Performance of 2020 real-time Atlantic hurricane forecasts from high-resolution global-nested hurricane models: HAFS-globalnest and GFDL T-SHiELD

The global-nested Hurricane Analysis and Forecast System (HAFS-globalnest) is one piece of NOAA's Unified Forecast System (UFS) application for hurricanes. In this study, results are analyzed from 2020 real-time forecasts by HAFS-globalnest and a similar global-nested model, the Tropical Atlant...

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Published in:Weather and Forecasting
Other Authors: Hazelton, Andrew (author), Gao, Kun (author), Bender, Morris (author), Cowan, Levi (author), Alaka, Ghassan J. (author), Kaltenbaugh, Alex (author), Gramer, Lew (author), Zhang, Xuejin (author), Harris, Lucas (author), Marchok, Timothy (author), Morin, Matt (author), Mehra, Avichal (author), Zhang, Zhan (author), Liu, Bin (author), Marks, Frank (author)
Format: Article in Journal/Newspaper
Language:English
Published: 2022
Subjects:
Online Access:https://doi.org/10.1175/WAF-D-21-0102.1
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spelling ftncar:oai:drupal-site.org:articles_25374 2024-04-28T08:31:05+00:00 Performance of 2020 real-time Atlantic hurricane forecasts from high-resolution global-nested hurricane models: HAFS-globalnest and GFDL T-SHiELD Hazelton, Andrew (author) Gao, Kun (author) Bender, Morris (author) Cowan, Levi (author) Alaka, Ghassan J. (author) Kaltenbaugh, Alex (author) Gramer, Lew (author) Zhang, Xuejin (author) Harris, Lucas (author) Marchok, Timothy (author) Morin, Matt (author) Mehra, Avichal (author) Zhang, Zhan (author) Liu, Bin (author) Marks, Frank (author) 2022-01-01 https://doi.org/10.1175/WAF-D-21-0102.1 en eng Weather and Forecasting--0882-8156--1520-0434 articles:25374 doi:10.1175/WAF-D-21-0102.1 ark:/85065/d7c53qj8 Copyright 2022 American Meteorological Society. article Text 2022 ftncar https://doi.org/10.1175/WAF-D-21-0102.1 2024-04-04T17:34:52Z The global-nested Hurricane Analysis and Forecast System (HAFS-globalnest) is one piece of NOAA's Unified Forecast System (UFS) application for hurricanes. In this study, results are analyzed from 2020 real-time forecasts by HAFS-globalnest and a similar global-nested model, the Tropical Atlantic version of GFDL's System for High-resolution prediction on Earth-to-Local Domains (T-SHiELD). HAFS-globalnest produced the highest track forecast skill compared to several operational and experimental models, while T-SHiELD showed promising track skills as well. The intensity forecasts from HAFS-globalnest generally had a positive bias at longer lead times primarily due to the lack of ocean coupling, while T-SHiELD had a much smaller intensity bias particularly at longer forecast lead times. With the introduction of a modified planetary boundary layer scheme and an increased number of vertical levels, particularly in the boundary layer, HAFS forecasts of storm size had a smaller positive bias than occurred in the 2019 version of HAFS-globalnest. Despite track forecasts that were comparable to the operational GFS and HWRF, both HAFS-globalnest and T-SHiELD suffered from a persistent right-of-track bias in several cases at the 4-5-day forecast lead times. The reasons for this bias were related to the strength of the subtropical ridge over the western North Atlantic and are continuing to be investigated and diagnosed. A few key case studies from this very active hurricane season, including Hurricanes Laura and Delta, were examined. Article in Journal/Newspaper North Atlantic OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) Weather and Forecasting 37 1 143 161
institution Open Polar
collection OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research)
op_collection_id ftncar
language English
description The global-nested Hurricane Analysis and Forecast System (HAFS-globalnest) is one piece of NOAA's Unified Forecast System (UFS) application for hurricanes. In this study, results are analyzed from 2020 real-time forecasts by HAFS-globalnest and a similar global-nested model, the Tropical Atlantic version of GFDL's System for High-resolution prediction on Earth-to-Local Domains (T-SHiELD). HAFS-globalnest produced the highest track forecast skill compared to several operational and experimental models, while T-SHiELD showed promising track skills as well. The intensity forecasts from HAFS-globalnest generally had a positive bias at longer lead times primarily due to the lack of ocean coupling, while T-SHiELD had a much smaller intensity bias particularly at longer forecast lead times. With the introduction of a modified planetary boundary layer scheme and an increased number of vertical levels, particularly in the boundary layer, HAFS forecasts of storm size had a smaller positive bias than occurred in the 2019 version of HAFS-globalnest. Despite track forecasts that were comparable to the operational GFS and HWRF, both HAFS-globalnest and T-SHiELD suffered from a persistent right-of-track bias in several cases at the 4-5-day forecast lead times. The reasons for this bias were related to the strength of the subtropical ridge over the western North Atlantic and are continuing to be investigated and diagnosed. A few key case studies from this very active hurricane season, including Hurricanes Laura and Delta, were examined.
author2 Hazelton, Andrew (author)
Gao, Kun (author)
Bender, Morris (author)
Cowan, Levi (author)
Alaka, Ghassan J. (author)
Kaltenbaugh, Alex (author)
Gramer, Lew (author)
Zhang, Xuejin (author)
Harris, Lucas (author)
Marchok, Timothy (author)
Morin, Matt (author)
Mehra, Avichal (author)
Zhang, Zhan (author)
Liu, Bin (author)
Marks, Frank (author)
format Article in Journal/Newspaper
title Performance of 2020 real-time Atlantic hurricane forecasts from high-resolution global-nested hurricane models: HAFS-globalnest and GFDL T-SHiELD
spellingShingle Performance of 2020 real-time Atlantic hurricane forecasts from high-resolution global-nested hurricane models: HAFS-globalnest and GFDL T-SHiELD
title_short Performance of 2020 real-time Atlantic hurricane forecasts from high-resolution global-nested hurricane models: HAFS-globalnest and GFDL T-SHiELD
title_full Performance of 2020 real-time Atlantic hurricane forecasts from high-resolution global-nested hurricane models: HAFS-globalnest and GFDL T-SHiELD
title_fullStr Performance of 2020 real-time Atlantic hurricane forecasts from high-resolution global-nested hurricane models: HAFS-globalnest and GFDL T-SHiELD
title_full_unstemmed Performance of 2020 real-time Atlantic hurricane forecasts from high-resolution global-nested hurricane models: HAFS-globalnest and GFDL T-SHiELD
title_sort performance of 2020 real-time atlantic hurricane forecasts from high-resolution global-nested hurricane models: hafs-globalnest and gfdl t-shield
publishDate 2022
url https://doi.org/10.1175/WAF-D-21-0102.1
genre North Atlantic
genre_facet North Atlantic
op_relation Weather and Forecasting--0882-8156--1520-0434
articles:25374
doi:10.1175/WAF-D-21-0102.1
ark:/85065/d7c53qj8
op_rights Copyright 2022 American Meteorological Society.
op_doi https://doi.org/10.1175/WAF-D-21-0102.1
container_title Weather and Forecasting
container_volume 37
container_issue 1
container_start_page 143
op_container_end_page 161
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