Predictive Understanding of Compound and Cascading Extremes and their Impacts

Session ID#: 123557

Session Description:
Compound extremes are simultaneous or sequential occurrence of multiple environmental stressors over the same geographical region that collectively represent extreme hazardous conditions, or it can be concurrent occurrence of similar or distinct extremes with common drivers over multiple geographical regions. Some examples of compounding extremes include: i) drought and heatwave, ii) extreme precipitation and strong winds/storm surge, iii) hot, dry and windy conditions, and iv) spatially concurrent droughts. They represent rare states in the Earth system that expose social-ecological systems to hazardous unaccustomed environments with adverse consequences. The research in this area is relatively new and, therefore, robust frameworks for defining such extremes and evaluating their impacts are still a work in progress. We invite submissions that advance our understanding in the detection, attribution, prediction and projection of compound, concurrent and cascading extremes and their impacts at sub-seasonal to centennial timescales, using observational, modeling, and modern machine learning approaches.
Index Terms:

1655 Water cycles [GLOBAL CHANGE]
1942 Machine learning [INFORMATICS]
3305 Climate change and variability [ATMOSPHERIC PROCESSES]
4313 Extreme events [NATURAL HAZARDS]


Primary Convener:  Moetasim Ashfaq, Oak Ridge National Laboratory, Oak Ridge, TN, United States
Conveners:  Vimal Mishra, Indian Institute of Technology Gandhinagar, Ahmedabad, 382, India and Subimal Ghosh, Indian Institute of Technology Bombay, Mumbai, India
Primary Liaison:  Jonathan R. Buzan, University of Bern, Oeschger Centre for Climate Change Research, Bern, Switzerland