[Thesis]. Manchester, UK: The University of Manchester; 2016.
Arctic clouds are poorly represented in numerical models due to the complex, small-scale
interactions which occur within them. Modelled cloud fractions are often significantly
less than observed in this region; therefore, the radiative budget is not accurately
simulated and forecasts of the melting cryosphere are fraught with uncertainty. Our
ability to accurately model Arctic clouds can be improved through observational studies.
Recent in situ airborne measurements from the springtime Aerosol-Cloud Coupling and
Climate Interactions in the Arctic (ACCACIA) campaign are presented in this thesis
to improve our understanding of the cloud microphysical interactions unique to this
region. Aerosol-cloud interactions – where aerosol particles act as ice nucleating
particles (INPs) or cloud condensation nuclei (CCN) – are integral to the understanding
of clouds on a global scale. In the Arctic, uncertainties caused by our poor understanding
of these interactions are enhanced by strong feedbacks between clouds, the boundary
layer, and the sea ice. In the Arctic spring, aerosol-cloud interactions are affected
by the Arctic haze, where a stable boundary layer allows aerosol particles to remain
in the atmosphere for long periods of time. This leads to a heightened state of mixing
in the aerosol population, which affects the ability of particles to act as INPs or
CCN. Aerosol particle compositional data are presented to indicate which particles
are present during the ACCACIA campaign, and infer how they may participate in aerosol-cloud
interactions. Mineral dusts (known INPs) are identified in all flights considered,
and the dominating particle classes in each case vary with changing air mass history.
Mixed particles, and an enhanced aerosol loading, are identified in the final case.
Evidence is presented which suggests these characteristics may be attributed to biomass
burning activities in Siberia and Scandinavia. Additionally, in situ airborne observations
are presented to investigate the relationship between the Arctic atmosphere and the
mixed-phase clouds – containing both liquid cloud droplets and ice crystals – common
to this region. Cloud microphysical structure responds strongly to changing surface
conditions, as strong heat and moisture fluxes from the comparatively-warm ocean promote
more turbulent motion in the boundary layer than the minimal heat fluxes from the
frozen sea ice. Observations over the transition from sea ice to ocean show that the
cloud liquid water content increases four-fold, whilst ice crystal number concentrations,
N_ice, remain consistent at ~0.5/L. Following from this study, large eddy simulations
are used to illustrate the sensitivity of cloud structure, evolution, and lifetime
to N_ice. To accurately model mixed-phase conditions over sea ice, marginal ice, and
ocean, ice nucleation must occur under water-saturated conditions. Ocean-based clouds
are found to be particularly sensitive to N_ice, as small decreases in N_ice allow
glaciating clouds to be sustained, with mixed-phase conditions, for longer. Modelled
N_ice also influences precipitation development over the ocean, with either snow or
rain depleting the liquid phase of the simulated cloud.