A statistical/dynamical model for North Atlantic seasonal hurricane prediction
Colorado State University (CSU) has been issuing seasonal hurricane forecasts since 1984, with statistical modeling techniques primarily underpinning these outlooks. CSU has recently begun issuing statistical/dynamical forecasts, using the SEAS5 forecast system from the European Centre for Medium‐Ra...
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ftupcatalunyair:oai:upcommons.upc.edu:2117/330979 2023-05-15T17:34:04+02:00 A statistical/dynamical model for North Atlantic seasonal hurricane prediction Klotzbach, Philip Caron, Louis-Philippe Bell, Michael Barcelona Supercomputing Center 2020-10 9 p. application/pdf http://hdl.handle.net/2117/330979 https://doi.org/10.1029/2020GL089357 eng eng American Geophysical Union https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL089357 Klotzbach, P.; Caron, L.-P.; Bell, M. A statistical/dynamical model for North Atlantic seasonal hurricane prediction. "Geophysical Research Letters", Octubre 2020, vol. 47, núm. 20, e2020GL089357. doi:10.1029/2020GL089357 1944-8007 http://hdl.handle.net/2117/330979 Open Access Àrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia Climatology Cyclone forecasting Seasonal climate forecasting Hurricane Tropical cyclone Statistical modeling Climate modeling Seasonal forecasting Climatologia Ciclons Huracans Article 2020 ftupcatalunyair https://doi.org/10.1029/2020GL089357 2021-04-13T23:05:01Z Colorado State University (CSU) has been issuing seasonal hurricane forecasts since 1984, with statistical modeling techniques primarily underpinning these outlooks. CSU has recently begun issuing statistical/dynamical forecasts, using the SEAS5 forecast system from the European Centre for Medium‐Range Weather Forecasts to forecast the three predictors that currently comprise CSU's early August statistical forecast model. SEAS5 shows skill at forecasting all three of these July predictors from an initialization as early as 1 March. The SEAS5 model forecasts for the three parameters are then regressed against seasonal accumulated cyclone energy. The model has a cross‐validated correlation skill of r = 0.60 with accumulated cyclone energy for a 1 March initialization, improving to r = 0.67 for a 1 June initialization over the period from 1982–2019. The combination of the statistical/dynamical model with the currently existing statistical models shows improved skill over either model individually for the April, June, and July outlooks. Phil Klotzbach would like to acknowledge grants from the Severo Ochoa Mobility Program and the G. Unger Vetlesen Foundation. Michael Bell was funded by the Office of Naval Research award N000141613033. Peer Reviewed Postprint (published version) Article in Journal/Newspaper North Atlantic Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge Geophysical Research Letters 47 20 |
institution |
Open Polar |
collection |
Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge |
op_collection_id |
ftupcatalunyair |
language |
English |
topic |
Àrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia Climatology Cyclone forecasting Seasonal climate forecasting Hurricane Tropical cyclone Statistical modeling Climate modeling Seasonal forecasting Climatologia Ciclons Huracans |
spellingShingle |
Àrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia Climatology Cyclone forecasting Seasonal climate forecasting Hurricane Tropical cyclone Statistical modeling Climate modeling Seasonal forecasting Climatologia Ciclons Huracans Klotzbach, Philip Caron, Louis-Philippe Bell, Michael A statistical/dynamical model for North Atlantic seasonal hurricane prediction |
topic_facet |
Àrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia Climatology Cyclone forecasting Seasonal climate forecasting Hurricane Tropical cyclone Statistical modeling Climate modeling Seasonal forecasting Climatologia Ciclons Huracans |
description |
Colorado State University (CSU) has been issuing seasonal hurricane forecasts since 1984, with statistical modeling techniques primarily underpinning these outlooks. CSU has recently begun issuing statistical/dynamical forecasts, using the SEAS5 forecast system from the European Centre for Medium‐Range Weather Forecasts to forecast the three predictors that currently comprise CSU's early August statistical forecast model. SEAS5 shows skill at forecasting all three of these July predictors from an initialization as early as 1 March. The SEAS5 model forecasts for the three parameters are then regressed against seasonal accumulated cyclone energy. The model has a cross‐validated correlation skill of r = 0.60 with accumulated cyclone energy for a 1 March initialization, improving to r = 0.67 for a 1 June initialization over the period from 1982–2019. The combination of the statistical/dynamical model with the currently existing statistical models shows improved skill over either model individually for the April, June, and July outlooks. Phil Klotzbach would like to acknowledge grants from the Severo Ochoa Mobility Program and the G. Unger Vetlesen Foundation. Michael Bell was funded by the Office of Naval Research award N000141613033. Peer Reviewed Postprint (published version) |
author2 |
Barcelona Supercomputing Center |
format |
Article in Journal/Newspaper |
author |
Klotzbach, Philip Caron, Louis-Philippe Bell, Michael |
author_facet |
Klotzbach, Philip Caron, Louis-Philippe Bell, Michael |
author_sort |
Klotzbach, Philip |
title |
A statistical/dynamical model for North Atlantic seasonal hurricane prediction |
title_short |
A statistical/dynamical model for North Atlantic seasonal hurricane prediction |
title_full |
A statistical/dynamical model for North Atlantic seasonal hurricane prediction |
title_fullStr |
A statistical/dynamical model for North Atlantic seasonal hurricane prediction |
title_full_unstemmed |
A statistical/dynamical model for North Atlantic seasonal hurricane prediction |
title_sort |
statistical/dynamical model for north atlantic seasonal hurricane prediction |
publisher |
American Geophysical Union |
publishDate |
2020 |
url |
http://hdl.handle.net/2117/330979 https://doi.org/10.1029/2020GL089357 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL089357 Klotzbach, P.; Caron, L.-P.; Bell, M. A statistical/dynamical model for North Atlantic seasonal hurricane prediction. "Geophysical Research Letters", Octubre 2020, vol. 47, núm. 20, e2020GL089357. doi:10.1029/2020GL089357 1944-8007 http://hdl.handle.net/2117/330979 |
op_rights |
Open Access |
op_doi |
https://doi.org/10.1029/2020GL089357 |
container_title |
Geophysical Research Letters |
container_volume |
47 |
container_issue |
20 |
_version_ |
1766132768643743744 |