Is My Tropical Cyclone Storm Recurrence Rate Biased? … An Evaluation of Epistemic Uncertainty in Storm Recurrences Rates

The joint probability method (JPM) has become a preferred approach for probabilistically assessing storm surge hazards from tropical cyclone (TC) events in numerous applications. Probabilistic storm surge hazard assessment (PSSA) using the JPM calculates the rate of exceeding a given measure of surge severity (typically surge elevation) at a given site using the Theorem of Total Probability. The JPM accounts for the rate at which TCs affect a region as well as all TC parameter combinations and their relative probabilities. In this study, we identify, assess, and characterize epistemic uncertainties associated with the estimation of TC storm recurrence rates. We build upon work performed by previous researchers and consider the following factors contributing to epistemic uncertainty in storm recurrence rates: use of recorded storm track data versus interpolated storm track data, the weighting method used for "counting" historical storms in the vicinity of a site, the kernel size used in the selected weighting method, the intensity parameter used to filter "inconsequential storms" from the historical record, the threshold value associated with the selected intensity filter, the historical time period considered in the evaluation (with emphasis on missing data bias), and the impact of coastline geometry definition when partitioning storm populations.

To illustrate the potential effects of epistemic uncertainty, we develop a range of storm surge recurrence rates at representative locations along the North Atlantic coast of the United States and assess how storm rate uncertainty affects estimates of storm surge hazards. We observe that storm rate varies over orders of magnitude when considering the above combinations of factors. We also find that the corresponding range of storm surge elevation spans multiple meters for a given annual exceedance frequency.