Closing the gap — Hurricane Prediction Advances in the US FV3-based Models

Jan-Huey Chen NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Timothy Marchok NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Morris Bender NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Kun Gao Cooperative Institute for Modeling the Earth System, Princeton University, Princeton, New Jersey

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Sundararaman Gopalakrishnan NOAA/Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, Miami, Florida

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Lucas Harris NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Andrew Hazelton NOAA/Environmental Modeling Center, College Park, Maryland

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Bin Liu Lynker at NOAA/NWS/NCEP/EMC, College Park, Maryland

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Avichal Mehra NOAA/Environmental Modeling Center, College Park, Maryland

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Matthew Morin University Corporation for Atmospheric Research, Boulder, Colorado
NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Fanglin Yang NOAA/Environmental Modeling Center, College Park, Maryland

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Xuejin Zhang NOAA/Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, Miami, Florida

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Zhan Zhang NOAA/Environmental Modeling Center, College Park, Maryland

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Linjiong Zhou Cooperative Institute for Modeling the Earth System, Princeton University, Princeton, New Jersey

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Open access

Abstract

The Integrated Forecasting System (IFS) developed by the European Centre for Medium-range Weather Forecasts (ECMWF) has been regarded as the best guidance for hurricane track forecasts for years. However, the performance of US models on hurricane forecasts have been catching up. Since 2019, various FV3 (Finite-Volume Cubed-Sphere Dynamical Core)-based models, including National Centers for Environmental Prediction (NCEP) operational Global Forecast System (GFS), newly operational Hurricane Analysis and Forecast System (HAFS), and research-oriented Geophysical Fluid Dynamics Laboratory (GFDL) System for High-resolution prediction on Earth-to-Local Domains (SHiELD), have consistently demonstrated improved hurricane forecasts in the North Atlantic basin, relative to the previous generation of National Oceanic and Atmospheric Administration (NOAA) operational and research models. This article presents the progress that has been made, and identifies areas for improvement for US model development on hurricane forecasts.

© 2025 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jan-Huey Chen, Jan-Huey.Chen@noaa.gov

Abstract

The Integrated Forecasting System (IFS) developed by the European Centre for Medium-range Weather Forecasts (ECMWF) has been regarded as the best guidance for hurricane track forecasts for years. However, the performance of US models on hurricane forecasts have been catching up. Since 2019, various FV3 (Finite-Volume Cubed-Sphere Dynamical Core)-based models, including National Centers for Environmental Prediction (NCEP) operational Global Forecast System (GFS), newly operational Hurricane Analysis and Forecast System (HAFS), and research-oriented Geophysical Fluid Dynamics Laboratory (GFDL) System for High-resolution prediction on Earth-to-Local Domains (SHiELD), have consistently demonstrated improved hurricane forecasts in the North Atlantic basin, relative to the previous generation of National Oceanic and Atmospheric Administration (NOAA) operational and research models. This article presents the progress that has been made, and identifies areas for improvement for US model development on hurricane forecasts.

© 2025 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jan-Huey Chen, Jan-Huey.Chen@noaa.gov
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