impact of carbonaceous aerosol emissions on regional ......modiﬁed by aerosol dynamics, i.e., by...

E. Roeckner Æ P. Stier Æ J. Feichter Æ S. KlosterM. Esch Æ I. Fischer-Bruns

Impact of carbonaceous aerosol emissions on regional climate change

Received: 11 October 2005 / Accepted: 17 March 2006� Springer-Verlag 2006

Abstract The past and future evolution of atmosphericcomposition and climate has been simulated with aversion of the Max Planck Institute Earth System Model(MPI-ESM). The system consists of the atmosphere,including a detailed representation of troposphericaerosols, the land surface, and the ocean, including amodel of the marine biogeochemistry which interactswith the atmosphere via the dust and sulfur cycles. Inaddition to the prescribed concentrations of carbondioxide, ozone and other greenhouse gases, the model isdriven by natural forcings (solar irradiance and volcanicaerosol), and by emissions of mineral dust, sea salt,sulfur, black carbon (BC) and particulate organic matter(POM). Transient climate simulations were performedfor the twentieth century and extended into the twenty-first century, according to SRES scenario A1B, with twodifferent assumptions on future emissions of carbona-ceous aerosols (BC, POM). In the first experiment, BCand POM emissions decrease over Europe and Chinabut increase at lower latitudes (central and SouthAmerica, Africa, Middle East, India, Southeast Asia). Inthe second experiment, the BC and POM emissions arefrozen at their levels of year 2000. According to theseexperiments the impact of projected changes in car-bonaceaous aerosols on the global mean temperature isnegligible, but significant changes are found at low lat-itudes. This includes a cooling of the surface, enhancedprecipitation and runoff, and a wetter surface. Theseregional changes in surface climate are caused primarilyby the atmospheric absorption of sunlight by increasing

BC levels and, subsequently, by thermally driven circu-lations which favour the transport of moisture from theadjacent oceans. The vertical redistribution of solar en-ergy is particularly large during the dry season in centralAfrica when the anomalous atmospheric heating of upto 60 W m�2 and a corresponding decrease in surfacesolar radiation leads to a marked surface cooling, re-duced evaporation and a higher level of soil moisture,which persists throughout the year and contributes tothe enhancement of precipitation during the wet season.

1 Introduction

It is well established that the increase in greenhousegases and aerosols since the beginning of industrializa-tion can be attributed to human activities. This pertur-bation in atmospheric composition caused a majorradiative forcing of the climate system (Ramaswamyet al. 2001). There is strong evidence from climatemodelling studies that this forcing is sufficient toreproduce to first order the observed global warmingtrend in the past three decades, whilst the early twentiethcentury warming is more likely caused by natural forc-ings (Stott et al. 2000; Broccoli et al. 2003; Meehl et al.2004; Hansen et al. 2005) or unforced natural variability(Delworth and Knutson 2000).

Nevertheless, there are still large gaps in our under-standing of radiative forcings and their climatic impacts.This applies, in particular, to the indirect aerosol effects(see review by Lohmann and Feichter 2005) and to therole of carbonaceous aerosols (Haywood and Shine 1995;Haywood and Ramaswamy 1998; Penner et al. 1998,2003; Jacobson 2001; Koch 2001; Chung and Seinfeld2002; Roberts and Jones 2004; Wang 2004). Black car-bon (BC) released from the burning of fossil fuel andbiomass is of special interest because, unlike sulfate, it isable to absorb sunlight thus heating the atmosphere andcooling the surface. From many sources BC is co-emitted

E. Roeckner (&) Æ P. Stier Æ J. Feichter Æ S. KlosterM. Esch Æ I. Fischer-BrunsMax Planck Institute for Meteorology,Bundesstrasse 53, 20146 Hamburg, GermanyE-mail: [email protected]

P. StierCalifornia Institute of Technology, Pasadena, USA

S. KlosterInstitute for the Environment and Sustainability,European Commission Joint Research Centre, Ispra, Italy

Climate Dynamics (2006)DOI 10.1007/s00382-006-0147-3

with particulate organic matter (POM) forming inter-nally mixed agglomerates commonly referred to as ‘soot’.The absorption efficiency of BC can become significantlyenhanced in soot particles, depending on the mixing stateand geometric alignment (Jacobson 2001). On the globalscale, the radiative perturbations in the atmosphere andat the surface are about an order of magnitude largerthan the BC direct radiative forcing at the tropopauselevel (Ramanathan et al. 2001a), which has been esti-mated as +0.40 W m�2 with a factor of three uncer-tainty (Haywood and Ramaswamy 1998) and between+0.31 and +0.62 W m�2 depending on mixing state(Jacobson 2001).

Equally important are regional and seasonal effects ofabsorbing aerosols, which have been identified duringseveral measurement campaigns. For example, the In-dian Ocean Experiment (INDOEX; Ramanathan et al.2001b) documented the Indo-Asian haze spreadingduring the winter monsoon season over the North In-dian Ocean, and South and Southeast Asia. Althoughthe BC contribution to the fine particle mass was only14%, the resulting radiative perturbation was sub-stantial (�20 W m�2 at the surface and +18 W m�2 inthe atmosphere). A similar decrease in surface solarradiation (�26 W m�2) was found during the Trop-opheric Aerosol Radiative Forcing Experiment (TAR-FOX; Russell et al. 1999). Large direct radiative effects(about �15 W m�2 at the surface and about+12 W m�2 in the atmosphere) were also reported forbiomass burning aerosols in southern Africa during thedry season (Abel et al. 2005). Based on BC measure-ments during a field campaign in northern India, asurface forcing of –62 ± 23 W m�2 and a top-of-atmosphere forcing of +9 ± 3 W m�2 has been esti-mated (Tripathi et al. 2005), resulting in a mean atmo-spheric absorption of +71 W m�2 due to an extremelylarge BC load. Possible climatic consequences of thevertical redistributions in solar heating were discussedby Krishnan and Ramanathan (2002) who found evi-dence for a surface cooling due to absorbing aerosols ofabout 0.3 K since the 1970s over the Indian subconti-nent and suggested that the Indo-Asian haze might havecontributed to regional surface cooling but warmingelsewhere. This view is supported by atmosphere-onlymodelling studies on the climatic effect of increased BCconcentrations in China and India (Menon et al. 2002).Surface cooling was simulated in parts of China butsurface warming in most other regions.

Previous studies on future climate projections withcoupled atmosphere-ocean general circulation models(AOGCMs) were based on emission scenarios forgreenhouse gases and sulfur dioxide. In these studies thetemporal evolution of anthropogenic sulfate concentra-tions was either pre-calculated with an aerosol transportmodel, and subsequently prescribed in the respectiveAOGCM (Haywood et al. 1997; Mitchell and Johns1997; Boer et al. 2000; Dai et al. 2001), or calculatedonline in the climate model (Roeckner et al. 1999; Johnset al. 2003). The major aerosol compounds like sulfate,

carbonaceous aerosols, sea salt and soil dust were con-sidered by Nozawa et al. (2001) in IPCC SRES (SpecialReport on Emissions Scenarios, Nakicenovic et al. 2000)scenario experiments with prescribed aerosol mass andnumber concentrations pre-calculated with an aerosoltransport model.

The model used in this study consists of an AOGCMand includes a size-resolving representation of the maintropospheric aerosol components as well as a model ofthe marine biology. This allows us to simulate not onlythe climatic response to enhanced levels of greenhousegases and anthropogenic aerosols of different chemicalcomposition but also the feedbacks arising from theinteraction between climate parameters and naturalaerosol components like mineral dust, sea salt andmarine dimethyl sulfide (DMS). However, the main fo-cus of this study is on the climatic consequences ofchanging BC and POM emissions. In the next section wedocument the model and then describe the experiments(Sect. 3). The results are presented in Sect. 4, and themain findings are summarized and discussed in Sect. 5.

2 Model description

The atmospheric component of the coupled model(ECHAM5, Roeckner et al. 2003, 2006) uses the spectraltransform method for vorticity, divergence, temperatureand the logarithm of surface pressure at T63 horizontalresolution. For positive definite variables such as thewater components the advective transport is calculatedwith a flux-form semi-Lagrangian scheme (Lin and Rood1996) on the Gaussian grid. The model has 19 levels in ahybrid sigma/pressure vertical coordinate system withthe top level at 10 hPa. It uses state-of-the-art parame-terizations for shortwave and longwave radiation, strat-iform clouds, cumulus convection, boundary layer andland surface processes, and gravity wave drag. The modelincludes a detailed representation of tropospheric aero-sols (Hamburg Aerosol Module, HAM; Stier et al.2005a). The aerosol size spectrum in HAM is approxi-mated by a superposition of seven lognormal distribu-tions. The modes are grouped into four size classes withvarying number median radii r : nucleation moder � 0:005 lmð Þ; Aitken mode 0:005 lmð accumulationmode 0:05 lmð and coarse mode 0:5 lmð Three of themodes (hydrophobic Aitken, accumulation, and coarsemodes) are composed of hydrophobic compounds andfour of the modes contain at least one hydrophilic com-pound (see mixing state configuration in Table 1 of Stieret al. 2005a). The governing equations for mass andnumber concentrations in the respective size/solubilityclasses are solved for the following aerosol components:Sulfate, BC, POM, sea salt, and mineral dust. Thecomposition of each internally mixed mode can bemodified by aerosol dynamics, i.e., by coagulation, con-densation of gas-phase sulfuric acid on the aerosol sur-face, and thermodynamical water uptake depending onambient humidity. The sulfur chemistry module uses

E. Roeckner et al.: Impact of carbonaceous aerosol emissions on regional climate change

three-dimensional monthly mean oxidant fields of OH,H2O2, NO2, and O3 pre-calculated with a chemicaltransport model. Emissions of mineral dust, sea salt andoceanic DMS are calculated from variables internal tothe coupled model (wind speed at 10 m above the sur-face, soil moisture, snow cover, sea surface temperature,sea ice cover, DMS concentration in the uppermost layerof the ocean model). All other emissions are prescribed(see Sect 3). Sink processes such as dry deposition, sed-imentation, and wet deposition are calculated in explicitdependence of the ambient particle properties. Theprognostic treatment of size-distribution, composition,and mixing state allows the explicit calculation of theaerosol optical properties for each aerosol mode in theframework of the Mie scattering theory. Unlike the morecommon assumption of an external mixture, this methodaccounts for the observed large variability of the aerosolmixing state by incorporating its distinct effect on theaerosol radiative properties such as the absorptionenhancement of BC due to mixing with other aerosolcomponents (Ackerman and Toon 1981; Chylek et al.1995). Because the online calculation is computationallyexpensive, the optical properties are pre-computed andsupplied in look-up tables with three dimensions (Miesize parameter, real and imaginary part of the refractiveindex). This procedure provides extinction cross-section,single scattering albedo and asymmetry factor for eachmode and, thus, the necessary input to the radiationscheme in ECHAM5.

An additional prognostic equation, including trans-port, sources and sinks, is solved for the cloud dropletnumber concentration Nd (Lohmann et al. 1999).Nucleation of cloud droplets is parameterized semi-empirically in terms of the aerosol number size distribu-tion and updraft velocity (Lin and Leaitch 1997), whereasthe sink processes are parameterized in analogy to thoseformulated in ECHAM5 for the in-cloud liquid watercontent (ql). The cloud optical properties depend on thedroplet effective radius, which is a function of the internalmodel variables ql and Nd. These co-determine also theautoconversion rate expressed as Qaut � ql

2.47 Nd�1.79

(Khairoutdinov and Kogan 2000). Thus, the knowledgeof ql and Nd enables us to calculate both the first indirecteffect and the second indirect effect without employingthe prevalent empirical relationships for derivingNd fromsulfate aerosol mass only (e.g. Boucher and Lohmann1995). Finally, the model includes the semidirect aerosoleffect, i.e. the effect of absorbing aerosols on clouds viaatmospheric heating (Hansen et al. 1997; Ackermannet al. 2000; Lohmann and Feichter 2001). This heatingreduces the relative humidity and modifies the atmo-spheric stability. All BC is assumed to be interstitialbetween the cloud droplets. Since the specific absorptionof interstitial BC is smaller than the specific absorption ofBC within the cloud droplets (Chylek et al. 1996) thesemidirect effect is probably underestimated in ourmodel.

The Max Planck Institute ocean model (MPI-OM,Marsland et al. 2003) employs the primitive equations

for a hydrostatic Boussinesq fluid with a free surface at aresolution of 1.5�. The vertical discretization is on 40z-levels, and the bottom topography is resolved bymeans of partial grid cells. The poles of the curvilineargrid are shifted to land areas over Greenland and Ant-arctica. Parameterized processes include along-isopycnaldiffusion, horizontal tracer mixing by advection withunresolved eddies, vertical eddy mixing, near-surfacewind stirring, convective overturning, and slope con-vection. Concentration and thickness of sea ice are cal-culated by means of a dynamic and thermodynamic seaice model. In the AOGCM (Jungclaus et al. 2006), theocean passes to the atmosphere the sea surface temper-ature, sea ice concentration, sea ice thickness, snowdepth on ice, and the ocean surface velocities. Usingthese boundary values, the atmosphere model accumu-lates the forcing fluxes (wind stress, heat, freshwaterincluding river runoff and glacier calving, 10 m windspeed) during the coupling time step of 1 day. The dailymean fluxes are then passed to the ocean. All fluxes arecalculated separately for ice-covered and open waterpartitions of the grid cells. The model does not employflux adjustments. The marine biology is represented inthe HAMOCC5 model (Maier-Reimer et al. 2005). Itinteracts with the atmosphere via marine DMS emis-sions, affecting the sulfur cycle, and also via the depo-sition of mineral dust acting as micronutrient for themarine biosphere. The penetration depth of solar radi-ation in the ocean is parameterized in terms of the cal-culated chlorophyll concentration (Wetzel et al. 2006).The basic model features are summarized in Table 1.

3 Model experiments

The experiments include a pre-industrial control run(CTL), two twentieth century simulations (20C1, 20C2;

Table 1 Model summary

Model structure/processes

Model components Atmosphere (physical part):ECHAM5 (Roeckner et al. 2003)Aerosols: HAM (Stier et al. 2005a)Ocean (physical part): MPI-OM(Jungclaus et al. 2006)Marine biosphere: HAMOCC5(Maier-Reimer et al. 2005)

Resolution Atmosphere: T63L19Ocean: 1.5�L40

Time step Atmosphere: 20 minOcean: 72 min

Coupling timestep 1 dayPenetration of solarradiation in the ocean

Profile depends on calculatedchlorophyll concentration

Aerosol concentrations Calculated distributions of mineraldust, sea salt, sulfate, black carbon,particulate organic matter

Aerosol effectson radiation

Direct (all components), firstand second indirect effects,semidirect effect


years 1860–2000) with natural and anthropogenic radi-ative forcings, and two sensitivity experiments (EXP_1,EXP_2; years 2001–2050) both based on the SRES A1Bscenario, but with different assumptions on the emis-sions of carbonaceous aerosols. The 20C1 and 20C2

experiments are initialized at different states of CTL,15 years apart, and EXP_1 and EXP_2 are both ini-tialized at the end of year 2000 of experiment 20C1. Asummary of these experiments is given in Table 2. In theCTL run, the concentrations of well-mixed greenhousegases are fixed at year 1860 values (CO2 = 286.2 ppmv;CH4 = 805.6 ppbv, N2O = 276.7 pptv, CFC-11* = 12.5 pptv; CFC-12 = 0) where CFC-11* ac-counts for the radiative effect of minor species, includinga small contribution from natural sources (CF4). Theaerosol concentrations are calculated online from thenatural emission sources (see Stier et al. 2005a and ref-erences therein), whilst the ozone concentrations areprescribed as in ECHAM5. In the 20C runs the con-centrations of the well-mixed greenhouse gases are pre-scribed annually according to observations (smoothlyfitted to ice core data, direct observations, and SRESvalues for the year 2000; http://www.cnrm.meteo.fr/ensembles/public/results/results.html). Monthly strato-spheric and tropospheric ozone concentrations are pre-scribed as two-dimensional (latitude, height)distributions (Kiehl et al. 1999). Since backgroundozone is already used in the CTL run, only the‘anthropogenic perturbation’ is added to the back-ground field, i.e., the difference of concentrations in therespective year and the first year (1870) of the dataset.

The fossil fuel and industry emissions of SO2, BC andPOM are prescribed annually, whilst the emissions fromwildfires, domestic fuelwood consumption and agricul-tural waste burning are prescribed monthly, all accord-ing to the Japanese National Institute for EnvironmentalStudies (NIES) inventory (T. Nozawa et al., personalcommunication). Most of the emissions are prescribed inthe surface layer as lower boundary condition for the

vertical diffusion scheme. An exception is the SO2

emission from fossil fuel burning, where 88% are re-leased in the second lowest model layer at a height ofabout 150 m, and 12% are released in the surface layer(at about 30 m). The NIES inventory has been compiledfrom several databases of the Food and AgriculturalOrganization (FAO) of the United Nations, GlobalEmissions Inventory Activities (GEIA), energy statisticsin each nation, and the History Database of the GlobalEnvironment (HYDE) used for population changes andland use. This dataset has also been applied, for exam-ple, in the modeling study of Takemura et al. (2005). Theemissions of POM are derived from the BC emissions byassuming source specific emission ratios: POM/BC = 1.4 for fossil fuel, 5.6 for domestic fuelwoodconsumption and agricultural waste burning, and 11 forwildfires, respectively (F. Dentener, personal communi-cation). Optical depths of volcanic aerosols above thetropopause level are prescribed year to year in fourlatitude bands based on an updated dataset of Sato et al.(1993; http://www.giss.nasa.gov/data/strataer/). Varia-tions in solar irradiance are specified according to So-lanki and Krivova (2003).

In both scenario experiments EXP_1 and EXP_2 theconcentrations of greenhouse gases and SO2 emissionsare prescribed according to the SRES A1B scenario(years 2001–2050). The experiments differ only with re-spect to the assumptions on carbonaceous aerosolemissions. In EXP_1, since BC emission scenarios havenot been proposed by IPCC, we employ a BC emissionprojection suggested by NIES on the basis of the his-torical emissions for four major sources, i.e., fossil fuelcombustion, domestic fuelwood consumption, agricul-tural waste burning, and wildfires (T. Nozawa et al.,personal communication). For each of these sources,individual scaling indices and emission factors are ap-plied year to year for fuel consumption, regional popu-lation, area of cropland, and global population. Therespective POM emissions are obtained by using the

Table 2 Experiments and forcing data

Experimentname

Simulatedyears

Prescribed concentrations Prescribed emissions(DMS, dust, and seasalt are calculated)

Natural forcings

CTL 150 CO2, CH4, N2O, O3, CFC-11*, CFC-12 Natural emissionsonly: SO2, POM

–

20C1 1860–2000 CO2, CH4, N2O, O3, CFC-11*, CFC-12 SO2, BC, POM(observational estimates)

SolarVolcanic

20C2 1860–2000 CO2, CH4, N2O, O3, CFC-11*, CFC-12 SO2, BC, POM(observational estimates)

SolarVolcanic

EXP_1 2001–2050 CO2, CH4, N2O, O3, CFC-11*, CFC-12 SO2 (SRES A1B) BC,POM (NIES)a

–

EXP_2 2001–2050 CO2, CH4, N2O, O3, CFC-11*, CFC-12 SO2 (SRES A1B) BC andPOM fixed at year 2000 levels

–

In the pre-industrial CTL run concentrations/emissions are constant and anthropogenic emissions are zero. In the transient runsgreenhouse gas concentrations and anthropogenic emissions are time dependent. CFC-11* includes the radiative effects of minor species.The superscripts in experiment names denote simulations with identical forcing, initialized at different years of the CTL experimentaThe emission scenario of BC and POM is based on the National Institute for Environmental Studies (NIES) inventory (T. Nozawa,personal communication)


same emission ratios as for the 20C simulations. InEXP_2 the emissions of both BC and POM are keptconstant at the levels of year 2000 throughout the wholesimulation period (years 2001–2050).

4 Results

4.1 Global mean climate parameters

A thorough evaluation of the model simulations is be-yond the scope of this paper. However, the comparisonof a few key climate variables with observations shownin Table 3 indicates that the global mean state is inreasonable accordance with the observations. Never-theless, there are systematic biases such as the overesti-mation of column water vapor, cloud water path andprecipitation over the oceans, and the underestimationof total cloud cover and southern hemisphere (SH) seaice area. However, the expected impact of these biaseson the radiative fluxes is obviously not crucial: all of thesimulated fluxes are within the range of observationaluncertainty, which is about 5 W m�2 at the top of theatmosphere (TOA) and presumably even higher at thesurface.

4.2 Temporal evolution of global mean surface airtemperature

As shown in Fig. 1a, the model is able to simulate astable pre-industrial climate without a noticeable trendin the atmosphere (and also in the upper part of theocean including the sea ice, not shown). Furthermore,the observed twentieth century warming is well capturedin the 20C simulations. This includes the warming trendduring the first part of the twentieth century, the smalltrend between about 1950 and 1970 and, in particular,the positive quasi-linear trend in the last three decades(0.15 K/decade in 20C1, 0.20 K/decade in 20C2 com-pared to 0.17 K/decade in the observations). The overlystrong cooling after the volcanic eruption of the Krak-atoa (in year 1883) is an indication for a too large vol-canic forcing in the years following this event. In fact,the uncertainty in estimated volcanic forcings for thelarge eruptions from 1880–1915 could be a factor of twoor more (Ramaswamy et al. 2001).

In the scenario simulations (Fig. 1b), there is littleevidence for a noticeable impact of the future carbona-ceous aerosol emissions (as prescribed in EXP_1) on theevolution of global, annual mean surface air tempera-ture. Until about year 2040 the differences betweenEXP_1 and EXP_2 are negligibly small. In the lastdecade, the carbonaceous aerosol changes seem to exerta global cooling effect, but the difference lies within therange of the relatively large internal model variability.

4.3 Aerosols, optical depth and shortwave radiativeresponse

Table 4 gives an overview of the global mean totalemissions, aerosol burdens and lifetimes for the timeperiods (2001–2020) and (2031–2050). In addition, theresults for the year 2000 are compared with previousestimates. For dust and sea salt no references are givenbecause the results depend crucially on the assumed cut-off in the size distribution. In year 2000, the simulated orprescribed emissions are within the range of previousestimates, whilst the burdens of BC and POM aresomewhat on the high side. The changes (2031–2050)–(2001–2020) in the natural emissions are relatively small,i.e., +2% for dust,�1% for sea salt, and�3% for DMS.The total (natural plus anthropogenic) emission changesare negative for SO2 (�21%) but positive for BC(+37%) and POM (+25%). The changes in the burdensare even higher (+2% for SO4, despite the reduction inemissions, +50% for BC, and+38% for POM), becausethe average lifetimes increase by almost 1 day. This in-crease in aerosol lifetimes can most likely be attributed tothe projected shift of the emission sources frommiddle tolow latitudes, with a strong contribution of dry seasonwildfire emissions for BC and POM.

The spatial distribution of the annual BC emissionchanges between the time periods (2031–2050) and(2001–2020) is shown in Fig. 2. The total change

Table 3 Simulated and observed global, annual mean climatevariables

Variable 20C1,2 OBS

Surface air temperature 14.4 ± 0.1 14.3a

Precipitation (globe) 2.88 ± 0.01 2.61b, 2.66c

Precipitation (land) 1.94 ± 0.03 2.01b, 1.88c

Column water vapor 26.2 ± 0.3 24.5d

Cloud water path(liquid + ice)

110.0 ± 1.0 65.8e

Total cloud cover 61.7 ± 0.2 67.6e, 64.0f

NH sea ice area 9.8 ± 0.3 10.3g

SH sea ice area 6.9 ± 0.5 8.5g,h

Top-of-atmosphere (TOA)net shortwave radiation

232.3 ± 0.4 230e, 240i

Outgoing longwave radiation 231.5 ± 0.2 234e, 234i

TOA net shortwaveradiation (clear sky)

285.5 ± 0.1 284e, 288i

Outgoing longwaveradiation (clear sky)

260.7 ± 0.2 256e, 264i

TOA shortwave cloudradiative forcing

�53.3 ± 0.4 �54e, �48i

TOA longwave cloudradiative forcing

29.2 ± 0.1 21e, 30i

Surface net shortwaveradiation

160.0 ± 0.5 165e, 161j

Surface incominglongwave radiation

342.8 ± 0.8 348e,j, 344k

For the simulations the mean of 20C1 and 20C2 (years 1961–1990)is shown together with the standard deviation. Units are �C forsurface air temperature, mm day�1 for precipitation, kg m�2 forcolumn water vapor, g m�2 for liquid water path, % for cloudcover, 1012 m2 for sea ice area, and W m�2 for radiative fluxesReferences are aERA40 (Simmons and Gibson 2000), bGPCP(Huffmann et al. 1997), cCMAP (Xie and Arkin 1997), dRandelet al. (1996), eRossow and Schiffer (1999), fWarren and Hahn(2002), gParkinson et al. (1999), hGloersen et al. (1999), iHartmann(1993), jGupta et al. (1999), kWild et al. (2001)


(Fig. 2a) is characterized by increasing emissions overthe low-latitude continents and decreasing emissionsover Europe and China due to a reduction in fossil fuelemissions. Increased fossil fuel emissions are assumedpredominantly for India, the Middle East, Mexico andBrazil. The changes in biofuel emissions (sum ofdomestic fuelwood consumption and agricultural wasteburning) are relatively minor, whilst wildfires due toenhanced land clearing contribute substantially to theincrease in total BC emissions over Africa.

Figure 3 shows the geographic distributions of thedifferences (EXP_1–EXP_2) in the 20-year-mean aerosolburdens for BC and POM. A marked increase in EXP_1is simulated during the dry biomass-burning season(DJF) over central Africa and also over northern Indiain the Ganges–Brahmaputra valley. In JJA, the largestchanges are simulated in the relatively dry regions southof the equator (Africa, South America). Somewhatsmaller changes than in DJF are found in India due toenhanced wet deposition of BC and POM during thesummer monsoon season. The changes in total aerosolburden, including its seasonal variations, are reflected inthe changes of total mid-visible (550 nm) aerosol opticaldepth (AOD) shown in Fig. 4. Noteworthy is, in par-ticular, the substantial AOD increase during DJF incentral Africa. The increase in the mid-visible (550 nm)absorption AOD (Fig. 4c, d) is caused by the increase inthe BC burden (c.f., Fig. 3a, b) and likely to be inten-sified by the internal mixing with POM (Schnaiter et al.2005). More details on the transient evolution of theemissions, burdens and optical depths in 20C1 andEXP_1 can be found in Stier et al. (2005b).

a)

b)

Fig. 1 a Temporal evolution (years 1860–2000) in global, annualmean surface air temperature anomalies (K) with respect to themean 1860–1900 in observations (black) and model simulations (seeTable 2 for experiment notations). Green: Unforced pre-industrialcontrol run (CTL). Red: Twentieth century simulations 20C1 (fullline) and 20C2 (dashed line). Shown are smoothed time series (5-year running means). Observations: Jones et al. (2001): Global andhemispheric temperature anomalies 1856 to 2000—land and marineinstrumental records. http://www.cdiac.ornl.gov/trends/temp/jone-scru/jones.html. b Temporal evolution (2000–2050) in global,annual mean surface air temperature anomalies (K) with respectto the mean 1961–1990 (unsmoothed). Red: EXP_1, blue: EXP_2

Table 4 Global and annual mean aerosol and aerosol-precursor emissions, aerosol burdens and lifetimes (days in parantheses)

Species Emissions Burdens

2000 2001–2020 2031–2050 2000 2001–2020 2031–2050

SO2 88.8 104.0 82.5IPCC (2001)a 67–130SO4 1.02 (4.3 days) 1.18 (4.4 days) 1.20 (5.3 days)IPCC (2001)a 0.55–1.10Othersb 0.53–1.03DMS (ocean) 24.0 23.4 22.6 0.068 0.068 0.068IPCC (2001)a 13–36Othersb 0.059–0.102BC 16.0 19.1 26.2 0.28 (6.5 days) 0.34 (6.4 days) 0.51 (7.1 days)IPCC (2001)a 11–17Othersb 0.11–0.26BC (FF) 5.3 7.0 10.9BC (BF) 3.2 3.6 4.5BC (WF) 7.5 8.5 10.8POM 127.4 143.5 179.5 2.31 (6.6 days) 2.64 (6.7 days) 3.64 (7.4 days)IPCC (2001)a 55–200Othersb 0.99–1.87Dust 1,201 1,174 1,201 16.9 (5.1 days) 16.8 (5.2 days) 17.9 (5.4 days)Sea salt 6,396 6,319 6,273 12.9 (0.7 days) 12.9 (0.8 days) 13.0 (0.8 days)

The black carbon emissions are shown separately for fossil fuel (FF), biofuel (BF) and wildfires (WF). Note that BF is the sum of domesticfuelwood consumption and agricultural waste burning. Units are Tg year�1 for emissions and Tg for burden (TgS for sulfuric species)aPenner et al. (2001)bSee references in Stier et al. (2005a)


Figure 5 shows the differences (EXP_1–EXP_2) inclear-sky shortwave radiation, diagnosed separately forthe TOA, for the whole atmosphere (ATM = TOA-SFC) and for the surface (SFC). Figure 5a, b representsthe impact of BC and POM changes on the clear-skydirect aerosol effect but also, at higher latitudes, differ-ences in surface albedo due to slightly different snow andsea ice distributions in EXP_1 and EXP_2. In most landareas, especially over the bright desert regions, the in-creases in BC and POM result in a positive TOA clear-sky direct forcing. The increase in clear-sky atmosphericabsorption in EXP_1 (Fig. 5c, d) is caused by the in-crease in BC load. Noteworthy is the similarity in thedifference patterns of BC, absorption AOD, and clear-sky solar absorption in the atmosphere. The markedincrease in atmospheric absorption of up to 60 W m�2

in DJF over central Africa, which is comparable to thatestimated during a field campaign in northern India(Tripathi et al. 2005), is due to the strong increase inwildfire emissions in this particular emission scenario(c.f., Fig. 2c). The smaller changes in parts of Asia(Arabian Peninsula, India, Southeast Asia) are caused,predominantly, by the incease in fossil fuel combustion(Fig. 2b), whereas South America is affected by in-creases in both wildfire emissions and fossil fuel com-bustion. Consistent with the respective changes in BCand absorption AOD is the marked seasonality in the

atmospheric absorption. The change in clear-sky solarradiation at the surface (Fig. 5e, f) is almost a mirrorimage of the changes in the atmosphere. A widespreaddecrease is found in those regions where the increase inatmospheric absorption is large. To summarize, the as-sumed increase in BC emissions in EXP_1 leads to amarked change in the vertical distribution of solar en-ergy. More solar radiation is absorbed within theatmosphere and less at the surface. This vertical redis-tribution is most pronounced in central Africa duringthe dry biomass-burning season.

4.4 Annual mean climate response

Figure 6 shows the trend in annual mean surface airtemperature as simulated in EXP_1 (Fig. 6a), and alsothe response to changing emissions of carbonaceousaerosols (Fig. 6b). In most aspects the response patternis similar to that obtained from previous climate changestudies (e.g., Cubasch et al. 2001) with a markedwarming in the Arctic and over most parts of thenorthern hemisphere continents, but little change in theNorth Atlantic and in the southern Ocean. The mostobvious deviation from the familiar pattern is themoderate temperature change over central Africa wherethe greenhouse gas induced warming is largely

a) b)

d)c)

Fig. 2 Differences in black carbon (BC) emissions (EXP_1) between years (2031–2050) and (2001–2020). Units are gC m�2 year�1


compensated by a cooling caused by increasing emis-sions of carbonaceaous aerosols (Fig. 6b). This coolingis not only confined to central Africa but covers essen-tially all regions affected by increasing levels of carbo-naceous aerosols (c.f., Fig. 3) and, therefore, bydecreasing amounts of solar radiation absorbed at thesurface (c.f., Fig. 5e, f). The largest cooling relative toEXP_2 is found in regions with the strongest decrease inshortwave radiation at the surface (central Africa andnorthern India), but also downstream of the source re-gions in the tropical Atlantic. The extended low-latitudecooling pattern shown in Fig. 6b extends up to a heightof about 2 km above the surface (not shown). As to beexpected the most significant cooling is found during therespective dry seasons (DJF for central Africa and thetropical Atlantic, and JJA for Brazil and South Africa,not shown).

As for surface air temperature, considerable differ-ences between EXP_1 and EXP_2 are also found for thecomponents of the hydrological cycle shown in Fig. 7.The left panels show the difference (2031–2050)–(2001–2020) of precipition, runoff and soil moisture in EXP_1,whereas the right panels represent the respective differ-ences (EXP_1–EXP_2) for the time period (2031–2050),i.e., the impact of changing emissions of carbonaceousaerosols on precipitation, runoff and soil moisture. Inequatorial Africa, between about 15�N and 15�S, thetrend in all hydrological parameters is positive (left

panels), and the increases in BC and POM (c.f., Fig. 3)contribute significantly to this positive trend (rightpanels). In the southern part of Africa, the trend inprecipitation, runoff and soil moisture is negative, butthe increasing levels of BC and POM tend to reduce thenegative trend. Less systematic is the hydrological re-sponse in Brazil and India where spatially coherent po-sitive changes can only be found for soil moisture(Fig. 7f).

For testing the statistical significance of the changesshown in Figs. 6b, 7b, d, f, a non-parametric test hasbeen applied. The null hypothesis is formulated as fol-lows: the difference (DIFF = EXP_1–EXP_2) of anyvariable averaged over the years (2031–2050) is withinthe range of variations between randomly chosen20-year segments of a control run. This null hypothesisis tested against the alternative hypothesis that DIFF islarger than such random differences. The usual (para-metric) hypothesis test for the comparison of two meansis the Student’s t test, which, apart of some less criticaldistributional assumptions, requires that the sampleswithin the 20-year intervals under considerationare independent. Since this assumption is violated(Von Storch and Zwiers 2002), we apply a Gaussian test,i.e., we estimate the distribution of differences of20 years means from many additional data and deter-mine if DIFF is sufficiently far away in the tail of thefrequency distribution. If DIFF is larger than the 95%

a) b)

d)c)

Fig. 3 Differences (EXP_1 � EXP_2) of carbonaceous aerosol burdens in years (2031–2050). Units are mgC m�2


percentile, we reject our hypothesis with a risk of lessthan 5%. In order to enlarge the sample size, not onlydata from the unforced control run are used, but alsodata from both (detrended) twentieth century simula-tions 20C1 and 20C2. The resulting total of 380 years issplit into n = 19 chunks of 20 years. By forming dif-ferences across all available 20-year means we obtain(n(n � 1)/2) = 171 differences. We believe that thisrepresents an unbiased and robust estimation of the truedistribution.

The result of this test is shown in Fig. 8. The shadingdenotes those regions where a significant impact ofchanging BC and POM emissions on the respectivevariable is found. A comparison of Figs. 6b and 8ashows that the low-latitude surface cooling is statisticallysignificant at the 95% level in regions with a large in-crease in carbonaceous aerosol emissions (Brazil, centraland southern Africa, northern India), and also down-stream of the main African source region in the tropicalAtlantic, but no significant response can be detected inthe extratropics. The cooling pattern bears a strikingresemblance to the moistening of the soil (Fig. 7f), whichis also significant at the 95% level in parts of Brazil,Africa and northern India (Fig. 8d), whilst the patternof significant precipitation changes is spatially lesscoherent (Fig. 8b). Significant runoff changes are con-fined to equatorial Africa between about 15�N and 15�S(Fig. 8c). This change due to increasing BC and POM

levels explains almost 100% of the trend shown inFig. 7c. In the long-term mean, the runoff (R) is equal tothe difference between precipitation (P) and evaporation(E), and the excess water (R = P � E) is identical to thevertically integrated moisture convergence in the atmo-sphere. Although this is not exactly valid in transientclimate simulations, the changes in water storage in boththe atmosphere and the soil are orders of magnitudesmaller than the runoff changes shown in Fig. 7d, whichreflect the changes in the atmospheric dynamics andmoisture transport caused by increasing levels of car-bonaceous aerosols at lower latitudes.

4.5 Seasonal and regional changes

In this section the main focus is on the climate response inregions where the differences between EXP_1 and EXP_2are most apparent. In Fig. 9a, c the temporal changes of850 hPa wind in EXP_1 are shown for DJF and JAS,whilst the impact of changingBCandPOM levels on thesetrends is shown in Fig. 9b, d. In DJF, the most prominentfeature is the flow anomaly in the Gulf of Guinea(Fig. 9b), which is triggered by the strong atmosphericheat source (c.f., Fig. 5c). The flow anomaly (EXP_1–EXP_2) shown in Fig. 9b is actually larger than the tem-poral change inEXP_1 (Fig. 9a), i.e., the temporal changein EXP_2 (not shown) is opposite to that in EXP_1. The

Optical Depth DJF

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

a) Optical Depth JJA

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

b)

Absorption Optical Depth JJA

-0.12 -0.10 -0.08 -0.05 -0.03 0.00 0.03 0.05 0.08 0.10 0.12

d)Absorption Optical Depth DJF

-0.12 -0.10 -0.08 -0.05 -0.03 0.00 0.03 0.05 0.08 0.10 0.12

c)

Fig. 4 As Fig. 3 but for the differences in total mid-visible (550 nm) aerosol optical depth and mid-visible absorption optical depth


strong westerly anomaly shown in Fig. 9b bears someresemblance to the analytical solution obtained fromlinear theory with a diabatic heat source placed slightlynorth of the equator (see Gill 1980, Fig. 3).

The hydrological impact of the anomalous inflowinto the African continent during DJF is confined to thewet regions south of the equator that are susceptible toincreased moisture convergence (not shown). In the drysubsidence regions to the north of the equator, the en-hanced inflow from the ocean is able to modify thethermodynamical structure of the atmosphere, and alsothe surface energy fluxes, but its impact on precipitationis negligibly small. In the summer months, on the otherhand, (Fig. 9c, d) the anomalous westerlies across theWest African coast between the equator and 20�N are

indicative of an enhanced monsoon flow, which couldincrease the probability and amount of rainfall.

To see this, the seasonal evolution of the thermal andhydrological response to an increasing load of BC andPOM (EXP_1–EXP_2) is presented in Fig. 10 in theform of time-latitude Hovmoller diagrams for the low-latitude part of the African continent (average between10�W and 40�E). As already shown in Fig. 5e, there is asubstantial decrease in clear-sky shortwave radiation atthe surface, between about 0 and 10�N, during the rel-atively dry period November to March. Consistent withthe strong reduction in solar radiation along this latitudebelt is the marked surface cooling of more than 2 K, thedecrease in evaporation, and the increase in soil mois-ture. The precipitation response, on the other hand, is

a) b)

d)c)

e) f)

Fig. 5 As Fig. 3 but for the differences in shortwave clear-sky radiation. Units are W m�2


closely related to its climatological annual cycle withpositive anomalies being simulated in the respective wetseasons (October through March to the south of theequator, and June to October to the north of the equa-tor). The enhanced precipitation in June and July, in theSahel region between about 10 and 15�N, is supportedby the enhanced level of soil moisture, persistingthroughout the year, and by the higher evaporation ratesin the pre-monsoon season. This is consistent with themain conclusion from the Global Land-AtmosphereCoupling Experiment (GLACE; Koster et al. 2004) thatthe Sahel is one of a few regions in the world where thecoupling between soil moisture and precipitation isparticularly strong. The largest changes in runoff areconfined to near-equatorial regions where the soil isgenerally closer to saturation than further north orsouth. Here, the soil moisture anomalies are relativelysmall. As a result of the weaker BC forcing in the SH(Fig. 10a), the thermal and hydrological changes aregenerally smaller than those in the northern hemisphere.

Figure 11 shows the differences in annual mean heatfluxes, water fluxes and cloud parameters in EXP_1 andEXP_2 for three regions (central Africa, India, tropicalAtlantic) between the time periods (2031–2050) and(2001–2020). The most obvious difference between bothexperiments is the large increase in atmosphericabsorption in EXP_1 and the corresponding decrease insolar radiation at the surface. As discussed above, this iscaused by the substantial increase in the BC load in theseregions. The decrease in surface solar radiation, and theadditional cooling due to enhanced latent heat fluxes(Africa, India), are balanced by positive contributionsfrom longwave radiation and sensible heat fluxes, i.e.,the sensible heat fluxes are diminished. In the tropicalAtlantic, the latent heat fluxes are diminished as well andthe additional TOA cloud radiative cooling in both theshortwave and the longwave is substantially larger thanover the land areas. This is also evident for the responsein the shortwave cloud radiative cooling at the surface,which is about twice as high (�4 W m�2) compared toboth land areas. As for the heat fluxes, the changes in the

water fluxes, soil moisture and in the cloud parametersover Africa and India are systematically larger inEXP_1, and also positive with only one exception(Fig. 11b, d). For example, the runoff change in Africa isabout four times higher than in EXP_2. In India, therunoff increases in EXP_1 but decreases in EXP_2. Inthe tropical Atlantic (Fig. 11f) both precipitation andevaporation increase in EXP_2 but decrease in EXP_1although the liquid water path is increasing.

As shown in Fig. 12, the liquid water content in thetropical Atlantic is increased at model level 17, whichcorresponds to a height of approximately 400 m abovethe surface. The enhanced formation of a non-precipi-tating stratocumulus cloud is caused by the stabilizationof the boundary layer through the absorbing BC layerabove the cloud (Fig. 12a), which tends to heat theatmosphere and cool the surface (c.f., Fig. 11e). Addi-tionally, the cloud itself contributes to the total surfacecooling (c.f., Figs. 6b, 11e), which helps to maintain thestratocumulus formation. This response is consistentwith the results of large-eddy simulations of a marinestratocumulus-capped boundary layer (Johnson et al.2004), which show that cloud formation in the boundarylayer is enhanced if the absorbing aerosol layer residesabove the cloud layer (as in Fig. 12). This negativesemidirect aerosol effect is caused by the radiativeheating of the air above the inversion, which leads to alower cloud-top entrainment rate and a shallower,moister boundary layer (Johnson et al. 2004). As shownin Fig. 12b, the cloud response over the continent isdifferent. Here the positive cloud water anomaly be-tween about 3 and 5 km is related to the more frequentoccurrence of mid-level convective clouds, which detrainmoisture and cloud water above the BC heat source inthe lower troposphere and, thus, contribute to theenhancement of rainfall (c.f., Fig. 11d).

In Fig. 13 the global and annual mean changes inheat and water fluxes, as simulated in EXP_1, arecompared for three time periods denoted by 19C (years1861–1880), 20C (years 1961–1980) and 21C (years2031–2050). The heat flux changes are somewhat larger,

a) b)

Fig. 6 Differences in annual mean surface air temperature. a Years (2031–2050) minus (2001–2020) in experiment EXP_1 and b difference(EXP_1 – EXP_2) in years (2031–2050). Units are K


by typically 1 W m�2, in the twenty-first century (21C–20C) than in the twentieth century (20C–19C) (Fig. 13a).For the water components the differences are moresubstantial. For example, the precipitation over land isdecreasing by 1% in the twentieth century but increasingby almost 4% in the twenty-first century. In the twenty-first century, the increase in runoff (equivalent to themoisture flux from the oceans to the continents) is anorder of magnitude larger than in the twentieth century,and the increase in the liquid water path has more thandoubled. Obviously, the ocean to land transport of

moisture is substantially enhanced in the warmer andmoister atmosphere. Consistent with results from pre-industrial and present-day equilibrium experimentsincluding greenhouse gas, sulfate and carbonaceousaerosol forcing (Feichter et al. 2004; Liepert et al. 2004;Paeth and Feichter 2006), the global mean precipitationis decreasing in the twentieth century. In the twenty-firstcentury, due to the strong non-linearities associated withthe water cycle, the global mean precipitation increasesby 1%. This increase is more pronounced over land(3.8%) than over the ocean (0.2%).

a) b)

c) d)

e) f)

Fig. 7 Differences in annual mean precipitation, runoff and soilmoisture. Left panels: Differences (2031–2050) – (2001–2020) inEXP_1 for a precipitation, c runoff, and e soil moisture. Rightpanels: Differences between experiments (EXP_1 – EXP_2) for the

time period (2031–2050) for b precipitation, d runoff, and f soilmoisture. Units are mm day�1 for precipitation and runoff, and cmfor soil moisture


Fig. 8 Regions where the differences between EXP_1 and EXP_2(years 2031–2050) of annual mean surface air temperature (seeFig. 6b), precipitation (see Fig. 7b), runoff (see Fig. 7d) and soil

moisture (see Fig. 7f) are statistically significant at the 95% levelaccording to the non-parametric significance test described in thetext

a) b)

d)c)

Fig. 9 a, c Temporal change of 850 hPa wind (2031–2050) – (2001–2020) in EXP_1, and b, d differences (EXP_1 – EXP_2) of 850 hPawind in years (2031–2050)


The changes in the surface heat fluxes in the twentiethcentury are similar to those found in equilibriumexperiments by Liepert et al. (2004, numbers in paran-theses). The strong decrease in net shortwave radiationof �2.9 (�3.8) is approximately balanced by positivechanges of +1.7 (+1.9) for the net longwave radiation,+1.1 (+1.0) for the sensible heat flux, and +0.6 (+0.8)for the latent heat flux (in units of W m�2), i.e., thesensible and latent heat fluxes are decreasing. Note thatthe change in the total surface heat budget of 0.5 W m�2

in our transient experiment is identical to the change inthe total radiation budget at the top of the atmosphere.

This imbalance is due to the delayed response of theclimate system to the total radiative forcing by green-house gases and aerosols.

5 Summary and conclusions

The climate of the twentieth and twenty-first century hasbeen simulated with a coupled atmosphere-ocean modelincluding a detailed representation of troposphericaerosols and their climatic effects. The model predictsthe evolution of an ensemble of interacting internally

a) b)

c) d)

e) f)

Fig. 10 Hovmoller diagrams of monthly and zonal mean (10�W–40�E, land only) differences (EXP_1 – EXP_2) in years (2031–2050) of selected climate variables between 20�S and 20�N across

the African continent. Units are W m�2 for clear-sky shortwaveradiation at the surface, K for surface air temperature, cm for soilmoisture, and mm day�1 for precipitation, evaporation and runoff


Fig. 11 Changes in annual mean heat fluxes (left, units are W m�2)and components of the hydrological cycle (right, percentagechanges) between years (2031–2050) and (2001–2020) for threeregions: a, b Central Africa (10�W–40�E, 0–20�N) (land pointsonly); c, d Indian subcontinent (70–90�E, 5–30�N) (land pointsonly); e, f tropical Atlantic (10–60�W, 0–20�N) (sea points only).The results of experiment EXP_1 (grey columns) are compared withthose of experiment EXP_2 (white columns). Notations: toa top-

of-atmosphere, atm atmosphere, sfc surface, swo net clear-skyshortwave radiation, swc shortwave cloud forcing, lwc longwavecloud forcing, sw net shortwave radiation, lw net longwaveradiation, sh sensible heat flux (negative upward), lh latent heatflux (negative upward), prec precipitation, evap evaporation(positive upward), soil wat soil water, cc total cloud cover, lwpcloud liquid water path, iwp cloud ice water path


and externally mixed aerosol populations of differentchemical composition. Direct and indirect aerosol effectsare treated in a mechanistic way. This includes aparameterization of cloud droplet nucleation in terms ofthe aerosol size distribution and the dependency of cloudoptical properties and rain formation on the numberconcentrations of cloud droplets and aerosols. Exter-nally prescribed are the anthropogenic emissions ofaerosols and aerosol precursor gases, atmosphericgreenhouse gas concentrations, and variations in solarirradiance and volcanic aerosol optical depth.

The main focus of this study is on climate projectionsuntil year 2050, according to SRES scenario A1B, withdifferent assumptions on the future emissions of carbo-naceous aerosols (BC, POM). In the first experiment(EXP_1) the carbonaceous aerosols decrease at northern

mid-latitudes but increase at lower latitudes. In thesecond experiment (EXP_2) the carbonaceous aerosolemissions remain constant at the year 2000 levels. Thus,the difference EXP_1–EXP_2 represents the climate re-sponse to changing BC + POM emissions. The mostnotable response is a statistically significant surfacecooling in those regions, which are directly or indirectlyaffected by increasing BC + POM emissions (Brazil,tropical Atlantic, central and southern Africa, northernIndia). In contrast, the changes in the global-mean andmid-latitude temperatures are insignificant. The low-latitude surface cooling is caused primarily by the in-crease in the BC absorption of solar radiation of5–60 W m�2, depending on region and season, and by asimilar decrease in solar radiation absorbed at the sur-face. These results are qualitatively similar to those ob-

a) b)

Fig. 12 Differences of BC and cloud water mixing ratios(EXP_1 – EXP_2) in years (2031–2050). Shown are longitude/height (model levels) cross sections of the respective differencesaveraged in the latitude band 0–20�N. Units are lg kg�1 for BC

and mg kg�1 for cloud water. Model levels 11, 13, 15, 17 refer toheights above the surface of about 5,600, 3,100, 1,400, 400 m,respectively

Fig. 13 Changes in annual and global mean heat fluxes (left, unitsare W m�2) and components of the hydrological cycle (right,percentage changes) according to experiment EXP_1. The figurescompare the changes between years (2031–2050) and (1981–2000),shown as grey columns, with those between years (1981–2000) and(1861–1880), shown as white columns. The notations are as in

Fig. 11, except for precipitation, which is shown separately for thewhole globe (gl), for land (ld) and for sea (open water only). Notethat the sign convention for the sensible and latent surface heatfluxes is the same as in Fig. 11, with upward fluxes being negative.Accordingly, negative (positive) changes in sh and lh indicateincreasing (decreasing) fluxes


tained in an observational study by Krishnan and Ra-manathan (2002) and in a modeling study by Menonet al. (2002). The cooling of the tropical Atlantic can berelated to the increase in carbonaceous aerosols, whichhave their origin in the biomass burning regions incentral Africa. The radiative heating in the BC layer andthe corresponding surface cooling are causing a stabil-ization of the boundary layer over the tropical Atlantic.This favours the formation of stratiform clouds belowthe BC layer and amplifies the surface cooling.

The hydrological cycle is enhanced over the low-lat-itude continents where the increase in the carbonaceousaerosol load is most pronounced. Here the increase inprecipitation, runoff, and soil moisture is caused pri-marily by the additional atmospheric absorption ofsunlight due to higher BC levels and, subsequently, bythermally driven circulations which favour the transportof moisture from the adjacent oceans. The verticalredistribution of solar energy is particularly large duringthe dry season in central Africa when the anomalousatmospheric heating of up to 60 W m�2 and a corre-sponding decrease in surface solar radiation leads to amarked surface cooling, reduced evaporation and ahigher level of soil moisture, which persists throughoutthe year and contributes to the enhancement of precip-itation during the wet season. The moistening of the soilcovers essentially all land areas where the surface iscooling, whereas increased runoff is confined to centralAfrica, between about 15�S and 15�N, due to the in-creased atmospheric moisture transport from theAtlantic Ocean in response to the strong BC inducedatmospheric heat source.

The changes in the global mean surface heat fluxesand in the hydrology involve strong nonlinearities be-tween temperature, the water holding capacity of theatmosphere and the radiative perturbation, specificallythe BC induced absorption of solar radiation within theatmosphere. The increase in anthropogenic aerosolload since the beginning of the industrialization haspossibly caused a decrease in solar irradiation at thesurface (the so-called solar dimming) and a decrease inprecipitation despite global warming (Feichter et al.2004; Liepert et al. 2004; Wild et al. 2004). This is alsofound in our simulations. However, the future responsein the warmer and moister climate is different. Al-though the decrease in solar irradiance at the surfacecontinues, the global hydrological cycle is enhanced,specifically the moisture transport from ocean to land,which leads to an increase in global continental runoffof about 8%. As discussed above, this is primarilycaused by the marked increase in the low-latitude BCload in the twenty-first century. In these regions the BCdriven anomalous circulations are able to carry addi-tional moisture from the oceans to the continents.Thus, the soil becomes wetter, which, in turn, supportsthe monsoonal inflow of moisture during the rainyseason. This positive feedback loop is particularly effi-cient in a warmer and moisture atmosphere at lowerlatitudes. In the twentieth century simulation this

feedback loop cannot be identified for two reasons:First, because the atmosphere is colder and drier thanin the twenty-first century due to the lower level ofgreenhouse gases and, second, because the increase inthe BC load is confined to mid-latitude regions where,in contrast to the tropics, the dynamical response to athermal forcing depends crucially on advective effects.

Finally we note that past, present and future BCemissions are less reliable than those for greenhousegases or sulfur dioxide (Schaap et al. 2005; Streets et al.2004). IPCC has not provided ‘official’ BC emissionscenarios except for scaling the present-day inventorywith CO emission projections. Although the scenarioused in this sensitivity study is more elaborate, the futureBC emissions are subject to large uncertainties.

Acknowledgements We thank Toru Nozawa for providing the blackcarbon emissions, Gareth Jones for providing the stratosphericaerosol optical depths, Eigil Kaas for providing the solar irradi-ances, Jean-Francois Royer for providing the greenhouse gasconcentrations, and Gary Strand for providing the ozone data.Special thanks to Wolfgang Muller, Martin Schultz and Hans vonStorch for helpful comments on the original manuscript. This re-search was financed by the German Ministery for Education andResearch (BMBF) under the DEKLIM Project grant 01LD0021,and by the European Community under the ENSEMBLES Project.Part of this work has been funded by the Collaborative ResearchCentre (SFB) 512 sponsored by the German Science Foundation(DFG). The simulations were performed on the NEC SX-6supercomputer at the German Climate Computing Centre (DKRZ)in Hamburg.

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