2025 Workshop: Hazards

Synoptic atmospheric hazards, such as hurricanes and strong frontal activity, and defined geological hazards, such as seismic and volcanic activities, can trigger acoustic and gravity waves that propagate upwards and can be detected in the upper atmosphere. Additionally, man-made artificial, accidental, and intentional explosive events are also equally responsible for generating shock or acoustic wave signatures in the geospace environment. Observation and modeling of these events can give new insights into our understanding of the dynamics, chemistry, and fundamental coupling processes between the troposphere and the middle and upper atmosphere. In system theory, such lower atmospheric events can be thought of as a defined input, x(t), into a complex system, h(t), where the CEDAR/GEM community can observe y(t) and gain insight on the fundamental transfer function(s) representing the underlying physical processes controlling the upper atmospheric response. This workshop welcomes short interactive presentations on the upper atmospheric response to various natural and artificial phenomena occurring in the oceans, on land, and in the lower atmosphere. Such phenomena include but are not limited to, earthquakes, surface and submarine volcanic eruptions, tsunamis, typhoons, cyclones, hurricanes, tornados, thunderstorms, non-nuclear explosions, nuclear detonations, rocket exhausts, etc., which are studied from different observational and modeling approaches. Improved capabilities in forecasting these disasters can save hundreds of lives and protect billions of dollars in property from damage. Rapidly growing and practical automated processes, such as Artificial Intelligence (AI) and Machine Learning (ML), can analyze massive data sets, enabling scientists to gain new insights and optimize performance. These advancements are crucial for hazard-related preparedness and response. The workshop seeks to bring together the CEDAR and GEM communities from different disciplines and backgrounds so as to fundamentally develop a deeper understanding of the geophysical processes involved. It is anticipated that the impact of this activity can lead to new projects related to natural and artificial hazard-induced upper atmospheric dynamics, including research-based AI/ML tools that may lead to early warning systems against such disasters.