# Large-Scale Modeling of Absorbing Aerosols and Their Semi-Direct Effects
## 2 Methods  
### Model Description  
The model simulations were carried out with the ECHAM6-HAM2 global aerosol-climate model (version echam6.3-ham2.3) [26]. ECHAM6 is the atmospheric general circulation model developed by the Max Planck Institute for Meteorology (MPIM) in Hamburg, Germany [25]. The dynamical core uses the spectral transform method, while tracer transport is realized with a semi-Lagrangian transport algorithm [27]. Subgrid-scale stratiform clouds are represented using the scheme of [PERSON] et al. [28] that diagnostically calculates the cloud fraction as a function of the relative humidity in the given grid cell if a threshold value is exceeded. Cloud liquid water and ice mixing ratios are computed prognostically according to [PERSON] and [PERSON] [29]. Radiative transfer in ECHAM6 is computed using the radiation transfer broadband model RRTMG (Rapid Radiative Transfer Model for GCMs) [30], using 16 and 14 bands for the shortwave and longwave parts of the spectrum, respectively. Atmospheric radiative transfer is computed based on compounds present in the atmosphere and their related optical properties. Optical properties of clouds are calculated for each band of the RRTMG scheme using Mie theory and the concentration of liquid water and ice condensates. The aerosol module HAM (Hamburg Aerosol Model) predicts the evolution of an aerosol ensemble considering the species sulfate, black carbon (BC), organic carbon, sea salt, and mineral dust. The aerosol size spectrum is described by seven log-normal modes: Nucleation mode, soluble (mixed) and insoluble Aitken, accumulation and coarse modes. The aerosol components are assumed to be internally mixed such that individual particles can consist of different species. To be considered soluble, at least one species within a particle must be soluble. Through condensation of soluble substances insoluble particles can become mixed (soluble). The aerosol distribution in each mode is described by the aerosol number, the median radius, and the standard deviation, which is set to 1.59 for the nucleation, Aitken, and accumulation modes and to 2 for the coarse modes. The median radius of each mode is calculated from the aerosol number and mass, which are transported as tracers within the respective mode. If interactions between aerosol particles and cloud droplets are considered explicitly with ECHAM6-HAM2, the cloud droplet activation is computed prognostically according to [PERSON] et al. [31] and [PERSON] and Ghan [32]. Anthropogenic emissions of particles and gaseous aerosol precursors in the model are specified for individual sectors. Here the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) emission dataset [5] is used. It is based on horizontally gridded decadal monthly mean anthropogenic emissions for the years 1850 to 2000 combined from regional and global inventories. SO\({}_{2}\), BC, and OC emissions from the relevant anthropogenic sectors including agricultural waste burning, aircraft, domestic, energy, industry, ships, transport, and waste are taken into account. In addition the ACCMIP dataset contains biomass burning emission fields including historical emissions. 75% of the smoke from biomass fires are injected evenly distributed vertically into the planetary boundary layer 17% in the first level and 8% in the second level above the boundary layer [33]. Emissions from biomass burning can be alternatively be prescribed from the Global Fire Assimilation System (GFAS) [34] for BC, OC, and SO\({}_{2}\). GFAS fire emissions are assimilated from fire radiative power from MODIS satellite observations, with combustion rates computed using conversion factors for specific land covers. In order to optimally match observed aerosol optical thickness [PERSON] et al. [34] recommend to scale the particulate emissions from the GFAS emission files by the factor 3.4. Mineral dust emissions are computed on-line utilizing modeled 10 m surface wind speeds [35; 36].