Steering flow and vortex tilt in basin-scale HWRF

• Main Author: Camposano, Samantha
• Format: Other/Unknown Material
• Published: Scholarly Repository 2018
• Subjects: layer mean wind; tropical cyclone; vortext tilt; Hurricane Weather Research and Forecasting; North Atlantic; hurricane season; Environmental Sciences
• Online Access: https://scholarlyrepository.miami.edu/rsmas_intern_reports/320; https://scholarlyrepository.miami.edu/cgi/viewcontent.cgi?article=1317&context=rsmas_intern_reports

The purpose of this project is to evaluate layer mean wind (i.e., “steering flow”), tropical cyclone (TC) vortex tilt, and TC motion produced by the “Basin-Scale” Hurricane Weather Research and Forecasting (HWRF-B) Model. This evaluation improves understanding of the relationship between these three parameters, especially for different TCs, forecast lead times, TC intensities, and vertical wind shear. In particular, analyses of steering flow and vortex tilt provided evidence of how TC vortex structure and TC motion respond to the vertical environmental wind profile in a regional numerical weather prediction model. Distributions of steering flow and vortex tilt were evaluated in HWRF-B forecasts from an active period in the 2017 North Atlantic hurricane season (i.e., 1 August to 31 October). Consequently, this project aims to improve guidance on TC motion and structure as a function of environmental wind profiles and identifies model biases through the rigorous study of near-TC winds. The results of this project suggest that there may be a strong influence of surface level features on overall steering flow of TCs. Moreover, consistencies with conventional knowledge of TC steering flow and structure are discussed. By evaluating HWRF-B output from the 2017 North Atlantic hurricane season, we can begin to understand how steering flow and vortex tilt parameters are accounted for and if there is any noticeable bias compared to expectations based on other studies. These results from HWRF-B may guide interpretation of such parameters from the operational HWRF and other high-resolution models, providing official forecasters, scientific communicators, and decision makers the best available resources to warn communities of TC hazards and plan for evacuation and mitigation in a timely manner.