| Summary: | While a number of research groups offer quantitative diagnostic indices of aggregate annual Atlantic Basin tropical cyclone (TC) activity, the literature is comparatively thin concerning methods to similarly quantify seasonal U.S. landfall risks. An accurate diagnostic assessment of annual TC risk would be of great public utility and economic value, but the methods used to assess yearly activity demonstrate little skill in evaluating count or severity of TCs making landfall in the continental United States. As existing models are optimized to capture variability in cumulative seasonal TC activity, they are suboptimal statistical diagnostic tools for assessing the potential for sensible impacts of storms on populated areas. This project aims to address this utility gap in existing seasonal aggregate TC potential indices 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 most closely linked to the historical conditions associated with U.S. landfall events. Using an extended record of Atlantic TC activity and reanalysis model datasets, characteristic atmospheric and oceanic traits of elevated U.S. TC landfall risk are identified, with the aim of quantifying the internal variance and predictability of these risks using empirical Poisson regression models. The resulting product, the Landfall Diagnostic Index (LDI), incorporates spatially and temporally averaged measures of relative sea surface temperature, layer-averaged steering winds, zonal shear vorticity, and upper-level divergence to yield a seasonal TC activity metric that has significant fidelity to the interannual and seasonal cycle variability of continental U.S. hurricane landfalls. The LDI offers physical insight into the causes and nature of TC risk on each of these scales, in particular highlighting a potential inherent tension between the conditions most favorable for elevated TC counts and those favoring steering currents directed towards the continental ...
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