The Evaluation of Real-Time Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) Model Performance for the 2019 Atlantic Hurricane Season
The next generation Hurricane Analysis and Forecast System (HAFS) has been developed recently in the National Oceanic and Atmospheric Administration (NOAA) to accelerate the improvement of tropical cyclone (TC) forecasts within the Unified Forecast System (UFS) framework. The finite-volume cubed sph...
Published in: | Atmosphere |
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Main Authors: | , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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MDPI AG
2020
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Online Access: | https://doi.org/10.3390/atmos11060617 https://doaj.org/article/3e53138cdd1f447d83ef1ba3e8a19c5e |
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author | Jili Dong Bin Liu Zhan Zhang Weiguo Wang Avichal Mehra Andrew T. Hazelton Henry R. Winterbottom Lin Zhu Keqin Wu Chunxi Zhang Vijay Tallapragada Xuejin Zhang Sundararaman Gopalakrishnan Frank Marks |
author_facet | Jili Dong Bin Liu Zhan Zhang Weiguo Wang Avichal Mehra Andrew T. Hazelton Henry R. Winterbottom Lin Zhu Keqin Wu Chunxi Zhang Vijay Tallapragada Xuejin Zhang Sundararaman Gopalakrishnan Frank Marks |
author_sort | Jili Dong |
collection | Directory of Open Access Journals: DOAJ Articles |
container_issue | 6 |
container_start_page | 617 |
container_title | Atmosphere |
container_volume | 11 |
description | The next generation Hurricane Analysis and Forecast System (HAFS) has been developed recently in the National Oceanic and Atmospheric Administration (NOAA) to accelerate the improvement of tropical cyclone (TC) forecasts within the Unified Forecast System (UFS) framework. The finite-volume cubed sphere (FV3) based convection-allowing HAFS Stand-Alone Regional model (HAFS-SAR) was successfully implemented during Hurricane Forecast Improvement Project (HFIP) real-time experiments for the 2019 Atlantic TC season. HAFS-SAR has a single large 3-km horizontal resolution regional domain covering the North Atlantic basin. A total of 273 cases during the 2019 TC season are systematically evaluated against the best track and compared with three operational forecasting systems: Global Forecast System (GFS), Hurricane Weather Research and Forecasting model (HWRF), and Hurricanes in a Multi-scale Ocean-coupled Non-hydrostatic model (HMON). HAFS-SAR has the best performance in track forecasts among the models presented in this study. The intensity forecasts are improved over GFS, but show less skill compared to HWRF and HMON. The radius of gale force wind is over-predicted in HAFS-SAR, while the hurricane force wind radius has lower error than other models. |
format | Article in Journal/Newspaper |
genre | North Atlantic |
genre_facet | North Atlantic |
id | ftdoajarticles:oai:doaj.org/article:3e53138cdd1f447d83ef1ba3e8a19c5e |
institution | Open Polar |
language | English |
op_collection_id | ftdoajarticles |
op_doi | https://doi.org/10.3390/atmos11060617 |
op_relation | https://www.mdpi.com/2073-4433/11/6/617 https://doaj.org/toc/2073-4433 doi:10.3390/atmos11060617 2073-4433 https://doaj.org/article/3e53138cdd1f447d83ef1ba3e8a19c5e |
op_source | Atmosphere, Vol 11, Iss 6, p 617 (2020) |
publishDate | 2020 |
publisher | MDPI AG |
record_format | openpolar |
spelling | ftdoajarticles:oai:doaj.org/article:3e53138cdd1f447d83ef1ba3e8a19c5e 2025-01-16T23:41:31+00:00 The Evaluation of Real-Time Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) Model Performance for the 2019 Atlantic Hurricane Season Jili Dong Bin Liu Zhan Zhang Weiguo Wang Avichal Mehra Andrew T. Hazelton Henry R. Winterbottom Lin Zhu Keqin Wu Chunxi Zhang Vijay Tallapragada Xuejin Zhang Sundararaman Gopalakrishnan Frank Marks 2020-06-01T00:00:00Z https://doi.org/10.3390/atmos11060617 https://doaj.org/article/3e53138cdd1f447d83ef1ba3e8a19c5e EN eng MDPI AG https://www.mdpi.com/2073-4433/11/6/617 https://doaj.org/toc/2073-4433 doi:10.3390/atmos11060617 2073-4433 https://doaj.org/article/3e53138cdd1f447d83ef1ba3e8a19c5e Atmosphere, Vol 11, Iss 6, p 617 (2020) tropical cyclones numerical weather prediction high resolution tropical cyclone forecasts finite-volume cubed sphere (FV3) Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) models Meteorology. Climatology QC851-999 article 2020 ftdoajarticles https://doi.org/10.3390/atmos11060617 2023-12-10T01:49:17Z The next generation Hurricane Analysis and Forecast System (HAFS) has been developed recently in the National Oceanic and Atmospheric Administration (NOAA) to accelerate the improvement of tropical cyclone (TC) forecasts within the Unified Forecast System (UFS) framework. The finite-volume cubed sphere (FV3) based convection-allowing HAFS Stand-Alone Regional model (HAFS-SAR) was successfully implemented during Hurricane Forecast Improvement Project (HFIP) real-time experiments for the 2019 Atlantic TC season. HAFS-SAR has a single large 3-km horizontal resolution regional domain covering the North Atlantic basin. A total of 273 cases during the 2019 TC season are systematically evaluated against the best track and compared with three operational forecasting systems: Global Forecast System (GFS), Hurricane Weather Research and Forecasting model (HWRF), and Hurricanes in a Multi-scale Ocean-coupled Non-hydrostatic model (HMON). HAFS-SAR has the best performance in track forecasts among the models presented in this study. The intensity forecasts are improved over GFS, but show less skill compared to HWRF and HMON. The radius of gale force wind is over-predicted in HAFS-SAR, while the hurricane force wind radius has lower error than other models. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Atmosphere 11 6 617 |
spellingShingle | tropical cyclones numerical weather prediction high resolution tropical cyclone forecasts finite-volume cubed sphere (FV3) Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) models Meteorology. Climatology QC851-999 Jili Dong Bin Liu Zhan Zhang Weiguo Wang Avichal Mehra Andrew T. Hazelton Henry R. Winterbottom Lin Zhu Keqin Wu Chunxi Zhang Vijay Tallapragada Xuejin Zhang Sundararaman Gopalakrishnan Frank Marks The Evaluation of Real-Time Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) Model Performance for the 2019 Atlantic Hurricane Season |
title | The Evaluation of Real-Time Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) Model Performance for the 2019 Atlantic Hurricane Season |
title_full | The Evaluation of Real-Time Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) Model Performance for the 2019 Atlantic Hurricane Season |
title_fullStr | The Evaluation of Real-Time Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) Model Performance for the 2019 Atlantic Hurricane Season |
title_full_unstemmed | The Evaluation of Real-Time Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) Model Performance for the 2019 Atlantic Hurricane Season |
title_short | The Evaluation of Real-Time Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) Model Performance for the 2019 Atlantic Hurricane Season |
title_sort | evaluation of real-time hurricane analysis and forecast system (hafs) stand-alone regional (sar) model performance for the 2019 atlantic hurricane season |
topic | tropical cyclones numerical weather prediction high resolution tropical cyclone forecasts finite-volume cubed sphere (FV3) Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) models Meteorology. Climatology QC851-999 |
topic_facet | tropical cyclones numerical weather prediction high resolution tropical cyclone forecasts finite-volume cubed sphere (FV3) Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) models Meteorology. Climatology QC851-999 |
url | https://doi.org/10.3390/atmos11060617 https://doaj.org/article/3e53138cdd1f447d83ef1ba3e8a19c5e |