CEE Seminar (ZOOM): Compound and Cascading Hazards - Modeling and Risk Assessment
Professor
Department of Civil and Environmental Engineering
Department of Earth System Science
UC Irvine
Zoom Link: https://uci.zoom.us/j/9126848538?pwd=eFJpSStqemh6OFBVUnV4RTBtdGlhQT09
Meeting ID: 912 684 8538 ~~ Password: 12345
Abstract: Ground-based observations and model simulations show substantial increases in extreme events including rainfall , droughts, wildfires, hot spells and heatwaves. The first step toward improving our societal resilience is to identify the new patterns of climate extremes and natural hazards. This requires a better understanding of tempo-spatial characteristics of natural hazards and also the interactions between different hazards in a changing climate. A combination of climate events (e.g., high temperatures and high humidity, or low precipitation and high temperatures) may cause a significant impact on the ecosystem and society, although individual events involved may not be severe extremes themselves – a notion known as a compound event (e.g., extreme rain over burned areas, combined ocean and terrestrial flooding). Numerous studies have focused on how different types of extremes have changed or might change in the future. However, very few studies have investigated the changing risk of compound and cascading events. This presentation focuses on three different types of compound and cascading events including drought-heatwaves, sea level rise-terrestrial flooding, and meteorological-anthropogenic drought. We present different methodological frameworks and perspectives for detecting, modeling and risk assessment of compound and cascading events.
Bio: Amir AghaKouchak is a professor of civil and environmental engineering at UC Irvine. His research focuses on natural hazards and climate extremes and crosses the boundaries between hydrology, climatology and remote sensing. Website: http://amir.eng.uci.edu/
Share
Upcoming Events
-
MSE 298 Seminar: Electrocatalysis as Enabling Technology for Decarbonization
-
CEE Ph.D. Defense Announcement: Modeling the Spatiotemporal Heterogeneities of Electric Vehicle Adoption in the United States through Sentiment-Mediated Mechanisms - A Large Language Model-Assisted Data-Fusion Framework
-
EECS Seminar: Random Thoughts After More Than 60 years in the Trenches
-
MAE 298 Seminar: Machine Learning Acceleration of Turbulent Combustion and Nonequilibrium Flow Predictions
-
CBE 298: Green Steel: Design, Supply Chain, H2 Storage and Dispatch Strategies