Development of a Probabilistic Tropical Cyclone Rainfall Model: P-Rain

Heavy precipitation is a major hazard in landfalling tropical cyclones (TCs). Historically, heavy rainfall has induced freshwater floods and mudslides during TC landfalls, accounting for 27% of deaths and devastating property. Hence, improving current TC quantitative precipitation forecasts is indispensable. A new tropical cyclone rainfall probability model is described that provides five-day probabilistic forecasts of extreme rainfall accumulation above a selected threshold, e.g., 1”, 3”, 6”, etc.. This rainfall probability product is based on the Parametric Hurricane Rainfall Model (PHRaM), which utilizes wind shear forecasts and the National Hurricane Center (NHC) track, intensity, and wind radii forecasts, as well as on NHC forecast error statistics for those forecast variables during recent years. Because of the interdependence of the track, intensity, and structure forecasts, the model utilizes the same Monte Carlo model as the operational wind speed probability model, generating 1000 realizations by randomly sampling from the operational forecast center track and intensity forecast error distributions from the past 5 years. The extent of rainfall accumulations above certain thresholds for each realization is obtained from PHRaM and its underlying rainfall error distributions. Much like the existing wind speed probability model, the extreme rainfall model provides cumulative probabilities that rainfall exceeding a certain extreme rainfall accumulation threshold will occur during cumulative time periods at each specific point on the map. The cumulative periods begin at the start of the forecast period and extend through the entire five-day forecast period at cumulative 12-hour intervals. Examples of the model probability of extreme rainfall accumulations for recent Hurricanes Florence and Michael will be shown.