Journal article
Multi-model ensemble forecasting of North Atlantic tropical cyclone activity
Climate dynamics, Vol.53(12), pp.7461-7477
12/2019
DOI: 10.1007/s00382-016-3369-z
Abstract
North Atlantic tropical cyclones (TCs) and hurricanes are responsible for a large number of fatalities and economic damage. Skillful seasonal predictions of the North Atlantic TC activity can provide basic information critical to our improved preparedness. This study focuses on the development of statistical–dynamical seasonal forecasting systems for different quantities related to the frequency and intensity of North Atlantic TCs. These models use only tropical Atlantic and tropical mean sea surface temperatures (SSTs) to describe the variability exhibited by the observational records because they reflect the importance of both local and non-local effects on the genesis and development of TCs in the North Atlantic basin. A set of retrospective forecasts of SSTs by six experimental seasonal-to-interannual prediction systems from the North American Multi-Model Ensemble are used as covariates. The retrospective forecasts are performed over the period 1982–2015. The skill of these statistical–dynamical models is quantified for different quantities (basin-wide number of tropical storms and hurricanes, power dissipation index and accumulated cyclone energy) for forecasts initialized as early as November of the year prior to the season to forecast. The results of this work show that it is possible to obtain skillful retrospective forecasts of North Atlantic TC activity with a long lead time. Moreover, probabilistic forecasts of North Atlantic TC activity for the 2016 season are provided.
Details
- Title: Subtitle
- Multi-model ensemble forecasting of North Atlantic tropical cyclone activity
- Creators
- Gabriele Villarini - University of IowaBeda Luitel - University of IowaGabriel Vecchi - NOAA Geophysical Fluid Dynamics LaboratoryJoyee Ghosh - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Climate dynamics, Vol.53(12), pp.7461-7477
- Publisher
- Springer Berlin Heidelberg
- DOI
- 10.1007/s00382-016-3369-z
- ISSN
- 0930-7575
- eISSN
- 1432-0894
- Grant note
- U.S. Army Corps of Engineers (http://dx.doi.org/10.13039/100006752) AGS-1262099 / Directorate for Geosciences (http://dx.doi.org/10.13039/100000085) NA14OAR4830101 / National Oceanic and Atmospheric Administration (http://dx.doi.org/10.13039/100000192)
- Language
- English
- Date published
- 12/2019
- Academic Unit
- Statistics and Actuarial Science; Civil and Environmental Engineering
- Record Identifier
- 9984196969202771
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