Webinar: Introduction to STRAND project & exploring sources of uncertainty
Join us for an insightful webinar on the STRAND Marsden Fund Project, a pioneering interdisciplinary initiative funded by the Royal Society of New Zealand ($869,000 between 2021 and 2024). Delve into an exploration of climate-change flooding risks impacting residential property values over space and time, and their profound implications for financial stability.In this session, we will have guest speakers providing an overview of the project and highlight two key workstreams focusing on uncertainties in estimating flooding risks associated with climate change-related hazards (e.g., sea level rise and extreme precipitation). Uncertainties in risk estimates arise from, inter alia, methodological choices, alternative scenarios, and uncertainty inherent in input datasets.
The presenters' first workstream dissects how methodological choices and scenario uncertainties intersect to shape these risks. Discover how climate scenario divergence incrementally impacts risk magnitude and uncertainty levels until the end of the 21st century, with the evolving significance of different uncertainty sources over time.
In the second workstream, they expand the investigation to systematically address data uncertainties alongside methodological and scenario uncertainties. Utilizing a Monte Carlo approach, they generate thousands of probabilistic flood maps on the NeSI platform, providing a comprehensive understanding of these multifaceted uncertainties. Their findings underscore the pressing need for financial actors and regulators to prioritize data and methodological uncertainties in disclosing and pricing flooding risk over the next two decades.Join us as we explore the implications of this research for emerging accounting disclosure standards, such as IFRS S1 and S2, and uncover the crucial role of disclosing methodological choices and assumptions in addition to risk estimates.
NeSI has partnered on a consultancy project aimed at enhancing the efficiency of Dask code execution on our systems for the STRAND project, and have presented on this topic at the eResearch NZ 2024 conference earlier this year.
CLICK HERE TO REGISTER FOR THE WEBINAR
Speaker Bio:
Professor Ivan Diaz-Rainey - Ivan is a leading international expert in climate and sustainable finance. He is a Professor of Finance at Griffith University (Gold Coast, Australia). Previously he has held academic positions at the University of Otago (Dunedin, New Zealand), University of East Anglia (Norwich, UK), the European University Institute (Florence, Italy), where he held a prestigious Jean Monnet Fellowship, and the Higher Colleges of Technology (Abu Dhabi, UAE). His research expertise includes climate finance, carbon markets, energy finance, banking, financial regulation, green Fintech and energy and environmental policy.
Professor Antoni Moore - Antoni is a Professor in Geographical Information Science at the School of Surveying, University of Otago (Dunedin, New Zealand). He is the current dean and director of the Geographical Information Systems (GIS) degrees (BSc, MAppSc, MSc). He was previously in the Department of Information Science from 2001 to 2008 and before that working as a coastal / marine GIS Analyst at Plymouth Marine Laboratory in the UK. He has research interests in geovisualisation and cartography. He completed his BSc in Geographical Science in 1993, an MSc in GIS in 1994 and his PhD (on the application of holistic expert systems to integrated coastal zone management) in 2001.
Dr Murray Cadzow - Murray is a Scientific Programmer within Research and Teaching IT Support at the University of Otago. Murray has a background in research, and now works alongside researchers to help them achieve their computational research goals.
Dr Maxime Rio - Maxime is a data science engineer at the New Zealand eScience Infrastructure (NeSI) HPC center, and a data scientist at the National Institute of Water and Atmospheric Research (NIWA). He works closely with scientists, helping them deploy, scale and optimise their data pipelines, as well as develop and apply machine learning methods tuned for their research area.
Dr Quyen Nguyen - Quyen is a Climate Change Economist at GNS Science (Dunedin, New Zealand). Previously, she was a Postdoctoral Fellow in the STRAND Marsden Fund Project hosted at the School of Surveying, University of Otago. Her research interests are climate finance, climate economics, and data science.
