The importance of vertical velocity variability for estimates of the indirect aerosol effects

Abstract

The activation of aerosols to form cloud droplets is dependent upon vertical velocities whose local variability is not typically resolved at the GCM grid scale. Consequently, it is necessary to represent the sub-grid-scale variability of vertical velocity in the calculation of cloud droplet number concentration. <br><br> This study uses the UK Chemistry and Aerosols community model (UKCA) within the Hadley Centre Global Environmental Model (HadGEM3), coupled for the first time to an explicit aerosol activation parameterisation, and hence known as UKCA-Activate. We explore the range of uncertainty in estimates of the indirect aerosol effects attributable to the choice of parameterisation of the sub-grid-scale variability of vertical velocity in HadGEM-UKCA. Results of simulations demonstrate that the use of a characteristic vertical velocity cannot replicate results derived with a distribution of vertical velocities, and is to be discouraged in GCMs. <br><br> This study focuses on the effect of the variance (&sigma;_w²) of a Gaussian pdf of vertical velocity. Fixed values of &sigma;_w² (spanning the range measured in situ by nine flight campaigns found in the literature) and a configuration in which &sigma;_w² depends on turbulent kinetic energy are tested. Results from the mid-range fixed &sigma;_w² and TKE-based configurations both compare well with observed vertical velocity distributions and cloud droplet number concentrations. <br><br> The radiative flux perturbation due to the total effects of anthropogenic aerosol is estimated at &minus;1.4 W m^&minus;2 with &sigma;_w² = 0.1 m s^&minus;1, &minus;1.7 W m^&minus;2 with &sigma;_w² derived from TKE, &minus;1.9 W m^&minus;2 with &sigma;_w = 0.4 m s^&minus;1 and &minus;2.0 W m^&minus;2 with &sigma;_w = 0.7 m s^&minus;1. The breadth of this range (0.6 W m^&minus;2) corresponds to almost a third of the total estimate of &minus;1.9 W m^&minus;2, obtained with the mid-range value of &sigma;_w = 0.4 m s^&minus;1, and is comparable to the total diversity of current aerosol forcing estimates. Reducing the uncertainty in the parameterisation of &sigma;_w would therefore be an important step towards reducing the uncertainty in estimates of the indirect aerosol effects. <br><br> Detailed examination of regional radiative flux perturbations reveals that aerosol microphysics can be responsible for some climate-relevant radiative effects, highlighting the importance of including microphysical aerosol processes in GCMs

Satellite-Surface Perspectives of Air Quality and Aerosol-Cloud Effects on the Environment: An Overview of 7-SEAS/BASELInE

“…These observations were comparable with those of κ-parameter estimated from H-TDMA measurements (κ ~0.07-0.08) in the Amazonia (Rissler et al, 2004(Rissler et al, , 2006, as well as consistent with previous studies on water uptake of carbon-dominated aerosols (e.g., Petters et al, 2009;Carrico et al, 2010;Dusek et al, 2011;Engelhart et al, 2012). Although κ-values derived from ground-based observations of biomass-burning aerosols are generally less than 0.1, with sufficient atmospheric updraft velocity (i.e., strong adiabatic cooling) the aerosols can serve as CCN and influence cloud microphysical and radiative properties (e.g., West et al, 2014). Reutter et al (2009) have further investigated the sensitivity of the formation of cloud droplets to κ-values under pyro-convective conditions and found that a 50% change in κ alters the droplet concentration by more than 10% for aerosols with very low hygroscopicity (κ < 0.05) in the updraft-limited regime.…”

Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability

“…K.CA use the same droplet nucleation scheme, SPRINTARS and ECHAM6-HAM apply a lower bound on N d (16,17) that clearly substantially limits the droplet number sensitivity to CCN for clean conditions such as the preindustrial (18). Differences in updraft velocity and in natural emissions could also contribute to the diversity (19), but additional experiments without lower bounds would be required to determine the contribution of the lower bound to the diversity.…”

On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models

“…The tropospheric chemistry part of UKCA is described in O'Connor et al (2014). HadGEM3 uses a prognostic treatment of rain formulation (Abel and Boutle, 2012) and employs a prognostic cloud fraction and condensation cloud scheme (PC2) (Wilson et al, 2008), in which the cloud droplet number concentration is diagnosed from the expected number of aerosols that are available to activate at each timestep (West et al, 2014). Cumulus convection is represented by a mass flux convection scheme based on Gregory and Rowntree (1990) with various extensions (Walters et al, 2014).…”