Description and evaluation of GMXe: a new aerosol submodel for global simulations (v1)
- 1Max Planck Institute for Chemistry, Mainz, Germany
- 2School of Earth and Environment, University of Leeds, Leeds, UK
- 3Schools of Earth & Atmospheric Sciences and Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
- 4Institute of Chemical Engineering and High Temperature Chemical Processes, Foundation for Research and Technology – Hellas, Patras, Greece
- 5Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
- 6Joint Research Centre, Institute for Environment and Sustainability, Climate Change Unit, Ispra, Italy
- 7The Cyprus Institute, Energy, Environment and Water Research Centre, Nicosia, Cyprus
Abstract. We present a new aerosol microphysics and gas aerosol partitioning submodel (Global Modal-aerosol eXtension, GMXe) implemented within the ECHAM/MESSy Atmospheric Chemistry model (EMAC, version 1.8). The submodel is computationally efficient and is suitable for medium to long term simulations with global and regional models. The aerosol size distribution is treated using 7 log-normal modes and has the same microphysical core as the M7 submodel (Vignati et al., 2004).
The main developments in this work are: (i) the extension of the aerosol emission routines and the M7 microphysics, so that an increased (and variable) number of aerosol species can be treated (new species include sodium and chloride, and potentially magnesium, calcium, and potassium), (ii) the coupling of the aerosol microphysics to a choice of treatments of gas/aerosol partitioning to allow the treatment of semi-volatile aerosol, and, (iii) the implementation and evaluation of the developed submodel within the EMAC model of atmospheric chemistry.
Simulated concentrations of black carbon, particulate organic matter, dust, sea spray, sulfate and ammonium aerosol are shown to be in good agreement with observations (for all species at least 40% of modeled values are within a factor of 2 of the observations). The distribution of nitrate aerosol is compared to observations in both clean and polluted regions. Concentrations in polluted continental regions are simulated quite well, but there is a general tendency to overestimate nitrate, particularly in coastal regions (geometric mean of modelled values/geometric mean of observed data ≈2). In all regions considered more than 40% of nitrate concentrations are within a factor of two of the observations. Marine nitrate concentrations are well captured with 96% of modeled values within a factor of 2 of the observations.