Dr Bethan White

Quantifying CCN Effects on Deep Convection

Supervisor: Dr Bethan White
Field of Study: Atmospheric Science: Convection-permitting modelling
Collaborating Organisation: Aerosol, Cloud, Precipitation and Climate Initiative
Preferred Program: Atmospheric Science

Clouds require cloud condensation nuclei (CCN) in order to form cloud droplets and rain. CCN exist in the form of atmospheric aerosol. Sources of aerosol can be natural (e.g. volcanoes) or anthropogenic (e.g. sulphates). The amount of CCN present in the atmosphere affects cloud properties.

Cloud processes and feedbacks as well as lack of observations mean that the impact of aerosol on deep convective clouds is poorly understood. Some studies have shown an invigoration of updrafts by CCN, while other studies have shown weakening of convection. This means that large uncertainties in CCN-cloud interactions still exist, with implications for weather and climate forecasting.

The Aerosol-Clouds-Precipitation Climate (ACPC) Model Intercomparison Project (MIP) ran case study simulations of deep convection near Houston, Texas. This ensemble simulation using lots of different cloud-resolving models run by different modelling centres allows us to see not only what the impact of atmospheric aerosol on the deep convective event in the simulations was but also how much uncertainty is in the results due to variability between different models.

Initial analysis has quantified the range of responses of cloud properties in the models to CCN concentrations. In this project, you will work with the ACPC-MIP data and investigate the physical processes driving the differences in responses to CCN. This project will allow you to work with high-resolution cloud model data, investigate cloud physics processes, has the opportunity to collaborate with the international ACPC group, and ultimately may help us to reduce model uncertainty and improve forecasts.

For further information contact: Bethan White

Tropical precipitation extremes in a warming climate

Supervisor(s): Martin Singh & Bethan White.
Fields of study: Atmospheric Science

The heaviest precipitation events (precipitation extremes) are expected to become more intense as the climate warms and the concentration of water vapour in the atmosphere increases. However, the rate at which precipitation extremes will increase remains highly uncertain, particularly in the tropics. Recent studies have suggested that the intensity of precipitation extremes is related to the tendency of thunderstorms to organise into clusters in the tropics. A high degree of organisation results in heavier precipitation rates. It has been suggested that such convective organisation may increase in a warming climate, and this could have important implications for precipitation extremes under anthropogenic climate change.
In this project, we will investigate convective organisation in the tropics in satellite precipitation data and in climate models. By analysing such data sets from an event-based perspective, we will tackle such questions as: is convective organisation increasing in the tropics? Does the intensity of precipitation extremes in climate models depend on how they represent convective organisation? Does the representation of convective organisation in such models change under warming, and how does this relate to projections of tropical precipitation extremes?
This project involves computational analysis of large data sets, and so strong coding skills, including familiarity with a language such as Python, R, or MATLAB are highly desirable.

For further information contact: Martin Singh