The causes of natural disasters such as flooding, wildfires, heatwaves, and droughts are often connected to a complex combination of physical processes occurring over multiple time scales. It is referred to as a ‘compound event’ when several processes, climate drivers and hazards, combine to have a considerable impact. As extreme events often interact and are either spatially or temporally dependent, considering only one driver and/or hazard at a time may lead to an underestimation of risk.

In studying alternative outcomes, Dr. Gordon Woo, Catastrophist at Risk Management Solutions, London, United Kingdom, reviewed the comprehensive literature to gain new insights into compound weather risk, especially concerning severe impact consequences related to extreme weather events, and he suggested creation of a database of counterfactual compound events. The study was published in the journal Weather and Climate Extremes last February.

According to Dr. Woo, research on compound events and climate change is a key step in strengthening the robustness of current risk models. Climate change projections are uncertain due to three factors: the human-induced forcing; the climate’s response to this forcing; and the climate’s behavior actual to a particular time. “The first governs a choice of climate change scenario. The second is epistemic uncertainty, which can be reduced as knowledge improves but is subjective. The third is an aleatoric uncertainty, reflecting randomness in the realization of climate for a particular time window,’ said Dr. Woo.

It is possible to visualize climate change response uncertainty via a variety of visually consistent storyline configurations. Physical laws of thermodynamics limit the quantitative uncertainty of global warming. Associated with these will be a substantial aleatoric component that determines the intensity of extreme weather. Considering the aleatoric uncertainty in catastrophe weather risk models is particularly useful for making prudent insurance decisions since estimating uncertainty is crucial to this process.

Advances in catastrophe science have often come from major catastrophes. After such events, changes in building codes and risk management are likely to be implemented. A phase space analysis of historical extreme weather events can also yield actionable insights. Dr. Woo emphasized: “Counterfactual analysis provides illuminating new insights into the impact potential associated with extreme compound events, which cannot be obtained by event scaling or statistical analysis.” It takes a lot of time and effort to study aleatoric uncertainty, typically associated with significant historical events. Otherwise, most studies of aleatoric uncertainty are not undertaken to find rare extreme events.

To interpret climate change scenarios, a database of counterfactual compound events would be helpful. Moreover, it will contribute to climate change attribution studies, aiming to quantify the impact of natural and human-caused forces on extreme events. Dr. Woo stated in his critical review that a database of counterfactual compound events would make it easier to create a narrative about future weather. “The online database should provide far more information than a list of dates and qualitative descriptions. It should include impact assessments and maps of hazard footprints associated with the counterfactuals,” he added.

The lessons learned from the past can help us imagine better the weather in the future.  Scenarios can be developed by exploring counterfactuals, even if they have no historical precedent.  Such scenarios have the potential to encourage future disaster mitigation efforts.

Journal Reference and Main Image Credit:

Woo, Gordon. “A counterfactual perspective on compound weather risk.” Weather and Climate Extremes 32 (2021): 100314. DOI:

About the Author

Dr. Gordon Woo, Ph.D.

Dr. Gordon Woo is a catastrophist at Risk Management Solutions addressing quantitative aspects of all extreme hazards and risks, especially those involving complex dynamics. In 2004, Newsweek magazine named him as one of the world’s leading catastrophists. He has written widely on risk assessment and is the author of the Imperial College Press books: ‘The Mathematics of Natural Catastrophes (1999)’ and ‘Calculating Catastrophe (2011)’. His recent research has focused on counterfactual risk analysis, exploring alternative realizations of past hazard events. This type of analysis probes the hazard frontier in ways that can lead to the discovery of Black Swans – surprising events with no historical precedent. This branch of analysis is potentially highly insightful in the study of climate risk. A top Cambridge University graduate in mathematics, he completed his Ph.D. at MIT in theoretical physics as a Kennedy Scholar and was a member of the Harvard Society of Fellows. He is currently a visiting professor at the University College London Institute for Risk and Disaster Reduction, as well as an adjunct professor at the Institute of Catastrophe Risk Management, Nanyang Technological University, Singapore. In addition, he is the chief specialty editor of the Geohazards and Georisks section of Frontiers in Earth Science.