In this session we will address recent research in natural hazard risk assessment at the continental to global scales, and discuss future research needs required to advance this rapidly developing field. The session also focuses on the inclusion of spatial and temporal aspects in large-scale risk assessments, including compound events.
The demand from stakeholders for information on natural hazard risks at the continental to global scale has grown explosively in recent years, and large-scale risk assessments have played a prominent role in several major reports (e.g. Global Assessment Reports (GAR) on Disaster Risk Reduction and IPCC SREX report). Moreover, 2016 was a landmark year for international development with the renewal of major international policies - the Millennium Development Goals, Sustainable Development Goals, COP21, and the Sendai framework. Access to evidence on disaster and climate risks is fundamental to these continuing developments. This has led to increased scientific research to develop new, and improve existing, methodologies for the collection and development of fundamental hazard, exposure and vulnerability datasets. Specific research needs include the robust assessment of risks that address both spatial and temporal changes in underlying risk drivers, i.e. hazard, exposure, and vulnerability. Moreover, research is required on how society can best reduce, or manage, this risk.
Such information is of key value to stakeholders such as (re-)insurers, governments, development agencies, and disaster planning and preparedness institutes. We invite contributions related to the full range of natural hazards, and to chains of hazards leading to worst-case scenarios. We encourage contributions focusing on the influence of risk of human systems and economic and urban development; short-term variability in natural hazards; and short to long term changes in natural hazards. We also encourage contributions examining the use of scientific methods in practice, and the appropriate use of continental to global risk assessment data in efforts to reduce risks.