09:40 〜 10:00
[U01-03] How to convey scientific results and uncertainties for better understanding between scientists and society
★招待講演
キーワード：science communication 、uncertainty、probabilistic assessment、deterministic assessment
Geophysics is closely related to societal risks, through natural hazards such as earthquakes, tsunamis, volcanic eruptions or floods. In order to convey and utilize scientific knowledge to society, mutual understanding and interaction are essential between scientists and society. Science involves uncertainty, and probabilistic approaches are often employed particularly for future predictions or forecasts.
For example, deterministic short-term (hours to days) earthquake prediction is currently impossible. In contrast, probabilistic forecasts of future earthquakes for intermediate-term (days to weeks) or long-term (years or longer) have been studied and implemented.
Deterministic assessments are often employed to estimate disaster risks or hazard maps. In such cases, worst-case scenarios are often assumed. In recent years, probabilistic seismic or tsunami hazard assessments have been formulated worldwide, and the results are presented as hazard curves or maps showing the annual frequency of exceedance of ground shaking intensity (seismic intensity or peak ground acceleration) or tsunami heights. Probabilistic forecasts are more challenging to convey to society than deterministic predictions.
In the probabilistic hazard analysis, multiple sources of uncertainty are considered. Two types of uncertainty, aleatory and epistemic, are distinguished. Aleatory uncertainty, or random variability, relates to a physical system's natural or stochastic uncertainty. Epistemic uncertainty is due to our incomplete knowledge and data, and can be reduced by new theories or data. Epistemic uncertainties in various model parameters and alternative techniques are treated as logic trees, in which experts’ judgments are often used.
Building the interface between science, policy-making, and practice is not an easy task. Coordination and cooperation between scientists and society must be improved to facilitate interaction with stakeholders and improve communication and awareness of risks transparently and trustfully at local, national, or global levels. Scientists should engage in a learning process to be able to communicate science in non-technical ways to various stakeholders and discuss how best to mitigate disaster risks through science-based initiatives that can be translated into practice.
For example, deterministic short-term (hours to days) earthquake prediction is currently impossible. In contrast, probabilistic forecasts of future earthquakes for intermediate-term (days to weeks) or long-term (years or longer) have been studied and implemented.
Deterministic assessments are often employed to estimate disaster risks or hazard maps. In such cases, worst-case scenarios are often assumed. In recent years, probabilistic seismic or tsunami hazard assessments have been formulated worldwide, and the results are presented as hazard curves or maps showing the annual frequency of exceedance of ground shaking intensity (seismic intensity or peak ground acceleration) or tsunami heights. Probabilistic forecasts are more challenging to convey to society than deterministic predictions.
In the probabilistic hazard analysis, multiple sources of uncertainty are considered. Two types of uncertainty, aleatory and epistemic, are distinguished. Aleatory uncertainty, or random variability, relates to a physical system's natural or stochastic uncertainty. Epistemic uncertainty is due to our incomplete knowledge and data, and can be reduced by new theories or data. Epistemic uncertainties in various model parameters and alternative techniques are treated as logic trees, in which experts’ judgments are often used.
Building the interface between science, policy-making, and practice is not an easy task. Coordination and cooperation between scientists and society must be improved to facilitate interaction with stakeholders and improve communication and awareness of risks transparently and trustfully at local, national, or global levels. Scientists should engage in a learning process to be able to communicate science in non-technical ways to various stakeholders and discuss how best to mitigate disaster risks through science-based initiatives that can be translated into practice.