In an effort to better represent aerosol transport in meso- and global-scale models, large eddy simulations (LES) from the NCAR Turbulence with Particles (NTLP) code are used to develop a Markov chain random walk model that predicts aerosol particle vertical profiles in a cloud-free marine atmospheric boundary layer (MABL). The evolution of vertical concentration profiles are simulated for a range of aerosol particle sizes and in a neutral and an unstable boundary layer. For the neutral boundary layer we find, based on the LES statistics, that there exist temporal correlation structures for particle positions, meaning that over short time intervals (T= 500 s, or T/Tneut= 0.25), particles near the bottom of the boundary are more likely to remain near the bottom of the boundary layer than being abruptly transported to the top, and vice versa. For the unstable boundary layer, a similar time interval of T= 500 s (T/Teddy= 0.39) exhibits weaker temporal correlation compared to the neutral case due to the strong non-local convective motions. In the limit of a large time interval, T= 2000 s (T/Teddy= 1.56), particles have been mixed throughout the MABL and virtually no correlation exists. We leverage this information to parameterize a Markov chain random walk model that accurately predicts the evolution of vertical concentration profiles for the range of particle size and stability tested in LES, even over short time intervals which exhibit substantial correlation. The new methodology has significant potential to be applied at the subgrid level for coarser-scale weather and climate models.