node.llnl.gov/projects/cmip6, last
access: 23 July 2020). The model source IDs are UKESM1-0-LL for UKESM1 and
CESM2-WACCM for CESM2-WACCM6.
Author contributions
AJ and JMH led the analysis and wrote the article with contributions
from ACJ, ST, BK and AR. The UKESM1 and CESM2-WACCM6 simulations were
carried out by AJ and ST, respectively. BK was central in coordinating the
GeoMIP6 activity.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
Andy Jones would like to thank the Met Office team responsible for the
managecmip software which greatly simplified the work
involved. Andy Jones and Jim M. Haywood were supported by the Met Office
Hadley Centre Climate Programme funded by the UK Government Department for
Business, Energy and Industrial Strategy (BEIS) and the UK Government
Department for Environment, Food and Rural Affairs (Defra). The CESM project
is supported primarily by the US National Science Foundation (NSF). Some
of the material is based upon work supported by the National Center for
Atmospheric Research (NCAR) which is a major facility sponsored by the NSF.
Computing and data storage resources for CESM, including the Cheyenne
supercomputer (10.5065/D6RX99HX), were provided by the
Computational and Information Systems Laboratory (CISL) at NCAR.
Support for Ben Kravitz was provided in part by the NSF, the Indiana
University Environmental Resilience Institute and the Prepared for
Environmental Change Grand Challenge initiative. The Pacific Northwest
National Laboratory is operated for the US Department of Energy by Battelle
Memorial Institute. Alan Robock is supported by the NSF.
We acknowledge the World Climate Research Programme which, through its Working
Group on Coupled Modelling, coordinated and promoted CMIP. We thank the climate
modelling groups for producing and making available their model output, ESGF
for archiving the data and providing access, and the multiple funding agencies
that support CMIP6 and ESGF. We also thank all participants of the
Geoengineering Model Intercomparison Project and their model development teams.
Financial support
This research has been supported by the Department for Business, Energy and
Industrial Strategy, UK Government, the Department for Environment, Food
and Rural Affairs, UK Government, the US National Science Foundation
under cooperative agreement 1852977, agreement CBET-1931641 and grant
AGS-2017113, the US National Center for Atmospheric Research, the Indiana
University Environmental Resilience Institute and the Prepared for
Environmental Change Grand Challenge initiative.
Review statement
This paper was edited by Peter Haynes and reviewed by two anonymous referees.
ReferencesAndrews, T., Andrews, M. B., Bodas-Salcedo, A., Jones, G. S., Kuhlbrodt, T.,
Manners, J., Menary, M. B., Ridley, J., Ringer, M. A., Sellar, A. A., and
Senior, C. A.: Forcings, feedbacks, and climate sensitivity in HadGEM3-GC3.1
and UKESM1, J. Adv. Model. Earth Sy., 11, 4377–4394, 10.1029/2019MS001866, 2019.Archibald, A. T., O'Connor, F. M., Abraham, N. L., Archer-Nicholls, S., Chipperfield, M. P., Dalvi, M., Folberth, G. A., Dennison, F., Dhomse, S. S., Griffiths, P. T., Hardacre, C., Hewitt, A. J., Hill, R. S., Johnson, C. E., Keeble, J., Köhler, M. O., Morgenstern, O., Mulcahy, J. P., Ordóñez, C., Pope, R. J., Rumbold, S. T., Russo, M. R., Savage, N. H., Sellar, A., Stringer, M., Turnock, S. T., Wild, O., and Zeng, G.: Description and evaluation of the UKCA stratosphere–troposphere chemistry scheme (StratTrop vn 1.0) implemented in UKESM1, Geosci. Model Dev., 13, 1223–1266, 10.5194/gmd-13-1223-2020, 2020.Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, 10.5194/gmd-4-677-2011, 2011.Burt, T. P. and Howden, N. J. K.: North Atlantic Oscillation amplifies orographic precipitation and river flow in upland Britain, Water Resour. Res., 49, 3504–3515, 10.1002/wrcr.20297, 2013.Casanueva, A., Rodríguez-Puebla, C., Frías, M. D., and González-Reviriego, N.: Variability of extreme precipitation over Europe and its relationships with teleconnection patterns, Hydrol. Earth Syst. Sci., 18, 709–725, 10.5194/hess-18-709-2014, 2014.Da-Allada, C. Y., Baloïtcha, E., Alamou, E. A., Awo, F. M., Bonou, F., Pomalegni, Y., Biao, E. I., Obada, E., Zandagba, J. E., Tilmes, S., and Irvine, P. J.: Changes in West African summer monsoon precipitation under stratospheric aerosol geoengineering, Earths Future, 8, e2020EF001595, 10.1029/2020EF001595, 2020.Danabasoglu, G., Bates, S. C., Briegleb, B. P., Jayne, S. R., Jochum, M., Large, W. G., Peacock, S., and Yeager, S. G.: The CCSM4 Ocean Component, J. Climate, 25, 1361–1389, 10.1175/JCLI-D-11-00091.1, 2012.Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D. A., DuVivier,
A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A.,
Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M.,
Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R.,
Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Tilmes, S., van
Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J, Deser, C., Fischer,
C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E.,
Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch,
P. J., and Strand, W. G.: The Community Earth System Model Version 2
(CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001916, 10.1029/2019MS001916, 2020.Deser, C., Hurrell, J. W., and Phillips, A. S.: The role of the North Atlantic Oscillation in European climate projections, Clim. Dynam., 49, 3141–3157, 10.1007/s00382-016-3502-z, 2017.Dhomse, S. S., Emmerson, K. M., Mann, G. W., Bellouin, N., Carslaw, K. S., Chipperfield, M. P., Hommel, R., Abraham, N. L., Telford, P., Braesicke, P., Dalvi, M., Johnson, C. E., O'Connor, F., Morgenstern, O., Pyle, J. A., Deshler, T., Zawodny, J. M., and Thomason, L. W.: Aerosol microphysics simulations of the Mt. Pinatubo eruption with the UM-UKCA composition-climate model, Atmos. Chem. Phys., 14, 11221–11246, 10.5194/acp-14-11221-2014, 2014.Dickinson, R. E.: Climate engineering a review of aerosol approaches to changing the global energy balance, Climatic Change, 33, 279–290, 10.1007/BF00142576, 1996.Dunstone, N., Smith, D., Scaife, A., Hermanson, L., Eade, R., Robinson, N., Andrews, M., and Knight, J.: Skilful predictions of the winter North Atlantic Oscillation one year ahead, Nat. Geosci., 9, 809–814, 10.1038/NGEO2824, 2016.Durkee, J. D., Frye, J. D., Fuhrmann, C. M., Lacke, M. C., Jeong, H. G., and Mote, T. L.: Effects of the North Atlantic Oscillation on precipitation-type frequency and distribution in the eastern United States, Theor. Appl. Climatol., 94, 51–65, 10.1007/s00704-007-0345-x, 2008.Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, 10.5194/gmd-9-1937-2016, 2016.Forster, P., Ramaswamy, V., Artaxo, P., Berntsen, T., Betts, R., Fahey, D. W., Haywood, J., Lean, J., Lowe, D. C., Myhre, G., Nganga, J., Prinn, R., Raga, G., Schulz, M., and Van Dorland, R.: Changes in Atmospheric Constituents and in Radiative Forcing, in: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, USA, 2007.Fowler, H. J. and Kilsby, C. G.: Precipitation and the North Atlantic Oscillation: a study of climatic variability in northern England, Int. J. Climatol., 22, 843–866, 10.1002/joc.765, 2002.Guerreiro, S. B., Dawson, R. J., Kilsby, C., Lewis, E., and Ford, A.: Future heat-waves, droughts and floods in 571 European cities, Environ. Res. Lett., 13, 034009, 10.1088/1748-9326/aaaad3, 2018.Gettelman, A., Mills, M. J., Kinnison, D. E., Garcia, R. R., Smith, A. K., Marsh, D. R., Tilmes, S., Vitt, F., Bardeen, C. G., McInerny, J., Liu, H.-L., Solomon, S. C., Polvani, L. M., Emmons, L. K., Lamarque, J.-F., Richter, J. H., Glanville, A. S., Bacmeister, J. T., Phillips, A. S., Neale, R. B., Simpson, I. R., DuVivier, A. K., Hodzic, A., and Randel, W. J.: The Whole Atmosphere Community Climate Model Version 6 (WACCM6), J. Geophys. Res., 124, 12380–12403, 10.1029/2019JD030943, 2019a.Gettelman, A., Hannay, C., Bacmeister, J. T., Neale, R. B., Pendergrass, A. G., Danabasoglu, G., Lamarque, J.-F., Fasullo, J. T., Bailey, D. A., Lawrence, D. M., and Mills, M. J.: High climate sensitivity in the Community Earth System Model Version 2 (CESM2), Geophys. Res. Lett., 46, 8329–8337, 10.1029/2019GL083978, 2019b.Graf, H.-F., Perlwitz, J., and Kirchner, I.: Northern Hemisphere
tropospheric mid-latitude circulation after violent volcanic eruptions,
Contr. Atmos. Phys., 67, 3–13, 1994.Graf, H.-F. and Walter, K.: Polar vortex controls coupling of North Atlantic Ocean and atmosphere, Geophys. Res. Lett., 32, L01704,
10.1029/2004GL020664, 2005.Grant, W. B., Browell, E. V., Long, C. S., Stowe, L. L., Grainger, R. G., and Lambert, A.: Use of volcanic aerosols to study the tropical
stratospheric reservoir, J. Geophys. Res., 101, 3973–3988,
10.1029/95JD03164, 1996.Gray, L. J., Scaife, A. A., Mitchell, D. M., Osprey, S., Ineson, S., Hardiman, S., Butchart, N., Knight, J. R., Sutton, R., and Kodera, K.: A lagged response to the 11 year solar cycle in observed winter
Atlantic/European weather patterns, J. Geophys. Res., 118, 13405–13420,
10.1002/2013JD020062, 2013.Guo, S., Bluth, G. S., Rose, W. I., Watson, I. M., and Prata, A. J.: Re-evaluation of the SO2 release of the 15 June 1991 Pinatubo eruption using ultraviolet and infrared satellite sensors, Geochem. Geophys. Geosys., 5, Q04001, 10.1029/2003GC000654, 2004.Haywood, J. M., Jones, A., Clarisse, L., Bourassa, A., Barnes, J., Telford, P., Bellouin, N., Boucher, O., Agnew, P., Clerbaux, C., Coheur, P., Degenstein, D., and Braesicke, P.: Observations of the eruption of the Sarychev volcano and simulations using the HadGEM2 climate model, J. Geophys. Res., 115, D21212, 10.1029/2010JD014447, 2010.Haywood, J. M., Jones, A., and Jones, G. S.: The impact of volcanic eruptions in the period 2000-2013 on global mean temperature trends evaluated in the HadGEM2-ES climate model, Atmos. Sci. Lett., 15, 92–96.
10.1002/asl2.471, 2013.Hunke, E. C., Lipscomb, W. H., Turner, A. K., Jeffery, N., and Elliott, S.: CICE: The Los Alamos Sea Ice Model. Documentation and Software User's Manual. Version 5.1, T-3 Fluid Dynamics Group, Los Alamos National Laboratory, Tech. Rep. LA-CC-06-012, 2015.Hurrell, J. W.: Decadal trends in the North Atlantic Oscillation: regional temperatures and precipitation, Science, 269, 676–679,
10.1126/science.269.5224.676, 1995.Ineson, S., Scaife, A. A., Knight, J. R., Manners, J. C., Dunstone, N. J., Gray, L. J., and Haigh, J. D.: Solar forcing of winter climate variability in the Northern Hemisphere, Nat. Geosci., 4, 753–757, 10.1038/ngeo1282, 2011.Irvine, P., Ridgwell, A., and Lunt, D. J.: Assessing the regional
disparities in geoengineering impacts, Geophys. Res. Lett., 37, L18702,
10.1029/2010GL044447, 2010.Irvine, P., Emanuel, K., He, J., Horowitz, L. W., Vecchi, G., and Keith, D.: Halving warming with idealized solar geoengineering moderates key climate hazards, Nat. Clim. Change, 9, 295–299, 10.1038/s41558-019-0398-8, 2019.Jones, A., Haywood, J., Boucher, O., Kravitz, B., and Robock, A.: Geoengineering by stratospheric SO2 injection: results from the Met Office HadGEM2 climate model and comparison with the Goddard Institute for Space Studies ModelE, Atmos. Chem. Phys., 10, 5999–6006, 10.5194/acp-10-5999-2010, 2010.Jones, A. C., Haywood, J. M., Jones, A., and Aquila, V.: Sensitivity of volcanic aerosol dispersion to meteorological conditions: A Pinatubo case study, J. Geophys. Res., 121, 6892–6908, 10.1002/2016JD025001, 2016a.Jones, A. C., Haywood, J. M., and Jones, A.: Climatic impacts of stratospheric geoengineering with sulfate, black carbon and titania injection, Atmos. Chem. Phys., 16, 2843–2862, 10.5194/acp-16-2843-2016, 2016b.Jones, A. C., Haywood, J. M., Dunstone, N., Emanuel, K., Hawcroft, M. K., Hodges, K. I., and Jones, A.: Impacts of hemispheric solar geoengineering on tropical cyclone frequency, Nat. Commun., 8, 1382,
10.1038/s41467-017-01606-0, 2017.Jones, A. C., Hawcroft, M. K., Haywood, J. M., Jones, A., Guo, X., and Moore, J. C.: Regional climate impacts of stabilizing global warming at 1.5 K using solar geoengineering, Earths Future, 6, 230–251,
10.1002/2017EF000720, 2018.Kirtman, B., Power, S. B., Adedoyin, J. A., Boer, G. J., Bojariu, R., Camilloni, I., Doblas-Reyes, F. J., Fiore, A. M., Kimoto, M., Meehl, G. A., Prather, M., Sarr, A., Schär, C., Sutton, R., van Oldenborgh, G. J., Vecchi G., and Wang, H. J.: Near-term Climate Change: Projections and Predictability, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013.Kodera, K.: Influence of volcanic eruptions on the troposphere through stratospheric dynamical processes in the northern hemisphere winter, J. Geophys. Res., 99, 1273–1282, 10.1029/93JD02731, 1994.Kodera, K.: Solar cycle modulation of the North Atlantic Oscillation: Implication in the spatial structure of the NAO, Geophys. Res. Lett., 29, 59-1–59-4, 10.1029/2001GL014557, 2002.Kodera, K. and Kuroda, Y.: A possible mechanism of solar modulation of the spatial structure of the North Atlantic Oscillation, J. Geophys. Res., 110, D02111, 10.1029/2004JD005258, 2005.Kravitz, B., Robock, A., Boucher, O., Schmidt, H., Taylor, K. E., Stenchikov, G. and Schulz, M.: The geoengineering model intercomparison project (GeoMIP), Atmos. Sci. Lett., 12, 162–167, 10.1002/asl.316, 2011.Kravitz, B., Caldeira, K., Boucher, O., Robock, A., Rasch, P. J.,
Alterskjær, K., Karam, D. B., Cole, J. N., Curry, C. L., Haywood, J. M.
and Irvine, P. J.: Climate model response from the Geoengineering Model
Intercomparison Project (GeoMIP), J. Geophys. Res., 118, 8320–8332, 10.1002/jgrd.50646, 2013.Kravitz, B., MacMartin, D. G., Robock, A., Rasch, P. J., Ricke, K. L., Cole, J. N. S., Curry, C. L., Irvine, P. J., Ji, D., Keith, D. W.,
Kristjánsson, J. E., Moore, J. C., Muri, H., Singh, B., Tilmes, S.,
Watanabe, S., Yang, S., and Yoon, J.-H.: A multi-model assessment of
regional climate disparities caused by solar geoengineering, Environ. Res. Lett., 9, 074013, 10.1088/1748-326/9/7/074013, 2014.Kravitz, B., Robock, A., Tilmes, S., Boucher, O., English, J. M., Irvine, P. J., Jones, A., Lawrence, M. G., MacCracken, M., Muri, H., Moore, J. C., Niemeier, U., Phipps, S. J., Sillmann, J., Storelvmo, T., Wang, H., and Watanabe, S.: The Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6): simulation design and preliminary results, Geosci. Model Dev., 8, 3379–3392, 10.5194/gmd-8-3379-2015, 2015.Kravitz, B., MacMartin, D. G., Visioni, D., Boucher, O., Cole, J. N. S., Haywood, J., Jones, A., Lurton, T., Nabat, P., Niemeier, U., Robock, A., Séférian, R., and Tilmes, S.: Comparing different generations of idealized solar geoengineering simulations in the Geoengineering Model Intercomparison Project (GeoMIP), Atmos. Chem. Phys. Discuss. [preprint], 10.5194/acp-2020-732, in review, 2020.Latham, J.: Control of global warming? Nature, 347, 339–340,
10.1038/347339b0, 1990.López-Moreno, J. I. and Vicente-Serrano, S. M.: Positive and negative phases of the wintertime North Atlantic Oscillation and drought occurrence over Europe: a multitemporal-scale approach, J. Climate, 21, 1220–1243, 10.1175/2007JCLI1739.1, 2008.Lorenz, D. J. and Hartmann, D. L.: Eddy-zonal flow feedback in the Northern Hemisphere winter, J. Climate, 16, 1212–1227,
10.1175/1520-0442(2003)16<1212:EFFITN>2.0.CO;2, 2003.MacMartin, D. G., Keith, D. W., Kravitz, B., and Caldeira, K.: Management of trade-offs in geoengineering through optimal choice of non-uniform radiative forcing, Nat. Clim. Change, 3, 365–368, 10.1038/NCLIMATE1722, 2013.Malavelle, F., Haywood, J. M., Jones, A., Gettelman, A., Clarisse, L., Bauduin, S., Allan, R. P., Karset, I. H., H., Kristjánsson, J. E., Oreopoulos, L., Cho, N., Lee, D., Bellouin N., Boucher, O., Grosvenor, D. P., Carslaw, K. S., Dhomse, S., Mann, G. W., Schmidt, A., Coe, H., Hartley, M. E., Dalvi, M., Hill, A. A., Johnson, B. T., Johnson, C. E., Knight J. R., O'Connor, F. M., Partridge, D. G., Stier, P., Myhre, G., Platnick, S., Stephens, G. L., Takahashi, H., and Thordarson, T.: Strong constraints on aerosol-cloud interactions from volcanic eruptions, Nature, 546, 485–491, 10.1038/nature22974, 2017.Mann, G. W., Carslaw, K. S., Spracklen, D. V., Ridley, D. A., Manktelow, P. T., Chipperfield, M. P., Pickering, S. J., and Johnson, C. E.: Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model, Geosci. Model Dev., 3, 519–551, 10.5194/gmd-3-519-2010, 2010.Matthes, K., Kuroda, Y., Kodera, K., and Langematz, U.: Transfer of the solar signal from the stratosphere to the troposphere: Northern winter, J. Geophys. Res., 111, D06108, 10.1029/2005JD006283, 2006.Mills, M. J., Schmidt, A., Easter, R., Solomon, S., Kinnison, D. E., Ghan, S. J., Neely III, R. R., Marsh, D. R., Conley, A., Bardeen, C. G. and Gettelman, A.: Global volcanic aerosol properties derived from emissions, 1990–2014, using CESM1 (WACCM), J. Geophys. Res., 121, 2332–2348, 10.1002/2015JD024290, 2016.Mills, M. J., Richter, J. H., Tilmes, S., Kravitz, B., MacMartin, D. G., Glanville, A. A., Tribbia, J. J., Lamarque, J.-F., Vitt, F., Schmidt, A., and Gettelman, A.: Radiative and chemical response to interactive stratospheric sulfate aerosols in fully coupled CESM1 (WACCM), J. Geophys. Res., 122, 13061–13078, 10.1002/2017JD027006, 2017.Morgenstern, O., Braesicke, P., O'Connor, F. M., Bushell, A. C., Johnson, C. E., Osprey, S. M., and Pyle, J. A.: Evaluation of the new UKCA climate-composition model – Part 1: The stratosphere, Geosci. Model Dev., 2, 43–57, 10.5194/gmd-2-43-2009, 2009.Mulcahy, J. P., Jones, C., Sellar, A., Johnson, B., Boutle, I. A., Jones, A., Andrews, T., Rumbold, S. T., Mollard, J., Bellouin, N., Johnson, C. E., Williams, K. D., Grosvenor, D. P., and McCoy, D. T.: Improved Aerosol Processes and Effective Radiative Forcing in HadGEM3 and UKESM1, J. Adv. Model. Earth Sy., 10, 2786–2805, 10.1029/2018MS001464, 2018.Muntjewerf, L., Petrini, M., Vizcaino, M., Ernani da Silva, C., Sellevold, R., Scherrenberg, M.D., Thayer-Calder, K., Bradley, S. L., Lenaerts, J. T., Lipscomb, W. H. and Lofverstrom, M.: Greenland Ice Sheet Contribution to 21st Century Sea Level Rise as Simulated by the Coupled CESM2.1-CISM2.1, Geophys. Res. Lett., 47, e2019GL086836, 10.1029/2019GL086836, 2020.Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J., Huang, J., Koch, D., Lamarque, J.-F., Lee, D., Mendoza, B., Nakajima, T., Robock, A., Stephens, G., Takemura, T., and Zhang, H.: Anthropogenic and Natural Radiative Forcing, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and
New York, USA, 2013.Niemeier, U., Schmidt, H., Alterskjær, K., and Kristjánsson, J. E.: Solar irradiance reduction via climate engineering: Impact of different techniques on the energy balance and the hydrological cycle, J. Geophys. Res., 118, 11905–11917, 10.1002/2013JD020445, 2013.Niemeier, U. and Timmreck, C.: What is the limit of climate engineering by stratospheric injection of SO2?, Atmos. Chem. Phys., 15, 9129–9141, 10.5194/acp-15-9129-2015, 2015.O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, 10.5194/gmd-9-3461-2016, 2016.Pitari, G., Aquila, V., Kravitz, B., Robock, A., Watanabe, S., Cionni, I., Luca, N. D., Genova, G. D., Mancini, E., and Tilmes, S.: Stratospheric ozone response to sulfate geoengineering: Results from the Geoengineering Model Intercomparison Project (GeoMIP), J. Geophys. Res., 119, 2629–2653, 10.1002/2013JD020566, 2014.Polvani, L. M., Banerjee, A., and Schmidt, A.: Northern Hemisphere continental winter warming following the 1991 Mt. Pinatubo eruption: reconciling models and observations, Atmos. Chem. Phys., 19, 6351–6366, 10.5194/acp-19-6351-2019, 2019.Rasch, P. J., Tilmes, S., Turco, R. P., Robock, A., Oman, L., Chen, C.-C., Stenchikov, G. L., and Garcia, R. R.: An overview of geoengineering of climate using stratospheric sulfate aerosols, Phil. T. Roy. Soc. A., 366, 4007–4037, 10.1098/rsta.2008.0131, 2008.Riahi, K., Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G., Kindermann, G., Nakicenovic, N., and Rafaj, P.: RCP 8.5 – A scenario of comparatively high greenhouse gas emissions, Clim. Change, 109, 33–57,
10.1007/s10584-011-0149-y, 2011.Ridley, J. K., Blockley, E. W., Keen, A. B., Rae, J. G. L., West, A. E., and Schroeder, D.: The sea ice model component of HadGEM3-GC3.1, Geosci. Model Dev., 11, 713–723, 10.5194/gmd-11-713-2018, 2018.Robock, A.: Volcanic eruptions and climate, Rev. Geophys., 38, 191–219, 10.1029/1998RG000054, 2000.Robock, A.: Benefits and risks of stratospheric solar radiation management for climate intervention (geoengineering), Bridge, 50, 59–67, 2020.Robock, A. and Mao, J.: Winter warming from large volcanic eruptions, Geophys. Res. Lett., 19, 2405–2408, 10.1029/92GL02627, 1992.Robock, A., MacMartin, D. G., Duren, R., and Christensen, M. W.: Studying geoengineering with natural and anthropogenic analogs, Climatic Change, 121, 445–458, 10.1007/s10584-013-0777-5, 2013.Rodwell, M. J., Rowell, D. P., and Folland, C. K.: Oceanic forcing of the wintertime North Atlantic Oscillation and European climate, Nature, 398, 320–323, 10.1038/18648, 1999.Royal Society: Geoengineering the climate: Science, governance and uncertainty, RS Policy Document 10/09 RS1636, The Royal Society, London,
UK, available at: https://eprints.soton.ac.uk/156647/1/Geoengineering_the_climate.pdf (last access: 22 January 2021), 2009.Santer, B. D., Bonfils, C., Painter, J. F., Zelinka, M. D., Mears, C., Solomon, S., Schmidt, G. A., Fyfe, J. C., Cole, J. N., Nazarenko, L., and Taylor, K. E.: Volcanic contribution to decadal changes in tropospheric temperature, Nat. Geosci., 7, 185–189, 10.1038/ngeo2098, 2014.Scaife, A. A., Folland, C. K., Alexander, L. V., Moberg, A., and Knight, J. R.: European climate extremes and the North Atlantic Oscillation, J. Climate, 21, 72–83, 10.1175/2007JCLI1631.1, 2008.Scaife, A. A., Ineson, S., Knight, J. R., Gray, L., Kodera, K., Smith, D. M.: A mechanism for lagged North Atlantic climate response to solar variability, Geophys. Res. Lett., 40, 434–439, 10.1002/grl.50099, 2013.Sellar, A., Jones, C. G., Mulcahy, J. P., Tang, Y., Yool, A., Wiltshire, A., O'Connor, F. M., Stringer, M., Hill, R., Palmieri, J., Woodward, S., de Mora, L., Kuhlbrodt, T., Rumbold, S., Kelley, D. I., Ellis, R., Johnson, C. E., Walton, J., Abraham, N. L., Andrews, M. B., Andrews, T., Archibald, A. T., Berthou, S., Burke, E., Blockley, E., Carslaw, K., Dalvi, M., Edwards, J., Folberth, G. A., Gedney, N., Griffiths, P. T., Harper, A. B., Hendry, M. A., Hewitt, A. J., Johnson, B., Jones, A., Jones, C. D., Keeble, J., Liddicoat, S., Morgenstern, O., Parker, R. J., Predoi, V., Robertson, E., Siahaan, A., Smith, R. S., Swaminathan, R., Woodhouse, M., Zeng, G., and Zerroukat, M.: UKESM1: Description and evaluation of the UK Earth System Model, J. Adv. Model. Earth Sy., 11, 4513–4558, 10.1029/2019MS001739, 2019.Shindell, D. T., Schmidt, G. A., Miller, R. L., and Rind, D.: Northern Hemisphere winter climate response to greenhouse gas, ozone, solar, and volcanic forcing, J. Geophys. Res., 106, 7193–7210, 10.1029/2000JD900547, 2001.Shindell, D. T., Schmidt, G. A., Mann, M. E., and Faluvegi, G.: Dynamic winter climate response to large tropical volcanic eruptions since 1600, J. Geophys. Res., 109, D05104, 10.1029/2003JD004151, 2004.Simpson, I. R., Tilmes, S., Richter, J. H., Kravitz, B., MacMartin, D. G., Mills, M. J., Fasullo, J. T., and Pendergrass, A. G.: The regional hydroclimate response to stratospheric sulfate geoengineering and the role of stratospheric heating, J. Geophys. Res., 124, 12587–12616, 10.1029/2019JD031093, 2019.Smith, D. M., Scaife, A. A., Eade, R., and Knight, J. R.: Seasonal to decadal prediction of the winter North Atlantic Oscillation: emerging
capability and future prospects, Q. J. Roy. Meteor. Soc., 142, 611–617,
10.1002/qj.2479, 2016.Solomon, S.: Stratospheric ozone depletion: A review of concepts and history, Rev. Geophys., 37, 275–316, 10.1029/1999RG900008, 1999.Stenchikov, G. L., Kirchner, I., Robock, A., Graf, H.-F., Antuña, J. C., Grainger, R. G., Lambert, A., and Thomason, L.: Radiative forcing from the 1991 Mount Pinatubo volcanic eruption, J. Geophys. Res., 103, 13837–13857, 1998.Stenchikov, G., Robock, A., Ramaswamy, V., Schwarzkopf, M. D., Hamilton, K., and Ramachandran, S.: Arctic Oscillation response to the 1991 Mount Pinatubo eruption: Effects of volcanic aerosols and ozone depletion, J. Geophys. Res., 107, 4803, 10.1029/2002JD002090, 2002.Storkey, D., Blaker, A. T., Mathiot, P., Megann, A., Aksenov, Y., Blockley, E. W., Calvert, D., Graham, T., Hewitt, H. T., Hyder, P., Kuhlbrodt, T., Rae, J. G. L., and Sinha, B.: UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions, Geosci. Model Dev., 11, 3187–3213, 10.5194/gmd-11-3187-2018, 2018.Thomson, A. M., Calvin, K. V., Smith, S. J., Kyle, G. P., Volke, A., Patel, P., Delgado-Arias, S., Bond-Lamberty, B., Wise, M. A., Clarke, L. E., and Edmonds, J. A.: RCP4.5: A pathway for stabilization of radiative forcing by 2100, Climatic Change, 109, 77–94, 10.1007/s10584-011-0151-4, 2011.Tilmes, S., Garcia, R. R., Kinnison, D. E., Gettelman, A., and Rasch, P. J.: Impact of geoengineered aerosols on the troposphere and stratosphere, J. Geophys. Res., 114, D12305, 10.1029/2008JD011420, 2009.
Tilmes, S., Richter, J. H., Kravitz, B., MacMartin, D. G., Mills, M. J., Simpson, I. R., Glanville, A. S., Fasullo, J. T., Phillips, A. S., Lamarque, J.-F., Tribbia, J., Edwards, J., Mickelson, S., and Ghosh, S.: CESM1(WACCM) Stratospheric Aerosol Geoengineering Large Ensemble Project, B. Am. Meteor. Soc., 99, 2361–2371, 10.1175/BAMS-D-17-0267.1, 2018.Tilmes, S., MacMartin, D. G., Lenaerts, J. T. M., van Kampenhout, L., Muntjewerf, L., Xia, L., Harrison, C. S., Krumhardt, K. M., Mills, M. J., Kravitz, B., and Robock, A.: Reaching 1.5 and 2.0 ∘C global surface temperature targets using stratospheric aerosol geoengineering, Earth Syst. Dynam., 11, 579–601, 10.5194/esd-11-579-2020, 2020.Walters, D., Baran, A. J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Carslaw, K., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Jones, C., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and Zerroukat, M.: The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations, Geosci. Model Dev., 12, 1909–1963, 10.5194/gmd-12-1909-2019, 2019.Yool, A., Popova, E. E., and Anderson, T. R.: MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies, Geosci. Model Dev., 6, 1767–1811, 10.5194/gmd-6-1767-2013, 2013.Zanardo, S., Nicotina, L., Hilberts, A. G., and Jewson, S. P.: Modulation of economic losses from European floods by the North Atlantic Oscillation, Geophys. Res. Lett., 46, 2563–2572, 10.1029/2019GL081956, 2019.