Constraining a terrestrial ecosystem model using greenhouse gas flux and remote sensing data

Supervisor: Andrew Friend

Project description

The project will involve compiling and processing existing greenhouse gas flux data, as collected within the CLR project and from other sources, and using them to test and parameterise the ecosystem dynamics model, HYBRID, across the three CLR landscapes. 

Remote sensing data will also be processed and used to test and parameterise phenological and management routines. The primary aim will be to improve simulations of the carbon balance of these landscapes under future climate and land use trajectories. 

The main aspects of the model of interest will be the extension of plant physiological and management routines to treat a range of plant types, including crops, and land uses. Depending on the skills and/or interests of the student the project could be narrowed to focus on one particular aspect within this broad scope of work.

Background information

This project is part of the Centre for Landscape Regeneration. 

Working environment

The role holder will work with teams from across the research group, the Centre for Landscape Regeneration and other disciplines, with lots of opportunity to learn and network. Some flexible working can be accommodated, but the role holder will need to be in the office in Cambridge regularly.

Essential knowledge, skills and attributes

  • You should be studying, or have completed a degree in a biological, environmental, or related sciences. Applicants would benefit from a knowledge of land surface-atmosphere interactions, hydrology and/or biogeochemistry, as well as an interest in the subject
  • Experience and skills in processing large datasets and /or simulation models, along with strong competencies in statistical analysis and the design of clear, effective graphical figures
  • Good analytical skills; able to collate, understand and draw conclusions from quantitative and qualitative information
  • Good interpersonal skills; confident in meetings with both internal and external colleagues and working with people from a range of backgrounds and disciplines
  • Well-developed organisational and timekeeping skills and the ability to manage projects
  • Ability to prioritise own workload and plan effectively as part of a small team.

Contact us

If you have questions about this project, email Andrew Friend