7.5.2.4 Global Climate Model Estimates of the Total Anthropogenic Aerosol Effect
The total anthropogenic aerosol effect as defined here includes estimates of the direct effect, semi-direct effect, indirect cloud albedo and cloud lifetime effect for warm clouds from several climate models. The total anthropogenic aerosol effect is obtained as the difference between a multi-year simulation with present-day aerosol emissions and a simulation representative for pre-industrial conditions, where anthropogenic emissions are turned off. It should be noted that the representation of the cloud lifetime effect in GCMs is essentially one of changing the auto-conversion of cloud water to rainwater.
The global mean total anthropogenic aerosol effect on net radiation at TOA from pre-industrial times to the present day is shown in Figure 7.21. Whereas Chapter 2 only considers the radiative forcing of the cloud albedo effect, here feedbacks are included in the radiative flux change. In most simulations shown in Figures 7.21 to 7.23, the total aerosol effect is restricted to warm clouds except for the simulations by Jacobson (2006) and Lohmann and Diehl (2006), who also include aerosol effects on mixed-phase and ice clouds. The total aerosol effect ranges from –0.2 W m–2 in the combined GCM plus satellite simulations (Quaas et al., 2006) to –2.3 W m–2 in the simulations by Ming et al. (2005), with an average forcing of –1.2 W m–2. The total aerosol effect is larger when sulphate aerosols are used as surrogates for all anthropogenic aerosols than if multiple aerosol types are considered (Figure 7.21). Although most model estimates also include the direct and semi-direct effects, their contribution to the TOA radiation is generally small compared with the indirect effect, ranging from +0.1 to –0.5 W m–2 due to variations in the locations of black carbon with respect to the cloud (Lohmann and Feichter, 2005). The simulated cloud lifetime effect in a subset of models displayed in Figure 7.21 varies between –0.3 and –1.4 W m–2 (Lohmann and Feichter, 2005), which highlights some of the differences among models. The importance of the cloud albedo effect compared with the cloud lifetime effect varies even when the models use the same aerosol fields (Penner et al., 2006). Other differences among the simulations include an empirical treatment of the relationship between aerosol mass and cloud droplet number concentration vs. a mechanistic relationship, the dependence of the indirect aerosol effect on the assumed background aerosol or cloud droplet number concentration, and the competition between natural and anthropogenic aerosols as CCN (Ghan et al., 1998; O’Dowd et al., 1999). Likewise, differences in the cloud microphysics scheme, especially in the auto-conversion rate, cause different cloud responses (e.g., A. Jones et al., 2001; Menon et al., 2002a, 2003; Penner et al., 2006).
All models agree that the total aerosol effect is larger over the NH than over the SH (Figure 7.21). The values of the NH total aerosol effect vary between –0.5 and –3.6 W m–2 and in the SH between slightly positive and –1.1 W m–2, with an average SH to NH ratio of 0.3. Estimates of the ocean/land partitioning of the total indirect effect vary from 0.03 to 1.8 with an average value of 0.7. While the combined European Centre for Medium Range Weather Forecasts/Max-Planck Institute for Meteorology Atmospheric GCM (ECHAM4) plus Polarisation and Directionality of the Earth’s Reflectance (POLDER) satellite estimate suggests that the total aerosol effect should be larger over oceans (Lohmann and Lesins, 2002), combined estimates of the Laboratoire de Météorologie Dynamique (LMD) and ECHAM4 GCMs with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data reach the opposite conclusion (Quaas et al., 2006). The average total aerosol effect over the ocean of –1 W m–2 agrees with estimates of between –1 and –1.6 W m–2 from the Advanced Very High Resolution Radiometer (AVHRR)/POLDER (Sekiguchi et al., 2003). Estimates from GCMs of the total aerosol effect are generally larger than those from inverse models (Anderson et al., 2003 and Chapter 9).
As compared with the estimates of the total aerosol effect in Lohmann and Feichter (2005), some new estimates (Chen and Penner, 2005; Rotstayn and Liu, 2005; Lohmann and Diehl, 2006) now also include the influence of aerosols on the cloud droplet size distribution (dispersion effect; Liu and Daum, 2002). The dispersion effect refers to a widening of the size distribution in the polluted clouds that partly counteracts the reduction in the effective cloud droplet radius in these clouds. Thus, if the dispersion effect is taken into account, the indirect cloud albedo aerosol effect is reduced by 12 to 42% (Peng and Lohmann, 2003; Rotstayn and Liu, 2003; Chen and Penner, 2005). The global mean total indirect aerosol effect in the simulation by Rotstayn and Liu (2005) has also been reduced due to a smaller cloud lifetime effect resulting from a new treatment of auto-conversion.
Global climate model estimates of the change in global mean precipitation due to the total aerosol effects are summarised in Figure 7.22. Consistent with the conflicting results from detailed cloud system studies, the change in global mean precipitation varies between 0 and –0.13 mm day–1. These differences are amplified over the SH, ranging from –0.06 mm day–1 to 0.12 mm day–1. In general, the decreases in precipitation are larger when the atmospheric GCMs are coupled to mixed-layer ocean models (green bars), where the sea surface temperature and, hence, evaporation are allowed to vary.