Evaluation of a Physics-Based Tropical Cyclone Rainfall Model and Its Application for Risk Assessment

Heavy rainfall generated by landfalling tropical cyclones (TCs) can cause extreme flooding to coastal and inland areas. Previous studies suggest that the impact of climate change on TCs may increase the risk of extreme TC rainfall. Therefore, it is important to analyze the climatology of TC rainfall and its evolution in a changing climate. A physics-based tropical cyclone rainfall model (TCRM) was developed (Lu et al. 2018) and coupled with TC climatology models to study the climatology of TC rainfall in previous research (Emanuel 2017). However, the statistics of the rainfall generated by TCRM was evaluated only in the coupled model and for limited U.S. mainland sites based on ground observations. In this study, we evaluate TCRM with satellite rainfall observation of North Atlantic TCs from 1999 to 2018. It is found that TCRM has satisfactory ability in simulating total rainfall from TCs, although it often overestimates TC rainfall in inner core and underestimate it in outer radii. The comparison also shows that TCRM has less capability in simulating TC rainfall in high latitudes. Special effort is made to analyze the ability of TCRM to reproduce the statistics of extreme rainfall event in historical storms, and it is found that TCRM may overestimate the occurrence rate of extreme events. Based on the observations, an analysis is carried out to evaluate the influence on the simulation of different wind field inputs to TCRM. Among the different input theoretical wind profiles for TCRM, the complete wind profile model developed by Chavas et al. (2015) works the best. TCRM is then coupled with a recently developed statistical synthetic storm generation framework and TC size models. The structure of TC rainfall and rainfall climatology based on generated synthetic storms are compared with the observation, and special attention is paid to analyze TC rainfall return periods in coastal cities. Results from this study will help to better apply TCRM in aiding policy makers and civil engineers in preparing of possible extreme TC rainfall events in both current and future climates. (Reference: 1. Emanuel, K. (2017). Assessing the present and future probability of Hurricane Harvey’s rainfall Proceedings of the National Academy of Sciences, 114(48), 12681–12684. https://doi.org/10.1073/pnas.1716222114 2. Lu, P., & Lin, N. , Emanuel, K., Smith, J., Chavas, D. (2018). Assessing Hurricane Rainfall Mechanisms Using a Physics-Based Model: Hurricanes Isabel (2003) and Irene (2011). Journal of the Atmospheric Sciences, 2337–2358. https://doi.org/10.1175/jas-d-17-0264.1 3. D. Chavas, N. Lin, and K. Emanuel, 2015: A model for the complete radial structure of the tropical cyclone wind field. Part I: Comparison with observed structure. J. Atmos. Sci., 72, 3647– 3662, http://doi.org/10.1175/JAS-D-15-0014.1 )