Postdoctoral Research Assistant in Atmospheric Convection

Responsibilities:
I am currently a postdoctoral research assistant working on the COSMIC project at NCAS.
Research Interests:

High-resolution (100 m) regional simulations
High-resolution (10 km) global simulations
Simulated Asian summer precipitation
High-resolution (10 km) global simulations
Simulated Asian summer precipitation
Understanding and improving convection parametrization schemes
Orographically induced precipitation
Mesoscale convective systems and their representation in simulations
Evaluating simulations against observations
Idealized cloud-resolving simulations (1 km)

Academic roles:

2021-2022: Postdoctoral Research Assistant, supervised by Thorwald Stein and Peter Clark
Project: Urban-Scale Modelling (USM)
Performed a number of simulations using the Unified Model Nesting Suite, with higher-resolution
simulations nested inside coarser simulations. Evaluated two different microphysics schemes
– Wilson–Ballard (control) and CASIM. Diagnosed the eddy dissipation rate, a measure of
turbulence, and will also evaluate cloud updraught statistics. Performed simulations with a
prognostic turbulent kinetic energy (TKE) turbulence scheme, i.e., a scheme which can advect
and diffuse a prognostic turbulence variable.

2019–2021: Postdoctoral Research Assistant, supervised by Reinhard SchiemannProject: COnvective-Scale Modelling In China (COSMIC), CSSP China WP4Evaluating the representation of precipitation in different configurations of a high-resolution (10 km) GCM over Asia, at different spatial scales defined by catchment basins. Simulations are run both with and without a convection parametrization scheme. Developed the BAsin-Scale Model Analysis ToolkIt (BASMATI) to facilitate decomposing the precipitation onto different sizes of catchment basin. Investigating the effect of orography on precipitation in the different configurations. Using BASMATI to analyse the 2020 floods in China.

Education

2015–2019, PhD, University of ReadingThesis: Designs for representing shear-induced cloud field organization in a convection parametrization scheme Current generation climate models rely on parametrizing the effects of deep convection. They do this by making certain assumptions, such as the quasi-equilibrium assumption of Arakawa and Schubert (1974), whereby the convective response in a given grid-column is assumed to be in equilibrium with the forcing. However, convection parametrization schemes do not take into account the degree of shear-induced organization of the cloud field. In this thesis, we attempted to address this shortcoming. We did this by first classifying the types of shear profile found in a typical climate model -- the Met Office Unified Model run globally for five years. We then ran high-resolution idealized radiative-convective equilibrium experiments with shear profiles taken from the climate model to characterize the convective response to the shear and the resulting organization of the cloud field. These experiments were used to design modifications to existing mass-flux based convective parametrization schemes, which would allow the schemes to represent some of the effects of shear-induced organization of cloud fields.
2013–2014, MSc in Environmental Modelling (Distinction), University College London Dissertation: Objective Tracking and Classification of Hurricanes in the 20th Century Reanalysis DatasetThe dissertation involved developing a novel tracking procedure for hurricanes in the 20th Century Reanalysis Project, using machine learning to classify hurricanes and identify tracks.

Centaur Publications

Last update: 7th November 2024