Tropical cyclone forecast model: Difference between revisions

Revision as of 06:55, 28 June 2023

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The Florida State Super Ensemble (FSSE) is produced from a suite of models which then uses statistical regression equations developed over a training phase to reduce their biases, which produces forecasts better than the member models or their mean solution. It uses 11&nbsp;global models, including five developed at [[Florida State University]], the Unified Model, the GFS, the NOGAPS, the United States Navy NOGAPS, the Australian Bureau of Meteorology Research Centre (BMRC) model, and Canadian [[Recherche en Prévision Numérique]] (RPN) model. It shows significant skill in track, intensity, and rainfall predictions of tropical cyclones.<ref>{{cite book|pages=532–545|url=https://books.google.com/books?id=c-rY28QQCj8C&q=Florida+State+Superensemble+hurricane+book&pg=PA532|title=Predictability of weather and climate|author1=Palmer, Tim |author2=Renate Hagedorn |name-list-style=amp |year=2006|publisher=Cambridge University Press|isbn=978-0-521-84882-4|access-date=2011-02-26}}</ref>

The Systematic Approach Forecast Aid (SAFA) was developed by the Joint Typhoon Warning Center to create a selective consensus forecast which removed more erroneous forecasts at a 72‑hour time frame from consideration using the United States Navy NOGAPS model, the GFDL, the Japan Meteorological Agency's global and typhoon models, as well as the UKMET. All the models improved during SAFA's five-year history and removing erroneous forecasts proved difficult to do in operations.<ref>{{cite journal|title=Notes and Correspondence: Operational Evaluation of a Selective Consensus in the Western North Pacific Basin|author=Sampson, Charles R., John A. Knaff, and Edward M. Fukada|pages=671–675|date=June 2007|journal=Weather and Forecasting|volume=22|doi=10.1175/WAF991.1|issue=3|bibcode = 2007WtFor..22..671S |doi-access=free}}</ref>

==Sunspot theory==