AAAR 31st Annual Conference
October 8-12, 2012
Hyatt Regency Minneapolis
Minneapolis, Minnesota, USA
Abstract View
Droplet Number Prediction Uncertainties from CCN: An Integrated Assessment Using Observations and a Global Model Adjoint
RICHARD MOORE, Vlassis Karydis, Shannon Capps, Athanasios Nenes, Georgia Institute of Technology
Abstract Number: 488 Working Group: Aerosols, Clouds, and Climate
Abstract Aerosols, acting as cloud condensation nuclei (CCN) to form clouds, are known to be a significant but highly uncertain contributor to the Earth’s climate. Current large-scale models almost exclusively use Kohler theory to predict CCN concentrations from aerosol size, chemical composition, and ambient water vapor supersaturation; however, given limited computational resources, models must make simplifying assumptions that introduce error into their application of Kohler theory. Consequently, a number of past field studies have attempted to quantify this error by comparing measured CCN concentrations to those predicted from simplified theory. Yet, this uncertainty represents only one link in our understanding of the aerosol-cloud climate impacts. The second link is the combination of CCN concentrations with cloud dynamics to determine the overall cloud droplet number concentration (CDNC). Limited attention to date has focused on extrapolating these CCN uncertainty studies to evaluate their impact on the overall CDNC uncertainty, and hence, climate.
We present results from a combined experimental and modeling study incorporating field data of aerosol size, composition, and CCN activity measured in diverse environments throughout North America, including the Alaskan Arctic, agricultural areas, and urban centers. First, the adjoint of a CDNC parameterization, driven by aerosol populations and updraft velocities obtained from a year-long execution of the NASA GMI chemical transport model, is used to determine the regional sensitivity of CDNC to CCN concentration. Then, these sensitivities are used to extrapolate the field-measurement-derived CCN uncertainties to the overall CDNC uncertainty associated with simplified Kohler theory predictions. It is found that this uncertainty is much lower over polluted continental regions than in more pristine environments. Given the past measurement focus on continental environments, this finding motivates future work in pristine regions in order to quantify the impact of and uncertainty associated with transient processes in effecting changes in cloud properties.