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Impact of aerosol processing in the transition of a stratocumulus cloud system to open cells: A comparison of Lagrangian and bin microphysics schemes in LES
  • Kamal Kant Chandrakar,
  • Hugh Morrison
Kamal Kant Chandrakar
NSF National Center for Atmospheric Research

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Hugh Morrison
National Center for Atmospheric Research (UCAR)
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Stratocumulus clouds, a key component of global climate, are sensitive to aerosol properties. Aerosol-cloud-precipitation interactions in these clouds influence their closed-to-open cell dynamical transition and hence cloud cover and radiative forcing. This study uses large-eddy simulations with Lagrangian super-particle and bin microphysics schemes to investigate impacts of aerosol scavenging and physical processing by clouds on drizzle initiation and the cellular transition process. The simulation using Lagrangian microphysics with explicit representation of cloud-borne aerosol and scavenging shows significant aerosol processing that impacts precipitation generation and consequently the closed-to-open cell transition. Sensitivity simulations using the bin scheme and their comparison with the Lagrangian microphysics simulation suggest that reduced aerosol concentration due to scavenging is a primary microphysical catalyst for enhanced precipitation using the Lagrangian scheme. However, changes in the aerosol distribution shape through processing also contribute appreciably to the differences in precipitation rate. Thus, both aerosol scavenging and processing drive earlier rain formation and the transition to open cells in the simulation with Lagrangian microphysics. This study also highlights a shortcoming of Eulerian bin microphysics producing smaller mean drop radius and cloud water mixing ratios owing to numerical diffusion. Initially larger mean radius and cloud mixing ratios using the Lagrangian scheme induce faster rain development compared to the bin scheme. A positive feedback in turn accelerates aerosol removal and further rain production using the Lagrangian scheme and, consequently, reduced cloud droplet number, increased mean size, and increased droplet spectral width.
02 Mar 2024Submitted to ESS Open Archive
05 Mar 2024Published in ESS Open Archive