Midway Evaluation in statistics - Brynjólfur G. Guðrúnar Jónsson

Title of thesis:
Improving 21st century projection of sub-daily extreme precipitation by modeling data level dependence using copulas

Student:
Brynjólfur Gauti Guðrúnar Jónsson

Doctoral committee:
Dr. Birgir Hrafnkelsson, Professor at the Faculty of Physical Sciences, University of Iceland
Dr. Raphael Huser, Associate Professor at Computer, Electrical and Mathematical Sciences and Engineering (CEMSE), King Abdullah University of Science and Technology (KAUST), Saudi Arabia
Dr. Stefan Siegert, Senior Lecturer at Mathematics and Statistics, University of Exeter, United Kingdom

Abstract:
The doctoral research project aims to improve projections of sub-daily extreme precipitation, focusing on hydrological risk assessment and climate adaptation. By developing a Matérn-like spatial copula within the Max-and-Smooth framework, the research offers an innovative approach to capturing data-level dependence, enabling more accurate modeling of intensity and frequency of rainfall extremes. The methodologies will be applied to recalibrate biased outputs from the UK Climate Projections (UKCP). The work consists of four components: methodological development, computational software development, application to climate projections, and stakeholder engagement. Key deliverables include a large-scale spatial copula, bias-corrected precipitation datasets, an open-source R package, peer-reviewed articles, and targeted workshops.

Zoom: https://eu01web.zoom.us/j/67484458865?from=addon