ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-16-7559-2016Strong modification of stratospheric ozone forcing by cloud and sea-ice adjustmentsXiaYanyan.xia3@mail.mcgill.cahttps://orcid.org/0000-0003-2858-4725HuYongyunhttps://orcid.org/0000-0002-4003-4630HuangYihttps://orcid.org/0000-0002-5065-4198Department of Atmospheric and Oceanic Sciences, McGill University,
Montréal, CanadaDepartment of Atmospheric and Oceanic Sciences, Peking University,
Beijing, ChinaYan Xia (yan.xia3@mail.mcgill.ca)21June201616127559756726February201623March20164June20166June2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/16/7559/2016/acp-16-7559-2016.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/16/7559/2016/acp-16-7559-2016.pdf
We investigate the climatic impact of stratospheric ozone
recovery (SOR), with a focus on the surface temperature change in
atmosphere–slab ocean coupled climate simulations. We find that although SOR
would cause significant surface warming (global mean: 0.2 K) in a climate
free of clouds and sea ice, it causes surface cooling (-0.06 K) in the real
climate. The results here are especially interesting in that the
stratosphere-adjusted radiative forcing is positive in both cases. Radiation
diagnosis shows that the surface cooling is mainly due to a strong radiative
effect resulting from significant reduction of global high clouds and, to a
lesser extent, from an increase in high-latitude sea ice. Our simulation
experiments suggest that clouds and sea ice are sensitive to stratospheric ozone
perturbation, which constitutes a significant radiative adjustment that
influences the sign and magnitude of the global surface temperature change.
Introduction
Observational records show that stratospheric ozone has declined prior to the
late 1990s and then started stabilizing and even slowly increasing,
especially in the polar regions (WMO, 2007, 2011). It is expected that the
ozone layer will return to the pre-1980 level in the 2050s (Bekki et al., 2011). It
is known that ozone is a greenhouse gas, and that stratospheric ozone has a
warming effect on tropospheric-surface climate, which has been demonstrated
by early simulation works with radiative-convective models (Ramanathan and
Dickinson, 1979; Lacis et al., 1990). Consistent with such understanding,
ozone depletion generally leads to a negative radiative forcing (after
accounting for stratospheric temperature adjustment) that cools the climate
(Forster and Shine, 1997; Hansen et al., 2005; Conley et al., 2013; Myhre et
al., 2013; Macintosh et al., 2016). On such a basis, one would expect that
stratospheric ozone recovery (SOR) exerts a positive forcing that should lead
to troposphere and surface warming. The single-column simulation by Hu et
al. (2011) agrees with such an expectation, although their efforts to
distinguish the responses to SOR in full general circulation models (GCMs) is
impeded by climate sensitivity differences between the two groups of models
(McLandress et al., 2012). Very interestingly, McLandress et al. (2012) show
a weak troposphere-surface cooling in response to SOR in a coupled
chemistry–climate model (CCM). As presented below, such a weak cooling is
also seen in our simulation with an atmospheric GCM coupled to a slab-ocean
model. These results raise important questions: how does surface cooling
result from the positive radiative forcing of SOR in GCM simulations? Why do
GCMs and radiative-convective models yield opposite results? In this paper,
we are motivated to answer these questions and reconcile the contradiction of
the warming prediction based on single-column model simulations.
One prominent deficiency of the one-dimensional radiative-convective models
is that they neglect effects of clouds as well as snow and ice albedo. Thus,
results from these simplified models may not realistically represent the
responses to SOR. Hence, our hypothesis is that the radiative adjustment of
clouds and sea ice may override the forcing of SOR and change the direction
of surface temperature change in more sophisticated GCMs. To test this
hypothesis, we perform two sets of SOR forcing experiments using a
three-dimensional climate model, one with standard settings and the other
with cloud and sea ice artificially removed in the simulation. Comparison of
the two sets of simulations shall elucidate the effects of cloud and sea
ice. In the following sections, we will describe the configuration and
results of these experiments, dissect the simulations from a radiative
budget perspective, and summarize our main findings in order.
Model and experiment design
Here, we conduct and analyze a series of SOR experiments using the NCAR
Community Atmosphere Model, version 3 (CAM3) coupled with a Slab Ocean Model
(SOM) (Collins et al., 2006; Neale et al., 2010). All of the runs presented
below are conducted with T42 horizontal resolution
(∼ 2.8∘× 2.8∘) and coupled to a 50 m deep
SOM. The SOM configuration uses a simple ocean component (Kiehl et al., 2006;
Danabasoglu and Gent, 2009), combined with a thermodynamic sea-ice component
that is based on the Community Sea Ice Model (CSIM5, Briegleb et al., 2004) and
allows for a fully interactive treatment of surface exchange processes in
CAM3. Danabasoglu and Gent (2009) compare the slab ocean and the fully
coupled configurations of CCSM3 and find that the slab-ocean setup provides a
good estimate of the climate sensitivity of the fully coupled model. Although
the slab-ocean component lacks explicit representation of ocean currents, GCM
surface winds drive the sea-ice dynamics, with advection simulated as a
cavitating fluid (Flato and Hibler, 1990, 1992). Compared with the coupled
atmosphere–ocean simulations by CESM1 (CAM5), the annual cycle of
climatological sea-ice extent has similar magnitude (varying from 3 to
15 × 106 km2) in SOM. The variabilities of the
annual mean sea-ice extent are also similar (about
2–3 × 106 km2) in SOM and coupled atmosphere–ocean
simulations. A few studies have documented the deficiencies in the
CAM3-simulated cloud fields, including the biases in climatological mean
cloud fraction and optical depth and cloud responses to tropospheric
eddy-driven jet shifts, especially in the Southern Hemispheric midlatitude
region (Kay et al., 2012, 2014; Ceppi et al., 2014; Grise and Polvani, 2014; Ceppi and Hartmann, 2015). We also notice that the climatological
mean fraction of the polar stratospheric clouds in the Antarctica is
noticeably larger in the CAM3 (∼ 15 % in austral spring) than in a
few other models (CCSM4: ∼ 10 % and CESM-CAM5: ∼ 3 %).
However, as the region under question is small, it is unlikely to
significantly affect the global mean cloud radiative effect that we are
concerned with in this paper. This will be further discussed in the
concluding section.
In order to isolate the effect of clouds and sea ice, two sets of experiments
are conducted here. In the first set, we use standard settings of the model,
without any modification of cloud and sea ice. In the other set of
integrations, we set the freezing temperature to -180∘C
so that there is effectively no sea ice in the simulation. We also set all
the cloud fractions to zero in radiative heating rate and flux calculations
and thus suppress the radiative effects of clouds, which is similar to the
configuration of the Clouds On Off Klima Intercomparison Experiment (COOKIE).
To restore radiative energy balance, following Koll and Abbot (2013) we
reduce the solar constant by 120 W m-2, because CAM3 has a global mean
cloud forcing of ∼ 30 W m-2. These two sets of experiments are
denoted as “Standard” and “No Cloud No Sea Ice (NCNSI)” respectively in
the following. The global and climatological mean surface temperature is
291.4 K in the NCNSI experiment, which is comparable to the climatology in
the Standard experiment (about 2 K warmer). Note that the cloud modification
used here does not affect the generation of clouds in GCM integration or
related latent heating of the atmosphere. The hydrological cycle, as
reflected by the climatology of precipitation, in the NCNSI experiment is
similar to that in the Standard experiment. Thus, the NCNSI simulation
provides a reasonable hypothetical situation for comparing the radiative
responses to SOR.
In order to examine the impact of SOR on surface temperature, two 100-year
integrations, prescribed with identical concentrations of well-mixed
greenhouse gases (CO2, CH4, N2O, etc.) but different
stratospheric ozone concentrations, are conducted in both the Standard and
the NCNSI experiments. The monthly mean ozone volume mixing ratios averaged
over 1999–2003 (scenario 2000) and 1979–1983 (scenario 1979), taken from
the ERA-Interim reanalysis (Dee et al., 2011), are prescribed in these two
integrations to represent “present” (2000) and “recovery” (1979)
scenarios respectively. In order to eliminate the influence of tropospheric
ozone, the ozone below 200 hPa in the recovery scenario is fixed at scenario
2000 level. To see the impact of SOR, the idealized ozone change in the
recovery scenario above 200 hPa is set to the absolute value of the
difference between 1979 and 2000 (Fig. 1a). In comparison, the ozone in the
recovery scenario increases by about 28 Dobson units (DU) in the tropics and
subtropical regions, about 63 DU in the Arctic, and about 73 DU in Antarctic
(Fig. 1b). Both scenario experiments are initialized from an equilibrated
present-day CAM3 simulation with sea surface temperature (SST) prescribed to
be the climatological mean values of the period 1980–2000. The atmospheric
states in all these experiments approach steady states after 10 years of
integration. We assess the SOR impacts by contrasting the means of
appropriate variables in the last 90 years of two 100-year simulations (the
difference between two equilibrium states).
The distribution of SOR. (a) The vertical cross section of the
annual and zonal mean difference of ozone, unit: ppmv. (b) The annual and
zonal mean difference of total column ozone, unit: DU.
Surface temperature change
As shown by Fig. 2, SOR causes noticeable changes in not only stratospheric
but also tropospheric and surface climate. The stratosphere in both the
Standard and NCNSI experiments is significantly warmed, as expected from the
radiative heating effect of stratospheric ozone. On the other hand, SOR leads
to tropospheric and surface warming in the NCNSI experiment, while noticeable
cooling is seen in the Standard experiment (compare Fig. 2a and b). The
global and annual mean surface temperature change is +0.2 and -0.06 K in
the two experiments, respectively. The surface warming in the NCNSI
experiment occurs in all seasons and at most latitudes. In comparison,
surface cooling in the Standard experiment is the strongest in the two polar
regions (reaching -0.8 K in Arctic in boreal autumn), and is also strong
(about -0.2 K) over the high-latitude Southern Ocean (40–70∘ S).
Responses to SOR of zonal mean surface temperature, annual and
zonal mean air temperature, annual and zonal mean cloud fraction, and zonal
mean sea-ice fraction. Latitude–month distribution of surface temperature in
the (a) NCNSI, and (b) Standard experiment. Vertical cross section of air
temperature in the (c) NCNSI, and (d) Standard experiment. (e) Vertical cross
section of cloud fraction, and (f) latitude–month distribution of sea-ice
fraction in the Standard experiment. In (a, b), the color interval is 0.05 K.
In (c, d), the color interval is 0.2 K. In (e–f), the color interval is
0.4 %. Regions with dots are the places where differences have statistical
significant levels higher than the 95 % confidence level (student t test
values are greater than 2.0). The black line in (c–e) indicates the tropopause of
climatology.
The results here support our hypothesis that the different responses to SOR
(cooling vs. warming) are caused by clouds and sea ice. It is interesting
that the same SOR perturbation drives surface climate changes in opposite
directions due to effects of clouds and sea ice. This is especially
interesting because the stratosphere-adjusted forcing of SOR (as detailed in
the following section) is similar (positive) in the NCNSI and Standard
experiments.
Radiative forcing and adjustments, evaluated at the top of the
atmosphere. The columns indicate the instantaneous radiative forcing (IRF) of
O3, the stratosphere-adjusted forcing (SAF), the effective radiative
forcing (ERF, i.e., stratosphere and troposphere-adjusted forcing), the
stratospheric adjustment, and the radiation changes caused by cloud, sea ice,
atmospheric temperature (TA), water vapor (WV), and surface
temperature (TS), respectively. Unit: W m-2.
IRF of O3SAFERFStratospheric adjustmentTropospheric/surface radiative effects CloudSea-iceTAWVTSNCNSI0.490.30NA-0.19NANA-0.770.77-0.26Standard0.600.290.01-0.31-0.39-0.10-0.040.100.08Fixed SST/SI0.600.290.01-0.31-0.25NA-0.150.12NARadiation diagnosisInstantaneous forcing
We calculate the instantaneous radiative forcing (IRF) of SOR using a
radiative transfer model, RRTMG (Mlawer et al., 1997). The radiative forcing
is calculated as the change in top-of-atmosphere (TOA) radiation fluxes in
response to the stratospheric ozone change (from 2000 to 1979 values) in
every grid box using monthly mean temperature, water vapor, and cloud
profiles from a 2000 equilibrium integration. Following Cronin (2014), we use
the insolation-weighted method to calculate the monthly mean solar zenith
angle. The global and annual mean forcing values are provided in Table 1. Due
to ozone absorption of shortwave solar radiation (mainly in the 200–315 nm
UV region) and long-wave terrestrial thermal emission (mainly around
9.6 µm), the SOR as prescribed in our experiments induces a
positive (downward at TOA, i.e., warming) forcing in both the NCNSI
and Standard experiments. The global mean values are 0.49 and
0.60 W m-2, respectively. Note that in our idealized SOR scenario
(Fig. 1), the ozone change is positive throughout the stratosphere, including
the tropical UTLS region, which renders very positive forcing across all the
latitudes. In both experiments, the long-wave forcing has a flat zonal mean
pattern, due to compensating effects of the latitudinal variations in surface
thermal radiation and ozone concentration (black lines in Fig. 3a and b). In
contrast, the shortwave SOR forcing peaks at two poles as shown in Fig. 3c
and d, which is caused by the higher local ozone concentration.
Annual and zonal mean distribution of the radiative contributions
at TOA for the NCNSI experiment: (a) long-wave (LW) radiation: stratospheric
temperature adjustment (blue line), ozone (black line), and water vapor
(green line); (c) shortwave (LW) radiation: ozone (black line), and water vapor
(green line). For the Standard experiment: (b) long-wave radiation:
stratospheric adjustment (blue line), ozone forcing (black line), water vapor
(green line), and radiative effect of cloud (red line); (d) shortwave
radiation: ozone forcing (black line), water vapor (green line), cloud (red
line), and ice-albedo (blue line) effects. Negative/positive values indicate
upward/downward radiative flux at TOA. The radiative forcing of ozone is
calculated with RRTMG.
Stratospheric adjustment
Ozone heats the stratosphere due to its absorption of solar radiation. Here,
the stratospheric adjustment, i.e., the radiative impact due to stratospheric
warming in response to SOR, is calculated using a kernel method, following
Zhang and Huang (2014) and Huang et al. (2016). The stratospheric temperature
kernels of Shell et al. (2008) are used here. The stratospheric temperature
change is calculated as the temperature difference between the 1979 and 2000
equilibrium integrations. As higher stratospheric temperatures mean more
thermal radiation radiated to the space, stratospheric adjustments evaluated
here are negative in both experiments (see Fig. 3a and b). Nevertheless, the
stratosphere-adjusted forcing (SAF, i.e., instantaneous forcing plus
stratospheric adjustment) remains positive in both NCNSI (0.30 W m-2)
and Standard experiments (0.29 W m-2). In addition, we also calculate
the SAF with RRTMG using the fixed dynamical heating method (Ramanathan and
Dickinson, 1979), and find the SAF in the Standard experiments to be
0.21 W m-2, which is in agreement with the kernel method. Note that as
discussed by Huang et al. (2016), the adjusted forcing evaluated using TOA
flux equals that evaluated using tropopause flux if the stratosphere adjusts
to a radiative equilibrium. The fact that the stratosphere-adjusted forcing
is positive indicates that the weak cooling in the Standard experiment is not
predictable from SAF, but is influenced by tropospheric adjustments.
Tropospheric adjustments
Here we analyze the radiative contributions by other atmospheric and surface
variables, namely temperature, water vapor, sea ice (albedo), and clouds,
mainly using the kernels of Shell et al. (2008). Note that the radiative
effect of clouds is obtained using the cloud forcing adjustment method that
incorporates the instantaneous forcing and stratospheric adjustment
calculated above (cf. Huang, 2013; Huang and Zhang, 2014).
In the Standard experiment, we find the radiative effects of clouds and
sea ice to be strongly negative (-0.39 and -0.10 W m-2,
respectively; see Table 1). The cloud effect consists of -0.26 W m-2
in the long wave and -0.13 W m-2 in the shortwave, which is in good
agreement with the 0.25 W m-2 effect in response to stratospheric
ozone depletion reported by Grise et al. (2013). This cloud radiative effect
offsets the warming effect of SOR forcing (a SAF of 0.29 W m-2). As a
result, there is a weak global cooling in surface temperature (-0.06 K).
The radiation budget is balanced by the positive radiation changes (reduction
of outgoing radiation) caused by the surface cooling (0.08 W m-2) and
by atmospheric temperature and water vapor changes (-0.04 and
0.10 W m-2, respectively).
In order to separate the fast adjustments in the troposphere from surface-temperature-related feedback effects, we conduct an SOR experiment using CAM3
with fixed SST and sea ice (Fixed-SST/SI). Two simulations forced with
prescribed climatological SST and SI averaged over the years 1980–2000 are
performed with different ozone concentrations as described above. The
stratosphere and troposphere-adjusted forcing (effective radiative forcing,
ERF) is obtained by contrasting the averages over the last 15 years of the
two 35-year integrations. The ERF is found to be 0.01 W m-2,
consisting of an instantaneous forcing of 0.60 W m-2, a stratospheric
adjustment of -0.31 W m-2, and a tropospheric adjustment of
-0.28 W m-2 (which is mainly contributed by clouds:
-0.25 W m-2) (Table 1). Evident from these results, the cloud
radiative effect in the Standard experiment is largely a tropospheric
adjustment, which together with the stratospheric adjustment offsets
instantaneous forcing of ozone and results in a neutralized ERF.
The latitude–month distribution of the responses to SOR of the zonal
mean surface radiation budget. (a) Net shortwave, (b) downward long wave, and
(c) panels (a, b) in the NCNSI experiment. (d) Net shortwave, (e) downward
long wave, and (f) panels (d, e) in the Standard experiment. (g) Shortwave
CRE, (h) long-wave CRE, and (i) panels (g, h) in the Standard experiment.
(j) The albedo-induced surface radiation in the Standard experiment. Color
interval is 0.5 W m-2.
In comparison, in the NCNSI experiment, without the offsetting negative
radiative effects of clouds and sea ice, a significant global warming
(0.2 K) results from the SOR forcing, which gives rise to a radiative effect
of -0.26 W m-2. The water vapor feedback in this experiment is
strong and positive (0.77 W m-2), although it is offset by the
atmospheric temperature feedback (-0.77 W m-2).
In summary, these results show that significant radiative cooling effects
caused by the adjustments of clouds and sea ice in response to SOR explains
the weak global cooling in the Standard experiment.
Surface radiation budget
Complementary to the TOA radiation budget decomposition, we also analyze the
surface radiation flux change driven by SOR. Figure 4 shows the changes in
the surface radiation budget from the 2000 equilibrium integration relative
to the 1979 equilibrium integration. The changes in the net surface shortwave
radiation in both experiments can be explained by ozone absorption of UV
radiation. In the NCNSI experiment, the global and annual mean reduction is
-0.60 W m-2. The maximum reduction reaches -2.4 W m-2 in
the Northern Hemisphere and -1.6 W m-2 in the Southern Hemisphere.
Both occur at high latitudes in summer because of the largest stratospheric
ozone increases there. In the Standard experiment, the global and annual mean
reduction is -0.62 W m-2. Compared to the NCNSI experiment, the
duration and spatial coverage of the net shortwave radiation change is also
significantly modified by clouds and sea ice (Fig. 4g and j). Here we measure
the cloud radiative effect (CRE) by the difference between the all-sky and
clear-sky surface radiation. The changes in long-wave and shortwave CRE in
response to SOR are shown separately, with global and annual mean values of
-0.26 and 0.04 W m-2, respectively. The radiative effect of sea ice
is measured as the surface radiation change caused by surface albedo change,
i.e., climatological surface downward shortwave radiation multiplied by surface
albedo change. The global mean shortwave radiation change due to albedo
change is measured to be -0.11 W m-2.
The greenhouse effect of ozone enhances the surface downward long-wave
radiation. This enhancement is augmented by the atmospheric warming and
moistening in the NCNSI experiment, which altogether overrides the cooling
effect of ozone in the shortwave (Fig. 4c). The global and annual mean net
radiation change is +1.1 W m-2. This explains the surface warming in
this experiment. In comparison, the enhancement in the downward long-wave
radiation in the Standard experiment is less strong and limited to low-latitude regions. This is mainly because of a strong negative change in cloud
forcing (Fig. 4h). The global and annual mean net radiation change is
-0.72 W m-2, which explains the global cooling in this experiment.
In summary, the surface temperature responses in both experiments (Fig. 2a
and b) are consistent with the changes in the net radiation at the surface
(Fig. 4c and f). The comparison between the NCNSI experiment and the Standard
experiment again highlights impacts of clouds and sea ice on the radiation
budget, which can override the initial radiative perturbation of ozone and
lead to different surface temperature responses. We will elaborate this point
in the following section.
The roles of cloud and sea ice
Figure 2e shows the response of the cloud fraction in the Standard
experiment. There is general reduction in cloud fraction, especially for
those high clouds near the tropopause. The decrease in high clouds is
associated with a decrease in relative humidity caused by the SOR warming of
the upper troposphere and lower stratosphere (Jenkins, 1999; Yang et al.,
2012), which is consistent with the significant increase in UTLS cirrus
clouds which resulted from in situ ozone depletion found in Nowack et al. (2015). This
then accounts for the aforementioned negative TOA long-wave cloud radiative
effect (Table 1; Fig. 3b) and the negative change in CRE at the surface
(Fig. 4h).
On the other hand, the responses of the middle- and low-level clouds are
consistent with the SOR-forced equatorward shift of the eddy-driven westerly
jet in the Southern Hemispheric midlatitudes (see the review by Thompson et
al., 2011). This occurs especially during late spring and summer in the
Southern Hemisphere. As the jet shifts, the associated storm track,
precipitation, and cloud patterns follow; so cloud fraction decreases in the
subtropical region (20–40∘ S), increases in the middle latitudes
(40–60∘ S), and decreases in the polar region (higher than
60∘). This then impacts the radiation budget, as documented by Grise
et al. (2013). As shown by the TOA radiative effect of cloud (Fig. 3d) and
surface CRE (Fig. 4g), there are strong shortwave radiation anomalies that
oscillate with the latitude. We find that these radiation anomalies are
largely accounted for by the redistribution of liquid cloud and have very
small global mean values: 0.04 W m-2 for surface radiation and
-0.13 W m-2 for TOA radiation. Although SOR has a positive radiative
forcing, the cloud changes due to SOR induce a net cooling effect on the
climate system, which is consistent with the results in Grise et al. (2013).
Sea-ice response is important for the surface radiation budget in both polar
regions. Arctic sea ice increases in boreal summer and autumn and Antarctic
sea ice increases throughout the year (Fig. 4j). These increases cause
considerable decreases in net shortwave radiation at surface, thus acting to
cool surface temperature. Recent studies suggest that the Antarctic ozone
hole has important influences on Antarctic sea ice (Sigmond and Fyfe, 2010;
Bitz and Polvani, 2012; Smith et al., 2012). The large sea-ice and radiation
changes seen here affirm such ozone impact.
In order to isolate and compare the effects of clouds and of sea ice, we
apply the same techniques as used in the NCNSI experiment to suppress cloud
and sea-ice effects respectively in two additional experiments. We find that
the global mean surface temperature response to SOR is 0.18 K in the
No Cloud experiment and is 0.03 K in the No Sea Ice experiment, which
confirms that the suppression of the warming effect of the SOR is largely
due to clouds.
Discussion and conclusion
The Standard and NCNSI experiments conducted here suggest that clouds and
sea ice are sensitive to stratospheric ozone perturbations and their
radiative effects are critical for predicting surface temperature changes.
Although the stratosphere-adjusted forcing of SOR is positive in both
experiments, the warming effect of ozone recovery is offset by the cooling
effect caused by high-cloud reduction and sea-ice increase in the Standard
experiment, which results in a weak global cooling. In addition, SOR also
causes equatorward shift of jet stream, precipitation, and middle and
low clouds, especially in the Southern Hemisphere, which results in dipole
patterns of zonal mean surface shortwave radiation anomalies and
corresponding temperature anomalies.
The cloud and sea-ice changes in the Standard experiment emerge as
significant signals in response to the SOR forcing. The reduction of high
clouds can be attributed to ozone-induced radiative warming and consequent
relative humidity reduction in upper troposphere and lower stratosphere, in
accordance with the findings of (Jenkins, 1999; Yang et al., 2012). The sea-ice changes in the Arctic and around the Antarctic are influenced by
ozone-induced indirect radiative effects, which are associated with the
reduction of downward infrared radiation over the sea-ice edge caused by the
in-situ decreases of clouds and water vapor, and also the atmospheric cooling
(Hu et al., 2016). The strong sea-ice response to SOR forcing suggests that the
ongoing SOR would mitigate Antarctic sea-ice loss from greenhouse warming in
the twenty-first century (Smith et al., 2012).
Although an isolated SOR forcing as prescribed in our experiments is
hypothetical, this forcing scenario makes a very unusual case of climate
change in that the radiative forcing is positive (a warming effect) but the
surface temperature response is negative (cooling). The key factor that leads
to the breakdown of the prediction appears to be a significant high cloud
change directly resulting from the forcing. Although this result is mainly
based on one GCM, CAM3, which has known deficiencies (see the discussions in
Sect. 2), a suite of experiments and diagnoses here suggests that this may be a
significant rapid adjustment to stratospheric ozone forcing and may have
important implications such as for climate projection and geoengineering.
Moreover, the globally occurring high-cloud response to the stratospheric
ozone change reported here and the weak surface cooling resulted are
corroborated by other studies that are based on different models (McLandress
et al., 2012; Nowack et al., 2015). An examination of the CMIP5 ozone-only
historical hindcast experiments shows that there are noticeable high-cloud
changes in many models, and the majority of the models show a weak warming in
response to the significant ozone depletion from 1960 to 2000, which is in
accordance with the results reported here; however, because the forcing
prescribed in the experiments is not exclusively stratospheric ozone change,
these results do not lead to conclusive assessment. It warrants further
research to verify whether the cloud and sea-ice responses to stratospheric
ozone are robust across different GCMs and whether the responses are
sensitive to details in the prescription of ozone change.
Data availability
The data generated in this work can be obtained by contacting Yan Xia
(yan.xia3@mail.mcgill.ca).
Acknowledgements
We thank Timothy Merlis, Bruno Tremblay, and Jun Yang for their helpful
comments and suggestions. Y. Xia and Y. Huang acknowledge grants from the
Natural Sciences and Engineering Research Council of Canada (RGPIN 418305-13)
and the Fonds de recherche du Québec (NC-181248). Y. Xia also
acknowledges a fellowship from the China Scholarship Council (CSC,
No. 201405990230). Y. Hu acknowledges grants from the National Natural
Science Foundation of China (NSFC grant nos. 41530423 and
41375072). Edited by: Q. Fu
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