The role
This position will contribute to the CLARiTy project, a five-year initiative that aims to dramatically reduce uncertainty in land carbon fluxes by integrating Earth observation data with advanced modeling techniques. By harmonizing definitions, improving spatial resolution, making modeling approaches converge, and aligning scientific estimates with national greenhouse gas inventories, CLARiTy is expected to deliver more accurate and operational carbon budget assessments to support climate policies and global stocktakes.
The successful applicant will join IIASA scientists from the ASA and ECE programs to contribute to this effort and related projects. Their modeling work will be split across various modeling tools, including
a spatially explicit model of the biophysical effect of land use change,
a machine learning emulation of dynamic global vegetation models.
Both activities aim to improve understanding and quantification of the effects of land management and environmental factors on land carbon and climate dynamics.
Tasks and Responsibilities
Develop and apply a first-order, spatially explicit model of the biophysical effects of land use change and its linkage with climate change
Develop and apply a machine learning emulation of dynamic global vegetation models to investigate land carbon fluxes
Set up, run, and share simulations using these models and potentially others
Exploit existing model data to better align land use change emissions with countries’ reporting
Write and contribute to project deliverables as required
Write and contribute to scientific articles arising from the above work, and present findings at scientific workshops and conferences