Predicting Tropical Cyclone Landfall Risk Through Genesis and Steering Climatology

While a number of research groups offer quantitative pre-seasonal assessments of aggregate annual Atlantic Basin tropical cyclone (TC) activity, with some noteworthy exceptions the literature is comparatively thin concerning methods to meaningfully quantify seasonal U.S. landfall risks. While an accurate probabilistic assessment of seasonal TC threat levels would be of immense public utility and economic value, the methods used to predict annual activity demonstrate relatively little skill for predicting annual count of landfalling systems in any intensity bin. Therefore, as current dynamical and statistical models are largely optimized to predict cumulative seasonal TC activity, they are not ideal tools for assessing the potential for sensible impacts of storms on populated areas.

This research project bridges a utility gap in seasonal TC forecasting by taking a broader view of the factors that influence where TCs develop and move in the Atlantic Basin, shifting the focus to the physical parameters that are most closely linked to conditions favorable for U.S. landfalls. As overall activity is demonstrated to have a limited relationship to sensible outcomes, this project concentrates on detecting predictability and trends in both cyclogenesis location and upper-level steering patterns. Using reanalysis model datasets, atmospheric and oceanic precursors to elevated risks of U.S. TC landfall are identified, and the variance and predictability of such patterns on seasonal timescales are quantified. These results concerning the spatial and temporal relationships of genesis and steering with TC landfall risk are used to construct a statistical model of U.S. hurricane landfall probability, which is designed to be a predictive tool for incorporation into TC risk mitigation strategies.