Descripción del proyecto
Rapidly thawing Arctic permafrost is an important, but poorly constrained, contributor to global carbon budgets and an unknown in the climate change equation. Arctic shelves are critical regions in terms of fluid dynamics due to high organic matter and groundwater fluxes, thin permafrost, and shallow gas hydrate stability zones. Predictive modelling of the Arctic subsurface is challenging due to highly transient multi-physics processes and data-acquisition constraints (related to harsh climate and remote terrains), which lead to critical data sparsity and high uncertainties. Using advanced computational methods, we aim to develop a systematic 'process-level' understanding of how climate-change related warming along Arctic shelves impacts permafrost integrity, ice-layer distribution, sub-permafrost groundwater, and gas and gas hydrate dynamics. We also aim to understand how these processes influence seafloor morphologies (e.g. pingos, pockmarks), which can provide useful proxies for linking (easier to access) seafloor observations with underlying (data-sparse) sub-seafloor processes. Our models and methods will be developed in a highly generalized framework which, within this project, will be specifically applied to study climate change impacts on the fjords of Svalbard in the high Arctic. Beneficiary of this funding will be University of Malta, where the applicant (a mathematician) will receive training in seafloor data acquisition, processing and interpretation, and practical aspects of continental shelf geomorphology and hydrogeology, which will empower her to make meaningful and judicial use of data in her modelling studies. The project goals align with UN Sustainable Development Goal on Climate Action, and our findings will have high scientific and socio-economic impacts by bridging key knowledge gaps and offering comprehensive predictive framework to government agencies, NGOs, and commercial entities for assessment of warming-related risks in the Arctics.