Alex Lewis
- Email: eeajl@leeds.ac.uk
- Thesis title: Characterising and improving understanding of mesoscale convective systems over south-east Asia using machine learning
- Supervisor: Dr Juliane Schwendike, Dr Simon Peatman, Professor Douglas Parker, Dr Prince Xavier, Dr Massimo Bollasina
Profile
I am a second-year PhD student and part of the SENSE CDT programme. I am using machine-learning techniques to look for clusters that exist within the population of mesoscale convective systems (MCSs) that form over the Maritime Continent in Southeast Asia.
MCSs are defined by a large, continuous area of rainfall and are typically made up of one or more convective region with heavy rainfall along with surrounding regions of stratiform cloud with lighter rainfall; they can also include associated regions of cloud with no precipitation. MCSs can exist for many hours and travel large distances during their lifetimes, potentially bringing heavy rainfall to a region for a porlonged period. MCSs can be organised into different structures and these different structures often indicate different MCS behaviour and evolution. By studying the different morphologies of MCSs in the Maritime Continent I hope to improve understanding of how their morphologies are affected by the conditions under which they form, mature and propagate with an aim towards understanding how the dynamical processes that maintain an MCS control it’s strucure.
Research interests
- Mesoscale Convective Systems
- Tropical Meteorology
- Atmospheric Physics
- Machine Learning
- Satellite Imagery
- Storm Tracking
Qualifications
- MPhys Theoretical Physics (Durham University)
Research groups and institutes
- Institute for Climate and Atmospheric Science