Substantial impacts of absorbing aerosols on PBL evolution in EDMF-AERO modeling framework

Understanding the interactions between atmospheric aerosols and the evolution of the planetary boundary layer (PBL) is important for human health, climate, and weather forecasting models. In this study, an eddy-diffusivity mass-flux (EDMF) model is coupled with a radiative transfer model (RTM) to investigate the effects of aerosol optical depth ${\tau }_{\lambda }$ and single scattering albedo $\omega$ on the growth and thermodynamics of the PBL, or the so-called aerosol-PBL interactions (API). The developed model, called EDMF-AERO, was first extensively validated against in-situ radiosonde and microwave radiometer (MWR) observations in the summer, showing very good performance and enabling us to study the API effects proposed in the literature called stove and dome. Having established the model’s satisfactory accuracy we performed a sensitivity study, isolated API effects study, and estimated which compound effect of API influences PBL development more. For the stove case for ${\tau }_{500}=0.4$ and $\omega =0.9$, the PBL growth speeds up $\sim 8\text{\%}$ and warms up $\sim 12.5\text{\%}$ faster compared to the reference (${\tau }_{500}=0,\omega =1.0$). For the dome case for ${\tau }_{500}=0.4$ and $\omega =0.9$, the PBL growth slows down $\sim 5\text{\%}$ and warms up $\sim 4.5\text{\%}$ slower compared to the reference. In extreme conditions (${\tau }_{500}=1.5$, $\omega =0.81$) for the stove case we recorded $\sim 62\text{\%}$ and $\sim 72\text{\%}$ increase in PBL growth and heating rates respectively. For the dome case, we recorded $\sim 21\text{\%}$ and $\sim 22\text{\%}$ decreases in PBL growth and heating rates respectively. In both cases, the feedback loop severely impacts surface aerosol concentrations and enhances heat index. Based on the sensitivity runs, a parametrization relating the ${\tau }_{500}$ and $\omega$ on the PBL heating rate and PBL growth is suggested. The EDMF-AERO model developed in this study proves to be capable of providing new insights into the topic of API.