Abstract
Abstract
Tropical cyclones (TCs) cause substantial disaster losses worldwide. Forecast skill for TC track and intensity has been improved by enhanced observations, high-resolution numerical models, advanced data assimilation methods, and applications of machine-learning methods. Yet these improvements have not consistently translated into reduced losses, in part because disaster outcomes depend on many other elements, including communications between weather agency and the public. Therefore, it is not straightforward to observe the damage reduction by improved TC forecast, and the impact of the improvement of TC track and intensity forecast on damage has not been comprehensively quantified using real-world data. In this study, we examine 32 TCs that made landfall in Japan between 2006 and 2023 and quantify how errors in Joint Typhoon Warning Center operational TC track and intensity forecasts relate to flood-induced damage. To our knowledge, this is the first nationwide assessment for Japan linking operational TC forecast accuracy to observed TC-induced damages. Our multi-linear regression analysis reveals that along-track forecast error—distance between forecast and actual positions along the direction of travel—is positively associated with building and household damages (
p
0.05), implying greater residential and structural impacts when forecasted TC positions deviate farther along the track. Conversely, landfall timing and intensity errors show no statistically significant association with flood damage. Despite the unclear causal relationships, these findings imply that further reductions in track error, particularly its along-track component, may contribute to mitigating TC-related flood losses.