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  Land-based climate mitigation, combining multi-data sources to assess potential contribution to the Paris Climate Agreement (NERC GW4+ DTP Projects 2018-19)


   School of Geographical Sciences

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  Dr Joanna House  No more applications being accepted  Funded PhD Project (European/UK Students Only)

About the Project

This PhD will compare and reconcile estimates of greenhouse gas sources and sinks from the land, identifying key reasons for the differences including data, methods, and attribution to “anthropogenic activity” versus “natural” processes. The project will include comparison of global models, satellite data, and country reporting under UNFCCC. This project will benefit from access to the Global Carbon Project’s international multimodel synthesis activity, and to ongoing projects co-ordinated by the supervision team. Results will feedback into methodological development, working with the UK JULES ecosystem model. Tropical South America and South East Asia are selected as case study regions as they account for over 60% of land sector emissions. These are areas where increasing amounts of inventory and satellite data are becoming available. This studentship will include an internship at INPE in Brazil working direct with data providers and remote sensing experts. Co-benefits of forest mitigation (biodiversity, flood and landslide resilience) will be explored at Cardiff University’s field site in Borneo. Outputs will provide evidence of relevance to country NDC development. The student will work with CASE partner UK Department of Business Energy and Industrial Strategy to embed understanding of, and co-produce information of relevance to, the UNFCCC policy process.


Funding Notes

The Great Western Four+ Doctoral Training Partnership (GW4+ DTP) provide a multidisciplinary training environment for postgraduate students in NERC sciences. Owing to the nature of the funding, this programme is open to UK/EU students only. This would suit a candidate with excellent numeric skills (able to analyse different types of data), preferably a science background, and with a strong interest in climate policy. Skills in GIS and remote sensing preferred, but training can be provided, with optional opportunities for training in running and developing models.

Where will I study?