November 6, 2020 - 3:00 pm
November 6, 2020 - 4:00 pm
CategoriesConvective Meteorology (Mesoscale Dynamics)
Name: Tyler Green
Title: Impact of Assimilating WSR-88D Radar Observations for the Analysis and Prediction of the Eyewall Replacement Cycle for Hurricane Matthew (2016) using the HWRF hybrid EnVar System
Time: 03:00 PM
Series: Convective Meteorology (Mesoscale Dynamics)
Abstract: As hurricane Matthew paralleled the east coast of Florida on October 6th-7th, its inner core was continuously sampled by ground-based radar starting at 15Z on the 6th, and by TDR for a shorter period from 19Z to 02Z as it completed an eyewall replacement cycle (ERC). In this study, WSR-88D radar observations are assimilated into the Hurricane Weather Research and Forecasting (HWRF) model using a rapidly updating Ensemble-Variational system (EnVar) data assimilation system. The primary objectives of this study are to determine if and how assimilating ground-based radar observations can increase the predictability of Matthewâ€™s ERC.
Four different experiments consisting of 12 hours of continuous hourly data assimilation cycling are performed. Varied types of inner core observations are assimilated to explore added benefits of assimilating ground-based radar observations on top of assimilating the airborne Tail Doppler radar observations. It was found that additionally assimilating ground-based radar observations can correct an initially weaker storm more quickly than experiments without them. In addition, assimilation of ground-based radar observations improves the analyzed structure and ERC for Matthew. The predictability of Matthewâ€™s ERC in the free forecasts are investigated using HovmÃ¶ler diagrams of azimuthally averaged tangential wind. The results suggest that assimilation of ground-based radar observations aid in the prediction of this ERC process which is known to affect the structure and intensity of TCâ€™s and has been notoriously difficult to forecast.