Abstract
Abstract. This work uses the number concentration-effective diameter phase-space to test cloud sensitivity to variations in the aerosol population characteristics, such as the aerosol size distribution, number concentration and hygroscopicity. It is based on the information from the top of a cloud simulated by a bin-microphysics single-column model, for initial conditions typical of the Amazon, using different assumptions regarding the entrainment and the aerosol size distribution. It is shown that the cloud-top evolution can be very sensitive to aerosol properties, but the relative importance of each parameter is variable. The sensitivity to each aerosol characteristic varies as a function of the parameter tested and is conditioned by the base values of the other parameters, showing a specific dependence for each configuration of the model. When both the entrainment and the bin treatment of the aerosol are allowed, the largest influence on the droplet size distribution sensitivity was obtained for the median radius of the aerosols and not for the total number concentration of aerosols. Our results reinforce that the cloud condensation nuclei activity can not be predicted solely on the basis of the w∕Na supersaturation-based regimes.
Highlights
We extended the discussion to the sensitivity to the aerosol median size and number concentration, and consider their effects on both droplet size and concentration
We illustrated the influence of the aerosol number concentration, the median radius and geometric standard deviation of the PSD, in addition to the hygroscopicity of the aerosols on the number concentration and effective diameter of droplets at the top of warm-phase clouds for initial conditions typical of the Amazon
In our analysis, the intensity of the droplet activation is mostly determined by the amount of suitable-sized aerosols, i.e., the shape and median radius of the PSD, rather than on the total number concentration of aerosols
Summary
Because of their role as cloud condensation nuclei (CCN) and ice nucleating particles, aerosols can affect the cloud optical properties (Twomey, 1974) and determine the onset of precipitation (Albrecht, 1989; Braga et al, 2017; Rosenfeld et al, 2008; Seifert and Beheng, 2006) and ice formation (Andreae et al, 2004; Fan et al, 2007; Gonçalves et al, 2015; Khain et al, 2005; Koren et al, 2010; Lee et al, 2008; Li et al, 2011). Aerosols play an indirect role in the thermodynamics of local cloud fields via the suppression of cold pools and the enhancement of atmospheric instability (Heiblum et al, 2016). Knowledge about the characteristics of the effects of atmospheric aerosols on clouds and precipitation is still lacking and remains an important source of uncertainty in meteorological models. Many studies have been dedicated to quantifying the effect of aerosols on clouds via sensitivity calculations, using both modeling and observational approaches. Sensitivity studies intend to determine whether the variability of some characteristics of the aerosol population can be neglected without introducing significant errors in the description of clouds
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