# Large-Scale Modeling of Absorbing Aerosols and Their Semi-Direct Effects
## 3 Results
### Radiative Effects
#### 3.2.2 Top of Atmosphere Radiative Effects
The resulting patterns (Figure 6c) indicate a higher positive forcing in US, Central Asia and Central Africa, where both BC and dust are present in BASE experiment. The direct radiative effect of BC above the comparably bright dust layer leads to additional positive forcing, similar to BC located above clouds. This effect is particularly relevant for dust from biomass burning in the northern hemisphere winter months. Biomass smoke layers located above dust layers were e.g., as observed during the SAMUM2 field experiment for winter conditions downwind of the Sahara/Sahel region over the Atlantic [6]. Similarly, the relation between cloud cover and SDE (Figure 7) from the effect of BC is actually slightly stronger without the effect of the dust aerosol, with a regression coefficient of \(-1.2\) Wm\({}^{-2}\)/(% cloud cover) (r\({}^{2}\) = 0.79) for the relationship of differences in SDE and cloud cover for the simulations noDUST and noABS. Figure 5: Scatterplot of model results of annual averaged BC TOA SDE in relation to cloud cover changes for the differences of the simulations BASE and noBC. Results from model grid cells that are statistically significant at 95% levels are plotted in dark blue, results from grid cells with results with statistical significance below 95% are plotted in light blue. Figure 6: (**a**) Direct radiative effect (DRE) of BC aerosol calculated from TOA radiative fluxes as difference of experiments noDUST-noABS; (**b**) instantaneous radiative effect (IDR) calculated as (**a**) but excluding changes in cloud cover by BC forcing via double call to the radiation scheme in the model, and (**c**) semi-direct effect (SDE) at the top of atmosphere in Wm\({}^{-2}\) calculated as DRE-IDR. (**d**): as (**c**), for the GFAS simulation. Grey areas indicate regions where the results are not statistically significant at 95% level. To isolate the effect of the aerosol-cloud interaction, the activation of cloud droplets by prognostic aerosol was not included in the model experiments. However, in reality the semi-direct effects and indirect effects of aerosol particles on clouds can be expected to interact with each other. An additional pair of model simulations including the indirect aerosol-cloud effect (BASEind, noBCind) have a radiative effect at TOA of +0.46 Wm\({}^{-2}\), with IDR of +0.41 Wm. The residual cloud effect due to the semi-direct and indirect effect is again small: SDE = 0.05 \(\pm\) 0.49) Wm\({}^{-2}\). Overall, semi-direct and indirect aerosol-cloud effects are presumably interacting and difficult to separate. Here, the values for the different components of BC forcing including the indirect aerosol-cloud effect are slightly smaller but still similar to the BASE case where the indirect effect is not considered. The standard deviations given in Table 2 are the consequence of the internal model variability. It can be considered as a lower limit for model errors. In addition, uncertainties in the atmospheric distribution of absorbing aerosol particles and their optical properties may cause uncertainties in the radiative aerosol radiative forcing and the atmospheric response. The response of the cloud cover and thus the semi-direct effect may depend on the parameterization of cloud formation in the model, a certain model dependence of the resolution can be expected.