Kinetic limitations on cloud droplet formation and impact on cloud albedo

Abstract

Under certain conditions mass transfer limitations on the growth of cloud condensation nuclei (CCN) may have a significant impact on the number of droplets that can form in a cloud. The assumption that particles remain in equilibrium until activated may therefore not always be appropriate for aerosol populations existing in the atmosphere. This work identifies three mechanisms that lead to kinetic limitations, the effect of which on activated cloud droplet number and cloud albedo is assessed using a one-dimensional cloud parcel model with detailed microphysics for a variety of aerosol size distributions and updraft velocities. In assessing the effect of kinetic limitations, we have assumed as cloud droplets not only those that are strictly activated (as dictated by classical Kö hler theory), but also unactivated drops large enough to have an impact on cloud optical properties. Aerosol number concentration is found to be the key parameter that controls the significance of kinetic effects. Simulations indicate that the equilibrium assumption leads to an overprediction of droplet number by less than 10% for marine aerosol; this overprediction can exceed 40% for urban type aerosol. Overall, the effect of kinetic limitations on cloud albedo can be considered important when equilibrium activation theory consistently overpredicts droplet number by more than 10%. The maximum change in cloud albedo as a result of kinetic limitations is less than 0.005 for cases such as marine aerosol; however albedo differences can exceed 0.1 under more polluted conditions. Kinetic limitations are thus not expected to be climatically significant on a global scale, but can regionally have a large impact on cloud albedo.

Aerosol- and updraft-limited regimes of cloud droplet formation: influence of particle number, size and hygroscopicity on the activation of cloud condensation nuclei (CCN)

“…In most earlier studies of cloud droplet formation, the number concentration of aerosol particles did not exceed 10 4 cm −3 (e.g. Hjelmfelt et al, 1978;Hegg, 1999;Nenes et al, 2001;Feingold, 2003;Lance et al, 2004;Lohmann et al, 2004;Ervens et al, 2005;Segal and Khain, 2006;Kivekas et al, 2008;Cubison et al, 2008;Altaratz et al, 2008). This is realistic for regions with low or moderate air pollution, but in biomass burning plumes the aerosol particle number concentrations can reach up to ∼10 5 cm −3 Reid et al, 2005;Janhäll et al, 2009).…”

Influence of dust composition on cloud droplet formation

“…Since our focus is on the formation of cloud droplets Ghan et al (1998) and allow water competition due to dust to be compared with previous results for sea salt. However, we initially equilibrate aerosol at an RH of 97% rather than 100% (Ghan et al, 1998) to account for kinetic limitations near the cloud base (Nenes et al, 2001;Phinney et al, 2003). Coarse dust is represented by a lognormal distribution with σ g = 2.0 and D g = 1.5 or 2.2 µm, which is suitable for long-range transported dust (e.g., Patterson and Gillette, 1977;McTainsh et al, 1997;Singer et al, 2004).…”

Understanding aerosol-cloud interactions in the development of orographic cumulus congestus during IPHEx

“…where the thermal accommodation coefficient ( ) is taken as 0.96 (Nenes et al, 2001). Additional sensitivity tests of 5 CDNC to , ranging from 0.1 to 1 (Shaw and Lamb, 1999), were conducted and the resulting droplet concentrations indicate little sensitivity to this input parameter (not shown here).…”

“…An alternative modelling approach to investigate ACI is the cloud parcel model (CPM) that simulates aerosol activation and cloud droplet growth, as well as thermodynamic adaptation of ascending air parcels at μm and ms scales (Abdul-Razzak et al, 1998;Cooper et al, 1997;Flossmann et al, 1985;Jacobson and Turco, 1995;Kerkweg et al, 2003;Nenes et al, 2001;Pinsky and Khain, 2002;Snider et al, 2003). A synthesis of model formulation including spectral binning strategy, principal physical processes (i.e., condensational growth, collision-coalescence, entrainment), and key 5 aspects of their numerical implementation is presented in Table 1 for CPMs frequently referred to in the peer-reviewed literature.…”

“…In the past, process studies using CPMs targeted principally aerosol-CDNC closure between model simulations and field observations. For example, Conant et al (2004) conducted an aerosol-cloud droplet number closure study against observations from NASA's Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE) using the adiabatic CPM by Nenes et al (2001; that solves activation and condensation processes 10 only (see Table 1 for details). Using a condensation coefficient ( ) value of 0.06, they reported that predicted CDNC was on average within 15% of the observed CDNC in adiabatic cloud regions.…”