Information about sea spray aerosol particle transport and their vertical distribution in the marine atmospheric boundary layer (MABL) is important in marine meteorological forecasting and geobiochemical models. However, due to difficulties in field observations, values of aerosol concentration are often limited to point measurements, and obtaining the size‐resolved concentration profiles is quite challenging. Hence, numerical and analytical studies are vital in modeling the transport of aerosols in the atmospheric boundary layer and beyond. Due to their coarse resolution, most mesoscale and global aerosol models do not accurately resolve the sea spray and aerosol concentrations in the MABL, especially in the surface layer. The objective of the present study is to develop a relatively simple, one‐dimensional analytical model to calculate concentration profiles of aerosols in the MABL. In this study, a new analytical model relating surface flux to vertical concentration profile in the MABL is proposed. The model accounts for the different atmospheric stability and particle settling velocity, thus providing size‐resolved vertical profiles of aerosol concentration. The equations developed here extend the surface layer similarity models to the mixed layer. Model results are compared to aerosol concentration profiles emitted from a surface source obtained from large eddy simulations, for both neutral and unstable atmospheric stability and for particle sizes ranging from 1 to 30 μm. Though the model is developed for sea spray aerosols, it can be used to calculate vertical concentration profiles for other types of settling particles, including dust and sand particles in the atmospheric boundary layer.
In an effort to better represent aerosol transport in mesoscale and global-scale models, large eddy simulations (LES) from the National Center for Atmospheric Research (NCAR) Turbulence with Particles (NTLP) code are used to develop a Markov chain random walk model that predicts aerosol particle 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 and a specific model time step, that there exist significant correlation for particle positions, meaning that 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 exhibits a weaker tendency for an aerosol particle to remain close to its current location compared to the neutral case due to the strong nonlocal convective motions. In the limit of a large time interval, particles have been mixed throughout the MABL and virtually no temporal correlation exists. We leverage this information to parameterize a Markov chain random walk model that accurately predicts the evolution of vertical concentration profiles. The new methodology has significant potential to be applied at the subgrid level for coarser-scale weather and climate models, the utility of which is shown by comparison to airborne field data and global aerosol models.
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