AUTHOR=Hazelton Andrew , Alaka Ghassan J. , Gramer Lew , Ramstrom William , Ditchek Sarah , Chen Xiaomin , Liu Bin , Zhang Zhan , Zhu Lin , Wang Weiguo , Thomas Biju , Shin JungHoon , Wang Chuan-Kai , Kim Hyun-Sook , Zhang Xuejin , Mehra Avichal , Marks Frank , Gopalakrishnan Sundararaman TITLE=2022 real-time Hurricane forecasts from an experimental version of the Hurricane analysis and forecast system (HAFSV0.3S) JOURNAL=Frontiers in Earth Science VOLUME=11 YEAR=2023 URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2023.1264969 DOI=10.3389/feart.2023.1264969 ISSN=2296-6463 ABSTRACT=

During the 2022 hurricane season, real-time forecasts were conducted using an experimental version of the Hurricane Analysis and Forecast System (HAFS). The version of HAFS detailed in this paper (HAFSV0.3S, hereafter HAFS-S) featured the moving nest recently developed at NOAA AOML, and also model physics upgrades: TC-specific modifications to the planetary boundary layer (PBL) scheme and introduction of the Thompson microphysics scheme. The real-time forecasts covered a large dataset of cases across the North Atlantic and eastern North Pacific 2022 hurricane seasons, providing an opportunity to evaluate this version of HAFS ahead of planned operational implementation of a similar version in 2023. The track forecast results show that HAFS-S outperformed the 2022 version of the operational HWRF model in the Atlantic, and was the best of several regional hurricane models in the eastern North Pacific for track. The intensity results were more mixed, with a dropoff in skill at Days 4–5 in the Atlantic but increased skill in the eastern North Pacific. HAFS-S also showed some larger errors than the long-time operational Hurricane Weather Research and Forecasting (HWRF) model in the radius of 34-knot wind, but other radii metrics are improved. Detailed analysis of Hurricane Ian in the Atlantic highlights both the strengths of HAFS and opportunities for further development and improvement.