Abstract
One fundamental question about atmospheric moist convection processes that remains debated is whether or under what conditions a relevant variability in background aerosol concentrations may have a significant dynamical impact on convective clouds and their associated precipitation. Furthermore, current climate models must parameterize both the microphysical and the cumulus convection processes, but this is usually implemented separately, whereas in nature there is a strong coupling between them. As a first step to improve our understanding of these two problems, we investigate how aerosol concentrations modify key properties of updrafts in eight large-eddy permitting regional simulations of a case study of scattered convection over Houston, Texas, in which convection is explicitly simulated and microphysical processes are parameterized. Dynamical and liquid-phase microphysical responses are investigated using two different reference frames: static cloudy-updraft grid cells versus tracked cumulus thermals. In both frameworks we observe the expected microphysical responses to higher aerosol concentrations, such as higher cloud number concentrations and lower rain number concentrations. In terms of the dynamical responses, both frameworks indicate weak impacts of varying aerosol concentrations relative to the noise between simulations over the observationally derived range of aerosol variability for this case study. On the other hand, results suggest that analysis of thermals can provide a better pathway to sample the most relevant convective processes. For instance, vertical velocity from thermals is significantly higher at upper levels than when sampled from cloudy-updraft grid points, and several microphysical variables have higher average values in the cumulus thermal framework than in the cloudy-updraft framework. In addition, the thermal analysis is seen to add rich quantitative information about the rates and covariability of microphysical processes spatially and throughout tracked thermal lifecycles, which can serve as a stronger foundation for improving subgrid-scale parameterizations. These results suggest that cumulus thermals are more realistic dynamical building blocks of cumulus convection, acting as natural cloud chambers for microphysical processes.
Highlights
The net impacts of atmospheric aerosol concentration on deep convective cloud systems and their environment remain highly uncertain, with mixed results that do not generally yield conclusive answers yet (e.g., Khain et al, 2008; Tao et al, 2012)
Microphysical quantities are found to peak at thermal centers nearly universally, which reinforces the important role of thermals as the building blocks of convection from both a dynamical and microphysical point of view
In order to investigate the coupling between updraft dynamics and microphysics, we study the impact of ambient aerosol concentration on deep convection in a series of eight simulations at 250 m horizontal grid spacing of a case study over Houston, Texas, where initial background aerosol concentrations are systematically varied from 500 to 4000 cm−3 in intervals of 500 cm−3
Summary
The net impacts of atmospheric aerosol concentration on deep convective cloud systems and their environment remain highly uncertain, with mixed results that do not generally yield conclusive answers yet (e.g., Khain et al, 2008; Tao et al, 2012). A higher aerosol concentration generally corresponds to more condensation nuclei at any given supersaturation, which, in turn, is expected to produce more but smaller cloud droplets within a convective updraft. This may delay the occurrence of initial warm precipitation formation due to a less efficient collision–coalescence process, enhancing latent heat release above the freezing level (Rosenfeld et al, 2008). It is even more challenging to represent such processes in a climate model because updraft microphysics and dynamics are often simplified by cumulus parameterization at a much coarser spatiotemporal resolution (McFarlane, 2011) To better represent such processes in climate models, it is imperative to disentangle aerosol-deep convection interactions from the wider spectrum of microphysics and dynamical processes
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