Aerosols affect the climate both directly and indirectly. The direct effect comes from their influence on the radiation balance by scattering and absorption of solar radiation, while the indirect effect is based on the ways in which aerosols interact via clouds. Currently the total anthropogenic aerosol forcing includes one of the main uncertainties in the assessment of human induced climate change. The aerosol direct radiative effect (ADRE) can be simulated with either the radiative transfer modelling or estimated with solar radiation and aerosol amount measurements. Both approaches include significant uncertainties and this thesis focuses on the uncertainties on the measurement based estimation of ADRE and the uncertainties therein.
The main scientific objectives of this thesis are to seek answers to the following four questions: 1) are the machine learning algorithms better than the a traditional lookup table (LUT) approach in estimating aerosol load (aerosol optical depth, AOD)?; 2) what is the role of water vapor (WVC) variability in the measurementbased regression method used to estimate the surface ADRE?; 3) how well do the radiative transfer codes, typically used in global aerosol models, agree?; 4) what is the impact of typically neglected diurnal aerosol variability in ADRE estimation?
The results show that: 1) the machine learning algorithms are able to provide AOD more accurately than the LUT approach for conditions of varying aerosol optical properties, since in the LUT approach the aerosol model (e.g. single scattering albedo, asymmetry factor) needs to be fixed in advance. 2) It was found that covariability of AOD and WVC can have an influence in ADRE estimates, when using groundbased measurements of surface solar radiation and AOD. This has not been taken into account previously, but needs to be considered when these methods are applied. 3) The model intercomparison
study, in which the models estimated the radiative fluxes for the same atmospheric states, revealed that there is relatively large diversity between models regarding the results from their radiative transfer modelling. 4) The main conclusion from the study focusing on the impact of systematic diurnal AOD cycles in aerosol direct radiative effect, was that even a notable diurnal change in AOD does not typically affect the 24h-average ADRE significantly
