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DOI 10.1007/s00382-014-2240-3Clim Dyn

Modeling of solar radiation management: a comparison of simulations using reduced solar constant and stratospheric sulphate aerosols

Sirisha Kalidindi · Govindasamy Bala · Angshuman Modak · Ken Caldeira

Received: 24 January 2014 / Accepted: 2 July 2014 © Springer-Verlag Berlin Heidelberg 2014

(~3 %). Based on our results we conclude that the climate states produced by a reduction in solar constant and addi-tion of aerosols into the stratosphere can be considered almost similar except for two important aspects: strato-spheric temperature change and the consequent implica-tions for the dynamics and the chemistry of the stratosphere and the partitioning of direct versus diffuse radiation reach-ing the surface. Further, the likely dependence of global hydrological cycle response on aerosol particle size and the latitudinal and height distribution of aerosols is discussed.

Keywords Geoengineering · Sulphate aerosols · Stratospheric warming · Diffuse radiation · GPP

1 Introduction

Global anthropogenic carbon dioxide emissions from fos-sil fuel burning have been accelerating in recent decades (IPCC 2013) and the efforts to mitigate these increasing emissions are proving to be challenging. This has led to an interest in geoengineering (Crutzen 2006) to counteract climate change. Geoengineering is defined as a large scale intentional manipulation of the environment particularly intended to reduce the undesired impacts of climate change caused by the increasing greenhouse gases (Keith 2000). There are two main categories of geoengineering methods: Solar Radiation Management (SRM) and Carbon Dioxide Removal methods (CDR) (The Royal Society 2009). While SRM would counteract the warming caused by green-house gases by reducing the incoming solar radiation or by increasing the planetary albedo, CDR methods propose to accelerate the removal of CO2 from the atmosphere and hence would directly deal with the root cause of the global warming problem.

Abstract The climatic effects of Solar Radiation Man-agement (SRM) geoengineering have been often modeled by simply reducing the solar constant. This is most likely valid only for space sunshades and not for atmosphere and surface based SRM methods. In this study, a global climate model is used to evaluate the differences in the climate response to SRM by uniform solar constant reduction and stratospheric aerosols. Our analysis shows that when global mean warming from a doubling of CO2 is nearly cancelled by both these methods, they are similar when important surface and tropospheric climate variables are considered. However, a difference of 1 K in the global mean strato-spheric (61–9.8 hPa) temperature is simulated between the two SRM methods. Further, while the global mean surface diffuse radiation increases by ~23 % and direct radiation decreases by about 9 % in the case of sulphate aerosol SRM method, both direct and diffuse radiation decrease by similar fractional amounts (~1.0 %) when solar constant is reduced. When CO2 fertilization effects from elevated CO2 concentration levels are removed, the contribution from shaded leaves to gross primary productivity (GPP) increases by 1.8 % in aerosol SRM because of increased diffuse light. However, this increase is almost offset by a 15.2 % decline in sunlit contribution due to reduced direct light. Overall both the SRM simulations show simi-lar decrease in GPP (~8 %) and net primary productivity

S. Kalidindi (*) · G. Bala · A. Modak Divecha Centre for Climate Change and Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bangalore 560 012, Indiae-mail: sirishakalidindi@caos.iisc.ernet.in

K. Caldeira Department of Global Ecology, Carnegie Institution, 260 Panama Street, Stanford, CA 94305, USA

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Though there are many methods under the SRM cat-egory, stratospheric aerosol injection and space-based SRM (solar constant reduction) have been extensively studied using climate models. Several modeling studies (Govin-dasamy and Caldeira 2000; Govindasamy et al. 2002, 2003; Matthews and Caldeira 2007; Bala et al. 2008; Caldeira and Wood 2008; Schmidt et al. 2012; Kravitz et al. 2013) investigated the response to SRM schemes by reducing the solar constant to offset the warming due to doubled CO2. In these studies, mitigation of the global mean temperature to its preindustrial level was achieved. However, a resid-ual cooling in the tropics and warming in polar- regions, a reduction in seasonal amplitude of temperature, and a reduced intensity of hydrological cycle were simulated. A recent multi-model study (Tilmes et al. 2013) on geoen-gineering using GeoMIP (Kravitz et al. 2011) simulations finds an increase in heavy precipitation events in the case of quadrupling of CO2 especially over the Asian monsoonal regions but a decrease in the SRM case.

SRM by injecting sulphate aerosols into stratosphere was suggested as early as in 1974 by Budkyo (1974). Later in 2006, Crutzen (2006) suggested research into this method since CO2 emission reductions are not taking place. Modeling studies such as Rasch et al. (2008a); Rob-ock et al. (2008); Jones et al. (2011) have investigated the effect of injecting sulphate aerosols into the stratosphere to counteract the warming caused by greenhouse gases. Rasch et al. (2008a) showed that smaller aerosol particles repre-sentative of background aerosols in the stratosphere are more effective in counteracting the warming from 2xCO2 compared to larger volcanic size particles as smaller par-ticles have larger single scattering albedo and also longer residence time. Robock et al. (2008) find that tropical SO2 injection can mitigate the surface temperature change with slightly more cooling over the continents while Arctic injection would result in cooling even over those regions which are beyond the Arctic. Tilmes et al. (2009), Ammann et al. (2010), Ferraro et al. (2011) and Heckendorn et al. (2009) demonstrate that SRM geoengineering using strato-spheric aerosols would result in stratospheric temperature change, increase in the stratospheric water vapor content and delay in the recovery of the ozone layer in the middle and higher latitudes.

SRM by sulphate aerosols and solar constant reduction have two major differences. First, aerosols in the strato-sphere cause a warming due to the absorption of the near infrared solar radiation and terrestrial radiation (Tilmes et al. 2009; Jones et al. 2011; Ferraro et al. 2011, 2014; Heckendorn et al. 2009) while solar constant reduction causes a cooling by reducing absorption of solar radia-tion in the stratosphere (Govindasamy and Caldeira 2000; Ammann et al. 2010). Second, a reduction in solar constant should cause uniform reduction in both diffuse and direct

sunlight reaching the surface while stratospheric aerosols should lead to an enhancement in diffuse light and reduc-tion in direct light. Several recent studies (Roderick et al. 2001; Gu et al. 2002, 2003; Knohl and Baldocchi 2008; Matsui et al. 2008; Mercado et al. 2009; Kanniah et al. 2011) have investigated the sensitivity of vegetation to changes in direct and diffuse radiation due to clouds and atmospheric particles. These studies suggest that the dif-fuse radiation is more advantageous than direct radiation for plant productivity as the plant canopy is more evenly illuminated under diffuse light conditions. Therefore, an increase in diffuse radiation could increase the canopy photosynthesis especially for plant canopies with high leaf area index (LAI) by redistributing the radiation load from saturated sunlit leaves to the non-saturated shaded leaves. Hence, SRM by aerosol injection could potentially increase plant productivity on land (Pongratz et al. 2012). However, reduction of total incoming solar radiation could decrease terrestrial CO2 sinks as well. To our knowledge, no model-ling study on SRM has investigated the response of vegeta-tion due to diffuse and direct changes in detail.

In spite of more than a decade of modeling research in SRM methods only few studies have compared differ-ent SRM techniques. Ammann et al. (2010) compared the climate response due to two SRM techniques (top of the atmosphere (TOA) solar irradiance reduction and sulphate aerosol SRM) using a coupled Atmosphere–Ocean General Circulation Model. In their study, the two SRM simulations were designed so that the global mean temperature change in SRES A2 scenario was brought to the reference climate state level (2000 stabilization scenario or IPCC Commit-ment scenario). While the global mean temperature change in both the cases was mitigated, there was a major differ-ence between the two SRM methods in the stratosphere where a temperature increase up to 3 K in the aerosol layer was simulated in the case of sulphate aerosol SRM. Hence, it was cautioned that the heating of the aerosol layer could lead to an enhanced flow of moisture across the tropical tropopause and may delay the ozone recovery. Further, it was shown that the heating due to the aerosol layer in sul-phate aerosol SRM leads to an enhanced horizontal temper-ature gradient between the mid and high latitudes resulting in an enhanced zonal flow in the lower stratosphere and the upper troposphere. However, no such response was seen in the case of solar irradiance reduction.

Jones et al. (2011) compared the climate impacts due to sulphate aerosol injection and from increased reflectiv-ity of marine stratocumulus clouds. For near cancellation of global mean temperature changes, they found significant differences in the regional climate between the two cases. The changes in the regional climate were attributed to the location and the degree of inhomogeneity of the radiative flux perturbations produced by each SRM method. The

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global mean radiative forcing from sulphate aerosol SRM was found to be 25 % greater than that from marine cloud brightening due to different geographical distributions of the two SRM techniques. The radiative forcing from sul-phate aerosol SRM was more uniformly distributed across the globe while for the cloud brightening technique it was concentrated mainly in the areas of marine stratocumu-lus. The surface temperature response was also found to be different for both the methods with a more heterogene-ous cooling seen in the case of marine cloud brightening. Though global mean precipitation response was found to be similar for both the SRM methods, significant differences were simulated for land precipitation and consequently for the net primary productivity (NPP).

A recent study (Niemeier et al. 2013) compared climate response to three different SRM techniques using transient simulations: sunshade, stratospheric aerosol and sea-salt SRM. In this study, the SRM simulations were designed such that the TOA net radiative fluxes were kept close to a reference climate (at the 2020 level). This is unlike other studies where the global mean temperature in SRM simulations is kept close to a Control simulation. Keep-ing the TOA net fluxes close to the reference climate does not constrain the global mean surface temperature changes to be the same which could influence hydrologi-cal cycle response. The main focus of this study was to investigate to what extent the response of global mean precipitation depends on the specific type of SRM tech-nique. Hydrological sensitivity (% change in global mean precipitation per unit change in global mean temperature) is reduced by all SRM methods but more by the aerosol based techniques (both stratospheric aerosols and sea-salt SRM). The larger reduction in aerosol based schemes was explained based on the surface energy budget: absorp-tion of longwave (LW) radiation by the aerosols adds to greenhouse effect which implies a larger reduction in the net shortwave (SW) surface fluxes since TOA fluxes were constrained to be close to year 2020 level in all the cases. The larger decrease in net shortwave surface flux results in larger decrease of latent heat flux and thus precipitation. The height and regional distribution of the applied aero-sols also could affect the climate response (Niemeier et al. 2013). The lower the height of the applied aerosols the larger is the decrease in precipitation because as the height of the applied aerosols decreases only a smaller fraction of the absorbed longwave energy by aerosols is radiated to space (Hansen et al. 1997) which necessitates a larger reduction in net shortwave fluxes at the surface (since the TOA net fluxes are fixed) leading to larger reduction in precipitation (Bala et al. 2008). Further, an increase in precipitation over land in contrast to a decrease over the oceans is simulated in the case of sea-salt SRM (Niemeier et al. 2013). This is because the negative solar radiative

forcing in sea—salt SRM is localized over the ocean areas only resulting in a monsoonal circulation with descending motion over the oceans and ascending motion over land leading to an increased precipitation over land (Bala et al. 2010).

Fyfe et al. (2013) simulated larger precipitation reduc-tions over oceans but smaller reduction over land in aero-sol SRM compared to sunshade SRM using equilibrium climate simulations where global mean surface tempera-ture changes were nearly cancelled. The larger decrease in precipitation over oceans in the aerosol case in this study is attributed to a decrease in available energy for evapora-tion at the surface (Fyfe et al. 2013): The longwave absorp-tion and downward emission by the aerosols in the aerosol SRM requires a larger reduction of incoming solar radia-tion to offset the same amount of CO2 forcing compared to sunshade SRM. The greater reduction of incoming radia-tion in aerosol SRM translates into a greater reduction in the net radiation at the surface and precipitation. The differ-ences in global mean precipitation responses, if any, are not reported in this study. However, it can be inferred from the global land and ocean mean values reported by Fyfe et al. (2013) that the global precipitation response shows larger reduction in case of aerosol SRM (−2.4 %) compared to Sunshade SRM (−1.7 %).

Ferraro et al. (2014) also compared the impacts of space sunshades (solar constant reduction) and sulphate aerosol SRM. The two SRM techniques were designed to mitigate the surface warming from a quadrupling of CO2. How-ever, the tropical mean precipitation reduction in the aer-osol SRM was almost twice relative to the solar constant reduction case. This is because while the solar irradiance was reduced uniformly around the globe in the sunshade SRM case, aerosol concentration was maximized at the equator around 50 hPa (20 km) in the aerosol SRM case. Further, the downward longwave emission from the added aerosols enhanced the precipitation suppression associated with the fast response due to CO2 forcing (Bala et al. 2009; Andrews et al. 2009; Fyfe et al. 2013). Similar weakening of the hydrological cycle when aerosols were maximized in the tropics has been also simulated by Modak and Bala (2013).

In this paper, we perform controlled climate model experiments where the global mean surface temperature change due to a doubling of CO2 is cancelled by both a reduction in solar constant and an increase in the load-ing of stratospheric SO4 aerosol. Unlike the earlier studies (Ferraro et al. 2014; Niemeier et al. 2013; Fyfe et al. 2013) which mainly investigated the effects of SRM techniques on global mean precipitation, the present study makes a detailed comparison of stratospheric climate change, dif-fuse and direct radiation changes and their effect on terres-trial vegetation.

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2 Model details and simulations

2.1 Model

We used an atmospheric general circulation model; Com-munity Atmosphere Model version 4 (CAM 4) developed by the National Center for Atmospheric Research (NCAR) (Collins et al. 2004) coupled to the land model CLM 4 (Community Land Model version 4) and a slab ocean model (SOM) with a thermodynamic sea ice model. The model horizontal resolution is 1.9° latitude and 2.5° lon-gitude with 26 vertical layers. It uses finite volume (FV) solution for atmospheric dynamics. The model’s vertical coordinate is a hybrid sigma-pressure system with upper levels in pressure co-ordinates and the lower levels in sigma. In the model, six types of aerosols are treated: sul-phate from natural and anthropogenic sources, sea-salt, soil dust, black and organic carbon. The background sulphate aerosol amount in this version of the model is 1.38 Mt SO4. Additional sulphate aerosols are added for countering cli-mate change in our experiments. The aerosol mass is pre-scribed and the aerosols are not transported around. The dry median radius, effective radius and standard deviation of the aerosol particle are of 0.05, 0.17 µm and 2.0, respec-tively. These size characteristics are similar to the “smaller” aerosol particles that are representative of background aer-osols in the stratosphere (Rasch et al. 2008b). When aero-sol precursor such as SO2 is injected into the stratosphere as envisioned in potential implementation, it would be oxi-dized to form H2SO4 aerosols. However, we have used the model’s default background aerosols (NH4)2SO4 (Ammo-nium Sulphate) as the additional prescribed aerosol in our simulations. While there could be some differences in the hygroscopic growth between (NH4)2SO4 and H2SO4, the

optical properties of (NH4)2SO4 are very similar to those of H2SO4 (Kiehl et al. 2000). In the model the optical proper-ties of (NH4)2SO4 are calculated assuming a constant rela-tive humidity (80 %). The aerosol indirect effects such as increase in cloud albedo and life time are not modeled and the aerosol loadings for species other than sulphates are same for all the simulations.

2.2 Experiments

The climate response to the two different SRM methods is compared using a set of four simulations: (a) “Control” with a CO2 concentration of 390 ppm and a solar con-stant of 1,367 W m−2, (b) “2xCO2” with doubled atmos-pheric CO2 concentration (780 ppm), and a solar constant of 1,367 W m−2, (c) “GeoSolar” with doubled atmos-pheric CO2 concentration and the solar constant reduced by 2.25 %, (d) “GeoSulphate” with doubled atmospheric CO2 concentration and an additional mass of 20 Mt sul-phate aerosols. The sulphate aerosols are prescribed in five layers in the stratosphere at the height of 15–30 km (61–9.8 hPa) with a maximum concentration at about 25 km (30 hPa) (Fig. 1). For comparison, we note that Fyfe et al. (2013) specified aerosols in a 10 km thick layer above the tropopause and Niemeier et al. (2013) injected SO2 at a height of 60 hPa. Ferraro et al. (2014) prescribed aerosols between 200 and 20 hPa with a maximum concentration at around 50 hPa. The additional amount of sulphate aerosols and the percentage reduction of solar constant are chosen so that near-zero global mean surface temperature change between the geoengineering simulations and Control case are simulated.

Each of the above simulation is performed with two con-figurations: (1) The Fixed SST (sea surface temperature)

Fig. 1 Vertical profile of sulphate aerosol concentra-tion in µg Kg−1 used in the model. a Background aerosol concentration in the model (Control). b Prescribed aerosol concentration after uniformly adding additional total amount of 20 Mt of sulphate aerosol to the background aerosol in five layers in the stratosphere (61–9.8 hPa) with a maximum at 22 km (30 hPa) (GeoSul-phate). The dotted line shows the tropopause in the model

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simulations are run for 60 years and the last 30 years were used to calculate the radiative forcing which is measured as the net radiative flux change at the top of the atmos-phere (Hansen et al. 1997). This is also referred as “Radia-tive Flux Perturbation” (Haywood et al. 2009), and (2) Slab Ocean simulations are run for 100 years and the last 50 years are used to study climate change. The SOM simu-lations take approximately 25 years to reach near equilib-rium climate state.

3 Results

3.1 Global and annual mean climate

Global mean changes in GeoSulphate and GeoSolar simu-lations relative to Control climate are listed in Table 1. The global mean surface temperature increases by 3.23 K and precipitation increases by 0.18 mm day−1 (6 %) in the dou-bled CO2 world. The changes are large and significant all over the globe in agreement with several previous studies (e.g. Bala et al. 2009; Modak and Bala 2013; Rasch et al. 2008b) as shown in Fig. 2. We find a near cancellation of global mean surface temperature change (within ± 0.1 K) in both the geoengineering simulations (Table 1). However, there is residual warming in the high latitudes and cooling in the tropical regions (Fig. 2) (Govindasamy and Calde-ira 2000; Schmidt et al. 2012; Kravitz et al. 2013). This is due to a positive radiative forcing in the high latitudes and

negative radiative forcing in the low latitudes in the geoen-gineering simulations (Fig. 3): while radiative forcing due to CO2 is spatially nearly uniform, solar forcing has large spatial variations with large magnitudes in the low lati-tudes and smaller magnitude in the high latitudes and hence a combination of these two radiative forcings (a doubling of CO2 and a reduction in solar radiation) has a pattern as shown in Fig. 3 (centre and the right panels).

There is a decline in global mean precipitation in both SRM methods which is in agreement with previous stud-ies (Bala et al. 2008; Caldeira and Wood 2008; Matthews and Caldeira 2007; Rasch et al. 2008a; Lunt et al. 2008; Robock et al. 2008; Schmidt et al. 2012) with maximum changes simulated over the tropical regions where pre-cipitation decreases by about 1.0 mm day−1 compared to the Control climate (Fig. 2). We find that the decrease in precipitation is slightly more for GeoSulphate compared to GeoSolar over land while over ocean the precipitation decrease is slightly more for solar constant reduction case compared to aerosol SRM (Fig. 4). The larger decrease in precipitation over land in aerosol SRM is likely associated with a larger decline in net surface SW flux (Fig. 5). As dis-cussed in Sect. 3.3, this larger decline in net surface SW flux in aerosol SRM case is due to large reduction in direct surface solar radiation which dominates a small increase in diffuse radiation. However, the precipitation changes over both land and ocean (Fig. 4) between the two SRM cases are not significant because the changes are within the range of standard deviation (shown as error bars) from the

Table 1 Global-annual means of key climate variables in Control simulation, the residual changes in global means in Geoengineering simula-tions relative to the Control case and the difference between them

NRMSD refers to spatial root mean square error between the two SRM simulations normalized by two standard deviations (95 % confidence level) in the Control case. Uncertainties are given by the standard errors computed from 50 annual means for the Control case (Column 2) and computed from 50 annual mean differences for global mean changes. Percentage changes are given in parenthesis

Variables Control GeoSolar minus Control

GeoSulphate minus Control

GeoSulphate minus GeoSolar

Spatial NRMSD

Radiative forcing (W m−2) – −0.5 ± 0.15 −0.3 ± 0.14 0.2 ± 0.14 0.35

Surface temperature (K) 289.22 ± 0.03 −0.04 ± 0.02 0.08 ± 0.02 0.1 ± 0.02 0.46

Precipitation (mm d−1) 2.95 ± 0.001 −0.04 ± 0.005 (−1.3 %) −0.03 ± 0.005 (−1.2 %) 0.005 ± 0.004 (0.1 %) 0.63

Evaporation (mm d−1) 3.02 ± 0.001 −0.03 ± 0.01 (−1.4 %) −0.04 ± 0.01 (−1.2 %) 0.005 ± 0.004 (0.2 %) 0.53

Precipitable water (kg m−2) 27.8 ± 0.03 −0.17 ± 0.04 (−1.9 %) −0.5 ± 0.04 (−0.7 %) 0.3 ± 0.05 (1.3 %) 0.58

Low clouds fraction 0.35 ± 0.0003 −0.005 ± 0.01 (−1.6 %) −0.005 ± 0.01 (−1.3 %) 0.001 ± 0.0006 (0.3 %) 0.6

High clouds fraction 0.32 ± 0.0003 0.003 ± 0.01 (1.4 %) 0.005 ± 0.01 (0.9 %) −0.001 ± 0.0004 (−0.5 %) 0.6

Total clouds fraction 0.54 ± 0.0003 −0.003 ± 0.001 (−0.5 %) −0.003 ± 0.001 (−0.5 %) −0.0002 ± 0.0006 (−0.03 %) 0.64

Sea ice extent (million Sq km) 20.59 ± 0.05 −0.21 ± 0.02 (−1.2 %) −0.62 ± 0.02 (−3.7 %) −0.41 ± 0.01 (−2.5 %) 0.65

Stratospheric temperature (K) (61–9.8 hPa)

215.62 ± 0.01 −3.1 ± 0.01 −2.1 ± 0.01 1.0 ± 0.02 0.76

Surface diffuse solar radiation (W m−2)

43.84 ± 0.08 −0.6 ± 0.10 (−1.3 %) 10.02 ± 0.11 (22.9 %) 10.59 ± 0.12 (10.6 %) 1.38

Surface direct solar radiation (W m−2)

142.88 ± 0.43 −1.73 ± 0.34 (−1.2 %) −12.85 ± 0.33 (−9.0 %) −11.11 ± 0.32 (−11 %) 0.86

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Fig. 2 Changes in annual-mean surface temperature (left panels) and precipitation (right panels) in the 2xCO2, GeoSolar and GeoSulphate simulations relative to the Control (1xCO2) climate. Hatching indicates the region where the changes are significant at 99 % level. Signif-icance level was estimated using Student’s t test with a sample of 50 annual means and standard error corrected for autocorrela-tion (Zwiers and von Storch 1995). Both surface temperature and precipitation changes are large and significant every-where in the 2xCO2 scenario. Although significant over large regions, both temperature and precipitation changes are small in both the geoengineering simulations

Fig. 3 Radiative forcing (net radiative flux change at the top of the atmosphere) when a CO2 is doubled, b CO2 is doubled and solar con-stant is reduced by 2.25 % and c CO2 is doubled and stratospheric total sulphate aerosol is increased by 20 Mt. Hatching indicates the regions where the changes are significant at a level of 99 %. Signifi-

cance level is estimated by using a Student’s t test with a sample of 40 annual mean values and standard error corrected for autocorrela-tion (Zwiers and von Storch 1995). Equatorial regions show a nega-tive residual forcing while polar-regions show positive forcing in b and c

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Control case. Therefore, we conclude that the global mean changes in precipitation and net surface radiation are simi-lar for both the SRM techniques in our study unlike some earlier studies (Fyfe et al. 2013; Ferraro et al. 2014) where larger declines in precipitation in aerosols SRM than in solar constant reduction case were simulated. The differ-ences in precipitation responses between our study and previous studies are likely associated with the differences in the size of prescribed aerosol particles, their latitude and altitude distribution. Further discussion is given in the last section.

The root mean square difference normalized by the standard deviation of the Control case (NRMSD) (Ricke et al. 2010; Kravitz et al. 2013) is calculated for key cli-matic variables between the GeoSulphate and GeoSolar simulations (Table 1). Values above two for this quantity indicate that the differences between the SRM simulations can be distinguished against the interannual variability at 95 % confidence level. We find that NRMSD for most of the climate variables is very small indicating that both the geoengineering simulations have similar climatic effects. However comparatively large values are seen for variables such as stratospheric temperature change and surface dif-fuse and direct radiation. Therefore, in the following sec-tions we discuss them in detail.

3.2 Stratospheric warming

One of the important responses discussed in the past stud-ies involving stratospheric sulphate aerosols is the strato-spheric warming (Tilmes et al. 2009; Ammann et al. 2010; Ferraro et al. 2011). Sulphate aerosols cool the surface and troposphere by reflecting incoming solar radiation but they cause stratospheric warming by absorbing a portion of the incoming near infrared solar radiation and also terrestrial radiation. In this study, we observe a warming of 1 K in the stratospheric temperature for GeoSulphate simulation com-pared to GeoSolar (Table 1). Geoengineering the climate with SRM results in an overall cooling of the stratosphere due to doubled CO2 and reduced amount of solar insola-tion which is seen in both the geoengineering simulations (Fig. 6a, b). This cooling is less in the GeoSulphate case compared to GeoSolar simulation due to the presence of

Fig. 4 Annual mean precipitation changes (%) in GeoSolar and Geo-Sulphate simulations for global, land and ocean relative to the Con-trol simulation. Error bars show the standard deviation from the Con-trol case calculated with a sample of 50 annual means

Fig. 5 Annual mean surface energy flux changes (W m−2) in GeoSolar and GeoSulphate simulations for global, land and ocean relative to the Control simulation. Error bars show the standard deviation from the Control case calculated with a sample of 50 annual means

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additional sulphate aerosols which absorb infrared radia-tion. This cooling effect in the stratosphere from CO2 increase can be removed by calculating the temperature difference between the geoengineering simulations and the 2xCO2 (Fig. 6c, d). In the GeoSulphate simulation, we observe a mean warming of 0.3 K in the stratosphere (61–9.8 hPa; 15–30 km) (Fig. 6d). In GeoSolar simulation, due to reduction of incoming solar radiation by 2.25 % a net cooling of 0.5 K is simulated (Fig. 6c).

As discussed above, the presence of the aerosol layer in the stratosphere in the GeoSulphate simulation results in the heating of the tropical tropopause region around 90 hPa (Fig. 6b) which is absent in the case of GeoSolar simulation. This warming leads to an increase of strato-spheric water vapor in the GeoSulphate case relative to the GeoSolar case (Fig. 7, centre and right panels) due to an increase in saturation mixing ratio of water vapor and hence increased transport of water vapor from tropo-sphere to the stratosphere (Davidoff Daniel et al. 1999). This increase of stratospheric water vapor can inten-sify the HOx catalyzed ozone destruction cycles leading to a decrease in the ozone concentrations in the lower and the upper stratosphere (Solomon 1999; Ammann

et al. 2010). Further, the increase in the stratospheric water vapor along with the cooling of the stratosphere could enhance the formation of polar stratospheric clouds resulting in the depletion of the ozone in the polar region. Unlike GeoSulphate, in the case of Geo-Solar simulation we find a decrease of 5.5 % in strato-spheric water vapor. The absence of ozone chemistry in our model limits further investigation of potential ozone destruction.

The warming of the stratosphere due to the presence of sulphate aerosols in the case of sulphate aerosol SRM results in an increased pole ward temperature gradient compared to Control climate because of differential heating in the meridional direction in the lower stratosphere. The stronger tropical heating is due to relatively larger absorp-tion of the near infrared shortwave flux by the sulphate aer-osols (Tilmes et al. 2009) since solar irradiance is stronger in the tropics. In association with this enhanced meridional temperature gradient, an enhanced westerly jet is simulated in the lower stratosphere and the upper troposphere (Fig. 8) as in Ammann et al. (2010). However, such an enhance-ment of the jet is not simulated in the case of solar constant reduction case.

Fig. 6 Zonal averaged tempera-ture difference for GeoSolar (left panels) and GeoSulphate (right panels) simulations rela-tive to Control (a, b) and 2xCO2 (c, d). Hatching indicates the region where the changes are significant at 99 % level. Significance level was estimated using Student’s t test with a sample of 50 annual means and standard error corrected for autocorrelation (Zwiers and von Storch 1995). A mean warming of 0.3 K (61–9.8 hPa) in Geo-Sulphate and a cooling of 0.5 K in GeoSolar simulations relative to 2xCO2 are simulated

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Fig. 7 Vertical profile of specific humidity changes for GeoSolar and GeoSulphate rela-tive to the Control in mg Kg−1 (120 to 3 hPa) (left panel), percentage changes in specific humidity (centre panel) and temperature change in K (right panel)

Fig. 8 Vertical profile of changes in zonal wind in m s−1 for DJF (top panels) and JJA (bottom panels) (120 to 3 hPa) for GeoSolar (left panels) and GeoSulphate (right panels) simulations relative to the Con-trol case. Hatching indicates the region where the changes are significant at 99 % level. Significance level was estimated using Student’s t test with a sample of 50 annual means and standard error corrected for autocorrelation (Zwiers and von Storch 1995)

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Geo

Sulp

hate

m

inus

Con

trol

Geo

Sola

r

min

us 2

xCO

2

Geo

Sulp

hate

m

inus

2xC

O2

Geo

Sulp

hate

m

inus

Geo

Sola

r

Surf

ace

dire

ct r

adia

tion

(W m

−2 )

142.

88 ±

0.4

3−

1.73

± 0

.34

(−1.

2 %

)−

12.8

5 ±

0.3

3 (−

9.0

%)

−1.

12 ±

0.3

4 (−

0.8

%)

−12

.24

± 0

.39

(−8.

6 %

)−

11.1

1 ±

0.3

2 (−

11 %

)

Surf

ace

diff

use

radi

atio

n (W

m−

2 )43

.84

± 0

.08

−0.

6 ±

0.1

0 (−

1.3

%)

10.0

2 ±

0.1

1 (2

2.9

%)

−0.

59 ±

0.1

2 (1

.4 %

)11

.18

± 0

.18

(26.

2 %

)10

.59

± 0

.12

(10.

6 %

)

Sunl

it gr

oss

prim

ary

prod

uctiv

ity

(Gt-

C y

ear−

1 )77

.16

± 0

.27

14.5

3 ±

0.5

2 (1

8.8

%)

7.61

± 0

.39

(9.8

%)

−8.

24 ±

0.4

2 (−

8.2

%)

−15

.17

± 0

.50

(−15

.2 %

)−

6.93

± 0

.29

(−7.

5 %

)

Shad

ed g

ross

pri

mar

y pr

oduc

tivity

(G

t-C

yea

r−1 )

64.7

2 ±

0.2

23.

91 ±

0.1

8 (6

.0 %

)10

.58

± 0

.26

(16.

3 %

)−

5.29

± 0

.22

(−7.

2 %

)1.

37 ±

0.2

9 (1

.8 %

)6.

67 ±

0.2

4 (9

.7 %

)

Gro

ss p

rim

ary

prod

uctiv

ity

(Gt-

C y

ear−

1 )14

1.88

± 0

.48

18.4

4 ±

0.5

7 (1

2.9

%)

18.1

8 ±

0.6

2 (1

2.8

%)

−13

.54

± 0

.55

(−7.

8 %

)−

13.7

9 ±

0.5

6 (−

7.9

%)

−0.

26 ±

0.3

9 (−

0.16

%)

Aut

otro

phic

res

pira

tion

(G

t-C

yea

r−1 )

93.9

3 ±

0.2

413

.35

± 0

.30

(14.

2 %

)13

.08

± 0

.35

(13.

9 %

)−

11.8

7 ±

0.3

8 (−

9.9

%)

−12

.14

± 0

.38

(−10

.1 %

)−

0.26

± 0

.22

(−0.

24 %

)

Net

Pri

mar

y pr

oduc

tivity

(G

t-C

yea

r−1 )

47.9

5 ±

0.2

65.

09 ±

0.3

3 (1

0.6

%)

5.10

± 0

.34

(10.

6 %

)−

1.66

± 0

.37

(−3.

0 %

)−

1.65

± 0

.35

(−3.

0 %

)0.

01 ±

0.1

9 (0

.02

%)

Het

erot

roph

ic r

espi

ratio

n

(Gt-

C y

ear−

1 )44

.97

± 0

.05

4.18

± 0

.19

(9.3

%)

4.07

± 0

.19

(9.0

%)

−1.

75 ±

0.2

3 (−

3.4

%)

−1.

87 ±

0.2

2 (−

3.7

%)

−0.

11 ±

0.1

4 (−

0.2

%)

Soil

carb

on (

Gt-

C)

552.

51 ±

0.0

613

.63

± 0

.49

(2.5

%)

15.2

9 ±

0.5

2 (2

.8 %

)26

.06

± 0

.57

(4.8

%)

27.7

2 ±

0.6

0 (5

.1 %

)1.

66 ±

0.0

5 (0

.3 %

)

Tota

l veg

etat

ion

carb

on (

Gt-

C)

759.

77 ±

0.2

713

3.39

± 1

.72

(17.

5 %

)12

4.28

± 1

.51

(16.

3 %

)4.

61 ±

0.7

1 (0

.5 %

)−

4.49

± 0

.61

(−0.

5 %

)−

9.1

± 0

.31

(−1.

0 %

)

Modeling of solar radiation management

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3.3 Effect of aerosols on diffuse radiation

Aerosols used in the stratospheric SRM not only reduce the total amount of solar radiation reaching the surface but also alter the fraction of diffuse/direct components. This was observed after the Mount Pinatubo eruption when large amounts of sulphate aerosols were injected into the atmosphere which interacted with incoming radiation resulting in an increase in the diffuse component of inci-dent radiation (Gu et al. 2003; Roderick et al. 2001). In order to study the effect of aerosols on diffuse radiation, we calculate the change in the surface incident solar radia-tion (direct and diffuse) in visible and near infrared for both the geoengineering simulations. We find a net decrease of 1.3 % (−0.6 W m−2) and 1.2 % (−1.7 W m−2) in diffuse and direct radiation respectively in GeoSolar simulation (Table 2). However, for GeoSulphate simulation (Table 2), a net decrease of 9 % (−12.8 W m−2) in direct radiation and a net increase of 23 % (10 W m−2) in diffuse radia-tion are simulated. The net increase in diffuse radiation in case of GeoSulphate is due to the effective scattering of the incoming radiation by the aerosols in the forward direc-tion. Consequently, a large decrease in direct radiation is seen to compensate this huge increase in diffuse radiation. Such large changes are not simulated in case of GeoSolar where both direct and diffuse radiation decrease by a simi-lar magnitude (~1 %). Also, we find that the diffuse radia-tion increase is larger for visible wavelengths (20 %) com-pared to near infrared (16 %) in the GeoSulphate case due to higher irradiance of the solar spectrum for visible wave-lengths (Kravitz et al. 2012).

Based on the mass mixing ratio and scattering cross section, we estimate that the addition of 20 Mt of sulphate aerosol to the background aerosol results in an increase in the optical depth by about 0.18 (Brovkin et al. 2008) in GeoSulphate simulation relative to Control climate. This increase is similar to the study by Bluth et al. (1997) where they find an increase in the aerosol optical depth (AOD) of the stratosphere by 0.14 post eruption (of Mount Pinatubo) compared to background AOD of 0.05. The optical depth in the present study is estimated using the relation defined by Brovkin et al. (2008): optical depth is the product of mass-scattering cross-section specified for the stratospheric sulfate aerosol and aerosol loading. The mass-scattering cross-section of stratospheric sulfate aerosol is considered to be 5 m2 g−1 for (NH4)2SO4 (Danny Harvey 2000). This increase in optical depth increases the forward scattering compared to Control climate leading to an overall increase in diffuse fraction by about 23 %.

To explain the dependence of additional sulphate load-ing on the diffuse radiation, results from a few geoengi-neering experiments performed using CAM3.1 (which uses the same radiation model) with different sulphate loadings

(2, 4, 6, 8, 10 and 12 Mt) are shown in Fig. 9. As the addi-tional sulphate loading increases the amount of diffuse radiation also increases following the approximate linear relationship,

where Fdiff is the total diffuse radiation reaching the surface in W m−2 and M is the additional sulphate loading in Mega tons (Mt).

Spatial pattern of changes in direct and diffuse radia-tion for GeoSolar simulation (Fig. 10a, b) shows a reduc-tion in most locations expect a few places where we find increases which are associated with decreases in cloudi-ness. Direct radiation change has large negative values over climatologically cloud-free regions such as the deserts and high elevations like Tibet (Fig. 10a) and the diffuse radia-tion changes follows the pattern of changes in total cloud fraction (Fig. 11). For GeoSulphate simulation, increase in diffuse radiation is simulated for most of the regions due to increase in aerosol forward scattering (Fig. 10d).

3.4 Vegetation response due to changes in direct and diffuse radiation

An increase in the diffuse radiation could result in an otherwise shaded canopy to be more evenly illuminated to produce a more uniform distribution of incident radia-tion within the canopy. This even distribution of incident diffuse radiation could result in an enhanced photosyn-thesis, an effect known as diffuse fertilization effect (Farquhar and Roderick 2003).The increase in diffuse radiation in the aerosol SRM could lead to increased light availability for shaded leaves, elevate the light and

(1)Fdiff = 0.585(M) + 49.92

Fig. 9 Variation of surface diffuse radiation with additional sulphate loadings in fixed-SST experiments in NCAR CAM 3.1 model

S. Kalidindi et al.

1 3

water use efficiencies of the canopy, and enhance the overall plant productivity (Mercado et al. 2009). The dif-fuse radiation may also have an effect on evapo-transpi-ration further affecting the hydrological cycle (Oliveira et al. 2011).

In this section we discuss the response of terrestrial vegetation to the changes in net surface diffuse and direct radiation. The changes in various land carbon variables for the geoengineering simulations with respect to Control and doubled CO2 climates are listed in Table 2. We find a

Fig. 10 Spatial distribution of changes in both direct (left pan-els) and diffuse (right panels) solar radiation at the surface for GeoSolar (top panels) and GeoSulphate (bottom panels) simulations relative to the Con-trol case. Hatching indicates the region where the changes are significant at 99 % level. Significance level was estimated using Student’s t test with a sample of 50 annual means and standard error corrected for autocorrelation (Zwiers and von Storch 1995)

Fig. 11 Spatial distribution of changes in total cloud fraction for GeoSolar (left panel) and GeoSulphate (right panel) rela-tive to the Control case. Hatch-ing indicates the region where the changes are significant at 99 % level. Significance level was estimated using Student’s t test with a sample of 50 annual means and standard error cor-rected for autocorrelation (Zwi-ers and von Storch 1995)

Modeling of solar radiation management

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large increase in sunlit gross primary productivity (GPP), shaded GPP, total GPP and NPP (Net Primary Productivity) for both the geoengineering simulations relative to Control climate and this large response can be mainly attributed to the higher concentration of CO2 (Table 3; Naik et al. 2003; Govindasamy et al. 2002; Pongratz et al. 2012; Kravitz et al. 2013; Jones et al. 2013). Therefore, to understand the individual effects of aerosols and solar constant reduction on the plant productivity we discuss the changes in geoen-gineering simulations with respect to the 2xCO2 climate hereafter.

After removing the effect of CO2 fertilization, we find that increase in diffuse radiation in aerosol SRM results in an increased shaded GPP of 1.4 Gt-C (1.8 %). However sunlit GPP shows a decrease of 15.1 Gt-C (15.2 %) due to large decrease in direct radiation which overwhelms the increase in diffuse radiation. Further, SRM by solar constant reduction shows decrease in both shaded GPP (-5.3 Gt-C) and sunlit GPP (−8.2 Gt-C) because of com-parable decreases in diffuse and direct radiation. The total GPP which is a sum of the sunlit and shaded GPP shows similar decrease for both the SRM simulations: 13.8 Gt-C or 7.9 % in GeoSulphate and 13.5 Gt-C or 7.8 % in GeoSolar indicating the negligible effect of the fractional changes in direct/diffuse radiation on the over-all plant productivity in our modeling study. Decrease in net primary productivity (NPP) is also similar in both cases (~3 %). Other carbon fluxes such as auto-trophic respiration (AR) and heterotrophic respiration (HR) also show similar changes in case of aerosol SRM and solar constant reduction. Total vegetation carbon and soil car-bon also show similar responses in GeoSulphate and GeoSolar. Further, we find that the influence of reduction in solar irradiance on the land carbon stocks in our SRM

simulations is very small compared to the CO2 fertiliza-tion effect (Table 2).

Spatial pattern of changes in land carbon variables for geoengineering simulations relative to 2xCO2 climate are shown in Figs. 12 and 13. Diffuse radiation shows a decrease in case of GeoSolar case and an increase in Geo-Sulphate case over most of the places around the globe while a decrease is seen for direct radiation over most regions in both the SRM simulations (Fig. 10). Conse-quently, changes in sunlit GPP show negative values for both GeoSolar and GeoSulphate simulations for regions with high productivity such as Amazon, Europe, Africa and South East Asia. However, changes in shaded GPP show positive values all over the globe for GeoSulphate case while GeoSolar simulation shows negative values (Fig. 12). Overall the changes in GPP are nearly similar in both the SRM simulations (Fig. 12). The spatial pattern of changes in NPP, total vegetation carbon and soil carbon are also similar in both the cases relative to 2xCO2 (Figs. 12, 13).

4 Discussion and conclusion

In this study, we have investigated the climate response in two SRM geoengineering methods: sunshades (solar con-stant reduction) and stratospheric sulphate aerosol loading. Both the geoengineering simulations are designed to cancel the global mean surface temperature change from a dou-bling of CO2. However, a residual warming in the high lati-tudes and cooling in low latitudes because of differences in the spatial patterns of solar and CO2 forcing are simulated in both geoengineering simulations as found in earlier stud-ies (Schmidt et al. 2012; Kravitz et al. 2013). The global mean precipitation decreases in both SRM cases relative to

Table 3 Particle size, vertical and latitudinal distribution of the aerosols, solar constant reduction, precipitation response and likely reason for the precipitation response in the present study, Fyfe et al. (2013) and Ferraro et al. (2014)

Aerosol distribution is uniform in zonal direction in all three studies

Parameters Present study Fyfe et al. (2013) Ferraro et al. (2014)

Aerosol particle size Dry median radius = 0.05 µmEffective radius = 0.17 µm

Effective radius = 0.35 µm Median radius = 0.1 µm

Vertical distribution of aerosols in the stratosphere

Distributed between 61–9.8 hPa with a maximum at 30 hPa (~25 km)

10 km thick layer just above the tropopause with uniform distribution

Distributed between 200 and 20 hPa with a maximum at 50 hPa (20 km)

Latitudinal distribution of aerosols Uniform Uniform Maximum mixing ratio in the tropics

Solar constant reduction Uniform around the globe Uniform around the globe Uniform around the globe

Result (precipitation response) Similar changes in global mean precipitation for both the methods

Larger decrease in aerosol SRM case

Larger reduction in tropical precipitation in the aerosol case

Likely causes Smaller aerosol particle size and aerosols prescribed at higher altitude

Larger particle size and lower altitude for aerosols

Larger particle size and maximum concentration in the tropics

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the Control case in agreement with previous studies (Bala et al. 2008; Caldeira and Wood 2008; Matthews and Calde-ira 2007; Rasch et al. 2008b; Lunt et al. 2008; Robock et al. 2008). Precipitation decreases slightly more over the land for aerosol SRM compared to the solar constant reduction case while the opposite is simulated over the ocean (Fig. 4). However, the differences between the two SRM cases are not statistically significant. The larger precipitation reduc-tion in the case of aerosol SRM as simulated by Fyfe et al. (2013) and Ferraro et al. (2014) is likely due to two causes: the size of prescribed aerosol particles and their altitude and latitudinal distributions (Table 3). Lower the altitude in the stratosphere at which the aerosols are prescribed and larger the size of the aerosol particles, larger would be

the greenhouse effect from longwave absorption by aero-sols. Larger absorption would increase the static stability and enhance the suppression of precipitation due to fast response from elevated CO2 leading to a larger reduction in precipitation (Ferraro et al. 2014). Prescribing maxi-mum concentration of aerosols at lower latitudes also leads to larger reduction in precipitation relative to a case with uniform distribution (Modak and Bala 2013). In our study, we simulate similar global mean precipitation changes for both the SRM methods because the maximum concentra-tion of aerosols is prescribed at a higher level and particle size is smaller (Table 3). In the case of Fyfe et al. (2013), the aerosol particles have relatively larger size and their prescribed altitude is lower. Drastic reduction in tropical

Fig. 12 Spatial distribu-tion of changes in sunlit GPP (g Cm− year−1), shaded GPP (g Cm− year−1), total GPP (g Cm−2 year−1) and NPP (g Cm−2 year−1) for GeoSolar (left panel) and GeoSulphate (right panel) relative to the 2xCO2 case. Hatching indicates the region where the changes are significant at 99 % level. Significance level was estimated using Student’s t test with a sample of 50 annual means and standard error corrected for autocorrelation (Zwiers and von Storch 1995)

Modeling of solar radiation management

1 3

precipitation in aerosol SRM is simulated in Ferraro et al. (2014) because aerosol concentration is maximized in the tropics and the particles have larger size too.

Apart from surface temperature and precipitation, the global mean changes relative to Control climate are simi-lar for key climate variables such as precipitable water, cloud fraction and sea ice fraction for both the geoengi-neering simulations (Table 1). However, the changes in the stratospheric temperature and diffuse and direct radiation reaching the surface differ. There is a mean warming of 1 K in the stratosphere (61–9.8 hPa) for GeoSulphate case compared to GeoSolar. This warming increases the water vapor content in the stratosphere in the GeoSulphate case (~1.2 %) while in the GeoSolar case there is a decrease in the water vapor content (5.5 %). Further, we simulate an enhanced westerly jet in the lower stratosphere in the aero-sol SRM case due to the differential heating in the meridi-onal direction in lower stratosphere (Stenchikov et al. 1998; Ammann et al. 2010). Such an enhancement in westerly jet is not seen in the case of solar constant reduction.

Effects of aerosols on the surface solar radiation are also investigated in this study. Because of enhanced forward scattering of solar radiation by sulphate aerosols, we find an increase of ~10 W m−2 (23 %) in diffuse radiation for the sulphate case and a reduction in global mean direct radiation of 12.8 W m−2 (9 %). In contrast, we simulate almost similar fractional changes (−0.6 W m−2 (−1.3 %) in diffuse and −1.7 W m−2 (−1.2 %) in direct radiation with a net reduction of about 2.3 W m−2) in solar constant reduction case. Interestingly the decrease in direct radiation

in GeoSulphate case largely compensates the increase in diffuse radiation.

The major finding in our study is related to vegetation response to differing fractional changes in direct and dif-fuse radiation in the two SRM techniques. Global mean NPP, and total vegetation carbon increase for both the geo-engineering simulations relative to the Control case and the increase is mainly attributed to the higher concentra-tion of CO2. When CO2 fertilization effects from elevated CO2 concentration levels are removed, the contribution from shaded leaves to GPP increases by 1.8 % in aerosol SRM because of increased diffuse light, this increase is almost offset by a 15.2 % decline in sunlit contribution due to reduced direct light. Overall both the SRM simulations show similar decrease in GPP (~8 %) and NPP (~3 %).

There are several limitations in our study. First, all our simulations are highly idealized. In the case of GeoSul-phate simulation, the aerosols are prescribed in the strato-sphere and they do not evolve with time and their transport by atmospheric circulations is not considered. The aerosol particle size is fixed in the model. The present study also does not consider the effect of sulphate aerosol on the strat-ospheric chemistry. In the real world the presence of sul-phate aerosol in the stratosphere could have adverse effects on the ozone chemistry as shown by Tilmes et al. (2009) where the authors find that the presence of additional sul-phate aerosols in the stratosphere fastens the heterogeneous reactions which cause ozone destruction and consequently the recovery of the ozone layer is delayed by 30 years. Changes in the aerosol particle size, the meridional and

Fig. 13 Spatial distribution of changes in SOILC (soil carbon, g Cm−2) and TOTVEGC (total vegetation carbon, g Cm−2) for GeoSolar (left panel) and Geo-Sulphate (right panel) relative to the 2xCO2 case. Hatching indicates the region where the changes are significant at 99 % level. Significance level was estimated using Student’s t test with a sample of 50 annual means and standard error cor-rected for autocorrelation (Zwi-ers and von Storch 1995)

S. Kalidindi et al.

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vertical distribution of the aerosols could quantitatively alter the changes in diffuse and direct solar radiation reported in this study.

Further, our model lacks a dynamic ocean and dynamic sea ice components and hence the deep ocean circulation and heat uptake are not modeled here and hence the deep ocean feedbacks are absent. The slab ocean assumption and a constant prescribed Q-flux (ocean heat transport) are only valid for relatively small radiative forcing changes. The spatial pattern of ocean heat uptake will have an effect on the spatial pattern of the surface warming and net forc-ing (Armour et al. 2012). This effect is not included in our simulations.

We have considered only two SRM techniques for com-parison here: solar constant reduction and sulphate aerosol SRM. The climate response due to other SRM techniques like marine cloud brightening is not considered in this study: the forcing due to cloud brightening is more local-ized compared to the two SRM methods considered in this study which provide a more uniform forcing across the globe. Finally it should be noted that there are several ethical, social, political, economic and governance issues linked to SRM which are not investigated in this study. SRM is associated with several undesired side effects and risks (Robock 2008). SRM does not address ocean acidifi-cation and associated disruptions to marine biology which are caused by elevated CO2 levels in the atmosphere. Therefore, reduction of CO2 emissions should be the top priority and SRM may be considered as a last option in case of a planetary emergency.

In summary, climate states produced by a reduction in solar constant and addition of aerosols into the stratosphere can be considered almost similar except for the following aspects: stratospheric temperature change and partition-ing of direct versus diffuse radiation reaching the surface. However, the reduction in terrestrial GPP and NPP are of the same magnitude in both the geoengineering scenarios relative to a 2xCO2 climate in our modeling study.

Acknowledgments This work was funded by Divecha Centre for Climate Change, Indian Institute of Science and the Department of Science and Technology (DST). Computational support from the Supercomputing Education and Research (SERC) and Mandhan clus-ter at the Center for Atmospheric and Oceanic Sciences supported by a FIST grant from DST is acknowledged. We also thank Prof. J. Srini-vasan of Divecha Center for Climate Change for his valuable com-ments and suggestions.

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