SPATIAL CHARACTERIZATION OF INLAND FLOODING ASSOCIATED WITH LANDFALLING TROPICAL CYCLONES

Abstract

Rainfall and freshwater flooding from tropical cyclones (TCs) cause large numbers of fatalities and vast economic damage, and they have been shown to play an important role in controlling the upper tail of flood distributions. This study aims to improve our understanding of TC rainfall mechanisms and associated flood characteristics with various observations and modeling efforts. First, we study and explore effective modeling approaches to four major TC rainfall mechanisms (i.e., surface frictional convergence, vortex stretching, interaction of the storm with topography, and interaction of the storm with large-scale baroclinity) with a recently-developed physics-based TC rainfall Model (TCRM) and Weather Research and Forecasting (WRF) model for Hurricanes Isabel (2003) and Irene (2011). We analyze the sensitivity of azimuthal and spatial distribution of rainfall to wind input and modeling parameters and rainfall extremely sensitive to the gradient wind input, as well as drag coefficient. Second, we develop a framework to characterize the distribution of flood magnitudes over large river networks with a distributed hydrologic model (CUENCAS). Summary statistics for characterizing the probability distribution and spatial correlation of flood magnitudes are developed, and their linkage to distributions of rainfall are analyzed with four flood events in Delaware River Basin that reflect the principal flood-generating mechanisms in eastern U.S.: landfalling tropical cyclones (Hurricane Ivan in September 2004 and Hurricane Irene in August 2011), late winter - early spring extratropical systems (April 2005) and warm-season convective systems (June 2006). The methodologies developed in these two projects are further applied to two flood events: a remote one with limited observations, the August 1955 flood over Delaware River Basin associated Hurricane Connie and Diane; and a recent one with various sources of observations, the event of Hurricane Matthew 2016 over the southeast of U.S. Given the high computational efficiency, TC rainfall modeling (TCRM) and hydrologic model (CUENCAS) can be coupled with an analytical wind model, and a TC climatology model to generate large numbers of synthetic events to assess the spatial characteristics of the risk of freshwater flooding associated with landfalling TCs.