2019 Atlantic Hurricane Forecasts from the Global-Nested Hurricane Analysis and Forecast System: Composite Statistics and Key Events

Abstract

NOAA’s Hurricane Analysis and Forecast System (HAFS) is an evolving FV3-based hurricane modeling system that is expected to replace the operational hurricane models at the National Weather Service. Supported by the Hurricane Forecast Improvement Program (HFIP), global-nested and regional versions of HAFS were run in real-time in 2019 to create the first baseline for the HAFS advancement. In this study, forecasts from the global-nested configuration of HAFS (HAFS-globalnest) are evaluated and compared with other operational and experimental models. The forecasts by HAFS-globalnest covered the period from July through October during the 2019 hurricane season. Tropical cyclone (TC) track, intensity, and structure forecast verifications are examined. HAFS-globalnest showed track skill superior to several operational hurricane models and comparable intensity and structure skill, although the skill in predicting rapid intensification was slightly inferior to the operational model skill. HAFS-globalnest correctly predicted that Hurricane Dorian would slow and turn north in the Bahamas and also correctly predicted structural features in other TCs such as a sting jet in Hurricane Humberto during extratropical transition. Humberto was also a case where HAFS-globalnest had better track forecasts than a regional version of HAFS (HAFS-SAR) due to a better representation of the large-scale flow. These examples and others are examined through comparisons with airborne tail Doppler radar from the NOAA WP-3D to provide a more detailed evaluation of TC structure prediction. The results from this real-time experiment motivates several future model improvements, and highlights the promise of HAFS-globalnest for improved TC prediction.

The Role of Eyewall Turbulent Transport in the Pathway to Intensification of Tropical Cyclones

“…It uses Geophysical Fluid Dynamics Laboratory (GFDL) finite‐volume dynamic core (FV3, e.g., Harris & Lin, 2013; Lin, 2004) with a static nest covering most of the Atlantic basin. The grid spacing of the global domain is ∼13 km and the grid spacing of the nest is ∼3 km for the Atlantic grid layout (Hazelton, Zhang, et al., 2021). There is a 2‐way feedback between the parent and nested domains.…”

“…But the surface layer scheme considers the variation of surface exchange coefficients at high wind speeds for oceanic conditions (Bender et al., 2007). HAFS‐globalnest has been used in near‐real‐time experiments (Hazelton, Zhang, et al., 2021), showing promising track skill compared to other operational models, and some skill in predicting TC structure and intensity changes. It has also been utilized in research to understand the processes underlying the intensification of Hurricanes Dorian (2019, Hazelton, Alaka, et al., 2021) and Michael (2018, Hazelton et al., 2020).…”

High-Definition Hurricanes: Improving Forecasts with Storm-Following Nests

“…Many TC research studies have used NWP models configured with nests that did not move during the model integration (e.g., Harrison 1973;Mathur 1974;Ookuchi 1974;Wu et al 2006;Rotunno et al 2009;Lin et al 2010;Hazelton et al 2021). However, static nests large enough to contain a TC throughout a multi-day forecast and that have resolution fine enough to realistically predict TC intensity and structure are computationally expensive and are not currently supported in operations.…”

“…However, static nests large enough to contain a TC throughout a multi-day forecast and that have resolution fine enough to realistically predict TC intensity and structure are computationally expensive and are not currently supported in operations. For example, Hazelton et al (2021) highlighted a global-nested model configured with a high-resolution static nest that spanned the entire North Atlantic hurricane basin, and, while this approach yielded promising results, it is currently too expensive for operations. Furthermore, if static nests are too small, the TC could exit the high-resolution region, where intensity forecasts degrade significantly (Gopalakrishnan et al 2006).…”

“…The goal of this study is to highlight the evolution and performance of high-resolution, storm-following nested grids in HWRF. This is timely because NOAA is currently developing moving nest technology to be implemented in the Hurricane Analysis and Forecast System (HAFS; Dong et al 2020;Gopalakrishnan et al 2020;Hazelton et al 2021), the hurricane application of the Unified Forecast System 2 (UFS; National Weather Service 2017; Rood et al 2018). UFS is a community-based, coupled, comprehensive NWP model for operational forecasts at NOAA and is based on the finite volume cubed-sphere (FV3) dynamical core (Lin and Rood 1996;Lin 2004;Harris and Lin 2013).…”