Advancements in hurricane prediction with NOAA's next‐generation forecast system

We use the fvGFS model developed at the Geophysical Fluid Dynamics Laboratory to demonstrate the potential of the upcoming United States Next-Generation Global Prediction System for hurricane prediction. The fvGFS retrospective forecasts initialized with the European Centre for Medium-Range Weather Forecasts (ECMWF) data showed much-improved track forecasts for the 2017 Atlantic hurricane season compared to the best-performing ECMWF operational model. The fvGFS greatly improved the ECMWF's poor track forecast for Hurricane Maria (2017). For Hurricane Irma (2017), a well-predicted case by the ECMWF model, the fvGFS produced even lower five-day track forecast errors. The fvGFS also showed better intensity prediction than both the United States and the ECMWF operational models, indicating the robustness of its numerical algorithms.

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Author Chen, Jan‐Huey
Lin, Shian‐Jiann
Magnusson, Linus
Bender, Morris
Chen, Xi
Zhou, Linjiong
Xiang, Baoqiang
Rees, Shannon
Morin, Matthew
Harris, Lucas
Publisher UCAR/NCAR - Library
Publication Date 2019-04-28T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T19:21:28.982469
Metadata Record Identifier edu.ucar.opensky::articles:22542
Metadata Language eng; USA
Suggested Citation Chen, Jan‐Huey, Lin, Shian‐Jiann, Magnusson, Linus, Bender, Morris, Chen, Xi, Zhou, Linjiong, Xiang, Baoqiang, Rees, Shannon, Morin, Matthew, Harris, Lucas. (2019). Advancements in hurricane prediction with NOAA's next‐generation forecast system. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7vt1w5j. Accessed 22 June 2025.

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