Liu, YiIrish, Jennifer L.2019-02-132019-02-132019http://hdl.handle.net/10919/87566Forerunner surge, a water level rise ahead of tropical cyclone landfall, often strikes coastal communities unexpectedly, stranding people and increasing loss of life. Surge forecasting systems and emergency managers almost exclusively focus on peak surge, while much less attention is given to forerunner surge. To address the need for fast and accurate forecasting of forerunner surge, we analyze high-fidelity surge simulations in Virginia, New York/New Jersey and Texas and extract physical scaling laws between readily available storm track information and forerunner surge magnitude and timing. We demonstrate that a dimensionless relationship between central-pressure scaled surge and wind-duration scaled time may effectively be used for rapid forerunner surge forecasting, where uncertainty is considered. We use our method to predict forerunner surge for Hurricanes Ike (2008)—a significant forerunner surge event—and Harvey (2017). The predicted forerunner surge 24 to 6 hours before Hurricane Ike’s landfall ranged from 0.4 to 2.8 m, where the observed forerunner surge ranged from 0.4 to 2.6 m. This new method has the potential to be incorporated into real-time surge forecasting systems to aid emergency management and evacuation decisions.application/pdfenCreative Commons Attribution-NonCommercial-NoDerivs 3.0 United StatesTropical cyclonesForerunner surgeModelingArticle - Refereedhttps://doi.org/10.1016/j.coastaleng.2019.01.005