معرفی
Dr. Jill Johnson is a Lecturer in Statistics at The University of Sheffield's School of Mathematics and Statistics. She holds a PhD in Statistics (Newcastle University, 2010), with a thesis on 'Modelling Dependence in Extreme Environmental Events'. Prior to academia, she worked as a research statistician at the UK Food and Environment Research Agency. Her research focuses on uncertainty quantification in climate models, surrogate modeling (emulation), and model-observation comparison. She has contributed to studies of aerosol processes, cloud dynamics, and climate system modeling using statistical methods. Notable work includes constraint of aerosol radiative forcing and analysis of climate model structural inconsistencies. Her research integrates data from simulations, satellites, and ground-based observations to address high-dimensional uncertainties in environmental systems.
- Education: PhD in Statistics (Newcastle University, 2010)
- Previous roles: Research Associate at University of Leeds (2012–2021)
- Research groups: Institute for Climate and Atmospheric Science, University of Leeds
Her work emphasizes statistical methodologies to improve climate model accuracy, particularly in aerosol-cloud interactions and environmental risk analysis. Key contributions include emulator-based approaches for complex climate models and constraint of uncertain parameters using observational data.
Publications span climate modeling, atmospheric science, and statistical emulation, with a focus on reducing uncertainties in climate projections and aerosol effects. Collaborations involve institutions like the University of Leeds, NASA, and international climate research networks.
