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1. Introduction Proper representation of cloud microphysical and precipitation processes is critical for the simulation of weather and climate in atmospheric models. Despite decades of advancement, microphysics parameterization schemes still contain many uncertainties. This is due to an incomplete understanding of the important physical processes as well as the inherent complexity of hydrometeors in the real atmosphere. To represent the range of particles and their physical properties within
1. Introduction Proper representation of cloud microphysical and precipitation processes is critical for the simulation of weather and climate in atmospheric models. Despite decades of advancement, microphysics parameterization schemes still contain many uncertainties. This is due to an incomplete understanding of the important physical processes as well as the inherent complexity of hydrometeors in the real atmosphere. To represent the range of particles and their physical properties within
nucleation, drop condensational growth, and evaporation, in addition to coagulation and gravitational fallout (sedimentation). These microphysical processes can be formulated in LES models in two ways. In the first approach, referred to as explicit microphysics, cloud drop size distributions (DSD) are described by many size categories and evolve in unconstrained manner according to dynamic and microphysical processes. The computationally less expensive approach is to predict several moments of DSD rather
nucleation, drop condensational growth, and evaporation, in addition to coagulation and gravitational fallout (sedimentation). These microphysical processes can be formulated in LES models in two ways. In the first approach, referred to as explicit microphysics, cloud drop size distributions (DSD) are described by many size categories and evolve in unconstrained manner according to dynamic and microphysical processes. The computationally less expensive approach is to predict several moments of DSD rather
homogeneous aerosol freezing, however ( Koop et al. 2000 ). Formation of precipitation tends to involve coagulation of cloud particles in both ice- and liquid-only clouds. The purpose of the present paper is to explore theoretically how such regulation of cloud particles occurs in a microphysical system consisting of in-cloud activation of cloud particles interacting with precipitation. The focus is on microphysical equilibria in a single phase of condensate, either water or ice, and their stability in
homogeneous aerosol freezing, however ( Koop et al. 2000 ). Formation of precipitation tends to involve coagulation of cloud particles in both ice- and liquid-only clouds. The purpose of the present paper is to explore theoretically how such regulation of cloud particles occurs in a microphysical system consisting of in-cloud activation of cloud particles interacting with precipitation. The focus is on microphysical equilibria in a single phase of condensate, either water or ice, and their stability in
Aerosol–Cloud Interaction in Deep Convective Clouds over the Indian Peninsula Using Spectral (Bin) Microphysicseffects on deep convective clouds and precipitation are difficult to determine because of the coupling between microphysics and dynamics ( Tao et al. 2012 ; Altaratz et al. 2014 ; Fan et al. 2016 ). Several observational and modeling studies support the hypothesis that higher aerosol loading leads to the invigoration of DCC [see, e.g., Andreae et al. (2004) , Khain et al. (2005) , Rosenfeld et al. (2008) , Fan et al. (2013) , Storer et al. (2014) , an extensive review article by Altaratz et al
effects on deep convective clouds and precipitation are difficult to determine because of the coupling between microphysics and dynamics ( Tao et al. 2012 ; Altaratz et al. 2014 ; Fan et al. 2016 ). Several observational and modeling studies support the hypothesis that higher aerosol loading leads to the invigoration of DCC [see, e.g., Andreae et al. (2004) , Khain et al. (2005) , Rosenfeld et al. (2008) , Fan et al. (2013) , Storer et al. (2014) , an extensive review article by Altaratz et al
way including comprehensive field investigations, statistical evaluation experiments, and numerical studies have been tried since the 1950s. Limitations in the fundamental understanding of cloud dynamics, microphysics, and seeding mechanisms; the capabilities of instruments to detect the key features and physical processes; and the model capability and computing resources in the early studies [see reviews from Smith (1979) , Elliott (1986) , Rangno and Hobbs (1987) , Reynolds (1988) , Orville
way including comprehensive field investigations, statistical evaluation experiments, and numerical studies have been tried since the 1950s. Limitations in the fundamental understanding of cloud dynamics, microphysics, and seeding mechanisms; the capabilities of instruments to detect the key features and physical processes; and the model capability and computing resources in the early studies [see reviews from Smith (1979) , Elliott (1986) , Rangno and Hobbs (1987) , Reynolds (1988) , Orville
due to entrainment and mixing is critical for radiative properties of stratocumulus ( Chosson et al. 2004 ) and shallow convection ( Grabowski 2006 ), cloud systems essential for the earth’s climate. Herein, we investigate interactions between the cloud microphysical processes and turbulence with the emphasis on the net effect on the spectrum of cloud droplets. This paper extends our earlier study ( Andrejczuk et al. 2004 , hereafter AGMS ) that reported results from the pilot series of numerical
due to entrainment and mixing is critical for radiative properties of stratocumulus ( Chosson et al. 2004 ) and shallow convection ( Grabowski 2006 ), cloud systems essential for the earth’s climate. Herein, we investigate interactions between the cloud microphysical processes and turbulence with the emphasis on the net effect on the spectrum of cloud droplets. This paper extends our earlier study ( Andrejczuk et al. 2004 , hereafter AGMS ) that reported results from the pilot series of numerical
adjacent to the entrained air evaporate completely but the other droplets in the mixed parcel maintain their original sizes ( Baker et al. 1980 ). If this parcel ascends, droplets can grow faster than those in undiluted adiabatic parcel because with the reduced concentration they would have less competition for water vapor than those in the undiluted cloudy air ( Yang et al. 2016 ). To examine which mixing scenario is relevant to real clouds, several studies analyzed the microphysical relationship
adjacent to the entrained air evaporate completely but the other droplets in the mixed parcel maintain their original sizes ( Baker et al. 1980 ). If this parcel ascends, droplets can grow faster than those in undiluted adiabatic parcel because with the reduced concentration they would have less competition for water vapor than those in the undiluted cloudy air ( Yang et al. 2016 ). To examine which mixing scenario is relevant to real clouds, several studies analyzed the microphysical relationship
. 2011 ). Since then, there have been continuous efforts to improve the realism of the microphysics scheme by adding the number concentration of hydrometeors (e.g., Ferrier 1994 ; Seifert and Beheng 2001 ; Milbrandt and Yau 2005 ; Morrison et al. 2005 ; Thompson et al. 2008 ; Lim and Hong 2010 ) or by introducing spectral bin microphysics (e.g., Lynn et al. 2005 ). As the parameterization of the effects of partial cloudiness and cloud vertical overlap was earlier popular for radiation in
. 2011 ). Since then, there have been continuous efforts to improve the realism of the microphysics scheme by adding the number concentration of hydrometeors (e.g., Ferrier 1994 ; Seifert and Beheng 2001 ; Milbrandt and Yau 2005 ; Morrison et al. 2005 ; Thompson et al. 2008 ; Lim and Hong 2010 ) or by introducing spectral bin microphysics (e.g., Lynn et al. 2005 ). As the parameterization of the effects of partial cloudiness and cloud vertical overlap was earlier popular for radiation in
feedback-type responses comprise dynamical, thermodynamical, radiative or microphysical effects that act locally and/or on the cloud scale and will be referred to as adjustments in the following ( Stevens and Feingold 2009 ). Local and especially microphysical effects occur in any cloudy volume of air, while cloud-scale effects are usually associated with some degree of convection. Adjustments to aerosol-induced changes in droplet and crystal number are tightly linked to precipitation ( Stevens and
feedback-type responses comprise dynamical, thermodynamical, radiative or microphysical effects that act locally and/or on the cloud scale and will be referred to as adjustments in the following ( Stevens and Feingold 2009 ). Local and especially microphysical effects occur in any cloudy volume of air, while cloud-scale effects are usually associated with some degree of convection. Adjustments to aerosol-induced changes in droplet and crystal number are tightly linked to precipitation ( Stevens and
Clouds play a key role at all different scales, from local weather to global climate ( Fu et al. 2011 ; Stevens and Bony 2013 ; Stephens et al. 2015 ; Bony et al. 2015) . Albeit measurements of cloud microphysics are possible with in situ cloud probes, these become impractical at a global scale. Conversely, observations from space offer the capability to monitor clouds over the entire globe, investigating cloud–radiation interactions and cloud microphysical properties ( Stephens and
Clouds play a key role at all different scales, from local weather to global climate ( Fu et al. 2011 ; Stevens and Bony 2013 ; Stephens et al. 2015 ; Bony et al. 2015) . Albeit measurements of cloud microphysics are possible with in situ cloud probes, these become impractical at a global scale. Conversely, observations from space offer the capability to monitor clouds over the entire globe, investigating cloud–radiation interactions and cloud microphysical properties ( Stephens and
