The causes of natural disasters such as floods, wildfires, heat waves, and droughts are often associated with a complex combination of physical processes that occur on multiple time scales. When several processes, climate drivers and hazards are combined to have considerable impact, it is called a “compound event.” Since extreme events often interact and are dependent on space or time, considering only one driver and/or hazards can lead to underestimation of risks.
While studying alternative results, Dr. Gordon Woo, a disaster agent at risk management solutions in London, UK, reviewed a comprehensive literature to gain new insights into complex weather risks, especially on serious issues related to extreme weather events. Influencing the consequences, he suggested creating a database of counterfactual events. The study was published in the journal Extreme weather and climate Last February.
According to Dr. Woo, research on compound events and climate change is a key step in enhancing the robustness of current risk models. Due to three factors, the prediction of climate change is uncertain: human-induced coercion; climate response to this coercion; and climate behavior to a specific time. “The first option to control climate change. The second is epistemological uncertainty, which can decrease with the improvement of knowledge, but subjective. The third is an uncertainty that reflects a specific time window. Randomness of climate realization,” Dr. Woo said.
Climate change response uncertainty can be visualized through a variety of visually consistent storyline configurations. The physical laws of thermodynamics limit the quantitative uncertainty of global warming. Related to these will be a substantial component of determining extreme weather intensity. Taking into account uncertainty in catastrophic weather risk models is particularly useful for making prudent insurance decisions, as estimating uncertainty is critical to this process.
Advances in disaster science often come from major disasters. Changes in building regulations and risk management may be implemented after such incidents. Phase spatial analysis of historical extreme weather events can also produce feasible insights. “Counterfactual analysis provides new insights into the impact potential associated with extreme composite events, which cannot be obtained through event scaling or statistical analysis.” Research uncertainty, often associated with major historical events, is costly A lot of time and energy. Otherwise, most studies on intense uncertainty are not intended to detect rare extreme events.
To explain climate change scenarios, a database of counterfactual composite events will be helpful. Furthermore, it will contribute to climate change attribution research, aiming to quantify the impact of natural and human-induced forces on extreme events. Dr. Woo noted in a key comment that a database of counterfactual compound events will make it easier to create narratives about future weather. “The online database should provide more information than a list of dates and qualitative descriptions. It should include impact assessments and maps of hazardous footprints related to counterfactuals,” he added.
Lessons learned from the past can help us imagine the weather in the future. Even if there is no historical precedent, scenarios can be developed by exploring counterfactuals. This situation has the potential to encourage future disaster relief efforts.
Journal Reference and Major Image Credit:
Wow, Gordon. “Counterfactual view on compound weather risks.” Extreme weather and climate 32 (2021): 100314. doi: https://doi.org/10.1016/j.wace.2021.100314
About the Author
Dr. Gordon Woo
Dr. Gordon Woo is a disaster-maker for risk management solutions that involves quantitative aspects of all extreme hazards and risks, especially those involving complex dynamics. In 2004, Newsweek magazine named him one of the world’s leading disaster homes. He has written extensively on risk assessments and is the author of The Journal of the Imperial University: “Mathematics of Natural Disasters (1999)” and “Computational Disasters (2011)”. His recent research focuses on counterfactual risk analysis and explores the alternative realization of past hazardous events. This type of analysis detects hazard boundaries in ways that may lead to the discovery of black swans – surprising events without historical precedent. This branch of analysis has high insight into studying climate risks. He is a Mathematics graduate from Cambridge University, where he received his Ph.D. In theory, MIT is a Kennedy Scholar and a member of the Harvard Fellows Society. He is currently a visiting professor at the Institute of Risk and Disasters at the University College London and an adjunct professor at the Institute of Disaster Management at the South-South Technical University of Singapore. Additionally, he is the leading professional editor in the Geohazards and Georisks section of the Geohazards in the field of geosciences.
