Albedo enhancement over land to counteract global warming:impacts on hydrological cycle

Govindasamy Bala • Bappaditya Nag

Received: 20 May 2011 / Accepted: 23 November 2011

� Springer-Verlag 2011

Abstract A recent modelling study has shown that pre-

cipitation and runoff over land would increase when the

reflectivity of marine clouds is increased to counter global

warming. This implies that large scale albedo enhancement

over land could lead to a decrease in runoff over land. In

this study, we perform simulations using NCAR CAM3.1

that have implications for Solar Radiation Management

geoengineering schemes that increase the albedo over land.

We find that an increase in reflectivity over land that

mitigates the global mean warming from a doubling of CO2

leads to a large residual warming in the southern hemi-

sphere and cooling in the northern hemisphere since most

of the land is located in northern hemisphere. Precipitation

and runoff over land decrease by 13.4 and 22.3%, respec-

tively, because of a large residual sinking motion over land

triggered by albedo enhancement over land. Soil water

content also declines when albedo over land is enhanced.

The simulated magnitude of hydrological changes over

land are much larger when compared to changes over

oceans in the recent marine cloud albedo enhancement

study since the radiative forcing over land needed

(-8.2 W m-2) to counter global mean radiative forcing

from a doubling of CO2 (3.3 W m-2) is approximately

twice the forcing needed over the oceans (-4.2 W m-2).

Our results imply that albedo enhancement over oceans

produce climates closer to the unperturbed climate state

than do albedo changes on land when the consequences on

land hydrology are considered. Our study also has impor-

tant implications for any intentional or unintentional large

scale changes in land surface albedo such as deforestation/

afforestation/reforestation, air pollution, and desert and

urban albedo modification.

1 Introduction

Solar Radiation Management (SRM) geoengineering pro-

posals (Royal Society Report 2009) aim to counter the

radiative effect of greenhouse forcing by reducing the

amount of solar radiation absorbed by the planet. Planetary

absorption of solar radiation can be reduced either by

deflecting solar radiation in space, in the atmosphere or at

the surface. Reflectors in L1 Lagrange point and mirrors in

low earth orbit are some examples for space based tech-

niques (Angel 2006; Early 1989; NAS 1992; Seifritz 1989).

Artificial injection of aerosols in the stratosphere (Crutzen

2006; Robock et al. 2009, 2008) and enhancement of

albedo of marine clouds (Bower et al. 2006; Latham 1990,

2002; Latham et al. 2008) are proposed SRM schemes for

reflecting solar radiation in the atmosphere. Increasing the

land surface albedo via whitening the roofs and pavements

in the urban area (Akbari et al. 2009; Oleson et al. 2010) or

covering deserts with more reflective polyethylene-alu-

minium to increase albedo (Gaskill 2004), making the color

of crops lighter (Doughty et al. 2011; Ridgwell et al. 2009)

or enhancing the surface albedo of the oceans (Evans et al.

2010; Flannery et al. 1997; PSAC 1965) are a few exam-

ples for surface based schemes.

Space based schemes and stratospheric injection of

aerosols are likely to lead to a more uniform reduction in

solar radiation across the planet: these schemes do not

Electronic supplementary material The online version of thisarticle (doi:10.1007/s00382-011-1256-1) contains supplementarymaterial, which is available to authorized users.

G. Bala (&) � B. Nag

Divecha Center for Climate Change and Center for Atmospheric

and Oceanic Sciences, Indian Institute of Science,

Bangalore 560012, India

e-mail: gbala@caos.iisc.ernet.in

123

Clim Dyn

DOI 10.1007/s00382-011-1256-1

differentiate land and oceans. Climate modelling studies

(Bala et al. 2008) have shown that uniform reduction in

sunlight as a geoengineering strategy to counter CO2-

induced warming will lead to a reduction in global mean

precipitation. This occurs because the fast response

(changes that occur before global mean surface tempera-

ture) of precipitation are different for CO2 and solar forc-

ings (Andrews et al. 2009; Bala et al. 2010a): CO2

absorption of longwave radiation in the atmosphere can

contribute to increased vertical stability and suppress pre-

cipitation but this fast response mechanism is nearly absent

for solar forcing because the atmosphere is not as opaque to

solar absorption as CO2 is to terrestrial radiation. However,

since the slow response (changes that are associated with

global mans surface temperature change) are the same for

CO2 and solar forcings, the total changes in rainfall are

more sensitive to variations in solar radiation than to

equivalent changes in CO2 levels (Andrews et al. 2009;

Bala et al. 2010a). Because of this differing hydrological

sensitivity to solar and CO2 forcing, insolation reductions

sufficient to offset the entirety of global-scale temperature

increases would lead to a decrease in global mean

precipitation.

All the surface based SRM schemes and marine cloud

albedo schemes introduce heterogeneity into the problem

by altering the albedo over either land or oceans. The

response of hydrological cycle to these schemes appears

different. In a recent idealized modelling study (Bala et al.

2010b), the effect of selectively enhancing the albedo over

the oceans on the hydrological cycle is assessed. When

cloud droplets are reduced in size over all oceans uniformly

to offset the temperature increase from a doubling of

atmospheric CO2, precipitation and runoff over land

increases 3.5 by 7.5% respectively. More reflective marine

clouds cool the atmospheric column over ocean which

results in a sinking motion over oceans and upward motion

over land. Increased precipitation and runoff over land are

associated with this enhanced monsoonal flow from ocean

to land in the lower levels when marine clouds are made

more reflective. The conclusion is that, in contrast to pro-

posals which uniformly increase planetary albedo, offset-

ting mean global warming by reducing marine cloud

droplet size does not necessarily lead to a drying of the

continents.

One immediate implication from this recent marine

cloud albedo enhancement study (Bala et al. 2010b) is that

large scale albedo enhancement, intentional or uninten-

tional, over land which is the inverse of enhancing the

albedo over oceans can lead to sinking motion and the

consequent drying of land. The impact of albedo modifi-

cation over land has been recognized much earlier (Char-

ney 1975): the patchy nature of the radiative forcings

arising from most surface albedo modifications has the

potential to change atmospheric circulation, and in some

locations brightening the surface could even lead to a

counterproductive reduction in cloud cover and rainfall.

Only a few climate modelling studies have investigated

the effect of land surface albedo modification to counteract

climate change. (Ridgwell et al. 2009) considered a 0.04

increase in the albedo of crops to be feasible and modelled

its impact using a coupled climate model. They found a

summertime cooling of up to 1�C in much of North

America and Central Europe, equivalent to seasonally

offsetting approximately one-fifth of regional warming due

to doubling of atmospheric CO2. Another modelling study

(Doughty et al. 2011) finds similar results for high latitudes

but it also finds that planting brighter crops at low latitudes

(\30�) may have repercussions including warming the land

surface and decreasing precipitation, because increasing

the land surface albedo tends to preferentially decrease

latent heat fluxes to the atmosphere, which decreases cloud

cover and rainfall. This later study also finds that increas-

ing plant albedo sufficiently to offset potential future

warming will require larger changes to plant albedo than

are currently available. The effects of albedo modifications

simulated in these modelling works are in agreement with

earlier studies on large scale land cover changes (Bala et al.

2007; Gibbard et al. 2005).

In this present study, we quantify the effect of increasing

the albedo over land to counteract warming from a dou-

bling of CO2 using idealized simulations. Our main goal

here is to investigate the effect on global scale hydrological

cycle. It is expected that the magnitude of decrease in

precipitation and runoff over land should be much higher

than the magnitude of decrease over oceans in the marine

cloud albedo enhancement modeling study (Bala et al.

2010b) because the area available for albedo enhancement

over land is less than over the oceans and hence the

required mean radiative forcing and the consequent sinking

motion over land is likely to be higher.

We recognise that while most land-surface based albedo

changes provide too little negative radiative forcing

(*-0.2 W-2 for whitening the roofs and *-1 W m-2

for lightening the color of crops) to counter global warming

(Lenton and Vaughan 2009), covering deserts with a

reflective polyethylene-aluminium surface to increase the

mean albedo from 0.36 to 0.8 has been estimated to provide

a significant global radiative forcing of -2.75 W m-2

(Gaskill 2004) which is close to the radiative forcing of

doubling CO2 (*3.5 W m-2).

Since the main purpose of this study is to understand the

fundamental property of the climate system for land versus

ocean differential forcing, we have applied a large enough

albedo change over land (to counter the warming from a

doubling of CO2) so the signal is stronger against the cli-

mate variability. We consider idealized case of increasing

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

the albedo of clouds over land, rather than directly

changing the albedo of land surface because we intend to

impose radiative forcing from albedo changes alone.

Changing the surface characteristics of land surface (such

as conversion of forests to grasslands or bare ground) will

include other climate forcings such as changes in evapo-

transpiration and roughness length besides albedo change.

Furthermore, changing only the albedo facilitates direct

comparison with the results of marine the albedo

enhancement study (Bala et al. 2010b).

2 The model

The model used for the study is the NCAR Community

Atmospheric Model (CAM) version 3.1. (Collins et al.

2006). We use the ‘‘Finite Volume’’ transport method for

the atmospheric dynamics. The horizontal resolution of the

model for this study is 2� in latitude and 2.5� in longitude.

There are 26 levels in the vertical. To represent the inter-

actions of the atmosphere with the ocean, the ocean is

represented by a slab ocean/thermodynamic sea ice model.

For the slab ocean, the mixed layer depths were prescribed

to climatological values, and the ocean heat transport is

prescribed as derived from the net energy flux over the

ocean surface in a climatological simulation performed

with prescribed sea surface temperatures. This slab ocean

configuration is used to calculate equilibrium climate

change. We have also used a configuration with prescribed

sea surface temperature (SST) for estimating radiative

forcings. The standard configuration of the model has an

effective cloud droplet size of 8 lm over land and 14 lm

over ocean. The droplet size over sea ice is the same as

over the ocean surface. The atmosphere model is coupled

with a land surface model, CLM3.0. CLM3.0 represents the

land surface by sixteen different plant functional types

(PFT) and simulates a number of biophysical processes for

each PFT, such as stomatal physiology and photosynthesis,

interactions of energy and water fluxes with vegetation

canopy and soil, and the surface hydrology.

3 Simulations

Three 70-year simulations are performed using the slab

ocean configuration: (1) a control ‘‘19 CO2’’ simulation

with an atmospheric CO2 concentration of 355 ppmv, (2) a

‘‘29 CO2’’ simulation in which the CO2 concentration is

doubled to 710 ppm v and (3) a ‘‘Geo’’ simulation in which

the CO2 concentration is doubled to 710 ppm and the cloud

droplet size over continental regions is decreased to 4.1 lm

from the standard value of 8 lm in the model. No changes

were made to the effective droplet size for ice clouds. For

the Geo experiment, we alter the effective radius of cloud

liquid water droplets over all land areas in the microphysics

package of the model since the shortwave optical properties

of clouds depend on the effective radius of the cloud drop-

lets. By this change, only the shortwave radiative properties

are altered and cloud microphysics is unchanged.

The choice of 4.1 lm over continental regions is based

on results of a series of simulations in which the droplet

radius over continental regions was decreased from 8 to 2,

3.7, 4.1 4.3, 4.4 and 4.5 lm. In steady state, we find that the

case with 4.1 lm has the least departure in the global mean

surface temperature from the control case. There was no

statistically significant trend in global mean surface tem-

perature after 30 years of simulation (Fig. 1): the last

40 years (out of the 70 years) of simulated global mean

temperatures have a standard error of 0.03 K and a drift of

only -5.8 9 10-6 K per year in the control simulation:

correction for serial correlation was taken into account in

computing the standard error (Zwiers and von Storch

1995). Therefore, we have analysed the last 40 years of

simulation for studying equilibrium climate change.

To estimate the radiative forcings and to quantify the

fast response of the climate system (Andrews et al. 2009;

Bala et al. 2010a), we repeat these experiments for a period

of 40 years each but with prescribed climatological SST.

The method of estimating the radiative forcing and fast

response using prescribed SST is known as ‘‘fixed–SST

method’’ (Hansen et al. 2005).

Fig. 1 Evolution of annual mean surface temperature for doubled

atmospheric CO2 content (29 CO2 - 19 CO2; red), enhanced albedo

(Geo - 29 CO2; blue) and geoengineered (Geo - 19 CO2; green)

cases. Global (solid), land (dashed) and ocean (dotted) means are

shown separately. Note that the model takes about 30 years for

reaching a steady state and hence we have chosen years 31–70 for

climate analysis

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

Besides the climate change caused by longwave radiative

effects of CO2, there is possible impacts of the physiolog-

ical effect of CO2 on plant stomatal conductance called ‘the

CO2 physiological forcing’ which can result in land surface

climate change. For example, there are many studies that

discuss the possible impacts of CO2 physiological forcing

on land surface warming and runoff (Betts et al. 2007;

Boucher et al. 2009; Cao et al. 2009, 2010; Doutriaux-

Boucher et al. 2009; Gedney et al. 2006). Though our

experiments include the CO2 physiological forcing, its

influence on our results are negligible because this version

of the model, CAM3.1 coupled to CLM3.0, is known to lead

to a mean land warming of only 0.1 K for a doubling of CO2

(Cao et al. 2009). This near-zero warming is caused by the

unrealistic partitioning of evapotranspiration in CLM3.0

with a greatly underestimated contribution from canopy

transpiration and overestimated contributions from canopy

and soil evaporation. Further, the CO2 physiological forc-

ing, though small, is present in both the 29 CO2 case and

the Geo simulation, and hence the CO2 physiological

forcing should be about the same in both cases and the

difference in these two cases is only due to the albedo

changes.

4 Results

The main focus of our analysis is to investigate the residual

hydrological impacts of enhancing the albedo over land

when the global mean warming is mitigated. For this

purpose, we discuss the following three cases: (1) climate

change from a doubling of CO2 (29 CO2 - 19 CO2), (2)

climate change due to albedo enhancement over land

(Geo - 29 CO2), and (3) climate change when both CO2

is doubled and albedo over land is enhanced (Geo - 19

CO2). These differences are referred to as ‘‘29 CO2 case’’,

‘‘enhanced albedo case’’ and ‘‘geoengineered case’’, resp-

ectively, in our discussions hereafter. Large changes are

expected in (1) and (2) since the climate forcings are large

in these cases. Because the global mean net forcing is

small, very small residual global mean changes are antic-

ipated in the geoengineered case. However, we shall see

that large residual regional changes do remain in (3), since

residual forcings over land and oceans separately are large

though global mean forcing is nearly zero.

4.1 Radiative forcing

Radiative forcing is a useful concept that has been intro-

duced to compare climate change from different forcing

mechanisms under the assumption that radiative forcing is

a good predictor of surface temperature response (IPCC

1990). It is estimated by calculating the change in planetary

energy balance at different atmospheric levels (i.e. usually

either at the tropopause, top of the atmosphere, or surface)

and at different times. Several different types of radiative

forcing have been defined over time (Hansen et al. 1997,

2005) so as to maximize the predictability and compara-

bility of equilibrium climate response by different forcing

agents. The most commonly used definitions of radiative

forcing (Hansen et al. 1997, 2005) aim to calculate plan-

etary energy balance (1) immediately after introducing the

forcing agent, usually termed ‘‘instantaneous radiative

forcing,’’ (2) after the stratosphere has adjusted to the

forcing agent (on the order of months), termed ‘‘strato-

sphere-adjusted radiative forcing,’’ or (3) after the tropo-

sphere, stratosphere, and land surface have undergone

‘‘rapid adjustment’’ to the forcing agent, termed ‘‘adjusted

radiative forcing’’. The aforementioned rapid adjustment

includes ‘‘fast responses’’ of the climate system that occur

before significant changes in global- and annual-mean

surface temperature (Andrews et al. 2009; Bala et al.

2010a; Gregory et al. 2004).

All of these concepts are well-defined and may be useful

in different circumstances. We adopt the ‘‘adjusted radia-

tive forcing’’ definition for estimating radiative forcing and

fast response in this paper since it has been recently found

that radiative forcing defined in this way is a better pre-

dictor of equilibrium climate change (Hansen et al. 2005;

Shine et al. 2003). We use the term ‘radiative forcing’ to

refer to ‘‘adjusted radiative forcing’’ hereafter, unless

otherwise noted. We adopt the ‘‘fixed-SST’’ method used

in (Bala et al. 2010a, b) for estimating this radiative forcing

though it can be also estimated from the slab-ocean sim-

ulations by performing a regression of changes in the top of

the atmosphere net radiative flux with surface temperature

change (Gregory et al. 2004). The adjusted radiative forc-

ing estimated by the regression method has been also called

‘‘regressed forcing’’ (Ban-Weiss et al. 2011). We use

Hansen’s method here because the spatial pattern of forc-

ing is directly available in this method while an ensemble

of simulations is needed to obtain a reliable estimate of the

forcing using the regression method. A comparison of these

methods is available in the literature (Bala et al. 2010a;

Gregory and Webb 2008; Hansen et al. 2005).

Table 1; Fig. 2 show that the radiative forcing is spatially

uniform when CO2 is doubled. The forcing is significant at

the 1% level over 86% the globe. The forcing over land and

ocean regions is nearly identical: the global, land, and

ocean mean forcings are 3.31 ± 0.05, 3.49 ± 0.07 and

3.24 ± 0.06 W m-2, respectively (Table 1). However, the

forcing is mostly confined to land when the cloud droplet

size over land is decreased in the enhanced albedo case

(Fig. 2, middle panel); in this case, the global, land, and

ocean mean values are -2.91 ± 0.04, -8.22 ± 0.09, and

-0.75 ± 0.06 W m-2, respectively. There is radiative

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

forcing over oceans in this case even though forcing was

applied only over land because the land surface and tropo-

sphere have been allowed to adjust which is likely to alter the

circulation around the globe. The spatial pattern (Fig. 2)

shows that the forcing is large and significant over land but

small and less significant over oceans: radiative forcing is

significant over 76% of land area and 45% of oceanic

regions (54% of the globe). The imposed global-mean

planetary albedo increase is 1% (Table S1) which is in good

agreement with the estimate provided in (Royal Society

Report 2009) for countering warming from a doubling of

CO2. The albedo change over land is nearly 3 times the

albedo change over the oceans (1.90 vs. 0.63%).

In the geoengineered case, there is residual negative

forcing over land and positive forcing over the oceans

(Fig. 2, bottom panel) because the forcings due to doubling

of CO2 and the reduction of cloud droplet size over land

sum up to produce the combined forcing. The global, land,

and ocean mean forcings simulated in this case are

0.40 ± 0.05, -4.73 ± 0.09, and 2.49 ± 0.06 W m-2,

respectively (Table 2), and the forcing is significant over

72, and 75% of the land and oceans, respectively. The large

non-zero ocean mean forcing in the geoengineered case is

mainly due to CO2 forcing which is not cancelled by

albedo enhancement over land.

The changes listed for variables other than TOA net

radiative flux in Tables 1 and S1 represent the fast response

of the climate system which we discuss in Sect. 4.3.

4.2 Equilibrium climate change

The climate change as shown in Tables 2 and S2, and

Figs. 3, 4, 5, 6 and 7 represent the total climate change as

simulated by the slab ocean model. The qualitative nature

of the results are similar but inverse to the recent study

(Bala et al. 2010b) that performed idealized simulations on

marine cloud albedo enhancement: in that study, albedo

over ocean is enhanced but albedo over land is enhanced in

this study. Therefore, we provide detailed discussions only

for findings that are new here.

In the present study, for a doubling of CO2, the land

mean warming is 2.48 ± 0.03 K and ocean mean warming

Table 1 Global and annual-mean changes in key climate variables in the prescribed SST experiments

Variable Region 19 CO2 29 CO2 - 19 CO2 Geo - 29 CO2 Geo - 19 CO2

Radiative forcing (W m-2) Global 0.39 ± 0.04a 3.31 ± 0.05 -2.91 ± 0.04 0.40 ± 0.05

Land -18.28 ± 0.05 3.49 ± 0.07 -8.22 ± 0.09 -4.73 ± 0.09

Ocean 7.99 ± 0.04 3.24 ± 0.06 -0.75 ± 0.06 2.49 ± 0.06

Surface temperature (K) Global 288.32 ± 0.01 0.15 ± 0.01 -0.16 ± 0.01 -0.01 ± 0.01

Land 282.86 ± 0.02 0.44 ± 0.03 -0.52 ± 0.03 -0.08 ± 0.03

Ocean 290.54 ± 0.003 0.04 ± 0.003 -0.02 ± 0.003 0.02 ± 0.004

Precipitation (mm/day, %)b,e Global 2.84 ± 0.001 -1.72 ± 0.05 -0.89 ± 0.05 -2.60 ± 0.05

Land 2.36 ± 0.003 2.05 ± 0.21 -14.77 ± 0.20 -13.02 ± 0.18

Ocean 3.04 ± 0.001 -2.92 ± 0.05 3.72 ± 0.06 0.70 ± 0.07

Evaporation (mm/day, %)b,e,f Land 1.54 ± 0.002 1.61 ± 0.17 -10.41 ± 0.15 -8.96 ± 0.14

Ocean 3.37 ± 0.001 -2.35 ± 0.04 0.96 ± 0.06 -1.41 ± 0.06

P - E (mm/day, %)b,c,e Land 0.81 ± 0.002 2.87 ± 0.40 -22.94 ± 0.38 -20.73 ± 0.37

Ocean -0.33 ± 0.001 -2.85 ± 0.40 22.93 ± 0.39 20.73 ± 0.37

Soil water (mm)g Land 137.81 ± 1.33 0.85 ± 0.14 -1.57 ± 0.12 -0.69 ± 0.10

Omega (mb/day)d Land 0.40 ± 0.04 -0.71 ± 0.06 2.79 ± 0.07 2.08 ± 0.06

Ocean -0.42 ± 0.02 0.29 ± 0.03 -1.15 ± 0.03 -0.86 ± 0.03

Precipitable water (kg m-2, %)b,e Global 24.16 ± 0.01 0.55 ± 0.06 -1.84 ± 0.07 -1.30 ± 0.06

Land 18.47 ± 0.02 1.54 ± 0.14 -4.03 ± 0.13 -2.55 ± 0.12

Ocean 26.48 ± 0.01 0.27 ± 0.06 -1.21 ± 0.07 -0.95 ± 0.06

a Uncertainty is given by the standard error computed from 40 annual means. The standard error is corrected for serial correlation (Zwiers and

von Storch 1995)b Percentage changes are relative to controlc Percentage changes are relative to the absolute value in the control. Land has positive P - E in the control and ocean has negative P - Ed Omega refers to the pressure velocity (negative is upward motion) at the 500 mb pressure levele The first unit is for the mean values in the 19 CO2 case, and the second unit is for the changes given in other columnsf Global-mean change in evaporation is equal to global-mean change in precipitation and hence not shown in the tableg Total soil water in the top six soil layers of the land model to a depth of 36.6 cm

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

is 1.92 ± 0.02 K (Table 2 and Fig. 3) with the ratio of the

land to the ocean mean surface temperature warming

yielding a value of 1.29. The global mean surface tem-

perature change is 2.08 K. (Sutton et al. 2007) showed that

the range of the land/sea warming ratio for the IPCC AR4

models lies between 1.18 and 1.58. The difference in

warming between the land and the ocean has been studied

detail in recent studies (Boer 2011; Joshi et al. 2008;

Lambert et al. 2011). When the land cloud albedo is

enhanced (Geo - 29 CO2), the land/ocean cooling ratio is

higher at 1.43 because radiative forcing is applied only

over land. In the geoengineered case, the residual global

mean temperature change is less than 0.1 K.

In climate change studies, the response of the climate

system to a given forcing is measured in terms of the

feedback parameter which is defined as the change in TOA

net radiative flux per unit change in global-mean surface

temperature as climate change progresses. Previous studies

have demonstrated that the feedback parameter is approx-

imately independent of the forcing mechanisms (Forster

et al. 2000; Hansen et al. 1997, 2005). We estimate the

feedback parameters from the global mean radiative

forcing (Table 1) and equilibrium temperature change

(Table 2): they are 1.59 and 1.44 W m-2 K-1, respec-

tively, for the 29 CO2 and the enhanced albedo cases.

When the ‘‘fast response’’ in global mean surface temper-

ature changes (Table 1) are subtracted from the equilib-

rium temperature change (Bala et al. 2010a), we get values

of 1.72 and 1.57 W m-2 K-1, respectively. In either

method, we find that the parameters differ by only about

10% between the two cases. This suggests that climate

sensitivity (the inverse of feedback parameter) is approxi-

mately constant and the radiative forcing concept is capa-

ble of predicting the global mean temperature change, at

least for the two types of forcings studied here (Forster

et al. 2000; Hansen et al. 1997, 2005).

The temperature changes are larger over land and high-

latitude regions in agreement with the published literature

for 29 CO2 (IPCC 2007) and enhanced albedo cases

(Fig. 3). We notice that the magnitude of temperature

change is larger in the southern hemisphere (SH) in the 29

CO2 case and in the northern hemisphere (NH) in the

enhanced albedo case: warming in NH and SH are 1.9 and

2.2 K, respectively, in the 29 CO2 case and the cooling are

2.3 and 1.8 K in the enhanced albedo case. SH warming is

more in the 29 CO2 case because of large warming in SH

high latitudes in the model (Fig. 3) and NH cooling is more

in the enhanced albedo case because albedo enhancement

is applied only over land which is mostly located in NH.

Because the geoengineered case is approximately the sum

of 29 CO2 and enhanced albedo cases, we find large

residual warming of 0.5 K in SH and a cooling of -0.3 K

in NH in the geoengineered case even though the global

mean change is nearly zero. The associated asymmetry in

the precipitable water change in the geoengineered case

can also be seen in Fig. 3 because precipitable water

changes are tightly controlled by temperature changes

(Allen and Ingram 2002; Held and Soden 2006).

Global mean precipitation increases by 4.20 ± 0.06% in

the 29 CO2 case, decreases by 6.34 ± 0.07% in the

Fig. 2 Radiative forcing calculated using the ‘‘fixed-SST method’’

(Hansen et al. 2005) for doubled atmospheric CO2 content (29

CO2 - 19 CO2), enhanced albedo (Geo - 29 CO2) and geoengi-

neered (Geo - 19 CO2) cases. The hatching indicates regions where

the changes are not significant at the 99% level of confidence.

Significance level is estimated using a Student t test with sample of 40

annual means and standard error corrected for serial correlation

(Zwiers and von Storch 1995)

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

enhanced albedo over land case and decreases by

2.41 ± 0.07% in the geoengineered case. Expressing these

changes as hydrological sensitivity (defined as % change in

global mean precipitation per degree of warming), we find

that the hydrological sensitivity is 2.01% per K for the 29

CO2 case and 3.13% per K for the albedo enhancement

case. These changes are in agreement with earlier studies

(Andrews et al. 2009; Bala et al. 2010a) which showed that

the global hydrological cycle is more sensitive to solar

forcing than to an equivalent CO2 forcing and hence geo-

engineering will lead to a decrease to global mean pre-

cipitation (Bala et al. 2008). When fast responses in

precipitation and temperature (Table 1) are subtracted from

the total equilibrium response (Table 2), hydrological

sensitivity in the 29 CO2 and enhanced albedo cases are

3.00 and 2.93%, respectively, which demonstrates that the

slow response or feedback in precipitation is independent

of the forcing mechanisms (Bala et al. 2010a).

There is large contrast in land versus ocean precipitation

changes. In the case of doubling CO2, percentage changes

in precipitation are more over land than over oceans:

7.40 ± 0.30% over land versus 3.20 ± 0.07% over oceans.

This contrast is amplified in the land cloud albedo

enhancement case: -19.35 ± 0.24% over land versus

-2.08 ± 0.07% over oceans. The geoengineering case is

nearly the sum of the above two cases where the land mean

precipitation decreases by 13.38 ± 0.28% and ocean mean

precipitation increases by 1.05 ± 0.07%. Therefore, we

find that enhancing the albedo over land as a geoengi-

neering technique could lead to a large reduction in rainfall

over land.

The magnitude of precipitation decrease over land in the

geoengineered case is much larger than the magnitude of

precipitation decrease simulated over oceans in the recent

modeling study that investigated the effect of marine cloud

albedo enhancement (13.4% in this study versus 2.9% in

the earlier study). This is expected because the areal extent

of clouds over land available for enhancing the albedo is

less than half available over ocean areas [land occupies

30% of global area and oceans cover 70% of the global

area, total cloud cover over land and oceans in our model

are 53 and 61%, respectively (Table S1)]. Therefore, the

required negative radiative forcing over land in our study to

counter warming from doubling of CO2 is approximately

twice the negative radiative forcing required over oceans in

the earlier study (-8.2 vs. -4.2 W m-2). Accordingly, the

Table 2 Global and annual-mean changes in key climate variables under equilibrium climate change

Variable Region 19 CO2 29 CO2 - 19 CO2 Geo - 29 CO2 Geo - 19 CO2

Surface temperature (K) Global 288.38 ± 0.02a 2.08 ± 0.03 -2.02 ± 0.03 0.06 ± 0.03

Land 282.82 ± 0.03 2.48 ± 0.04 -2.57 ± 0.05 -0.09 ± 0.04

Ocean 290.65 ± 0.01 1.92 ± 0.02 -1.80 ± 0.03 0.12 ± 0.03

Precipitation (mm/day, %)b,e Global 2.836 ± 0.001 4.20 ± 0.06 -6.34 ± 0.07 -2.41 ± 0.07

Land 2.349 ± 0.005 7.40 ± 0.30 -19.35 ± 0.24 -13.38 ± 0.28

Ocean 3.034 ± 0.002 3.20 ± 0.07 -2.08 ± 0.07 1.05 ± 0.07

Evaporation (mm/day, %)b,e,f Land 1.543 ± 0.002 6.50 ± 0.20 -14.28 ± 0.18 -8.71 ± 0.18

Ocean 3.363 ± 0.001 3.77 ± 0.06 -4.82 ± 0.06 -1.23 ± 0.06

P - E (mm/day, %)b,c,e Land 0.806 ± 0.004 9.11 ± 0.61 -28.80 ± 0.51 -22.31 ± 0.57

Ocean -0.329 ± 0.001 -9.10 ± 0.61 28.78 ± 0.50 22.31 ± 0.58

Soil water (mm)g Land 138.15 ± 1.41 5.02 ± 0.25 -6.47 ± 0.27 -1.48 ± 0.13

Omega (mb/day)d Land 0.52 ± 0.06 -0.37 ± 0.10 2.32 ± 0.09 1.95 ± 0.07

Ocean -0.47 ± 0.02 0.16 ± 0.04 -0.92 ± 0.04 -0.77 ± 0.03

Precipitable water (kg/m2, %)b,e Global 24.05 ± 0.03 13.97 ± 0.15 -14.24 ± 0.17 -2.26 ± 0.20

Land 18.34 ± 0.03 15.60 ± 0.24 -16.55 ± 0.21 -3.54 ± 0.23

Ocean 26.38 ± 0.03 13.51 ± 0.15 -13.57 ± 0.17 -1.90 ± 0.20

Sea ice fraction (million km2, %)b,e Global 18.06 ± 0.06 -30.06 ± 0.51 26.39 ± 0.90 -11.60 ± 0.63

a Uncertainty is given by the standard error computed from 40 annual means. The standard error is corrected for serial correlation (Zwiers and

von Storch 1995)b Percentage changes are relative to controlc Percentage changes are relative to the absolute value in the control. Land has positive P - E in the control and ocean has negative P - Ed Omega refers to the pressure velocity (negative is upward motion) at the 500 mb pressure levele The first unit is for the mean values in the 19 CO2 case, and the second unit is for the changes given in other columnsf Global-mean change in evaporation is equal to global-mean change in precipitation and hence not shown in the tableg Total soil water in the top six soil layers of the land model to a depth of 36.6 cm

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

precipitation decline over land in our enhanced albedo case

is 19.4% which is much larger when compared to the

precipitation decline over oceans of 7.3% in the previous

study when marine cloud albedo is increased. In the

enhanced albedo and geoengineered cases, most of the

decrease in precipitation is confined to the tropical land

areas such as central Africa, Amazon, India and Central

America (Fig. 4).

The impact on net water budget can be assessed by

investigating precipitation minus evaporation (P - E). In

our model, runoff over land increases by 9.11 ± 0.61%

when CO2 is doubled. However, in the enhanced albedo

and geoengineeed cases, runoff over land decreases by

28.80 ± 0.51 and 22.31 ± 0.57%. Therefore, we find that

albedo enhancement over land as a geoengineering strategy

could lead to a drying of the continents. As for precipita-

tion, the magnitude of runoff decrease in the geoengineered

case is much larger than the magnitude of runoff increase

in the corresponding case in the earlier study on marine

cloud albedo enhancement (22.3% in this study versus

7.5% in the earlier study). The drying is mostly confined to

tropical land areas: India, Amazon and central Africa

(Fig. 4). The large changes in P - E over the oceans are

likely driven by atmospheric circulation changes. The

changes in soil water content in 29 CO2, enhanced albedo

and geoengineered cases are about 5.02 ± 0.25,

-6.47 ± 0.27 and -1.48 ± 0.13 mm, respectively, which

are associated with an increase in precipitation in the 29

CO2 case and a decrease in the enhanced albedo and

geoengineered cases (Table 2).

In the earlier study on marine cloud albedo enhancement

(Bala et al. 2010b), the increase in precipitation and runoff

over land are associated with the enhanced monsoonal flow

and the associated upward motion over land and sinking

motion over oceans. We find that the reverse mechanism

operates here: there is sinking motion over land and

upward motion over oceans (Table 2; Figs. 3, 5). As for

precipitation and runoff changes over land, we find that the

magnitude of sinking motion over land in the enhanced

albedo case is larger than the magnitude of sinking motion

over oceans simulated in the marine cloud albedo

enhancement case (Bala et al. 2010b) (2.8 vs. 0.63 mb per

day at about 500 mb). The sinking motion over land and

rising motion over oceans extend throughout the tropo-

sphere in the globally averaged vertical profiles in the

enhanced albedo and geoengineered cases (Fig. 5). In these

cases, sinking motion over land is confined to the tropical

land areas such as central Africa, Amazon, India and

Fig. 3 Changes in global and

annual mean temperature,

precipitable water and upward

vertical pressure velocity at 500

mb for doubled atmospheric

CO2 content (29 CO2 - 19

CO2), enhanced albedo (Geo

- 29 CO2) and geoengineered

(Geo - 19 CO2) cases.

Vertical motion in height

coordinates (w, meter/day) can

be obtained from w = -x/(qg)

where x is the simulated

vertical pressure velocity. The

hatching indicates regions

where the changes are not

significant at the 99% level of

confidence. Significance level is

estimated using a Student t test

with sample of 40 annual means

and standard error corrected for

serial correlation (Zwiers and

von Storch 1995)

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

Central America (Fig. 3). The zonal mean profile of

changes in vertical motion at 500 mb clearly shows that the

sinking motion and declines in precipitation and runoff

over land in the enhanced albedo and geoengineered cases

are mostly confined to the tropical latitudes (Fig. 6).

An upper bound for the vertical motion over land or

oceans in the enhanced albedo or geoengineered case can

be estimated using the method adopted in (Bala et al.

2010b):

woT

ozþ Cd

� �¼ Q

where w is the vertical velocity, Cd is the dry adiabatic lapse

rate, (qT/qz) is the environmental lapse rate, and Q is the

diabatic heating rate. For illustrative purposes, we will make

an estimate of the sinking motion over land in the enhanced

albedo case. We use qT/qz = -7.5 9 10-3 K m-1 over

land, and Cd * 1.0 9 10-2 K m-1 (Holton 1992): we use

an environmental lapse rate over land that is between a dry

and moist adiabat. The change in diabatic heating rate in the

atmosphere is the change in net TOA energy flux since

the change in surface net flux is nearly zero (Table S2):

Q = -6.4 W m-2/(Mair*Cpair) where Mair(*104 kg m-2)

is the mass of air above a square meter and Cpair

(*1,000 J kg-1 K-1) is the specific heat capacity of air.

Substitution of the numerical values yields Q * -6.4 9

10-7 K s-1or *-6.4 9 10-2 K day-1, and w * -26 m

day-1 or x * 2.6 mb day-1 in pressure coordinates where

x is the pressure velocity. This value agrees well with the

value shown in Table 2 and Fig. 5 for the mid troposphere

for the enhanced albedo case.

The decrease in the net surface shortwave radiation and

increase in planetary albedo are confined to continental

areas such as central Africa, Amazon, Australia, North

America and Eurasia where the albedo enhancement is

imposed in the enhanced albedo and geoengineering cases

(Fig. 7). The reduction in net surface shortwave radiation

over land is much larger than the reduction over oceans in

these two cases: the global, land and ocean mean changes

in surface absorption of shortwave radiation are -1.98 ±

0.06, -4.92 ± 0.16, and -0.78 ± 0.07 W m-2, respec-

tively, in the enhanced albedo case and -3.10 ± 0.06,

-5.89 ± 0.14, and -1.97 ± 0.08 W m-2 in the geoengi-

neered case (Table S2). Total cloud amount changes do not

correlate well with net shortwave radiation or planetary

albedo changes (Fig. 7) because enhancement of albedo

over land was achieved through changing the cloud droplet

radius rather than cloud amounts. The correlation between

Fig. 4 Changes in global and

annual mean precipitation (P),

evaporation (E) and run-off

(P - E) due to doubled

atmospheric CO2 content

(29 CO2 - 19 CO2), enhanced

albedo (Geo - 29 CO2) and

geoengineered (Geo - 19

CO2) cases. The hatchingindicates regions where the

changes are not significant at the

99% level of confidence.

Significance level is estimated

using a Student t test with

sample of 40 annual means and

standard error corrected for

serial correlation (Zwiers and

von Storch 1995)

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

changes in total cloud fraction and planetary albedo is

between 0.51 and 0.59 for all the three cases and it is

between -0.53 and -0.60 for changes in total cloud

fraction and surface net solar radiation.

4.3 Fast response

When a climate forcing is imposed, the climate system

responds in all time scales in the real world. For our slab

ocean model, the longest time scale is dictated by the

thermal capacity of the mixed layer ocean which is about a

few decades. Fast response refers to rapid adjustments to

the climate system before the global mean surface tem-

perature changes. The rapid adjustments are associated

with fast changes in the atmosphere and land surface since

these components have much smaller heat capacity com-

pared to the mixed layer ocean. Though fast response is a

tiny fraction of the equilibrium climate change (discussed

in the previous section) for many variables such as water

vapour that are tightly coupled to the surface temperature,

it could constitute almost 40% of the total response for few

key variables like precipitation and evaporation on a global

mean basis (Bala et al. 2010a). Further, it has been dem-

onstrated that the climate sensitivity as well as hydrological

sensitivity, defined as the change in global mean precipi-

tation per unit warming, are independent of the forcing

mechanisms when the fast responses are excluded from the

definition of these sensitivities, suggesting that the slow

response or feedback (equilibrium climate change minus

fast response per unit temperature change) is independent

of the forcing mechanism. Therefore, it has been recom-

mended that the fast and slow response be compared sep-

arately in multi-model intercomparisons to discover and

understand robust responses in climate system (Bala et al.

2010a).

In this section, our main interest is to compare the

magnitudes of fast and slow responses and to find out the

fraction contributed by fast response to the total equilib-

rium climate change for key climate variables of interest

namely precipitation, evaporation, omega and runoff over

land (Table 3). The fast response is listed in Tables 1 and

S1 and equilibrium climate change in Tables 2 and S2. We

refer to the difference between equilibrium climate change

and fast response as ‘‘slow response’’ though by convention

this difference normalized by global mean surface tem-

perature is referred to as slow response or feedback. There

is no change in fraction of sea ice extent in prescribed SST

runs and hence the ratio for this variable is not listed in

Table 1. Equilibrium climate change in the geoengineering

case is too small which can lead to unrealistically large

values for the fraction and hence we do not list these

fractions for this case in Table 3.

We find that the fast response in global mean surface

temperature and precipitable water are smaller than slow

response in the 29 CO2 (relative to 19 CO2) and the

enhanced albedo (relative to 29 CO2) cases. (Table 3): fast

response contributes less than 10% to total global mean

surface temperature change and at most 15% to total global

mean precipitable water change in these cases. The non-

zero values in temperature over oceans are due to change in

surface temperature of the sea ice in this model. The global

mean changes in temperature and precipitable water are

primarily driven by changes over land which undergoes

rapid adjustment: in the enhanced albedo case, fast

response in precipitable water over land contributes 32% to

the total response.

Fast response constitutes a major fraction of the equilib-

rium response for precipitation, evaporation, P - E and

omega (vertical pressure velocity) in both 29 CO2 and

enhanced albedo cases (Table 3). The rapid response in

global mean precipitation is about 40% in the 29 CO2 in

agreement with the recent study (Bala et al. 2010a). How-

ever, the changes are vastly different between land and

oceans: the fast responses over land and ocean are 28 and

Fig. 5 Vertical profile of the changes in land-mean and ocean-mean

pressure velocity (omega). Negative values in omega changes

represent increases in upward motion and vice versa. Changes are

shown for doubled atmospheric CO2 content (29 CO2 - 19 CO2),

enhanced albedo (Geo - 29 CO2) and geoengineered (Geo - 19

CO2) cases. Vertical motion in height coordinates (w, meter/day) can

be obtained from w = -x/(qg) where x is the simulated vertical

pressure velocity. The data is vertically interpolated to the pressure

levels because omega is equivalent to mass flux and interpretation in

terms of mass conservation is made easier in the pressure coordinate

system

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

92% of total equilibrium response and the fast and slow

responses have opposite signs over the oceans in this case.

Over land and oceans, fast response is smaller than slow

response for precipitation, evaporation and P - E in the 29

CO2 case. However, fast response provides major contri-

butions of 76, 73, and 80%, respectively to total response in

precipitation, evaporation and P - E over land for the

enhanced albedo case: in this case, fast response is 3–4 times

larger than slow response in precipitation, evaporation and

P - E over land. For omega, fast response is almost 6 times

the slow response in the enhanced albedo case and total

change in omega results mainly from fast response. In

summary, we find that the fast response is larger than the

slow response in the case of enhanced albedo for the

hydrological cycle: fast response is the primary driver for

hydrological changes in the enhanced albedo case.

5 Discussion

In this study, we have performed simulations using an

atmospheric general circulation model (NCAR CAM3.1)

coupled to a ‘‘slab’’ ocean model to investigate the

potential for mitigation of climate change by enhancing the

albedo over land. In these simulations the albedo over land

is enhanced to approximately offset the global mean

warming from a doubling of atmospheric CO2 content. We

consider idealized case of increasing the albedo of clouds

over land, rather than directly changing the surface albedo

of land surface because our intention is to impose radiative

forcing from albedo change alone: surface albedo can be

changed by changing the surface types in the model but

such a change will result in evapotranspiration changes

besides albedo changes.

Fig. 6 Changes in zonally

averaged annual mean pressure

velocity (omega) at 500 mb,

precipitation (P), evaporation

(E) and run-off (P - E) due to

doubled atmospheric CO2

content (29 CO2 - 19 CO2),

enhanced albedo (Geo - 29

CO2) and geoengineered

(Geo - 19 CO2) cases.

Changes are shown for land

(brown), ocean (blue) and

global (green) means. The

horizontal axis is latitude for all

the panels. Negative values in

omega changes represent

increases in upward motion and

vice versa. Vertical motion in

height coordinates (w, meter/

day) can be obtained from

w = -x/(qg) where x is the

simulated vertical pressure

velocity

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

Relative to the 19 CO2 control climate, the geoengi-

neered world (29 CO2 world with enhanced albedo over

land) results in global land-mean precipitation decreases of

13.38 ± 0.28% and runoff (precipitation minus evapora-

tion) decreases of 22.31 ± 0.57%. These results are

inverse to those presented in a recent study (Bala et al.

2010b) which found increases in both precipitation and

runoff over land for geoengineering schemes that enhance

the albedo of marine clouds. The decrease in precipitation

and runoff over land in this study occurs because the

enhancement of albedo is applied only over the land areas.

This differential enhancement of albedo over land leads to

a reverse monsoonal circulation with sinking motion over

land (Tables 1, 2; Figs. 3, 5, 6), and rising motion over

ocean with associated decreases in precipitation and runoff

over land. The imposed radiative forcing and the conse-

quent vertical motions over land and ocean are illustrated

schematically in Fig. 8. Prior results indicated that albedo

increases over the ocean would result in an increase in

runoff over land. Consistent with these results are our

findings that albedo enhancements over land would result

in decrease in runoff over land. Simulations using other

models have also shown that the nature and distribution of

the response to geoengineering would depend on the

distribution of the applied forcing, and hence it is a chal-

lenge to understand the regional climate responses (Jones

et al. 2009, 2011).

There are three new key findings in this study: (1) Even

though the global mean warming from a doubling of CO2 is

mitigated in our geoengineered case, there is large unmiti-

gated warming (0.5 K) in the southern hemisphere and

cooling (-0.3 K) in the northern hemisphere since most of

the land for albedo enhancement is located in the northern

hemisphere. (2) Precipitation and runoff over land decrease

by 13.4 and 22.3% respectively, in the geoengineered case.

The magnitude of these changes are much larger than

changes over oceans in the marine cloud albedo enhance-

ment study (3.5 and 7.5%) (Bala et al. 2010b) because the

radiative forcing (or albedo enhancement) over land needed

(-8.2 W m-2) to counter global mean radiative forcing

from a doubling of CO2 (3.3 W m-2) is approximately

twice the forcing needed over the oceans (-4.2 W m-2) in

the previous study (Fig. 8). (3) Fast response constitutes

major fraction of the total response in climate variables such

as vertical velocity, precipitation, evaporation and runoff

over land in the cases where the albedo of land is enhanced.

In this model, we see that the decrease in precipitation

over land is larger than the decrease in evaporation when

Fig. 7 Changes in global and

annual mean surface net

shortwave radiation, total

cloudiness and planetary albedo

due to doubled atmospheric

CO2 content (29 CO2 - 19

CO2), enhanced albedo (Geo

- 29 CO2) and geoengineered

(Geo - 19 CO2) cases. The

hatching indicates regions

where the changes are not

significant at the 99% level of

confidence. Significance level is

estimated using a Student t test

with sample of 40 annual means

and standard error corrected for

serial correlation (Zwiers and

von Storch 1995)

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

the radius of cloud droplets over land is decreased,

resulting in decreased runoff over land (Table 2). We find

that this is associated with an increased sinking motion

over land triggered by an increase in albedo over land. In

our simulations, only the effect of decreased cloud droplet

size on shortwave radiative properties of clouds is rep-

resented and their effect on cloud microphysics is not

represented. Observational studies do show suppression of

rainfall in clouds with aerosols and hence elevated con-

centration of cloud droplets (Konwar et al. 2010;

Rosenfeld 2000; Rosenfeld et al. 2007, 2008). In these

studies, it has been suggested that the increased CCN

could lead to smaller droplets which do not rain out as

often because they do not reach ‘‘precipitable’’ raindrop

sizes as quickly. Thus, not only does the decreased cloud

droplet size lead to increased albedo and reduced surface

solar heating but it can also lead to suppression of rainfall

by distributing the cloud water among too many droplets.

Decreased cloud droplet size could also increase the

lifetime of clouds. The increased lifetime could further

increase the cloud-albedo and, therefore, the cloud life

time effect could amplify the effect from the increase in

cloud albedo. In our simulations, these cloud microphys-

ical effects are not represented and, hence, the effect of

reduced cloud droplet size is probably underestimated in

this study.

Caution should be exercised in interpreting our results

because we have used a single atmospheric general circu-

lation model coupled to a mixed layer ocean model. Tran-

sient responses and feedbacks from deep-ocean and dynamic

sea-ice are not simulated in this study. Our simulations also

lack many feedbacks associated with ocean and land bio-

spheres. A large spread exists in climate models’ precipita-

tion and evaporation responses to global warming (IPCC

2007) which implies that other climate models could yield

quantitatively different results. Therefore, it is important to

demonstrate if this result is robust across climate models.

Are there any fundamental constraints on the transport of

heat and water between land and oceans for increasing CO2

and increased albedo over land? Recent studies (Boer 2011;

Lambert et al. 2011) provide insights into changes in land–

ocean heat transport for radiative forcing and prescribed SST

changes. Their analysis indicates that land/ocean warming

ratio is not maintained by separate local balances over land

and ocean but by an energetic balance that also involves a

change in transport between the regions. Changes in heat

transport have large impacts on surface heat fluxes but small

impacts on precipitation, circulation, and cloud radiative

Table 3 Fast and slow response components of climate change for the 29 CO2 and enhanced albedo over land cases

Variable Region 29 CO2 - 19 CO2 Geo - 29 CO2 29 CO2 - 19

CO2

Geo - 29 CO2

Fast Slow Fast Slow

Surface temperature

(K)aGlobal 0.15 ± 0.01 1.93 ± 0.03 -0.16 ± 0.01 -1.86 ± 0.03 0.08 (0.07) 0.09 (0.08)

Land 0.44 ± 0.03 2.04 ± 0.05 -0.52 ± 0.03 -2.05 ± 0.06 0.22 (0.18) 0.25 (0.20)

Ocean 0.04 ± 0.003 1.88 ± 0.02 -0.02 ± 0.003 -1.78 ± 0.03 0.02 (0.02) 0.01 (0.01)

Precipitation (%) Global -1.72 ± 0.05 5.92 ± 0.08 -0.89 ± 0.05 -5.45 ± 0.09 -0.29 (-0.41)c 0.16 (0.14)a

Land 2.05 ± 0.21 5.35 ± 0.37 -14.77 ± 0.20 -4.58 ± 0.31 0.38 (0.28)a 3.22 (0.76)b

Ocean -2.92 ± 0.05 6.12 ± 0.09 3.72 ± 0.06 -5.8 ± 0.09 -0.48 (-0.91)c -0.64 (-1.79)c

Evaporation (%) Land 1.61 ± 0.17 4.89 ± 0.26 -10.41 ± 0.15 -3.87 ± 0.24 0.33 (0.25)a 2.69 (0.73)b

Ocean -2.35 ± 0.04 6.12 ± 0.07 0.96 ± 0.06 -5.78 ± 0.08 -0.38 (-0.62)c -0.17 (-0.20)c

P - E (%) Land 2.87 ± 0.40 6.24 ± 0.73 -22.94 ± 0.38 -5.86 ± 0.63 0.46 (0.32)a 3.91 (0.80)b

Ocean -2.85 ± 0.40 -6.25 ± 0.73 22.93 ± 0.39 5.85 ± 0.63 0.46 (0.32)a 3.92 (0.80)b

Soil water (mm) Land 0.85 ± 0.14 4.17 ± 0.29 -1.57 ± 0.12 -4.90 ± 0.30 0.20 (0.17)a 0.32 (0.24)a

Omega (mb/day) Land -0.71 ± 0.06 0.34 ± 0.12 2.79 ± 0.07 -0.47 ± 0.11 -2.09 (1.92)d -5.94 (1.20)d

Ocean 0.29 ± 0.03 -0.13 ± 0.05 -1.15 ± 0.03 0.23 ± 0.05 -2.23 (1.81)d -5 (1.25)d

Precipitable water

(kg m-2)aGlobal 0.55 ± 0.06 13.42 ± 0.16 -1.84 ± 0.07 -12.4 ± 0.18 0.04 (0.04) 0.15 (0.13)

Land 1.54 ± 0.14 14.06 ± 0.28 -4.03 ± 0.13 -12.52 ± 0.25 0.11 (0.10) 0.32 (0.24)

Ocean 0.27 ± 0.06 13.24 ± 0.16 -1.21 ± 0.07 -12.36 ± 0.18 0.02 (0.02) 0.10 (0.09)

Ratio of fast response to slow response is shown in last two columns. Values in parenthesis show the ratio of fast response to equilibrium

response

Slow response = equilibrium climate change (Table 2)—fast response (Table 1)a Fast and slow responses have same signs and magnitude of fast response is smaller than slow responseb Fast and slow responses have same signs and magnitude of fast response is larger than slow responsec Fast and slow responses have opposite signs and magnitude of fast response is less than slow responsed Fast and slow responses have opposite signs and magnitude of fast response is larger than slow response

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

123

forcing compared with the impacts of surface temperature

change (Lambert et al. 2011). Clearly, more theoretical and

modelling studies on climate change and multi-model

intercomparisons are required to further our understanding

of the constraints. However, we believe that the triggering of

sinking motion in the atmosphere for an albedo increase is so

fundamental that all models should show at least qualitative

agreement with our results.

The main goal of our study is to investigate the hydro-

logical consequences of enhancing albedo over land sur-

face. For this purpose, we have used an idealized case of

enhancing the cloud albedo over land. Our simulations are

intended only to elucidate fundamental properties of the

climate system; this study is not intended to realistically

represent future albedo modification over land. In the real

world, surface albedo modifications are proposed for

pavements and roofs of urban areas (Akbari et al. 2009)

and large desert regions (Gaskill 2004), and we can only

infer from our study that there will be large adverse

regional impacts on the hydrology. Our simulations suggest

the likelihood of reduced rainfall over the regions where

albedo is enhanced on a large spatial scale. The implica-

tions of our study are not restricted to intentional albedo

changes alone: it is likely that unintentional albedo changes

from activities such as large scale deforestation and par-

ticulate pollution (and consequent brighter clouds) will also

lead to regional reduction in precipitation and runoff.

Acknowledgments We thank Prof. J. Srinivasan for his helpful

comments on the original manuscript. Suggestions and comments by

Dr. Hugo Lambert and two anonymous reviewers helped us to

improve the manuscript substantially. Financial support for B. Nag

was provided by the Divecha Center for Climate Change, Indian

Institute of Science. Generous computational resources were provided

by the Supercomputer Education and Research Center, Indian Insti-

tute of Science. Technical assistance by S. Krishna, B. Pavana and

Dr. Devaraju in preparing the illustrations in this paper is gratefully

acknowledged.

References

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world-wide urban albedos to offset CO2. Climatic Change

94(3–4):275–286

Fig. 8 Schematic diagram illustrating the changes in vertical motion at

500 mb over land and oceans in 29 CO2 (top left panel), enhanced

albedo (top middle panel) and geoengineered (top right panel) cases.

Radiative forcings (positive downward) over land and oceans in each

case are shown at the top. Vertical motion in height coordinates (w,

meter/day) is obtained from w = -x/(qg) where x is the model

simulated pressure velocity. Changes in surface temperature, precip-

itation and precipitation minus evaporation are also shown. Horizontal

arrows show the changes in run off over land (towards right is an

increase). Corresponding changes in a recent study on marine cloud

albedo enhancement (Bala et al. 2010b) are illustrated in bottom panels:

29 CO2 (bottom left panel), enhanced marine cloud albedo (bottommiddle panel) and geoengineered (bottom right panel) cases. It should

be noted that CAM3.1 simulations are used for top panels and bottompanels use CAM3.5 simulations

G. Bala, B. Nag: Albedo enhancement over land to counteract global warming

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