Dr Amber LeesonSenior Lecturer in Applied Data Science
Amber’s main research interest is in ice-climate interactions; specifically how climate change affects the Greenland and Antarctic Ice sheets. Her day-to-day work mostly involves developing improved numerical models of the Cryosphere, in order to advance their capability for robust estimates of cryospheric change. This is supported by extensive work with Remote Sensing data and GIS techniques.
Current projects include:
- Extreme temperature events on Greenland and their impact on ice melting
- Supraglacial lakes and their impact of grounded and floating ice
- Firn modelling for the interpretation of observations of ice sheet height change
- Advanced analysis techniques for climate model evaluation
Amber was awarded her PhD in 2013 and has since published 12 refereed journal papers, mainly on ice sheet hydrology and climatology, in leading journals such as Geophysical Research Letters and Nature Climate Change. Her most recent paper (currently in review for The Cryosphere) presents the first estimate of the contribution of extreme temperature events to greenland ice sheet melting and suggests that regional climate models 'miss' a significant proportion of total melting because they underestimate extreme temperature events.
Amber has previously been the treasurer for the UK Polar Network and is currently:
- A member of the American Geosciences Union (AGU) Cryosphere Committee
- Early career representative to the UK National Committee for Antarctic Research (UKNCAR)
- Secretary of the International Glaciological Society British Branch
- Associate Editor for the Journal of Geophysical Research (Earth Surface)
I teach on LEC321 Glacial Systems and LEC103 Environmental Processes and Systems and I convene LEC497 Professional Experience Placement and LEC498 Professional Experience Dissertation.
DSI: Data Science of the Natural Environment
16/04/2018 → 15/04/2023
Meltwater Ice-sheet Interactions and the changing climate of Greenland (MII-Greenland)
01/01/1900 → …
ReCoVER : Advanced Data Clustering for Climate Science Applications
01/01/1900 → …
- Geospatial Data Science