In this study, we used a new version of BCC_AGCM2.0.1_CUACE/Aero (Wang et al. , 2014 ; Zhang et al. , 2014 ) to study the ERF of three anthropogenic aerosols (SF, BC, and OC) and their comprehensive effects on the present and future global climate. Section 2 introduces the model and simulation design; Section 3 presents the main results, including the ERF due to anthropogenic aerosols and their climatic effects at present and in the future; and Section 4 give discussions and conclusions.

Most studies, like those mentioned above, concentrate on the climatic effects of anthropogenic aerosols in a specific region. However, it is also valuable to study the climatic effects of anthropogenic aerosols from a global perspective, because aerosols are continuously emitted into the atmosphere and transported a great distance from their sources (Zuluaga et al. , 2012 ). The climate change caused by anthropogenic aerosols in a specific region might be affected by global changes. For example, the contrast in aerosol distribution between the two hemispheres, i.e. more emissions from the more industrialized northern hemisphere (NH) than from the south hemisphere (SH), has the potential to affect large‐scale circulation. Most anthropogenic aerosols are known to be emitted from mid‐latitude regions in the NH; this extratropical forcing may have important effects on tropical climate (Broccoli et al. , 2006 ).

Anthropogenic aerosols play an important role in regional and global climate changes. Based on model results, Bollasina et al. ( 2011 ) found that the decrease in precipitation over South Asia during the second half of the 20th century was mainly caused by anthropogenic aerosols. Using the Beijing Climate Center's Atmospheric General Circulation Model and China Meteorological Administration's (CMA) Unified Atmospheric Chemistry Environment for aerosols, the aerosol‐climate online model of BCC_AGCM2.0.1_CUACE/Aero, Zhang et al. ( 2012a ) suggested that anthropogenic aerosols led to a weakening of the East Asia summer monsoon by reducing land‐sea surface temperature and pressure differences. In contrast, Jiang et al. ( 2013 ) used the National Center for Atmospheric Research's Community Atmospheric Model (NCAR CAM5) to study the effects of anthropogenic aerosols on the East Asia summer monsoon, and found that all anthropogenic aerosols suppressed precipitation in North China and enhanced precipitation in South China. Hu and Liu ( 2013 ) found that only simulations including anthropogenic aerosols can reproduce the observed decreasing trend of late spring precipitation from 1950 to 2000 in South China, by using the Community Earth System Model version 1.

The IPCC ( 2007 ) used adjusted RF as a main criterion, which permits stratospheric temperature to be adjusted to a new radiative balance. For aerosols, IRF and RF values are nearly the same, and both neglect the rapid adjustments of the troposphere and land, which should be distinguished from the climate response resulting from global averaged surface temperature change. Therefore, the IPCC ( 2013 ) defined a new concept, effective radiative forcing (ERF), which represents the changes in the net top of the atmospheric (TOA) downward radiative flux after allowing for atmospheric temperature, water vapour, and clouds and land albedo adjust to perturbations in radiative processes, but leaves the global mean surface temperature or ocean and sea ice (SI) conditions unchanged. Compared with IRF and RF, ERF performs better in predicting climate response to forcing factors, especially for short‐lifetime components like aerosols. Therefore, the RF of aerosols should be recalculated using the new concept of ERF.

One important measure of the climatic effects of aerosols is radiative forcing (RF). Both the IPCC ( 2001 ) and IPCC ( 2007 ) used the concept of instant radiative forcing (IRF), which is pure forcing without any feedback. However, as the ocean which mainly determines climate change takes much longer time than the atmosphere or land to respond to forcing, due to its large heat capacity. Therefore, some fast response or adjustment in the atmosphere and land should not be excluded when calculating RF, in order to project long‐term climate change, especially global mean surface temperature (Hansen et al. , 2005 ).

Aerosols can affect the earth's atmospheric radiation budget, directly through absorbing and scattering shortwave and long‐wave radiation (IPCC, 2007 ; Zhang et al. , 2012a , 2012b ; Wang et al. , 2014 ), and/or indirectly by altering cloud microphysical properties as cloud condensation nuclei and/or ice nuclei (Denman et al. , 2007 ; Boucher et al. , 2013 ). Since the 1990s, studies have increasingly focused on the radiative and climatic effects of aerosols. The Intergovernmental Panel on Climate Change (IPCC) ( 2007 ) discussed the climatic effects of six aerosols: sulphate (SF), nitrate, black carbon (BC), organic carbon (OC), dust, and sea salt, of which the first four are mainly emitted by human activities and the last two are mainly emitted by natural processes. There still exist large uncertainties in the study of anthropogenic driving climate change up to now (Myhre et al. , 2013 ).

Three sets of simulations (Table 1 ) were conducted. For comparison, a reference simulation (REF_EXP) was run with the one‐moment bulk cloud microphysical scheme and emission data of 2010. Simulations for calculating aerosols ERF (ERF_EXP) were run with the two‐moment bulk cloud microphysical scheme, which takes into account the direct and indirect effects of aerosols. In REF_EXP and ERF_EXP, the initial fields were the climatological mean of the National Centers for Environmental Prediction's (NCEP) 1971–2000 reanalysed data, and SST and SI from 1981 to 2012 monthly mean observations (Hurrell et al. , 2008 ). Simulations of the climatic effects of aerosols (RES_EXP) were also run with the two‐moment cloud microphysical scheme, but the fixed SST and SI were replaced by coupling a slab ocean model (Hansen et al. , 1984 ). The first two sets were run for a period of 22 years, and the results of the last 20 years were used for analysis. Because the coupled slab ocean needs a much longer time to spin up, RES_EXP simulations were run for 60 years with the results of the last 30 years used for analysis. The climatic effects of anthropogenic aerosols on the present climate were analysed by comparing RES_EXP simulations with 2010 and 1850 aerosol emissions, and effects on the future climate were analysed by comparing RES_EXP simulations with 2100 and 2010 aerosol emissions.

Two main methods can be used to calculate ERF. The first is to keep sea surface temperature (SST) and SI undisturbed, and allow other aspects of the climate to adjust: the difference in the TOA net radiative flux between two runs with and without forcing factors is regarded as the ERF (Hansen et al. , 2005 ). In the second method, when a forcing factor has no inter‐annual variation, a linear relation can be regressed between the changes in TOA net radiation flux and surface temperature: the intercept is taken as the ERF and the slope as feedback parameter (Gregory et al. , 2004 ). The advantages and disadvantages of these two methods have been discussed in detail in IPCC ( 2013 ): based on these findings and the fact that our modelled aerosols vary with projected climate, we selected the former method.

This article tries to estimate the ERF due to anthropogenic aerosols and their climatic effects in present relative to the pre‐industrial period. The emission data of aerosols are from the IPCC ( http://www.iiasa.ac.at/web‐apps/tnt/RcpDb ), including 1850 and RCP4.5 2010 and 2100 aerosol emissions. The RCP4.5 was used in this work because it is closest to what we can expect in the future (Chylek et al. , 2014 ). Sulphur dioxide (SO 2 ) emission increased by ∼110.16 Tg year −1 globally from 1850 to 2010, primarily due to industrial processes: SO 2 emission increased most obviously in industrial regions (mainly located in the mid‐latitudes of the NH). The emission of BC and OC increased by ∼5.07 and 14.60 Tg year −1 , respectively, from 1850 to 2010. In East Asia and South Asia, the emission of carbonous aerosols increased remarkably, but in North America, emission of these aerosols decreased slightly (figures not given). By 2100, emissions of anthropogenic aerosols are predicted to decrease dramatically (SO 2 , BC, and OC will decrease by about 93.72, 4.36, and 23.21 Tg year −1 , respectively), compared with the year 2010. In particular, the OC emission rate will be lower than its pre‐industrial level. The industrial regions, where anthropogenic aerosols increased from 1850 to 2010, will also be the major areas where anthropogenic aerosols will decrease in the future.

The BCC_AGCM2.0.1_CUACE/Aero includes five aerosols: SF, BC, OC, dust, and sea salt. Each aerosol type is divided into 12 bins with particle radius between 0.005 and 20.48 µm, Intersectional transfer of aerosol particles is allowed through coagulation (Gong et al. , 2003 ). Aerosols are assumed to be externally mixed. SF, OC, and sea salt are assumed to be hygroscopic, and the other two are assumed to be insoluble. By the coupling between BCC_AGCM2.0.1 and CUACE/Aero, aerosols are affected by the weather conditions, and on the other side affect climate through clouds and radiation processes. Wang et al. ( 2014 ) incorporated a two‐moment bulk cloud microphysical scheme (Gettelman et al. ( 2008 ); Morrison and Gettelman ( 2008 )) into the model; this can predict both the mass and number concentrations of cloud droplets and ice crystals. As a result, we were able to study aerosol–radiation and aerosol–cloud interaction, and their climatic effects. Before the incorporation of the two‐moment bulk cloud microphysical scheme, the BCC_AGCM2.0.1_CUACE/Aero used a one‐moment bulk cloud microphysical scheme, in which the microphysical properties of cloud, e.g. cloud droplet numeric concentration and cloud droplet effective radius, were specified based on observations ( Collins et al. , 2004 ; Wang et al. , 2014 ).

The CMA Unified Atmospheric Chemistry Environment/Aerosol model (CUACE/Aero), developed by the Institute of Atmospheric Composition of Chinese Academy of Meteorological Sciences, based on the Canadian Aerosol Module (CAM) developed by Gong et al. ( 2002 , 2003 ), is a comprehensive module incorporating emission, gaseous chemistry, transport, removal, and size‐segregated multi‐component aerosol algorithms. Zhou et al. ( 2012 ) gave a detailed description of the improvements in CUACE/Aero compared with CAM. BCC_AGCM2.0.1_CUACE/Aero simulates the atmospheric concentrations and optical properties of aerosols well (Zhang et al. , 2012a ; Wang et al. , 2013a , 2013b , 2014 ; Zhao et al. , 2014 ). The model joined the Aerosol Comparison between Observations and Models (AeroCom) Phase II to estimate the direct RF due to aerosols (Myhre et al. , 2013 ), and has been used to study aerosol climatic effects (Zhang et al. , 2012a ; Wang et al. , 2013a , 2013b , 2014 ; Zhao et al. , 2014 ).

For this study, the cloud‐radiation processes in the BCC_AGCM2.0.1 was improved by incorporating the cloud overlapping scheme of the Monte Carlo Independent Column Approximation (McICA) (Pincus et al. , 2003 ) with the new Beijing Climate Center radiation transfer model (BCC_RAD) developed by Zhang et al. ( 2003 , 2006a , 2006b ) and Jing and Zhang ( 2013 ) with new ice optical properties (Zhang et al. , 2015 ) and new aerosol optical properties ( Wei and Zhang, 2011 ; Zhang et al. , 2012b ). These schemes have improved the accuracy of the subgrid cloud structure and its radiative transfer process (Zhang et al. , 2014 ).

The model used for this study is the aerosol‐climate online model BCC_AGCM2.0.1_CUACE/Aero, developed by Zhang et al. ( 2012a ). The Beijing Climate Center's Atmospheric General Circulation Model, BCC_AGCM2.0.1, is based on the Eulerian spectral formulation of dynamical equations, and employs a horizontal T42 spectral resolution (approximately 2.8° × 2.8°) and a terrain‐following hybrid vertical coordinate with 26 levels, with the top located at about 2.9 hPa. Wu et al. ( 2010 ) assessed the BCC_AGCM2.0.1 in detail, and found that it can simulate the modern climate reasonably well.

3 Results

3.1 Simulated aerosol concentration and optical property analysis In ERF_EXP, the global averaged column burdens of SF, BC, and OC increased by ∼2.62, 0.098, and 0.44 mg m−2, respectively, from 1850 to 2010. The global mean aerosol optical depths (AOD) at 550 nm of SF, BC, and OC increased by ∼0.035, 0.00065, and 0.0062, respectively, from 1850 to 2010 (see Table 2). In 1850, industry had already started in Europe and North America, but the largest source of SF was still dimethyl sulphide (DMS), emitted mainly from mid‐latitude ocean, especially in the SH. Industrial development during the recent century and a half has remarkably increased SF over mid‐latitudes of the NH, especially over East Asia (Figure 2). Carbonous aerosols have increased over East Asia, Southeast Asia, and middle Africa, but have decreased slightly over east America, west Europe, southern South America, and Australia. Figure 2 clearly shows that anthropogenic aerosols have increased obviously near the Malay Peninsula and Sumatra; this finding is notable because this region is in the warm pool and on the path of the East Asian summer monsoon. The increase in carbonous aerosols in Malay Peninsula and Sumatra is very likely due to the biomass burning over these regions. Table 2. The simulated load burdens and AOD of anthropogenic aerosols for 2010 in ERF_EXP and REF_EXP. Simulation ERF_EXP REF_EXP Column burden per mg m−2 SF 3.4 (0.78) 2.0 BC 0.17 (0.072) 0.14 OC 1.6 (1.1) 1.3 AOD SF 0.047 (0.012) 0.018 BC 0.0011 (0.00045) 0.00087 OC 0.015 (0.0088) 0.0080 Wang et al. (2014) compared the aerosols simulated by the BCC_AGCM2.0.1_CUACE/Aero with one‐moment and two‐moment cloud microphysical schemes, and found that the results with the latter scheme were closer to the median of AeroCom. We explored how these two schemes result in different aerosol values (see Table 2). We compared the aerosol depositions in ERF_EXP (with the aerosol emissions in 2010) and REF_EXP (see Table 3). When at balance, the total emission and deposition rates of a certain type of aerosol must be equal, and the atmospheric content of an aerosol is determined only by its emission (or deposition) rate and lifetime. Because the aerosol emissions of these two simulations were the same, the increased simulated aerosols in ERF_EXP can be attributed to their longer lifetime. The lifetime of a certain type of aerosol is determined by how quickly it is removed from the atmosphere. Dry deposition means gravitational sedimentation of particles. In wet deposition, aerosol particles are scavenged by atmospheric hydrometeors. Because wet deposition is a faster process than dry deposition, the smaller wet deposition of aerosols (see Table 3) in ERF_EXP is the main reason for the larger aerosol burdens. A second factor is the larger portion that aerosol in‐cloud deposition occupies in total wet deposition in ERF_EXP (e.g. OC, Figure 2). In CUACE/Aero, aerosol in cloud droplets can be transferred either into precipitation through precipitation process or into dry aerosols through evaporation process (Gong et al., 2003). During in‐cloud deposition, aerosols are incorporated into cloud droplets. When cloud droplets convert to rainfall, aerosols are removed from the atmosphere, but when cloud droplets evaporate, aerosols are released into the atmosphere again. Table 3. The global mean removal rates of anthropogenic aerosols in ERF_EXP (with year 2010 aerosol emission) and REF_EXP (unit: 10−12 kg m−2 s−1). Simulation ERF_EXP REF_EXP Dry SF 1.64 1.38 BC 0.30 0.29 OC 2.32 2.27 In‐cloud SF 3.71 4.04 BC 0.16 0.17 OC 1.61 1.63 Bellow‐cloud SF 3.55 3.28 BC 0.011 0.017 OC 0.088 0.13 The main difference between one‐moment and two‐moment cloud microphysical schemes is the former prescribes the number and effective radius of cloud droplets, while the latter predicts them based on projected aerosol number concentrations. The above discussion has revealed that cloud microphysics is not only important to clouds but also to aerosols. Not only do aerosols affect cloud, as has already been extensively studied (e.g. Qian et al., 2009; Li et al., 2011); cloud appears to affect aerosol values considerably by modifying aerosol removal.

3.2 ERF due to anthropogenic aerosols According to the definition of ERF in IPCC (2013), aerosol–radiation interaction is one contributor to ERF, and the other is aerosol–cloud interaction. In a climate‐aerosol online coupled model, aerosols can change the properties of clouds, while aerosol–cloud interaction can alter aerosol burdens and AODs (Section 3.1). So, ERF not only includes rapid adjustment of atmosphere, cloud, and land surface temperature but also the adjustment of aerosols themselves. The total ERF of the three anthropogenic aerosols (the difference in net radiative fluxes between the two ERF_EXP simulations) was −2.49 W m−2; it would have been −2.44 W m−2 if the 2010 emissions from RCP8.5 had been used, the least among all pathways. ERF was distributed mainly over middle and low latitude areas in the NH (Figure 3(a)). The maximum absolute value of ERF was 10 W m−2 over Southeast Asia and its surrounding oceans. The primary reason for the large ERF in this region is that anthropogenic aerosols increased remarkably from 1850 to 2010. Figure 3(a) shows an obvious contrast in ERF distribution between the NH and SH. A series of climate responses might be induced by this meridional contrast in radiation disturbance, which will be discussed in the next section. The ERF of each anthropogenic aerosol was obtained by setting its emission to the 2010 level and keeping the emissions of the other two aerosols at the 1850 level. In this way, we obtained the global mean ERF of SF, BC, and OC as −2.37, 0.12, and −0.31 W m−2, respectively. Figure 4 shows the global distributions of the ERF of the three aerosols. Comparison of Figures 4(a) and 3(a) reveals that the spatial distribution of the ERF of SF is very similar to that of total ERF, indicating that the total ERF of anthropogenic aerosols can be mainly attributed to SF. This is a reasonable finding, because SF is the most burdened anthropogenic aerosol in the atmosphere, and is also a water‐soluble aerosol that can affect the properties of cloud as cloud condensation nuclei. To separate ERFari and ERFaci is very difficult in practice as has been illustrated in IPCC (2013), and especially true in BCC_AGCM2.0.1_CUACE/Aero, because aerosol is a necessary condition in cloud formulation in it. The total RF of the three anthropogenic aerosols was calculated by invoking the radiation module twice at each step, with the absorption and scattering of aerosols included and excluded. This resulted in a total RF for the three anthropogenic aerosols of −0.34 W m−2, smaller than the best estimate given by IPCC (2013) (−0.35 ± 0.5 W m−2). We did not include nitrate, which could contribute the part of underestimation. Comparing with the increase in aerosol AOD (shown in Figure 1), the maximum centre of the total RF shifted to coast oceans in East Asia (Figure 2(b)). One reason might be relevant to surface albedo effect, because low surface albedo on the ocean could make the RF of scattering aerosols more negative. Another important reason might be attributed to the large humidity over the ocean, as pointed out in Li et al. (2012) that high relative humidity over North Pacific and Atlantic Oceans could result in large SF optical depth over these areas in summer. The RF of SF, BC, and OC was calculated in the same way as the total RF: values were −0.33, 0.076, and −0.070 W m−2, respectively. The ERFari could be calculated by adding RF and rapid adjustments (Boucher et al., 2013). Comparing the ERF and RF of BC, a residual of 0.044 W m−2 could be considered as the rapid adjustments, which is in the range of −0.3 to 0.1 W m−2 given by AR5 (Boucher et al., 2013). The total ERFari of anthropogenic aerosols was then estimated as ∼ −0.30 W m−2, smaller than the best estimate given by AR5 (−0.45 ± 0.5) W m−2, but still in its range. Figure 1 Open in figure viewer PowerPoint Increase in AOD of (a) SF, (b) BC, and (c) OC from 1850 to 2010, in ERF_EXP. Figure 2 Open in figure viewer PowerPoint Difference in ratio of in‐cloud deposition to total wet deposition (unit: %) between ERF_EXP (with year 2010 aerosol emissions) and REF_EXP. ERFaci can be considered as the residual between ERF and ERFari ∼ −2.19 W m−2, which is close to the anthropogenic aerosol indirect effects (AIE) in Wang et al. (2014) and the simulated AIE by CAM5 (Ghan et al., 2012), but much larger than the values given by IPCC (2013) [−0.45 (−1.2, 0) W m−2]. Hoose et al. (2009) found that the AIE was very sensitive to the lower bound of cloud droplet number concentration (CDNCmin), and the absolute value of AIE decreased rapidly when the CDNCmin increased from 0 to 40 cm−3. Many models have adopted different CDNCmin, but CDNCmin was set at 0 in this study, as the prescription of CDNCmin is still physically unclear (Hoose et al., 2009). This is the main reason for the much larger simulated ERFaci.

3.3 Effects of anthropogenic aerosols on global temperature and precipitation From this section to Section 3.6, the effects of the changes in anthropogenic aerosols on global climate would be discussed, based on the results of BCC_AGCM2.0.1_CUACE/Aero coupled with a slab ocean model (RES_EXP simulations in Table 1). In terms of the global mean, the three anthropogenic aerosols led to a decrease in surface temperature of about 2.53 K. This value is larger than that reported by Kristjάnsson et al. (2005) and Takemura et al. (2005). The large change in surface temperature caused by anthropogenic aerosols might be attributed to the large simulated ERF which has been discussed in Section 3.2. But the ratios of surface temperature change to RF simulated in this work and Takemura et al. (2005) are both 1.02 K W−1 m2. Figure 5(a) shows that aerosol‐caused surface cooling occurred mainly in the NH, especially over mid‐ and high latitudes. This pattern of temperature change is one effect of the contrast in ERF distribution between the NH and SH (Figure 3(a)), and indicates that the northward gradient of temperature is enhanced by anthropogenic aerosols. The large temperature change in northern high latitudes is mainly attributed to the positive feedback of snow albedo. Although there are snow and ice covers over Antarctic, the changes in surface temperature over Antarctic are much smaller than that over Arctic, because of the buffering effect of the southern oceans, and the thermal mass of the east Antarctic ice sheet (IPCC, 2013). Figure 3 Open in figure viewer PowerPoint Total (a) ERF and (b) RF (unit: W m−2) of three anthropogenic aerosols. Figure 4 Open in figure viewer PowerPoint Distributions of ERFs (unit: W m−2) of (a) SF, (b) BC, and (c) OC. A decrease of ∼0.20 mm day−1 was seen in the global mean precipitation due to anthropogenic aerosols. Unlike the changes in temperature, the most obvious change in precipitation was seen in equatorial regions, with an apparent contrast on the two sides of the equator (Figure 5(b)). Precipitation was decreased on the north side and increased on the south side of the equator caused by the increase in anthropogenic aerosols from pre‐industrial to present. This pattern of precipitation change suggests that the rainfall centre of the inter‐tropical convergence zone (ITCZ) is tending to shift southward. It is also seen in Figure 5(b) that precipitation is decreased over East Asia, South Asia, and West African monsoon region (near Gulf of Guinea), consistent with the findings of Bollasina et al. (2011) and Zhang et al. (2012a). Bollasina et al. (2011) suggested that anthropogenic aerosols were the main reason for the decreased precipitation during the second half of the 20th century over South Asia. Zhang et al. (2012a) found that anthropogenic aerosols (SF, BC, and OC) led to a decrease in temperature (−0.58 K) and precipitation (−0.14 mm day−1) in summer over East Asia, but they did not explore aerosol–cloud interactions. Figure 5 Open in figure viewer PowerPoint Changes in (a) surface temperature (unit: K) and (b) precipitation (unit: mm day−1) due to increased anthropogenic aerosols from 1850 to 2010, with black dots indicating results below the significance cutoff of 0.05.

3.4 Effects of anthropogenic aerosols on global circulation To understand the change in precipitation pattern caused by anthropogenic aerosols, the effects of anthropogenic aerosols on global circulation and evaporation are discussed in this and next section. It is seen in Figure 6(a) that air descend is enhanced (or ascend is weakened) between 10° and 30°N, and air ascend is enhanced (or descend is weakened) between 0° and 20°S, because of anthropogenic aerosols. Correspondingly, zonal mean easterly wind between 0° and 25°N and westerly wind between 25° and 45°N were enhanced in lower level, and in upper level (∼200 hPa) zonal mean westerly wind between 0° and 40°N was enhanced (Figure 6(b)). The change in zonal mean zonal wind in tropics in the SH was contrary to that in the NH, but much weaker. The change in circulation caused by anthropogenic aerosols suggested that anthropogenic aerosols could enhance the Hadley Cell in the NH, and weaken it in the SH. The enhancement of the NH Hadley Cell agrees with the change in the NH tropospheric temperature (not shown), of which the northward temperature gradient is enhanced in the lower level (>500 hPa), while the southward temperature gradient is enhanced in the upper level (<300 hPa). Figure 6 Open in figure viewer PowerPoint Changes in (a) meridional circulation, (b) zonal mean zonal wind (unit: m s−1), and (c) zonal and vertical mean meridional heat transport (unit: K m s−1), with shaded areas in (a) and (b) indicating results below the significance cutoff of 0.05 and bars in (c) representing 1 standard deviation. A southward displacement of the ITCZ is consistently observed in paleoclimate data during cold periods in the NH. Broccoli et al. (2006) created a Gedankenexperiment to investigate the underlying mechanism, and suggested that this phenomenon was likely caused by changes in the atmospheric heat exchange between the tropics and mid‐ and high latitudes. This is proved here as it is shown in Figure 6(c) that the zonal and vertical mean northward heat transport is enhanced (or southward heat transport is weakened) over tropics. As the Hadley Cell is mainly responsible for the transportation of heat from equatorial regions to mid‐ and high latitudes, it is enhanced in the NH to transport more heat from equatorial regions to mid‐ and high latitudes where surface cooling is enhanced by anthropogenic aerosols. It should be noted that although for present condition the atmosphere transports more energy polewards that does the ocean, the oceanic energy transport is still not negligible (Vallis and Farneti, 2009). Because the northward energy transport by ocean is prescribed in the slab ocean model, this forces the atmosphere to compensate all the changes in forcings. A fully coupled ocean would adjust part of northward energy transport, and more detail studies of this topic are needed in the future. The above analysis clearly reveals that anthropogenic aerosols, emitted mainly from the NH, and especially from mid‐latitudes, cause an asymmetric change in temperature about the equator (with heavy surface cooling over mid‐ and high latitudes in the NH). This asymmetric temperature change enhances (weakens) heat transport from the equator to higher latitudes and the Hadley Cell in the NH (SH). As a result, the ITCZ rainfall centre tends to shift southward. It is seen in Figure 7(a) (vector pattern) that easterly wind was enhanced on 850 hPa level over low latitudes in the NH by anthropogenic aerosols, in correspondence with the NH enhanced Hadley Cell. Wind from land to ocean was strengthened over South Asia and West African monsoon region, which was not favourable to the rainfall over these regions. This suggests that the change in meridional circulation should be considered when studying the effects of aerosols on monsoon region climate, apart from the changes in land‐ocean temperature gradient and atmospheric stabilities. Figure 7 Open in figure viewer PowerPoint Change in (a) evaporation (unit: mm day−1, shaded pattern) and 850 hPa wind field (unit: m s−1, vector pattern) and (b) surface relative humidity (unit: %), due to increased anthropogenic aerosols from 1850 to 2010, with black dots in (b) indicating results below the significant cutoff of 0.05.

3.5 Effects of anthropogenic aerosols on global evaporation and relative humidity The increase in anthropogenic aerosols from 1850 to 2010 depressed global annual mean evaporation by about 0.20 mm day−1, because of the surface cooling (Figure 5(a)). It is seen from Figure 7(a) (shaded pattern) that the decrease in evaporation, especially over mid‐latitude oceans in the NH, is the reason for the decrease in global mean precipitation. Although the three anthropogenic aerosols depressed evaporation and precipitation on global average, they increased global mean relative humidity at the surface by about 0.46%. Figure 7(b) shows that more obvious increase in relative humidity occurred on lands than over oceans, e.g. mid‐latitude Eurasia, northwest America, mid South America, the south part of Africa, and Australia. The change in surface relative humidity depends on the relative changes in actual vapour pressure and saturate vapour pressure. The latter one represents the water vapour need for the air to get saturated, and is determined by the change in surface temperature. And the former one represents the water vapour provided by the ground to the air. The increase in relative humidity over most land areas indicates that saturate vapour pressure is decreased more than actual vapour pressure over these areas, and can be easily explained by the fact that surface temperature decreased more over land (Figure 5(a)), whereas, evaporation decreased more over oceans (Figure 6(c)).

3.6 Effects of anthropogenic aerosols on global cloud The increases in anthropogenic aerosols from pre‐industrial era to present led to an increase in global mean cloud cover (‘CC’, including high, median, and low cloud) of about 0.94%, and in global mean cloud water path (‘CWP’, including liquid and ice) of about 2.16 g m−2. Figure 8 shows that CC and CWP were increased mostly over mid‐ and low latitudes, and decreased mostly over high latitudes. An obvious contrast was observed on the two sides of the equator on both Figure 8(a) and (b), especially over equatorial Pacific Ocean, with increased CC and CWP on the south side and decreased CC and CWP on the north side of the equator. The change in precipitation caused by anthropogenic aerosols (Figure 5(b)) is in line with that in CC and CWP. Figure 8 Open in figure viewer PowerPoint Changes in (a) cloud cover (high + median + low cloud cover, unit: %) and (b) cloud water path (liquid + ice, unit: g m−2), caused by increased anthropogenic aerosols from 1850 to 2010, with black dots indicating results below the significant cutoff of 0.05. To better understand the effects of anthropogenic aerosols on clouds, scatter diagrams constructed from all model grids are given in Figure 9(a) and (b). The most numerous aerosol loads are grouped within 0–2 and 4–6 mg m−2, which locate mostly over oceans as shown in Figure 9(c). In these regions, the responses of CC and CWP, both positive and negative, to increasing aerosol load are largely related to changed circulation (Figure 6(a) and (b)) and atmospheric states induced by anthropogenic aerosols. However, in or near aerosol source regions where aerosol load was larger than 10 mg m−2, e.g. over East Asia, North India, Southeast Asia, and parts in Arabian Peninsula and Africa, CC and CWP show uniformly positive change and an increasing trend with aerosol load. The positive responses are primarily due to the strong aerosol–cloud interaction. This clearly indicates that increasing anthropogenic aerosol emission acts to increase CC and CWP. Figure 9 Open in figure viewer PowerPoint Scatter diagrams between 1850 and 2010 aerosol load (x axis, unit: mg m−2) and relative changes in (a) cloud cover (high + median + low cloud cover) and (b) cloud water path (y axis, unit: fraction); (c) global distribution of 1850–2010 aerosol load (unit: mg m−2). The changes in CC and CWP when ocean is fixed (not shown) are compared with Figures 8 and 9, in order to diminish the effects of ocean feedbacks. It is found that the changes in CC are more irregular in spatial distribution, and do not show increasing trend obviously with aerosol load when ocean is fixed. But the increase in anthropogenic aerosols from 1850 to 2010 still leads to a global mean increase in CC of about 0.31% when ocean is fixed, and the CC increase is mostly distributed over NH land. Comparing with Figure 8(b) and Figure 9(b), the changes in CWP are more uniformly positive (with a global mean increase of 6.35 g m−2) when ocean is fixed, which indicates that the increase in CWP because of increasing anthropogenic aerosols is more robust than that in CC.