A method to represent subgrid-scale updraft velocity in kilometer-scale models: Implication for aerosol activation

Abstract

©2014. American Geophysical Union. All Rights Reserved. Updraft velocities strongly control the activation of aerosol particles or that component that act as cloud condensation nuclei (CCN). For kilometer-scale models, vertical motions are partially resolved but the subgrid-scale (SGS) contribution needs to be parametrized or constrained to properly represent the activation of CCNs. This study presents a method to estimate the missing SGS (or unresolved) contribution to vertical velocity variability in models with horizontal grid sizes up to ∼2 km. A framework based on Large Eddy Simulations (LES) and high-resolution aircraft observations of stratocumulus and shallow cumulus clouds has been developed and applied to output from the United Kingdom Met Office Unified Model (UM) operating at kilometer-scale resolutions in numerical weather prediction configuration. For a stratocumulus deck simulation, we show that the UM 1 km model underestimates significantly the variability of updraft velocity with an averaged cloud base standard deviation between 0.04 and 0.05 m s-1 compared to LES and aircraft estimates of 0.38 and 0.54 m s-1, respectively. Once the SGS variability is considered, the UM corrected averages are between 0.34 and 0.44 m s-1. Off-line calculations of CCN-activated fraction using an activation scheme have been performed to illustrate the implication of including the SGS vertical velocity. It suggests increased CCN-activated fraction from 0.52 to 0.89 (respectively, 0.10 to 0.54) for a clean (respectively, polluted) aerosol environment for simulations with a 1 km horizontal grid size. Our results highlight the importance of representing the SGS vertical velocity in kilometer-scale simulations of aerosol-cloud interactions. Key PointsWe seek to improve the aerosol activation behavior in kilometer-scale modelsA method to constrain the subgrid-scale updraft velocity is presentedWe highlight the potential implication for aerosol-cloud interactions modeling.