Primary Supervisor - Dr Benjamin Webber (UEA, ENV)
Secondary Supervisor - Professor Adrian Matthews (UEA, ENV)
Supervisory Team - Dr José Rodríguez (UK Met Office), Dr Dan Copsey (UK Met Office)
The Indian Ocean is a key component of global climate, surrounded by monsoon systems on which billions of people depend, and warming faster than any other ocean basin. However, state-of-the-art climate models fail to accurately capture the dynamical and thermodynamical processes that govern climatic variability around the Indian Ocean. The UK Met Office has identified model errors and biases in this region to be a significant problem for making seasonal climate forecasts, yet little is known about the source of these errors or how they could be reduced.
You will identify the key processes that generate errors in the Met Office weather and climate models to identify potential model improvements. Initially you will compute the ocean surface mixed layer heat budget, which controls variability in sea-surface temperature and atmosphere-ocean interaction, and compare this budget against observations to identify errors. You will then extend this work to evaluate model experiments where the atmosphere and ocean are “nudged” towards observed values, to identify the role of different regions and components of the climate system in generating model errors and biases. Finally you will run short sensitivity studies to identify optimal model setups and pathways for future development.
Training and research environment
You will join an active research group at UEA in tropical meteorology and climate and will be trained in relevant theory and methods. You will be trained in the analysis of weather forecasting and climate model output using the python programming language, including use of python modules developed by the Met Office for handling and visualising model output. In addition to frequent teleconferences with the Met Office co-supervisors, you will undertake visits to the Met Office for training in running and analysing Met Office models. You will have the opportunity to present your work at national and international conferences.
We seek an enthusiastic student with a degree in physical sciences (physics, mathematics, meteorology, oceanography, or similar), good numerical ability and a keen interest in applying theoretical understanding to solve real world environmental problems. Programming skills (e.g., Python, Matlab) would be beneficial.
For more information on the supervisor for this project, please visit the UEA website www.uea.ac.uk
The start date is 1 October 2022