Aerosols have a significant effect on the global radiation budget through their
interactions with radiation and clouds. However, estimates of their effect are the
dominant source of uncertainty in current estimates of total anthropogenic effect on
climate. A major cause of this uncertainty is the high degree of variability of aerosol
properties and processes that affect their lifetime. Prediction of the aerosol effect on
climate depends on the ability of three-dimensional numerical models to accurately
estimate aerosol properties. However, a limitation of traditional grid-based models is
their inability to resolve variability on scales smaller than a grid box. Past research has
shown that significant aerosol variability exists on scales smaller than these grid-boxes,
which can lead to discrepancies between observations and aerosol models.
This thesis uses a synthesis of aerosol observations, global climate model (GCM)
data, and a new aerosol modelling technique implemented within a regional-scale model
to quantify the important scales of aerosol variability and the extent to which different
sub-grid scale processes contribute to discrepancies in aerosol modelling.
Analysis of black carbon (BC) plumes from aircraft observations shows that BC
plumes represent a large portion of total BC mass and typically exist on scales of 65{
100 km. Comparison of observed plume scales to those simulated by GCMs at multiple
resolutions show that GCMs overestimate the scales of along-
ight-track variability by
64% at the highest resolution. Variability is shown to be greater near sources than in
remote regions, indicating that models may benefit from higher resolutions in regions
of high emissions. Additionally, GCMs at all resolutions show higher variability in
the latitudinal direction than the longitudinal direction, suggesting that capturing
latitudinal variability may result in greater improvements in aerosol modelling.
This work additionally presents a novel technique to allow one to isolate the effect
of aerosol variability from other sources of variability within the model. Processes
most affected by neglecting aerosol sub-grid variability are gas-phase chemistry and
aerosol uptake of water through the aerosol/gas equilibrium reactions. The inherent
non-linearities in these processes result in large changes in aerosol parameters when
aerosol and gaseous species are artificially mixed over large spatial scales. These
changes in aerosol and gas concentrations are exaggerated by convective transport,
which transports these altered concentrations to altitudes where their effect is more
pronounced. Future aerosol model development should focus on accounting for the
effect of sub-grid variability on these processes at global scales in order to improve
model predictions of the aerosol effect on climate.This thesis is not currently available via ORA