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Ezri Alkilani-Brown

Ezri Alkilani-Brown

  • Email: E.Alkilani-Brown@leeds.ac.uk
  • Thesis title: Exploiting machine-learning to provide a dynamical, microphysical, radiative and electrifying insight from observations of deep convective cloud
  • Supervisor: Professor Alan Blyth, Professor Paul Field, Professor Ben Murray, Dr Declan Finney, Dr Steven Boeing

Profile

I am a first year PhD student, that accidently specialised into cloud microphysics after four years at Manchester and undertaking two cloud-related research projects with Prof. Connolly. Previously, I have ran a large eddy simulation to understand the importance of a secondary ice process in a convective cloud. I have also operated an ice nucleation cold stage to calculate ice nucleating particle concentration from a La Palma rain sample, as part of a cloud seeding experiment.

Summer of 2023, I operated UAVs on behalf of Menapia for the WOEST-WesCon experiment. In the summer of 2022, I undertook a research project at the University of Saskatchewan, handling 20 years of WRF output under pseudo global warming to understand the changes in cloud microphysical structure across different landscapes.

Currently, my research focuses on constraining the graupel hydrometeor in the Unified Model (UM) Cloud AeroSol Interacting Microphysics (CASIM) scheme. This will be achieved by using both (un)supervised machine learning techniques on cloud ice crystal images from the Deep Convective Microphysics Experiment (DCMEX).

Research interests

  • Cloud microphysics

  • Machine learning

  • Numerical modelling

Qualifications

  • MEnvSci, Environmental Science - University of Manchester