Navigating and attributing uncertainty in future tropical cyclone risk estimates
Simona Meiler, Chahan M. Kropf, Jamie W. McCaughey, Chia‐Ying Lee, Suzana J. Camargo, Adam H. Sobel, Nadia Bloemendaal, Kerry Emanuel, David N. Bresch
Abstract
Future tropical cyclone risks will evolve with climate change and socioeconomic development, entailing substantial uncertainties. An uncertainty and sensitivity analysis of these risks is vital, yet the chosen model setup influences outcomes. This study investigates how much future tropical cyclone risks are driven by climate and socioeconomic changes, quantifies uncertainty from propagating alternate representations of these systems through the risk modeling chain, and evaluates how strongly each model input contributes to output uncertainty. By comparing these three elements-drivers, uncertainty, and sensitivity-across four distinct tropical cyclone models, we derive findings generalizable beyond individual model setups. We find that average tropical cyclone risk will increase 1 to 5% by 2050 globally, with maximum increases ranging from 10 to 400% by 2100, depending on tropical cyclone model choice, region, and risk model inputs, while the dominant source of uncertainty shifts with modeling choices. Last, we differentiate between aleatory, epistemic, and normative uncertainties, offering guidance to reduce them and inform better decision-making.