Cloud-aerosol-meteorology Interactions in Shallow Convection: Comparing the Southern Ocean against the North Atlantic

This PhD project is based at the University of Manchester with a 12 month stay at the University of Melbourne.

Project Description:

Shallow convective clouds are commonly observed over mid- and high-latitude oceans and have well been documented for their distinctive morphology. However, little is known about the properties of these clouds. Knowledge on any hemispheric contrast in these systems is even more limited. Unlike the often polluted Northern Hemisphere oceans, the Southern Ocean atmosphere is far removed from human and continental sources of aerosols and dust, close to pre-industrial conditions. As such, understanding of any hemispheric contrast in cloud properties is key to constraining the uncertainty in estimating Earth’s climate sensitivity to increased industrial emissions from the historical record.

The objectives of this PhD project are to: (1) characterise the properties of shallow convective clouds over the Southern Ocean and the North Atlantic; (2) understand how the examined cloud properties vary with meteorology, surface and environmental conditions, and aerosol characteristics, and (3) identify key dynamical, thermodynamical, and microphysical processes that define the nature of these clouds.

The project structure will be to take both existing and emerging in-situ aircraft observations and supplemented datasets to characterise the macrophysical and microphysical properties of shallow convective clouds to examine how they vary under different meteorological, environmental, and aerosol conditions. Findings from the Southern Ocean will be compared against the North Atlantic counterpart to explore any systematic hemispheric differences in the examined properties and to elucidate any human impacts. Representative cases will be identified, and idealised simulations will be performed with a state-of-the-art cloud model to understand what dynamical, thermodynamical, and microphysical details are needed to reproduce observations.

Ideal PhD candidates must demonstrate a genuine interest in meteorology, strong computing skills and expertise in analysing large datasets. Graduates with a strong academic record (e.g. Honours Class I or equivalent) in Physics, Atmospheric Science, Mathematics, Engineering or an equivalent quantitative discipline are particularly encouraged to apply.

Supervision team:

Dr Jonathan CrosierDr Paul ConnollyDr Keith Bower (The University of Manchester)

Dr Yi HuangProf Todd LaneProf Peter Rayner (The University of Melbourne)