1School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
2Department of Environmental Sciences, University of Virginia, Charlottesville, VA 22904, USA
3Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA
4Air Chemistry Department, Max-Planck Institute of Chemistry, 55020 Mainz, Germany
5Institute for Atmospheric Physics, University of Mainz, 55099 Mainz, Germany
6Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Abstract. A coupled atmospheric chemistry and climate system model was developed using the modal aerosol version of the National Center for Atmospheric Research Community Atmosphere Model (modal-CAM) and the Max Planck Institute for Chemistry's Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA) to provide enhanced resolution of multiphase processes, particularly those involving inorganic halogens, and associated impacts on atmospheric composition and climate. Three Rosenbrock solvers (Ros-2, Ros-3, RODAS-3) were tested in conjunction with the basic load balancing options available to modal CAM (1) to establish an optimal configuration of the implicitly-solved multiphase chemistry module that maximizes both computational speed and repeatability of Ros-2 and RODAS-3 results versus Ros-3, and (2) to identify potential implementation strategies for future versions of this and similar coupled systems. RODAS-3 was faster than Ros-2 and Ros-3 with good reproduction of Ros-3 results, while Ros-2 was both slower and substantially less reproducible relative to Ros-3 results. Modal-CAM with MECCA chemistry was a factor of 15 slower than modal-CAM using standard chemistry. MECCA chemistry integration times demonstrated a systematic frequency distribution for all three solvers, and revealed that the change in run-time performance was due to a change in the frequency distribution chemical integration times; the peak frequency was similar for all solvers. This suggests that efficient chemistry-focused load-balancing schemes can be developed that rely on the parameters of this frequency distribution.