A Framework to Understand Extreme Space Weather Event Probability.

Area of Science:

• Geophysics and space physics
• Statistical modeling
• Risk assessment for infrastructure resilience

Background:

• Extreme space weather events can severely impact global infrastructure and societal well-being.
• Historical extreme space weather events, like the 1859 Carrington event, offer insights but require probabilistic analysis.
• Previous research focused on event characteristics and specific geomagnetic disturbance probabilities.

Purpose of the Study:

• To present initial findings on a unified framework for visualizing space weather event probability.
• To apply a Bayesian model average to assess geomagnetic disturbance probabilities.
• To contextualize these probabilities with historical extreme space weather events for policymakers.

Main Methods:

• Utilizing a Bayesian model average for a unified framework approach.
• Visualizing disturbance storm time (Dst) probability across multiple return periods.
• Analyzing parameters relevant to policymakers and planners.

Main Results:

• Initial findings on a probabilistic framework for space weather events.
• Presentation of Dst probability distributions for various return periods.
• Identification of key parameters for policy and planning.

Conclusions:

• The developed framework aids in visualizing space weather event probability.
• The analysis provides valuable data for policymakers and planners regarding geomagnetic disturbances.
• Further research is needed to address limitations and enhance space weather risk assessments.