A key variable in the models when considering sea spray climate engineering
is the amount of low clouds over the ocean, in particular subtropical
stratocumulus clouds off the west coasts of North America, South America, and
southern and northern Africa. These regions have been assessed to be most
susceptible to brightening (Salter et al., 2008; Alterskjær et al., 2012;
Jones and Haywood, 2012). Figure 2 shows the low-level cloud fraction below
850 hPa for NorESM1-M (Fig. 2a) and HadGEM2-ES (Fig. 2c), and below
600 hPa for GISS-E2-R (Fig. 2b), averaged over years 2020–2030 in
the RCP4.5 scenario. Here we use the assumption of random overlapping cloud
layers for the estimates of the cloud cover. NorESM1-M (Fig. 2a) and
HadGEM2-ES (Fig. 2c) capture the maxima in low-level cloud cover associated
with the subtropical high-pressure cells in the eastern parts of the Pacific
Ocean and the Atlantic Ocean (e.g. Rossow and Schiffer, 1999). The reason for
including layers higher than 850 hPa in the estimate of low-level
cloud cover for GISS-E2-R is that for the region west of Peru the model
reaches its maximum in cloud cover slightly above 850 hPa. From
Fig. 2 it is clear that the low-cloud amounts over tropical and subtropical
ocean are considerably lower in GISS-E2-R than in NorESM1-M and HadGEM2-ES,
in particular when it comes to stratocumulus clouds in the subtropical high-pressure cells in the eastern parts of the Pacific Ocean and Atlantic Ocean.
This needs to be taken into account in the assessment of the impact of sea
spray climate engineering in GISS-E2-R.
Effective radiative forcing by the injected particles
The sea salt injection rates between 30∘ N and 30∘ S
required to generate a global-mean ERF of -2.0 Wm-2 at the TOA
are 250 Tgyr-1 in NorESM1-M, 590 Tgyr-1 in
GISS-E2-R, and 200 Tgyr-1 in HadGEM2-ES. The fact that GISS-E2-R
requires a larger injection rate than the two other ESMs is likely due to the
larger dry radius of the injected particles in GISS-E2-R
(0.44 µm) than in NorESM1-M (0.13 µm) and HadGEM2-ES
(0.10 µm). This means that a specific injection rate in GISS-E2-R
results in fewer particles than in the two other ESMs (Fig. 1a). The smaller
amount of low clouds in GISS-E2-R (Fig. 2b) may also be a contributing factor
to the larger injection rates required in this model. The injection rates in
this study are close to the rate reported by Partanen et al. (2012), who
obtained a -5.1 Wm-2 global-mean ERF in the aerosol–climate
model ECHAM5.5-HAM2 from wind-speed-dependent global sea salt injections at
a rate of 440 Tgyr-1. Our injection rates are also similar to
those reported by Alterskjær et al. (2013), who applied gradually
increasing sea salt injection rates between 30∘ N and 30∘ S
in three different ESMs to keep the TOA radiative forcing of an RCP4.5
scenario at the 2020 level for 50 years. The radiative forcing change
within the RCP4.5 scenario between 2020 and 2070 is
+1.64 Wm-2. During the last decade of their simulations, the
injection rates required varied between 266 and 560 Tgyr-1
across their three models.
The global-mean ERF by the injected sea salt particles, for the rates given
above, is relatively constant at -2.0 Wm-2 throughout the
10-year fixed SST simulation in all three ESMs (Fig. 3a). The radiative
fluxes in the ESMs are calculated also for clear-sky conditions. These
clear-sky radiative fluxes can be used to determine the clear-sky global-mean
ERF (Fig. 3b). This variable is not equal to the aerosol direct effect of the
injected particles, because the aerosol direct effect is larger in clear-sky
conditions than when clouds are present. This is because most of the injected
particles are located below cloud base when clouds are present, which reduces
the aerosol direct effect due to the high albedo of most clouds.
Nevertheless, it is interesting to note that the clear-sky global-mean ERF
(Fig. 3b) is almost equal to the total global-mean ERF (Fig. 3a) throughout
the 10 years in the three ESMs, indicating a large potential of the aerosol
direct effect in regions of low cloudiness. Although we cannot estimate the
contribution of the aerosol direct effect to the total ERF from Fig. 3, it is
evident that sea spray climate engineering can be effective even without
clouds.
TOA mean effective radiative forcing over the 10 years of
simulation with fixed SST for (a) NorESM1-M, (b) GISS-E2-R,
and (c) HadGEM2-ES.
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The clear-sky ERF by the injected particles in Fig. 3b is of comparable
magnitude for the three models, despite the higher sea salt mass injection
rates and larger size of the injected particles in GISS-E2-R compared to the
other two models. The surface area size distribution (Fig. 1b) is closely
related to the amount of light scattered by the sea salt particles and
thereby the clear-sky ERF in Fig. 3b. For a full description of Mie
scattering, however, one also needs to take into account variations in the
scattering coefficient with particle size, which is done in the radiative
transfer calculations in the models. The total particle number injections
(integrated over the particle number size distributions in Fig. 1a) are
1.8×1020, 2.7×1018, and 1.1×1020 s-1 for NorESM1-M, GISS-E2-R, and HadGEM2-ES; thus the number of injections is almost
2 orders of magnitude smaller in GISS-E2-R compared to the
other models. The corresponding particle surface injections (integrated over
the particle surface distributions in Fig. 1b) are 5.2×107,
1.7×107, and 3.1×107 m2s-1 for
NorESM1-M, GISS-E2-R, and HadGEM2-ES. Thus, although the difference in total
particle number injection between GISS-E2-R and the other two models is
large, the difference in total particle surface area injection is
considerably smaller. Hygroscopic growth is accounted for in all the three
models (Sect. 2.1), and this process will modify the injected particle size
distributions in the atmosphere, since the relative humidity within the
injection area is generally above the deliquescence relative humidity for sea
salt. The light-scattering enhancement factor (e.g. Titos et al., 2016)
describes the relative increase in aerosol light scattering at a certain
relative humidity compared to dry conditions. This parameter is not diagnosed
in the models for the injected sea salt particles, but decreases with
increasing particle dry diameter for a certain relative humidity (e.g. Zieger
et al., 2013). This means that hygroscopic growth of the injected particles
is expected to generate a larger increase in clear-sky ERF in NorESM1-M and
HadGEM2-ES than in GISS-E2-R, since the injected particles are larger in
GISS-E2-R than in the two other models. The main reason that sea salt
injections in GISS-E2-R still generates a clear-sky ERF as large as the other
two models, or even slightly larger (Fig. 3b), is likely due to GISS-E2-R
having the lowest background clear-sky atmospheric optical depth of the three
models (not shown). This means that GISS-E2-R is more sensitive to injections
than the two other models.
The ratio of the total ERF to the clear-sky ERF at the TOA averaged
over the 10 years of simulation with fixed SST for (a) NorESM1-M,
(b) GISS-E2-R, and (c) HadGEM2-ES.
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The effective radiative forcing by the injected particles at the TOA varies
spatially between -2.0 and -10 Wm-2 across the injection
area in the three ESMs (Fig. 4). The mean values over the injection area are
-4.3 Wm-2 in NorESM1-M, -4.9 Wm-2 in GISS-E2-R,
and -4.7 Wm-2 in HadGEM2-ES. The injection area here, and for
later calculations, represents all grid cells over ocean between
30∘ N and 30∘ S. In NorESM1-M (Fig. 4a), maximum ERF
appears
in the stratocumulus regions off the west coasts of northern South America
and southern Africa (Fig. 2a), locally exceeding -10 Wm-2.
This means that the ERF over these regions is a factor of 2–3 larger than
the average over the injection area. The location of these maxima is in
agreement with the studies by Jones and Haywood (2012) and Partanen
et al. (2012), who observed a strong aerosol indirect effect in these areas
from sea spray climate engineering. The ERF maximum off the west coast of
southern Africa is also pronounced in HadGEM2-ES (Fig. 4c), although weaker
in forcing than in NorESM1-M. In addition, there are maxima in ERF in the
marine stratocumulus regions west of northern Africa and west of Australia
for both NorESM1-M and HadGEM2-ES. Jones and Haywood (2012) saw a strong
aerosol indirect effect from sea spray climate engineering in these regions
in the HadGEM2-ES model.
Mean difference in sea salt mass concentration in the lowest model
layer between G4sea-salt and RCP4.5 averaged over 2035 and 2065, for
(a) NorESM1-M, (b) GISS-E2-R, and (c) HadGEM2-ES.
![]()
Mean relative change in CDNC due to sea salt injection for NorESM1-M
(a), GISS-E2-R (b), and HadGEM2-ES (c). CDNC
represents the cloud droplet number concentration within the model layer
below 700 hPa with maximum concentration, and the maps represent
averages over 2035–2065.
![]()
Although the effective radiative forcing by the injected particles in
NorESM1-M and HadGEM2-ES is at a maximum over some of the marine subtropical
stratocumulus regions previously identified as optimal for marine cloud
brightening, the ERFs in Fig. 4 are not as dominated by these regions as in
the study by Partanen et al. (2012) with ECHAM5.5-HAM2. In that study, the
maximum ERF of their sea spray climate engineering exceeded
-30 Wm-2 in the stratocumulus regions west of Peru and
southern Africa, whereas the mean ERF outside these regions was around
-5 Wm-2. This means that the ERF by the injected particles in
the subtropical stratocumulus regions was more than a factor of 6 higher
than the typical ERF outside these regions. Such a large difference in ERF
between subtropical stratocumulus regions and other regions within the
injection area is not seen here. For NorESM1-M and HadGEM2-ES the sea salt
injection also generates a strong ERF over large regions of the central and
western parts of the Pacific Ocean, where a low cloud-weighted susceptibility
to sea salt injections (Alterskjær et al., 2012) and a strong aerosol
direct effect from sea spray climate engineering (Jones and Haywood, 2012)
have been identified. The correlation between the strength of the effective
radiative forcing and low-level cloud cover (as defined in Fig. 2), when
including all grid cells over ocean within the injection area, is weak for
these two models (the Pearson correlation coefficient r is equal to 0.28
and 0.16 for NorESM1-M, and HadGEM2-ES respectively). Thus, over the
injection area as a whole, the presence of low-level clouds gives no clear
advantage for obtaining a large ERF from sea spray climate engineering.
Although GISS-E2-R (Fig. 4b) has maxima in ERF in the same subtropical
stratocumulus regions as the other two models, there is less horizontal
variability in ERF in GISS-E2-R. An exception is the Intertropical
Convergence Zone (ITCZ), where the ERF is considerably weaker, likely due to
the large amounts of high clouds in these regions (not shown). The presence
of middle to high-level clouds is not optimal for sea spray climate
engineering as these clouds block out some of the incoming solar radiation
and make a negligible contribution to the aerosol indirect effect. A weaker
ERF along the ITCZ can be seen to some extent also over the Pacific in
NorESM1-M (Fig. 4a). The more homogeneous ERF field for GISS-E2-R compared to
the two other models is likely due to the smaller amount of low-level clouds
in GISS-E2-R compared to the two other ESMs (Fig. 2). This means that the
aerosol direct effect likely contributes more to the total ERF in GISS-E2-R,
leading to fewer horizontal variations in ERF. This hypothesis of a low
contribution of the aerosol indirect effect to the ERF in GISS-E2-R is
supported by the absence of correlation between the strength of the ERF and
low-level cloud cover (r=-0.10) for this model.
Figure 5 shows the ratio of the total ERF to clear-sky ERF at the TOA for
each of the three models. This figure provides information on whether the
clouds that are present increase the ERF by the injected particles compared
to clear-sky conditions. Red-coloured areas indicate an increased ERF when
clouds are present, and thereby an effective aerosol indirect effect, whereas
blue-coloured regions indicate an enhanced ERF for clear-sky conditions. The
impact of the subtropical stratocumulus clouds on the ERF by the injected
particles, relative to clear-sky conditions, is largest in HadGEM2-ES
(Fig. 5c), with the ratio of total ERF to clear-sky ERF locally being higher
than 4:1 in regions west of California and Mexico, west of southern Africa,
and west of Australia. In NorESM1-M (Fig. 5a), the corresponding enhancement
in ERF in these regions due to the presence of low clouds is considerably
smaller, although with a ratio locally above 3:1 in the Atlantic region
west of northern Africa. In GISS-E2-R (Fig. 5b), the maximum values of the
total ERF to clear-sky ERF ratio appear in the same subtropical high-pressure
regions as in the other models, although much less pronounced due to the
smaller amount of low-level clouds in this model. For GISS-E2-R, there are
regions along the ITCZ where the presence of clouds reduces the ERF by the
injected particles (blue-coloured regions), likely due to the high presence
of high-level clouds in these regions, as discussed above. Total ERF to
clear-sky ERF ratios lower than one along the ITCZ indicate that the aerosol
direct effect of the injected particles in clear-sky conditions is larger
than the total radiative effect of the injected particles when clouds are
present, and such ratios also appear locally in the other two ESMs.
In summary, the presence of low clouds in the subtropical high-pressure
regions has the effect of increasing the ERF by the injected particles
compared to clear-sky conditions, and this enhancement in ERF due to the
aerosol indirect effect is most pronounced in HadGEM2-ES. However, in most
other regions within the area of sea salt injection, the ratio of total ERF
to clear-sky ERF is close to one in all the models, which indicates that the
presence of clouds in most regions does not significantly increase the ERF
compared to clear-sky conditions. This finding, together with the relatively
small horizontal variability in ERF compared to Partanen et al. (2012) and
weak or non-existent correlations between ERF and low-level cloud cover,
suggests that the aerosol direct effect probably makes a larger contribution
to the total ERF in this study compared to the study by Partanen
et al. (2012), where the aerosol direct effect contributed 29 % to the
total ERF by sea spray climate engineering.
Mean relative change between G4sea-salt and RCP4.5 in cloud-top
effective radius for NorESM1-M (a) and HadGEM2-ES (c) and
in cloud optical depth for NorESM1-M (b) and HadGEM2-ES
(d). The maps represent average change due to sea spray climate
engineering over the period 2035–2065. Hatching denotes areas where changes
are not significant at the 95 % confidence level (Student t test with
respect to variance of annual mean values).
![]()
Coupled simulations
Change in sea salt concentrations, cloud properties, and atmospheric circulation
The injection rates generating a global-mean effective radiative forcing of
-2.0 Wm-2 at the TOA in the simulations with fixed SST were
applied in the fully coupled G4sea-salt simulations between 2020 and 2070 in
the three ESMs. These sea salt injections elevate the sea salt mass
concentration within the injection area in all the models compared to the
RCP4.5 scenario (Fig. 6). As mentioned in Sect. 3.1, the injection rate in
GISS-E2-R was 2–3 times higher than in the two other ESMs, which explains
the larger enhancement in mass concentration in GISS-E2-R compared to the
other models. Despite equal sea salt flux increase in all grid cells within
the injection area, there are large spatial variations in the increase in sea
salt concentration in the lowest model layer in all the models. This is due
to differences in precipitation, boundary layer depth, and horizontal and
vertical transport across different regions. In NorESM1-M (Fig. 6a),
comparatively large increases in sea salt concentration occur in the
subtropical high-pressure regions. This is likely a combined effect of low
precipitation, thin boundary layer, and generally little vertical mixing in
these regions compared to regions with more convection. Similar patterns can
be seen in GISS-E2-R (Fig. 6b) and in part in HadGEM2-ES (Fig. 6c).
HadGEM2-ES has further peak increases in sea salt concentrations closer to
the Equator, which could indicate either more efficient aerosol transport
equatorward by trade winds or less efficient wet removal in the ITCZ.
The multi-model mean difference between the G4sea-salt experiment
and RCP4.5 averaged over years 2035–2065. The multi-model mean difference
refers to the mean of all three models, NorESM1-M, GISS-E2, and HadGEM2-ES.
Hatching denotes areas where the models disagree on the sign of the change.
Change in (a) omega-vertical velocity at 500 hPa (positive
values corresponds to reduced upward motion) (centipascal per second),
(b) cloud water path (vertically integrated cloud water content)
(%), and (c) precipitation rate (%).
![]()
Relations between the relative change in cloud optical depth
(τ) due to sea salt injection against the corresponding changes in
re for (a) NorESM1-M and (b) HadGEM2-ES;
CDNC for (c) NorESM1-M and (d) HadGEM2-ES; and
LWP for (e) NorESM1-M and (f) HadGEM2-ES. The
relations represent averages over the period 2035–2065 within the injection
area. Pearson's correlation coefficient (r) is given for each relation.
![]()
One of the advantages of simulating sea spray climate engineering in ESMs
through sea salt aerosol emissions, compared to just increasing the
CDNC, is that the cloud droplet activation process is taken into
account. Previous studies have shown that injection of sea spray particles in
some circumstances may actually reduce the CDNC due to increased
competition for water vapour and reduced activation of background aerosol
particles (Korhonen et al., 2010; Alterskjær et al., 2012).
Alterskjær and Kristjánsson (2013) showed in a single-model study
that while the injection of accumulation-mode particles increased the
CDNC, the injections of Aitken- or coarse-mode particles could have the
opposite effect with a reduction in CDNC. As mentioned in Sect. 2.2,
the injected particles in this study are accumulation-mode particles with
a median dry radius between 0.10 and 0.44 µm. The background
CDNC within the injection area at an altitude of ∼1000 m
averaged over 2035–2065 for RCP4.5 varies for NorESM1-M from
10–20 cm-3 in the remote areas of Pacific and reaches a maximum
of ∼100 cm-3 south of Mexico, west of northern Africa,
south-east of China, and over the northern parts of the Indian Ocean.
HadGEM2-ES has its maxima in CDNC at similar locations within the
injection area. However, HadGEM2-ES has somewhat higher concentrations with
a typical CDNC of 20–40 cm-3 in the remote Pacific Ocean
and CDNC reaching 250 cm-3 at coastal locations closer to
continental sources. GISS-E2-R has higher background CDNC than the
other models, with concentrations of 50–100 cm-3 in the remote
Pacific Ocean and concentrations higher than 1000 cm-3 in some
coastal regions influenced by continental sources. Whereas NorESM1-M and
HadGEM2-ES simulate CDNC close to estimates using MODIS (Moderate
Resolution Imaging Spectroradiometer) data for cloud-top CDNC (e.g.
Wood, 2012), GISS-E2-R predicts higher background CDNC than estimated
from MODIS.
As shown in Fig. 7, the sea salt injection enhances the CDNC in lower
layers within the whole injection area in all three ESMs. The mean percentage
increase in CDNC within the injection area averaged for the period
2035–2065 (only grid cells over ocean included) is 153 % in NorESM1-M,
42 % in GISS-E2-R, and 89 % in HadGEM2-ES (Table 1). The largest
enhancements in CDNC generally occur in regions where the background
CDNC is low. The smaller percentage increase in CDNC in
GISS-E2-R compared to the other two models is likely due to the higher
background CDNC in GISS-E2-R. Over the Arctic region, there is
a relatively large reduction in CDNC in NorESM1-M (Fig. 7a) and
HadGEM2-ES (Fig. 7c). However, the CDNC in the Arctic region is as low
as ∼1 cm-3, which implies that a very small absolute change
in concentration can result in a large relative change in CDNC. The
mechanism for the reduction of CDNC in the Arctic is likely related to
the cooling induced by the sea salt: the cooling increases the sea ice cover
in the Arctic and therefore reduces the source of natural sea salt and
dimethyl sulfide (DMS), both of which cause a reduction in CDNC. The
cooling also reduces the liquid water in the clouds, which may also
contribute to the reduction in CDNC, as this variable represents the
number concentration of cloud liquid water particles in the air.
Mean percentage changes in CDNC, cloud-top effective radius, cloud
water path, cloud cover, cloud optical depth,
precipitation, and surface air temperature (∘C) due to sea spray climate engineering. The changes represent the percentage
difference between G4sea-salt (with climate engineering) and RCP4.5 (without climate engineering) averaged over the period 2035–2065
for the injection area and globally. The change in CDNC represents the change in cloud droplet number concentration within the model
layer below 700 hPa with maximum concentration. Cloud-top effective radius and cloud optical depth could only be diagnosed
for NorESM1-M and HadGEM2-ES. Cloud optical depth has been estimated using Eq. (1) (Stephens, 1978).
NorESM1-M
GISS-E2-R
HadGEM2-ES
Injection
Global
Injection
Global
Injection
Global
area mean
mean
area mean
mean
area mean
mean
CDNC (%)
153
65
28
15
89
36
Cloud-top effective radius (%)
-8.6
-5.5
–
–
-6.4
-3.8
Cloud water path (%)
0.53
-0.11
-1.3
-1.9
-1.3
-1.4
Cloud cover (%)
-2.8
-2.0
0.05
0.11
-0.11
-0.24
Cloud optical depth (%)
10
5.9
–
–
5.7
2.1
Precipitation (%)
-3.7
-2.7
-1.2
-1.1
-2.6
-2.0
Surface temperature (∘C)
-0.68
-0.54
-0.83
-0.62
-0.76
-0.62
Difference in net SW radiation at the TOA between G4sea-salt and
RCP4.5 (a) global mean, (b) clear-sky global mean,
(c) injection area mean, and (d) clear-sky injection area
mean. The colours denote NorESM1-M (blue), GISS-E2-R (red), and HadGEM2-ES
(black). Only grid cells over ocean have been included in the mean values
representative of the injection area.
![]()
Mean change in net SW radiation (Wm-2) at the TOA
between G4sea-salt and RCP4.5 for the period 2035–2065 for
(a) NorESM1-M, (b) GISS-E2-R, and (c) HadGEM2-ES.
Hatching denotes areas where changes are not significant at the 95 %
confidence level (Student t test with respect to variance of annual mean
values).
![]()
As expected, the cloud-top effective droplet radius, re, is
reduced due to the sea salt injection over the whole injection area (Fig. 8a
and c). The mean reductions in re within the injection area are
-8.6 % for NorESM1-M and -6.4 % for HadGEM2-ES (re
could not be diagnosed in GISS-E2-R) (Table 1). Although the change in cloud
water path (vertically integrated cloud water content including both liquid
water and ice) due to the sea spray climate engineering is more than 15 %
locally in all three ESMs (shown as multi-model mean in Fig. 9b), the mean
changes globally and over the injection area are less than 2 % in all
three models (Table 1). Interestingly, there is no correlation between the
change in CDNC and the change in cloud water path within the injection
area for mean values of these variables over years 2035–2065. The Pearson
correlation coefficient r for this relation is 0.09 for NorESM1-M, -0.24
for GISS-E2-R, and -0.09 for HadGEM2-ES. The lack of such a correlation and
the fact that the mean change in cloud water path within the injection area
is small, and even negative in two of the models (Table 1), indicate that the
second aerosol indirect effect is weak (Malavelle et al., 2017). Local
changes in cloud water path within the injection area appear instead to be
linked to changes in the atmospheric circulation. This is seen in the
correlation between the change in cloud water path and the change in
omega-vertical velocity (Fig. 9a; r=-0.70 for NorESM1-M, r=-0.59 for
GISS-E2-R, and r=-0.63 for HadGEM2-ES). The negative r coefficients
here indicate an increasing cloud water path under increasing upward motion
in the atmosphere.
The cloud optical depth (τ) can be estimated from the cloud liquid water
path (LWP) and the cloud droplet effective radius at cloud top
(re) through the following relation (Stephens, 1978):
τ≈32LWPre.
LWP has units of g m-2 and re is in
µm. Note that Table 1 gives the change in cloud water path
including ice, whereas LWP in Eq. (1) only refers to liquid water. As
the estimate of τ using Eq. (1) requires the variable re,
τ could only be estimated for NorESM1-M (Fig. 8b) and HadGEM2-ES
(Fig. 8d). As seen in Fig. 8, the sea salt injection results in an increase
in τ in most regions within the injection area in both ESMs. The mean
increase in τ over the injection area is 10 % for NorESM1-M and
6 % for HadGEM2-ES (Table 1). However, locally τ increases by more
than 20 % in both models. An anti-correlation between the relative change
in τ and the corresponding change in re exists, although
moderate to weak, in the two models (Fig. 10a and b). A negative correlation
coefficient is expected due to the Twomey effect. The correlation between the
relative changes in τ and CDNC is even weaker (Fig. 10c and d).
By far the strongest correlation is the one between the relative changes in
τ and LWP (Fig. 10e and f). Thus, despite the increase in
CDNC due to the sea salt injection, it seems that local changes in
τ are controlled largely by changes in LWP, which in turn are
caused mainly by changes in the atmospheric circulation.
Figure 9 shows the multi-model mean changes in omega-vertical velocity (a),
cloud water path (b), and precipitation (c). In large regions over the
eastern Pacific Ocean, reduced ascent (or increased subsidence) (Fig. 9a) is
accompanied by reductions in cloud water path (Fig. 9b) and precipitation
(Fig. 9c). On the other hand, enhanced ascent over, for example, Africa, northern South America, and in
the South Pacific Convergence Zone coincides with
increased cloud water path and precipitation. These patterns of enhanced
cloud water, precipitation, and atmospheric upward motion over low-latitude
continents combined with reduced cloud water, precipitation, and ascent over
some low-latitude ocean regions have been reported previously by Bala
et al. (2011), Alterskjær et al. (2013), Niemeier et al. (2013), Crook
et al. (2015), and Stjern et al. (2017). This is a result of reduced
absorption of solar radiation over ocean where sea salt concentrations are
elevated while continental regions are left less affected, increasing the
land–sea gradient over the tropics. This induces enhanced convection over
land and thereby increased cloud formation and precipitation and reduced
cloud formation over ocean due to reduced upward motion or increased
subsidence. Furthermore, the increase in upward motion and cloud water
content north-east of Australia, and the reduction in these variables over
the eastern Pacific Ocean west of South America, indicate a strengthening of
the Pacific Walker cell and South Pacific Convergence Zone.
In summary, the aerosol indirect effect of the injected sea salt particles
can be seen in the mean increase in CDNC, mean decrease in cloud-top
effective droplet radius, and mean increase in cloud optical depth over the
injection area. However, in these fully coupled simulations the aerosol
direct and indirect effects of the injected sea salt particles also cause
changes in the atmospheric circulation that generate a redistribution of
cloud water, with increasing cloud water and precipitation in regions of
enhanced atmospheric ascent and decreasing cloud water and precipitation in
regions of decreased atmospheric upward motion. Within the injection area,
the local response in cloud optical depth is controlled to a larger extent by
these changes in cloud water than by changes in CDNC or
re. This means that it is not necessarily the regions that are
exposed to the largest aerosol indirect effect of the injected particles that
are exposed to the largest enhancement in cloud albedo.
Change in net SW radiation at the TOA
The global-mean difference in net SW radiation at the TOA (Fig. 11a) between
G4sea-salt and RCP4.5 is rather constant at -2.0 Wm-2
throughout the 50 years of sea spray climate engineering in NorESM1-M and
GISS-E2-R, and hence similar in magnitude to the global-mean ERF by the sea salt
injection. Thus, in these two ESMs a constant sea salt injection in time
increases the planetary albedo by a factor that is roughly constant in
time, despite slow feedbacks being included in these fully coupled
simulations. In HadGEM2-ES, the difference in net SW radiation at the TOA
between G4sea-salt and RCP4.5 is increasing somewhat during the 50 years of
sea spray climate engineering, which means that a constant sea salt injection
rate in HadGEM2-ES generates a slowly increasing planetary albedo. Positive
cloud feedback should be contributing to this in HadGEM2-ES, which will act
to increase the radiative effect of climate engineering over time, in
contrast to the negative cloud feedback in NorESM1-M (Andrews et al., 2012).
However, there is also some indication of an increasing difference in net SW
radiation between G4sea-salt and RCP4.5 over time in HadGEM2-ES for the
clear-sky fluxes (Fig. 11b), indicating a contribution from the sea ice
albedo feedback. The reduction in net SW radiation at the TOA over the Arctic
region, caused by the sea spray climate engineering, is larger in HadGEM2-ES
(Fig. 12c) than in the two other ESMs (Fig. 12a and b), which indicates that
the sea ice albedo feedback is strongest in HadGEM2-ES. HadGEM2-ES also has
a larger reduction in surface temperature than the other two models for the
Arctic region (not shown). However, reductions in global-mean surface
temperature are very similar in the three models (Table 1).
Whereas the global-mean changes in net SW radiation at the TOA shown in
Fig. 11a and b are to some extent influenced by changes in surface albedo,
the corresponding changes over the injection area over ocean between
30∘ N and 30∘ S are only due to atmospheric changes
(Fig. 11c and d). As expected, the reductions in net SW radiation are on
average larger between 30∘ N and 30∘ S, where the sea salt
injection occurs, than globally. The total change in net SW radiation over
the injection area (Fig. 11c) is rather constant with time in NorESM1-M and
GISS-E2-R, similar to the global-mean curves in Fig. 11a, but slowly
increasing with time in HadGEM2-ES. The change in clear-sky net SW radiation
over the injection area (Fig. 11d) is rather constant with time in all three
ESMs. Similar to the ERF in Fig. 3, the change in clear-sky net SW radiation
over the injection area is almost equal to the total change in net SW
radiation in the three ESMs, again indicating a large potential of the
aerosol direct effect in regions of low cloudiness. In GISS-E2-R and
NorESM1-M, the change in net SW radiation is even larger in clear-sky
conditions than in total.