PhD Studentship: Using Earth Observation to model fire carbon emissions over the tropics (PhD funded)

Around one quarter of anthropogenic carbon dioxide emissions are taken up by land ecosystems, mitigating climate change (Friedlingstein et al., ESSD 2025). The largest land sink is located in tropical ecosystems with their high productivity and biomass (Ahlstrom et al., Science 2015). Yet these ecosystems are also heavily impacted by deforestation, degradation through fire, climate change and extremes (Aragão et al., Nat comms 2018).

The Global Carbon Budget (GCB) is the most comprehensive source of data and information about regional-to-global scale carbon fluxes; it is updated annually and published at the UNFCCC COP meetings every year. The largest uncertainty in GCB is in emissions from land-use and land-cover change, which has an uncertainty of approximately 60%. This is mainly because, until now, we have lacked the tools and data to quantify emissions from deforestation and degradation in the tropics with sufficient accuracy and temporal consistency. To reduce uncertainty in the Global Carbon Budget, better quantification and understanding of the complex carbon flows involved in the land carbon cycle is paramount.

Our international consortium project entitled ‘Combining LAnd-use, modeling and Remote-sensing to Transform carbon budgets, CLARiTy’ (https://www.schmidtsciences.org/vicc/) will reduce the persistently high land flux uncertainties in GCB by an order of magnitude. To achieve this goal, we will combine new datasets, a deeper process-understanding, sophisticated models and improved experimental design.

As part of CLARiTy, this PhD will focus on modelling the impact of degradation and deforestation fires on the carbon cycle of tropical ecosystems and atmospheric composition across South America and Africa.

The PhD would entail the further development and application of a high-resolution Earth Observation-based fire carbon book-keeping model, REFIT.AC, originally designed the Brazil Amazon and Cerrado biomes (Fawcett et al., 2023 https://doi.org/10.5194/egusphere-egu23-6173, 2023; Forkel et al., Nat Geo, 2025). The student will benefit from access to empirical and remote-sensing data from complementary projects funded through two UK’s Natural Environment Research Council large grants (Amazon-SOS: a Safe Operating Space for Amazonian Forest and SECO: resolving the current and future carbon dynamics of the dry tropics), regional carbon budget projects supported by the European Space Agency (RECCAP2, TRAC3E), and the ENSURE UEXE-CUHK joint centre (https://www.exeter.ac.uk/global/cuhkpartnership/).

This fully funded PhD project is suited to candidates with a related research background with strong remote-sensing, numerical, analytical and coding skills with undergraduate and masters degree in Mathematics, Earth System Sciences, Natural Sciences and related subject areas.

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