Celine Tchaghlassian

Profile

I'm a Postgraduate Researcher in the School of Earth and Environment at the University of Leeds, within the Institute for Climate and Atmospheric Science. My research is funded by the Natural Environment Research Council through the UNRISK Centre for Doctoral Training.

I studied Environmental Science at the University of Leeds, where I completed my dissertation on radiative forcing estimates working with CMIP6 data, under the supervision of Professor Piers Forster. This project motivated me to strengthen my coding skills, leading me to pursue a Master's degree in Environmental Data Science and Machine Learning at Imperial College London. During my Master's, I learned machine learning techniques and key software development skills that I hope to continue to build upon in my PhD. For my Master's thesis, supervised by Dr. Paulo Ceppi, I investigated the seasonal variability of low clouds using cloud controlling factor analysis, a statistical learning method based on ridge regression.

Now, my research focuses understanding how representations of physical proceses in climate models influence global climate projection uncertainty. Aerosol–cloud interactions remain one of the largest sources of forcing uncertainty, masking the true extent of greenhouse gas warming. Using large ensembles of simulations with the UK Earth System Model (UKESM2) alongside multi-model perturbed parameter ensembles (PPEs), my research will identify how cloud microphysics, aerosol and atmospheric dynamics contribute to uncertainty. Using these PPEs, I will be able to train machine learning emulators to extend the sample of model simulations. Novel methods will disentangle structural from parametric causes of aerosol–cloud forcing uncertainty, providing insights into causes of model divergence, and guiding model developments that target improvements in climate prediction.

Research interests

• Aerosol-Cloud Interactions
• Perturbed Parameter Ensembles
• Structural model deficiencies
• Machine Learning

Qualifications

• BSc Environmental Science – University of Leeds
• MSc Environmental Data Science and Machine Learning – Imperial College London

Research groups and institutes

• Atmospheric Chemistry and Aerosols