Extreme Atlantic Hurricane Probability of Occurrence Through the Metastatistical Extreme Value Distribution

The estimation of extreme hurricane probability is hampered by small samples and by limitations in our models of extreme tropical storms. Current best estimates of extreme hurricane probability based on the traditional extreme value theory assume hurricane arrivals to be a homogeneous Poisson process. We reformulate here, for application to Atlantic hurricanes, the Metastatistical Extreme Value Distribution (MEVD) that relaxes this key assumption in the traditional extreme value theory and uses all available observations. The MEVD application to the 1886-2017 observational record improves the accuracy of extreme Atlantic hurricane estimation by about 50% with respect to current best estimates. The MEVD allows trends to emerge above estimation uncertainty: A sliding-window analysis shows a significant increase in extreme hurricane likelihood in the past century. This trend, previously uncertain and controversial, remains significant after correcting for hurricane underdetection in the presatellite era and when focusing only on the modern observational period (1970-2017). Plain Language Summary Extreme hurricanes are, by definition, rare. This makes it difficult to estimate their likelihood of occurrence and how it may change in time. We develop here a new approach to the statistical modeling of extreme hurricanes, based on the Metastatistical Extreme Value Distribution, which significantly improves our ability to evaluate their probability of occurrence, particularly when data are scarce. The application of the improved Metastatistical Extreme Value Distribution suggests a significant increase in the probability of occurrence of extreme hurricanes over the past century.